Yue, Chen; Chen, Shaojie; Sair, Haris I; Airan, Raag; Caffo, Brian S
2015-09-01
Data reproducibility is a critical issue in all scientific experiments. In this manuscript, the problem of quantifying the reproducibility of graphical measurements is considered. The image intra-class correlation coefficient (I2C2) is generalized and the graphical intra-class correlation coefficient (GICC) is proposed for such purpose. The concept for GICC is based on multivariate probit-linear mixed effect models. A Markov Chain Monte Carlo EM (mcm-cEM) algorithm is used for estimating the GICC. Simulation results with varied settings are demonstrated and our method is applied to the KIRBY21 test-retest dataset.
Magezi, David A
2015-01-01
Linear mixed-effects models (LMMs) are increasingly being used for data analysis in cognitive neuroscience and experimental psychology, where within-participant designs are common. The current article provides an introductory review of the use of LMMs for within-participant data analysis and describes a free, simple, graphical user interface (LMMgui). LMMgui uses the package lme4 (Bates et al., 2014a,b) in the statistical environment R (R Core Team).
Learning Graphical Models With Hubs.
Tan, Kean Ming; London, Palma; Mohan, Karthik; Lee, Su-In; Fazel, Maryam; Witten, Daniela
2014-10-01
We consider the problem of learning a high-dimensional graphical model in which there are a few hub nodes that are densely-connected to many other nodes. Many authors have studied the use of an ℓ1 penalty in order to learn a sparse graph in the high-dimensional setting. However, the ℓ1 penalty implicitly assumes that each edge is equally likely and independent of all other edges. We propose a general framework to accommodate more realistic networks with hub nodes, using a convex formulation that involves a row-column overlap norm penalty. We apply this general framework to three widely-used probabilistic graphical models: the Gaussian graphical model, the covariance graph model, and the binary Ising model. An alternating direction method of multipliers algorithm is used to solve the corresponding convex optimization problems. On synthetic data, we demonstrate that our proposed framework outperforms competitors that do not explicitly model hub nodes. We illustrate our proposal on a webpage data set and a gene expression data set.
Graphical Models for Ordinal Data
Guo, Jian; Levina, Elizaveta; Michailidis, George; Zhu, Ji
2014-01-01
A graphical model for ordinal variables is considered, where it is assumed that the data are generated by discretizing the marginal distributions of a latent multivariate Gaussian distribution. The relationships between these ordinal variables are then described by the underlying Gaussian graphical model and can be inferred by estimating the corresponding concentration matrix. Direct estimation of the model is computationally expensive, but an approximate EM-like algorithm is developed to provide an accurate estimate of the parameters at a fraction of the computational cost. Numerical evidence based on simulation studies shows the strong performance of the algorithm, which is also illustrated on data sets on movie ratings and an educational survey. PMID:26120267
Representing Learning With Graphical Models
NASA Technical Reports Server (NTRS)
Buntine, Wray L.; Lum, Henry, Jr. (Technical Monitor)
1994-01-01
Probabilistic graphical models are being used widely in artificial intelligence, for instance, in diagnosis and expert systems, as a unified qualitative and quantitative framework for representing and reasoning with probabilities and independencies. Their development and use spans several fields including artificial intelligence, decision theory and statistics, and provides an important bridge between these communities. This paper shows by way of example that these models can be extended to machine learning, neural networks and knowledge discovery by representing the notion of a sample on the graphical model. Not only does this allow a flexible variety of learning problems to be represented, it also provides the means for representing the goal of learning and opens the way for the automatic development of learning algorithms from specifications.
Model Evaluation of Continuous Data Pharmacometric Models: Metrics and Graphics
Nguyen, THT; Mouksassi, M‐S; Holford, N; Al‐Huniti, N; Freedman, I; Hooker, AC; John, J; Karlsson, MO; Mould, DR; Pérez Ruixo, JJ; Plan, EL; Savic, R; van Hasselt, JGC; Weber, B; Zhou, C; Comets, E
2017-01-01
This article represents the first in a series of tutorials on model evaluation in nonlinear mixed effect models (NLMEMs), from the International Society of Pharmacometrics (ISoP) Model Evaluation Group. Numerous tools are available for evaluation of NLMEM, with a particular emphasis on visual assessment. This first basic tutorial focuses on presenting graphical evaluation tools of NLMEM for continuous data. It illustrates graphs for correct or misspecified models, discusses their pros and cons, and recalls the definition of metrics used. PMID:27884052
Model Evaluation of Continuous Data Pharmacometric Models: Metrics and Graphics.
Nguyen, Tht; Mouksassi, M-S; Holford, N; Al-Huniti, N; Freedman, I; Hooker, A C; John, J; Karlsson, M O; Mould, D R; Pérez Ruixo, J J; Plan, E L; Savic, R; van Hasselt, Jgc; Weber, B; Zhou, C; Comets, E; Mentré, F
2017-02-01
This article represents the first in a series of tutorials on model evaluation in nonlinear mixed effect models (NLMEMs), from the International Society of Pharmacometrics (ISoP) Model Evaluation Group. Numerous tools are available for evaluation of NLMEM, with a particular emphasis on visual assessment. This first basic tutorial focuses on presenting graphical evaluation tools of NLMEM for continuous data. It illustrates graphs for correct or misspecified models, discusses their pros and cons, and recalls the definition of metrics used.
A graphical language for reliability model generation
NASA Technical Reports Server (NTRS)
Howell, Sandra V.; Bavuso, Salvatore J.; Haley, Pamela J.
1990-01-01
A graphical interface capability of the hybrid automated reliability predictor (HARP) is described. The graphics-oriented (GO) module provides the user with a graphical language for modeling system failure modes through the selection of various fault tree gates, including sequence dependency gates, or by a Markov chain. With this graphical input language, a fault tree becomes a convenient notation for describing a system. In accounting for any sequence dependencies, HARP converts the fault-tree notation to a complex stochastic process that is reduced to a Markov chain which it can then solve for system reliability. The graphics capability is available for use on an IBM-compatible PC, a Sun, and a VAX workstation. The GO module is written in the C programming language and uses the Graphical Kernel System (GKS) standard for graphics implementation. The PC, VAX, and Sun versions of the HARP GO module are currently in beta-testing.
Graphical Models via Univariate Exponential Family Distributions
Yang, Eunho; Ravikumar, Pradeep; Allen, Genevera I.; Liu, Zhandong
2016-01-01
Undirected graphical models, or Markov networks, are a popular class of statistical models, used in a wide variety of applications. Popular instances of this class include Gaussian graphical models and Ising models. In many settings, however, it might not be clear which subclass of graphical models to use, particularly for non-Gaussian and non-categorical data. In this paper, we consider a general sub-class of graphical models where the node-wise conditional distributions arise from exponential families. This allows us to derive multivariate graphical model distributions from univariate exponential family distributions, such as the Poisson, negative binomial, and exponential distributions. Our key contributions include a class of M-estimators to fit these graphical model distributions; and rigorous statistical analysis showing that these M-estimators recover the true graphical model structure exactly, with high probability. We provide examples of genomic and proteomic networks learned via instances of our class of graphical models derived from Poisson and exponential distributions. PMID:27570498
Graphical models for optimal power flow
Dvijotham, Krishnamurthy; Chertkov, Michael; Van Hentenryck, Pascal; Vuffray, Marc; Misra, Sidhant
2016-09-13
Optimal power flow (OPF) is the central optimization problem in electric power grids. Although solved routinely in the course of power grid operations, it is known to be strongly NP-hard in general, and weakly NP-hard over tree networks. In this paper, we formulate the optimal power flow problem over tree networks as an inference problem over a tree-structured graphical model where the nodal variables are low-dimensional vectors. We adapt the standard dynamic programming algorithm for inference over a tree-structured graphical model to the OPF problem. Combining this with an interval discretization of the nodal variables, we develop an approximation algorithm for the OPF problem. Further, we use techniques from constraint programming (CP) to perform interval computations and adaptive bound propagation to obtain practically efficient algorithms. Compared to previous algorithms that solve OPF with optimality guarantees using convex relaxations, our approach is able to work for arbitrary tree-structured distribution networks and handle mixed-integer optimization problems. Further, it can be implemented in a distributed message-passing fashion that is scalable and is suitable for “smart grid” applications like control of distributed energy resources. In conclusion, numerical evaluations on several benchmark networks show that practical OPF problems can be solved effectively using this approach.
Graphical models for optimal power flow
Dvijotham, Krishnamurthy; Chertkov, Michael; Van Hentenryck, Pascal; ...
2016-09-13
Optimal power flow (OPF) is the central optimization problem in electric power grids. Although solved routinely in the course of power grid operations, it is known to be strongly NP-hard in general, and weakly NP-hard over tree networks. In this paper, we formulate the optimal power flow problem over tree networks as an inference problem over a tree-structured graphical model where the nodal variables are low-dimensional vectors. We adapt the standard dynamic programming algorithm for inference over a tree-structured graphical model to the OPF problem. Combining this with an interval discretization of the nodal variables, we develop an approximation algorithmmore » for the OPF problem. Further, we use techniques from constraint programming (CP) to perform interval computations and adaptive bound propagation to obtain practically efficient algorithms. Compared to previous algorithms that solve OPF with optimality guarantees using convex relaxations, our approach is able to work for arbitrary tree-structured distribution networks and handle mixed-integer optimization problems. Further, it can be implemented in a distributed message-passing fashion that is scalable and is suitable for “smart grid” applications like control of distributed energy resources. In conclusion, numerical evaluations on several benchmark networks show that practical OPF problems can be solved effectively using this approach.« less
Operations for Learning with Graphical Models
NASA Technical Reports Server (NTRS)
Buntine, Wray L.
1994-01-01
This paper is a multidisciplinary review of empirical, statistical learning from a graphical model perspective. Well-known examples of graphical models include Bayesian net- works, directed graphs representing a Markov chain, and undirected networks representing a Markov field. These graphical models are extended to model data analysis and empirical learning using the notation of plates. Graphical operations for simplifying and manipulating a problem are provided including decomposition, differentiation, and the manipulation of probability models from the exponential family. These operations adapt existing techniques from statistics and automatic differentiation to graphs. Two standard algorithm schemes for learning are reviewed in a graphical framework: Gibbs sampling and the expectation maximization algorithm. Some algorithms are developed in this graphical framework including a generalized version of linear regression, techniques for feed-forward networks, and learning Gaussian and discrete Bayesian networks from data. The paper concludes by sketching some implications for data analysis and summarizing some popular algorithms that fall within the framework presented. The main original contributions here are the decomposition techniques and the demonstration that graphical models provide a framework for understanding and developing complex learning algorithms.
Graphical Models and Computerized Adaptive Testing.
ERIC Educational Resources Information Center
Almond, Russell G.; Mislevy, Robert J.
1999-01-01
Considers computerized adaptive testing from the perspective of graphical modeling (GM). GM provides methods for making inferences about multifaceted skills and knowledge and for extracting data from complex performances. Provides examples from language-proficiency assessment. (SLD)
Modelling structured data with Probabilistic Graphical Models
NASA Astrophysics Data System (ADS)
Forbes, F.
2016-05-01
Most clustering and classification methods are based on the assumption that the objects to be clustered are independent. However, in more and more modern applications, data are structured in a way that makes this assumption not realistic and potentially misleading. A typical example that can be viewed as a clustering task is image segmentation where the objects are the pixels on a regular grid and depend on neighbouring pixels on this grid. Also, when data are geographically located, it is of interest to cluster data with an underlying dependence structure accounting for some spatial localisation. These spatial interactions can be naturally encoded via a graph not necessarily regular as a grid. Data sets can then be modelled via Markov random fields and mixture models (e.g. the so-called MRF and Hidden MRF). More generally, probabilistic graphical models are tools that can be used to represent and manipulate data in a structured way while modeling uncertainty. This chapter introduces the basic concepts. The two main classes of probabilistic graphical models are considered: Bayesian networks and Markov networks. The key concept of conditional independence and its link to Markov properties is presented. The main problems that can be solved with such tools are described. Some illustrations are given associated with some practical work.
Graphical workstation capability for reliability modeling
NASA Technical Reports Server (NTRS)
Bavuso, Salvatore J.; Koppen, Sandra V.; Haley, Pamela J.
1992-01-01
In addition to computational capabilities, software tools for estimating the reliability of fault-tolerant digital computer systems must also provide a means of interfacing with the user. Described here is the new graphical interface capability of the hybrid automated reliability predictor (HARP), a software package that implements advanced reliability modeling techniques. The graphics oriented (GO) module provides the user with a graphical language for modeling system failure modes through the selection of various fault-tree gates, including sequence-dependency gates, or by a Markov chain. By using this graphical input language, a fault tree becomes a convenient notation for describing a system. In accounting for any sequence dependencies, HARP converts the fault-tree notation to a complex stochastic process that is reduced to a Markov chain, which it can then solve for system reliability. The graphics capability is available for use on an IBM-compatible PC, a Sun, and a VAX workstation. The GO module is written in the C programming language and uses the graphical kernal system (GKS) standard for graphics implementation. The PC, VAX, and Sun versions of the HARP GO module are currently in beta-testing stages.
Probabilistic graphical model representation in phylogenetics.
Höhna, Sebastian; Heath, Tracy A; Boussau, Bastien; Landis, Michael J; Ronquist, Fredrik; Huelsenbeck, John P
2014-09-01
Recent years have seen a rapid expansion of the model space explored in statistical phylogenetics, emphasizing the need for new approaches to statistical model representation and software development. Clear communication and representation of the chosen model is crucial for: (i) reproducibility of an analysis, (ii) model development, and (iii) software design. Moreover, a unified, clear and understandable framework for model representation lowers the barrier for beginners and nonspecialists to grasp complex phylogenetic models, including their assumptions and parameter/variable dependencies. Graphical modeling is a unifying framework that has gained in popularity in the statistical literature in recent years. The core idea is to break complex models into conditionally independent distributions. The strength lies in the comprehensibility, flexibility, and adaptability of this formalism, and the large body of computational work based on it. Graphical models are well-suited to teach statistical models, to facilitate communication among phylogeneticists and in the development of generic software for simulation and statistical inference. Here, we provide an introduction to graphical models for phylogeneticists and extend the standard graphical model representation to the realm of phylogenetics. We introduce a new graphical model component, tree plates, to capture the changing structure of the subgraph corresponding to a phylogenetic tree. We describe a range of phylogenetic models using the graphical model framework and introduce modules to simplify the representation of standard components in large and complex models. Phylogenetic model graphs can be readily used in simulation, maximum likelihood inference, and Bayesian inference using, for example, Metropolis-Hastings or Gibbs sampling of the posterior distribution.
Graphical Model Theory for Wireless Sensor Networks
Davis, William B.
2002-12-08
Information processing in sensor networks, with many small processors, demands a theory of computation that allows the minimization of processing effort, and the distribution of this effort throughout the network. Graphical model theory provides a probabilistic theory of computation that explicitly addresses complexity and decentralization for optimizing network computation. The junction tree algorithm, for decentralized inference on graphical probability models, can be instantiated in a variety of applications useful for wireless sensor networks, including: sensor validation and fusion; data compression and channel coding; expert systems, with decentralized data structures, and efficient local queries; pattern classification, and machine learning. Graphical models for these applications are sketched, and a model of dynamic sensor validation and fusion is presented in more depth, to illustrate the junction tree algorithm.
Faculjak, D.A.
1988-03-01
Graphics Manager (GFXMGR) is menu-driven, user-friendly software designed to interactively create, edit, and delete graphics displays on the Advanced Electronics Design (AED) graphics controller, Model 767. The software runs on the VAX family of computers and has been used successfully in security applications to create and change site layouts (maps) of specific facilities. GFXMGR greatly benefits graphics development by minimizing display-development time, reducing tedium on the part of the user, and improving system performance. It is anticipated that GFXMGR can be used to create graphics displays for many types of applications. 8 figs., 2 tabs.
Data Analysis with Graphical Models: Software Tools
NASA Technical Reports Server (NTRS)
Buntine, Wray L.
1994-01-01
Probabilistic graphical models (directed and undirected Markov fields, and combined in chain graphs) are used widely in expert systems, image processing and other areas as a framework for representing and reasoning with probabilities. They come with corresponding algorithms for performing probabilistic inference. This paper discusses an extension to these models by Spiegelhalter and Gilks, plates, used to graphically model the notion of a sample. This offers a graphical specification language for representing data analysis problems. When combined with general methods for statistical inference, this also offers a unifying framework for prototyping and/or generating data analysis algorithms from graphical specifications. This paper outlines the framework and then presents some basic tools for the task: a graphical version of the Pitman-Koopman Theorem for the exponential family, problem decomposition, and the calculation of exact Bayes factors. Other tools already developed, such as automatic differentiation, Gibbs sampling, and use of the EM algorithm, make this a broad basis for the generation of data analysis software.
Planar graphical models which are easy
Chertkov, Michael; Chernyak, Vladimir
2009-01-01
We describe a rich family of binary variables statistical mechanics models on planar graphs which are equivalent to Gaussian Grassmann Graphical models (free fermions). Calculation of partition function (weighted counting) in the models is easy (of polynomial complexity) as reduced to evaluation of determinants of matrixes linear in the number of variables. In particular, this family of models covers Holographic Algorithms of Valiant and extends on the Gauge Transformations discussed in our previous works.
Software for Data Analysis with Graphical Models
NASA Technical Reports Server (NTRS)
Buntine, Wray L.; Roy, H. Scott
1994-01-01
Probabilistic graphical models are being used widely in artificial intelligence and statistics, for instance, in diagnosis and expert systems, as a framework for representing and reasoning with probabilities and independencies. They come with corresponding algorithms for performing statistical inference. This offers a unifying framework for prototyping and/or generating data analysis algorithms from graphical specifications. This paper illustrates the framework with an example and then presents some basic techniques for the task: problem decomposition and the calculation of exact Bayes factors. Other tools already developed, such as automatic differentiation, Gibbs sampling, and use of the EM algorithm, make this a broad basis for the generation of data analysis software.
Item Screening in Graphical Loglinear Rasch Models
ERIC Educational Resources Information Center
Kreiner, Svend; Christensen, Karl Bang
2011-01-01
In behavioural sciences, local dependence and DIF are common, and purification procedures that eliminate items with these weaknesses often result in short scales with poor reliability. Graphical loglinear Rasch models (Kreiner & Christensen, in "Statistical Methods for Quality of Life Studies," ed. by M. Mesbah, F.C. Cole & M.T.…
Image segmentation with a unified graphical model.
Zhang, Lei; Ji, Qiang
2010-08-01
We propose a unified graphical model that can represent both the causal and noncausal relationships among random variables and apply it to the image segmentation problem. Specifically, we first propose to employ Conditional Random Field (CRF) to model the spatial relationships among image superpixel regions and their measurements. We then introduce a multilayer Bayesian Network (BN) to model the causal dependencies that naturally exist among different image entities, including image regions, edges, and vertices. The CRF model and the BN model are then systematically and seamlessly combined through the theories of Factor Graph to form a unified probabilistic graphical model that captures the complex relationships among different image entities. Using the unified graphical model, image segmentation can be performed through a principled probabilistic inference. Experimental results on the Weizmann horse data set, on the VOC2006 cow data set, and on the MSRC2 multiclass data set demonstrate that our approach achieves favorable results compared to state-of-the-art approaches as well as those that use either the BN model or CRF model alone.
Graphical models and automatic speech recognition
NASA Astrophysics Data System (ADS)
Bilmes, Jeff A.
2002-11-01
Graphical models (GMs) are a flexible statistical abstraction that has been successfully used to describe problems in a variety of different domains. Commonly used for ASR, hidden Markov models are only one example of the large space of models constituting GMs. Therefore, GMs are useful to understand existing ASR approaches and also offer a promising path towards novel techniques. In this work, several such ways are described including (1) using both directed and undirected GMs to represent sparse Gaussian and conditional Gaussian distributions, (2) GMs for representing information fusion and classifier combination, (3) GMs for representing hidden articulatory information in a speech signal, (4) structural discriminability where the graph structure itself is discriminative, and the difficulties that arise when learning discriminative structure (5) switching graph structures, where the graph may change dynamically, and (6) language modeling. The graphical model toolkit (GMTK), a software system for general graphical-model based speech recognition and time series analysis, will also be described, including a number of GMTK's features that are specifically geared to ASR.
Learning structurally consistent undirected probabilistic graphical models.
Roy, Sushmita; Lane, Terran; Werner-Washburne, Margaret
2009-01-01
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the statistical dependency structure than directed graphical models. Unfortunately, structure learning of undirected graphs using likelihood-based scores remains difficult because of the intractability of computing the partition function. We describe a new Markov random field structure learning algorithm, motivated by canonical parameterization of Abbeel et al. We provide computational improvements on their parameterization by learning per-variable canonical factors, which makes our algorithm suitable for domains with hundreds of nodes. We compare our algorithm against several algorithms for learning undirected and directed models on simulated and real datasets from biology. Our algorithm frequently outperforms existing algorithms, producing higher-quality structures, suggesting that enforcing consistency during structure learning is beneficial for learning undirected graphs.
Inferring cellular networks using probabilistic graphical models.
Friedman, Nir
2004-02-06
High-throughput genome-wide molecular assays, which probe cellular networks from different perspectives, have become central to molecular biology. Probabilistic graphical models are useful for extracting meaningful biological insights from the resulting data sets. These models provide a concise representation of complex cellular networks by composing simpler submodels. Procedures based on well-understood principles for inferring such models from data facilitate a model-based methodology for analysis and discovery. This methodology and its capabilities are illustrated by several recent applications to gene expression data.
Probabilistic graphical models for genetic association studies.
Mourad, Raphaël; Sinoquet, Christine; Leray, Philippe
2012-01-01
Probabilistic graphical models have been widely recognized as a powerful formalism in the bioinformatics field, especially in gene expression studies and linkage analysis. Although less well known in association genetics, many successful methods have recently emerged to dissect the genetic architecture of complex diseases. In this review article, we cover the applications of these models to the population association studies' context, such as linkage disequilibrium modeling, fine mapping and candidate gene studies, and genome-scale association studies. Significant breakthroughs of the corresponding methods are highlighted, but emphasis is also given to their current limitations, in particular, to the issue of scalability. Finally, we give promising directions for future research in this field.
ERIC Educational Resources Information Center
Post, Susan
1975-01-01
An art teacher described an elective course in graphics which was designed to enlarge a student's knowledge of value, color, shape within a shape, transparency, line and texture. This course utilized the technique of working a multi-colored print from a single block that was first introduced by Picasso. (Author/RK)
On the graphical extraction of multipole mixing ratios of nuclear transitions
NASA Astrophysics Data System (ADS)
Rezynkina, K.; Lopez-Martens, A.; Hauschild, K.
2017-02-01
We propose a novel graphical method for determining the mixing ratios δ and their associated uncertainties for mixed nuclear transitions. It incorporates the uncertainties on both the measured and the theoretical conversion coefficients. The accuracy of the method has been studied by deriving the corresponding probability density function. The domains of applicability of the method are carefully defined.
Spatiotemporal video segmentation based on graphical models.
Wang, Yang; Loe, Kia-Fock; Tan, Tele; Wu, Jian-Kang
2005-07-01
This paper proposes a probabilistic framework for spatiotemporal segmentation of video sequences. Motion information, boundary information from intensity segmentation, and spatial connectivity of segmentation are unified in the video segmentation process by means of graphical models. A Bayesian network is presented to model interactions among the motion vector field, the intensity segmentation field, and the video segmentation field. The notion of the Markov random field is used to encourage the formation of continuous regions. Given consecutive frames, the conditional joint probability density of the three fields is maximized in an iterative way. To effectively utilize boundary information from the intensity segmentation, distance transformation is employed in local objective functions. Experimental results show that the method is robust and generates spatiotemporally coherent segmentation results. Moreover, the proposed video segmentation approach can be viewed as the compromise of previous motion based approaches and region merging approaches.
Connections between Graphical Gaussian Models and Factor Analysis
ERIC Educational Resources Information Center
Salgueiro, M. Fatima; Smith, Peter W. F.; McDonald, John W.
2010-01-01
Connections between graphical Gaussian models and classical single-factor models are obtained by parameterizing the single-factor model as a graphical Gaussian model. Models are represented by independence graphs, and associations between each manifest variable and the latent factor are measured by factor partial correlations. Power calculations…
Teaching "Instant Experience" with Graphical Model Validation Techniques
ERIC Educational Resources Information Center
Ekstrøm, Claus Thorn
2014-01-01
Graphical model validation techniques for linear normal models are often used to check the assumptions underlying a statistical model. We describe an approach to provide "instant experience" in looking at a graphical model validation plot, so it becomes easier to validate if any of the underlying assumptions are violated.
Bayesian graphical models for genomewide association studies.
Verzilli, Claudio J; Stallard, Nigel; Whittaker, John C
2006-07-01
As the extent of human genetic variation becomes more fully characterized, the research community is faced with the challenging task of using this information to dissect the heritable components of complex traits. Genomewide association studies offer great promise in this respect, but their analysis poses formidable difficulties. In this article, we describe a computationally efficient approach to mining genotype-phenotype associations that scales to the size of the data sets currently being collected in such studies. We use discrete graphical models as a data-mining tool, searching for single- or multilocus patterns of association around a causative site. The approach is fully Bayesian, allowing us to incorporate prior knowledge on the spatial dependencies around each marker due to linkage disequilibrium, which reduces considerably the number of possible graphical structures. A Markov chain-Monte Carlo scheme is developed that yields samples from the posterior distribution of graphs conditional on the data from which probabilistic statements about the strength of any genotype-phenotype association can be made. Using data simulated under scenarios that vary in marker density, genotype relative risk of a causative allele, and mode of inheritance, we show that the proposed approach has better localization properties and leads to lower false-positive rates than do single-locus analyses. Finally, we present an application of our method to a quasi-synthetic data set in which data from the CYP2D6 region are embedded within simulated data on 100K single-nucleotide polymorphisms. Analysis is quick (<5 min), and we are able to localize the causative site to a very short interval.
Mining protein kinases regulation using graphical models.
Chen, Qingfeng; Chen, Yi-Ping Phoebe
2011-03-01
Abnormal kinase activity is a frequent cause of diseases, which makes kinases a promising pharmacological target. Thus, it is critical to identify the characteristics of protein kinases regulation by studying the activation and inhibition of kinase subunits in response to varied stimuli. Bayesian network (BN) is a formalism for probabilistic reasoning that has been widely used for learning dependency models. However, for high-dimensional discrete random vectors the set of plausible models becomes large and a full comparison of all the posterior probabilities related to the competing models becomes infeasible. A solution to this problem is based on the Markov Chain Monte Carlo (MCMC) method. This paper proposes a BN-based framework to discover the dependency correlations of kinase regulation. Our approach is to apply the MCMC method to generate a sequence of samples from a probability distribution, by which to approximate the distribution. The frequent connections (edges) are identified from the obtained sampling graphical models. Our results point to a number of novel candidate regulation patterns that are interesting in biology and include inferred associations that were unknown.
ModelMate - A graphical user interface for model analysis
Banta, Edward R.
2011-01-01
ModelMate is a graphical user interface designed to facilitate use of model-analysis programs with models. This initial version of ModelMate supports one model-analysis program, UCODE_2005, and one model software program, MODFLOW-2005. ModelMate can be used to prepare input files for UCODE_2005, run UCODE_2005, and display analysis results. A link to the GW_Chart graphing program facilitates visual interpretation of results. ModelMate includes capabilities for organizing directories used with the parallel-processing capabilities of UCODE_2005 and for maintaining files in those directories to be identical to a set of files in a master directory. ModelMate can be used on its own or in conjunction with ModelMuse, a graphical user interface for MODFLOW-2005 and PHAST.
On the Development of the ISAAC Graphic Model
Kim, K.R.; Kim, S.D.; Song, Y.M.
2006-07-01
Recently the development of graphical methods using the ISAAC code's calculation data has been started in order to show the Wolsong 1 and 2 PHWR plants behaviour during the severe accidents. This graphic model is designed to provide two basic functions: one is to provide the graphical display of several plants systems together with the important parameters. For example, the representative T/H behaviour, fuel behaviour, fuel channel behaviour, reactor core behaviour, containment behaviour and fission product behaviour are going to be displayed in a graphic window. The other function is the control capability equipped with the controllable valves and pumps in the PHWR SAMG. In this paper, details of the elementary technical aspects of the ISAAC graphic model are presented which are the system structure, ISAAC variable definition, data communication methods and graphical display generation. (authors)
Quantum Graphical Models and Belief Propagation
Leifer, M.S. Poulin, D.
2008-08-15
Belief Propagation algorithms acting on Graphical Models of classical probability distributions, such as Markov Networks, Factor Graphs and Bayesian Networks, are amongst the most powerful known methods for deriving probabilistic inferences amongst large numbers of random variables. This paper presents a generalization of these concepts and methods to the quantum case, based on the idea that quantum theory can be thought of as a noncommutative, operator-valued, generalization of classical probability theory. Some novel characterizations of quantum conditional independence are derived, and definitions of Quantum n-Bifactor Networks, Markov Networks, Factor Graphs and Bayesian Networks are proposed. The structure of Quantum Markov Networks is investigated and some partial characterization results are obtained, along the lines of the Hammersley-Clifford theorem. A Quantum Belief Propagation algorithm is presented and is shown to converge on 1-Bifactor Networks and Markov Networks when the underlying graph is a tree. The use of Quantum Belief Propagation as a heuristic algorithm in cases where it is not known to converge is discussed. Applications to decoding quantum error correcting codes and to the simulation of many-body quantum systems are described.
A Guide to the Literature on Learning Graphical Models
NASA Technical Reports Server (NTRS)
Buntine, Wray L.; Friedland, Peter (Technical Monitor)
1994-01-01
This literature review discusses different methods under the general rubric of learning Bayesian networks from data, and more generally, learning probabilistic graphical models. Because many problems in artificial intelligence, statistics and neural networks can be represented as a probabilistic graphical model, this area provides a unifying perspective on learning. This paper organizes the research in this area along methodological lines of increasing complexity.
Interactive graphical model building using telepresence and virtual reality
Cooke, C.; Stansfield, S.
1993-10-01
This paper presents a prototype system developed at Sandia National Laboratories to create and verify computer-generated graphical models of remote physical environments. The goal of the system is to create an interface between an operator and a computer vision system so that graphical models can be created interactively. Virtual reality and telepresence are used to allow interaction between the operator, computer, and remote environment. A stereo view of the remote environment is produced by two CCD cameras. The cameras are mounted on a three degree-of-freedom platform which is slaved to a mechanically-tracked, stereoscopic viewing device. This gives the operator a sense of immersion in the physical environment. The stereo video is enhanced by overlaying the graphical model onto it. Overlay of the graphical model onto the stereo video allows visual verification of graphical models. Creation of a graphical model is accomplished by allowing the operator to assist the computer in modeling. The operator controls a 3-D cursor to mark objects to be modeled. The computer then automatically extracts positional and geometric information about the object and creates the graphical model.
A general graphical user interface for automatic reliability modeling
NASA Technical Reports Server (NTRS)
Liceaga, Carlos A.; Siewiorek, Daniel P.
1991-01-01
Reported here is a general Graphical User Interface (GUI) for automatic reliability modeling of Processor Memory Switch (PMS) structures using a Markov model. This GUI is based on a hierarchy of windows. One window has graphical editing capabilities for specifying the system's communication structure, hierarchy, reconfiguration capabilities, and requirements. Other windows have field texts, popup menus, and buttons for specifying parameters and selecting actions. An example application of the GUI is given.
Multibody dynamics model building using graphical interfaces
NASA Technical Reports Server (NTRS)
Macala, Glenn A.
1989-01-01
In recent years, the extremely laborious task of manually deriving equations of motion for the simulation of multibody spacecraft dynamics has largely been eliminated. Instead, the dynamicist now works with commonly available general purpose dynamics simulation programs which generate the equations of motion either explicitly or implicitly via computer codes. The user interface to these programs has predominantly been via input data files, each with its own required format and peculiarities, causing errors and frustrations during program setup. Recent progress in a more natural method of data input for dynamics programs: the graphical interface, is described.
A probabilistic graphical model based stochastic input model construction
Wan, Jiang; Zabaras, Nicholas
2014-09-01
Model reduction techniques have been widely used in modeling of high-dimensional stochastic input in uncertainty quantification tasks. However, the probabilistic modeling of random variables projected into reduced-order spaces presents a number of computational challenges. Due to the curse of dimensionality, the underlying dependence relationships between these random variables are difficult to capture. In this work, a probabilistic graphical model based approach is employed to learn the dependence by running a number of conditional independence tests using observation data. Thus a probabilistic model of the joint PDF is obtained and the PDF is factorized into a set of conditional distributions based on the dependence structure of the variables. The estimation of the joint PDF from data is then transformed to estimating conditional distributions under reduced dimensions. To improve the computational efficiency, a polynomial chaos expansion is further applied to represent the random field in terms of a set of standard random variables. This technique is combined with both linear and nonlinear model reduction methods. Numerical examples are presented to demonstrate the accuracy and efficiency of the probabilistic graphical model based stochastic input models. - Highlights: • Data-driven stochastic input models without the assumption of independence of the reduced random variables. • The problem is transformed to a Bayesian network structure learning problem. • Examples are given in flows in random media.
Accelerating molecular modeling applications with graphics processors.
Stone, John E; Phillips, James C; Freddolino, Peter L; Hardy, David J; Trabuco, Leonardo G; Schulten, Klaus
2007-12-01
Molecular mechanics simulations offer a computational approach to study the behavior of biomolecules at atomic detail, but such simulations are limited in size and timescale by the available computing resources. State-of-the-art graphics processing units (GPUs) can perform over 500 billion arithmetic operations per second, a tremendous computational resource that can now be utilized for general purpose computing as a result of recent advances in GPU hardware and software architecture. In this article, an overview of recent advances in programmable GPUs is presented, with an emphasis on their application to molecular mechanics simulations and the programming techniques required to obtain optimal performance in these cases. We demonstrate the use of GPUs for the calculation of long-range electrostatics and nonbonded forces for molecular dynamics simulations, where GPU-based calculations are typically 10-100 times faster than heavily optimized CPU-based implementations. The application of GPU acceleration to biomolecular simulation is also demonstrated through the use of GPU-accelerated Coulomb-based ion placement and calculation of time-averaged potentials from molecular dynamics trajectories. A novel approximation to Coulomb potential calculation, the multilevel summation method, is introduced and compared with direct Coulomb summation. In light of the performance obtained for this set of calculations, future applications of graphics processors to molecular dynamics simulations are discussed.
Lee, S; Richard Dimenna, R; David Tamburello, D
2008-11-13
The process of recovering the waste in storage tanks at the Savannah River Site (SRS) typically requires mixing the contents of the tank with one to four dual-nozzle jet mixers located within the tank. The typical criteria to establish a mixed condition in a tank are based on the number of pumps in operation and the time duration of operation. To ensure that a mixed condition is achieved, operating times are set conservatively long. This approach results in high operational costs because of the long mixing times and high maintenance and repair costs for the same reason. A significant reduction in both of these costs might be realized by reducing the required mixing time based on calculating a reliable indicator of mixing with a suitably validated computer code. The work described in this report establishes the basis for further development of the theory leading to the identified mixing indicators, the benchmark analyses demonstrating their consistency with widely accepted correlations, and the application of those indicators to SRS waste tanks to provide a better, physically based estimate of the required mixing time. Waste storage tanks at SRS contain settled sludge which varies in height from zero to 10 ft. The sludge has been characterized and modeled as micron-sized solids, typically 1 to 5 microns, at weight fractions as high as 20 to 30 wt%, specific gravities to 1.4, and viscosities up to 64 cp during motion. The sludge is suspended and mixed through the use of submersible slurry jet pumps. To suspend settled sludge, water is added to the tank as a slurry medium and stirred with the jet pump. Although there is considerable technical literature on mixing and solid suspension in agitated tanks, very little literature has been published on jet mixing in a large-scale tank. If shorter mixing times can be shown to support Defense Waste Processing Facility (DWPF) or other feed requirements, longer pump lifetimes can be achieved with associated operational cost and
Lee, S; Dimenna, R; Tamburello, D
2011-02-14
height from zero to 10 ft. The sludge has been characterized and modeled as micron-sized solids, typically 1 to 5 microns, at weight fractions as high as 20 to 30 wt%, specific gravities to 1.4, and viscosities up to 64 cp during motion. The sludge is suspended and mixed through the use of submersible slurry jet pumps. To suspend settled sludge, water is added to the tank as a slurry medium and stirred with the jet pump. Although there is considerable technical literature on mixing and solid suspension in agitated tanks, very little literature has been published on jet mixing in a large-scale tank. One of the main objectives in the waste processing is to provide feed of a uniform slurry composition at a certain weight percentage (e.g. typically {approx}13 wt% at SRS) over an extended period of time. In preparation of the sludge for slurrying, several important questions have been raised with regard to sludge suspension and mixing of the solid suspension in the bulk of the tank: (1) How much time is required to prepare a slurry with a uniform solid composition? (2) How long will it take to suspend and mix the sludge for uniform composition in any particular waste tank? (3) What are good mixing indicators to answer the questions concerning sludge mixing stated above in a general fashion applicable to any waste tank/slurry pump geometry and fluid/sludge combination?
Integrating Surface Modeling into the Engineering Design Graphics Curriculum
ERIC Educational Resources Information Center
Hartman, Nathan W.
2006-01-01
It has been suggested there is a knowledge base that surrounds the use of 3D modeling within the engineering design process and correspondingly within engineering design graphics education. While solid modeling receives a great deal of attention and discussion relative to curriculum efforts, and rightly so, surface modeling is an equally viable 3D…
Mining functional modules in genetic networks with decomposable graphical models.
Dejori, Mathäus; Schwaighofer, Anton; Tresp, Volker; Stetter, Martin
2004-01-01
In recent years, graphical models have become an increasingly important tool for the structural analysis of genome-wide expression profiles at the systems level. Here we present a new graphical modelling technique, which is based on decomposable graphical models, and apply it to a set of gene expression profiles from acute lymphoblastic leukemia (ALL). The new method explains probabilistic dependencies of expression levels in terms of the concerted action of underlying genetic functional modules, which are represented as so-called "cliques" in the graph. In addition, the method uses continuous-valued (instead of discretized) expression levels, and makes no particular assumption about their probability distribution. We show that the method successfully groups members of known functional modules to cliques. Our method allows the evaluation of the importance of genes for global cellular functions based on both link count and the clique membership count.
A Thermal Model Preprocessor For Graphics And Material Database Generation
NASA Astrophysics Data System (ADS)
Jones, Jack C.; Gonda, Teresa G.
1989-08-01
The process of developing a physical description of a target for thermal models is a time consuming and tedious task. The problem is one of data collection, data manipulation, and data storage. Information on targets can come from many sources and therefore could be in any form (2-D drawings, 3-D wireframe or solid model representations, etc.). TACOM has developed a preprocessor that decreases the time involved in creating a faceted target representation. This program allows the user to create the graphics for the vehicle and to assign the material properties to the graphics. The vehicle description file is then automatically generated by the preprocessor. By containing all the information in one database, the modeling process is made more accurate and data tracing can be done easily. A bridge to convert other graphics packages (such as BRL-CAD) to a faceted representation is being developed. When the bridge is finished, this preprocessor will be used to manipulate the converted data.
Teaching Geometry through Dynamic Modeling in Introductory Engineering Graphics.
ERIC Educational Resources Information Center
Wiebe, Eric N.; Branoff, Ted J.; Hartman, Nathan W.
2003-01-01
Examines how constraint-based 3D modeling can be used as a vehicle for rethinking instructional approaches to engineering design graphics. Focuses on moving from a mode of instruction based on the crafting by students and assessment by instructors of static 2D drawings and 3D models. Suggests that the new approach is better aligned with…
Transient thermoregulatory model with graphics output
NASA Technical Reports Server (NTRS)
Grounds, D. J.
1974-01-01
A user's guide is presented for the transient version of the thermoregulatory model. The model is designed to simulate the transient response of the human thermoregulatory system to thermal inputs. The model consists of 41 compartments over which the terms of the heat balance are computed. The control mechanisms which are identified are sweating, vaso-constriction and vasodilation.
VR Lab ISS Graphics Models Data Package
NASA Technical Reports Server (NTRS)
Paddock, Eddie; Homan, Dave; Bell, Brad; Miralles, Evely; Hoblit, Jeff
2016-01-01
All the ISS models are saved in AC3D model format which is a text based format that can be loaded into blender and exported to other formats from there including FBX. The models are saved in two different levels of detail, one being labeled "LOWRES" and the other labeled "HIRES". There are two ".str" files (HIRES _ scene _ load.str and LOWRES _ scene _ load.str) that give the hierarchical relationship of the different nodes and the models associated with each node for both the "HIRES" and "LOWRES" model sets. All the images used for texturing are stored in Windows ".bmp" format for easy importing.
Greedy Learning of Graphical Models with Small Girth
2013-01-01
with the Department of Electrical and Computer Engineering , The University of Texas at Austin, USA, Emails: avik@utexas.edu, sanghavi@mail.utexas.edu...61, pp. 401-425, 1996. [7] A. Dobra , C. Hans, B. Jones, J. R. Nevins, G. Yao, and M. West, “Sparse graphical models for exploring gene expression data
Learning Design Based on Graphical Knowledge-Modelling
ERIC Educational Resources Information Center
Paquette, Gilbert; Leonard, Michel; Lundgren-Cayrol, Karin; Mihaila, Stefan; Gareau, Denis
2006-01-01
This chapter states and explains that a Learning Design is the result of a knowledge engineering process where knowledge and competencies, learning design and delivery models are constructed in an integrated framework. We present a general graphical language and a knowledge editor that has been adapted to support the construction of learning…
PGMC: a framework for probabilistic graphic model combination.
Jiang, Chang An; Leong, Tze-Yun; Poh, Kim-Leng
2005-01-01
Decision making in biomedicine often involves incorporating new evidences into existing or working models reflecting the decision problems at hand. We propose a new framework that facilitates effective and incremental integration of multiple probabilistic graphical models. The proposed framework aims to minimize time and effort required to customize and extend the original models through preserving the conditional independence relationships inherent in two types of probabilistic graphical models: Bayesian networks and influence diagrams. We present a four-step algorithm to systematically combine the qualitative and the quantitative parts of the different models; we also describe three heuristic methods for target variable generation to reduce the complexity of the integrated models. Preliminary results from a case study in heart disease diagnosis demonstrate the feasibility and potential for applying the proposed framework in real applications.
MAGIC: Model and Graphic Information Converter
NASA Technical Reports Server (NTRS)
Herbert, W. C.
2009-01-01
MAGIC is a software tool capable of converting highly detailed 3D models from an open, standard format, VRML 2.0/97, into the proprietary DTS file format used by the Torque Game Engine from GarageGames. MAGIC is used to convert 3D simulations from authoritative sources into the data needed to run the simulations in NASA's Distributed Observer Network. The Distributed Observer Network (DON) is a simulation presentation tool built by NASA to facilitate the simulation sharing requirements of the Data Presentation and Visualization effort within the Constellation Program. DON is built on top of the Torque Game Engine (TGE) and has chosen TGE's Dynamix Three Space (DTS) file format to represent 3D objects within simulations.
Workflow modeling in the graphic arts and printing industry
NASA Astrophysics Data System (ADS)
Tuijn, Chris
2003-12-01
The last few years, a lot of effort has been spent on the standardization of the workflow in the graphic arts and printing industry. The main reasons for this standardization are two-fold: first of all, the need to represent all aspects of products, processes and resources in a uniform, digital framework and, secondly, the need to have different systems communicate with each other without having to implement dedicated drivers or protocols. Since many years, a number of organizations in the IT sector have been quite busy developing models and languages on the topic of workflow modeling. In addition to the more formal methods (such as, e.g., extended finite state machines, Petri Nets, Markov Chains etc.) introduced a number of decades ago, more pragmatic methods have been proposed quite recently. We hereby think in particular of the activities of the Workflow Management Coalition that resulted in an XML based Process Definition Language. Although one might be tempted to use the already established standards in the graphic environment, one should be well aware of the complexity and uniqueness of the graphic arts workflow. In this paper, we will show that it is quite hard though not impossible to model the graphic arts workflow using the already established workflow systems. After a brief summary of the graphic arts workflow requirements, we will show why the traditional models are less suitable to use. It will turn out that one of the main reasons for the incompatibility is that the graphic arts workflow is primarily resource driven; this means that the activation of processes depends on the status of different incoming resources. The fact that processes can start running with a partial availability of the input resources is a further complication that asks for additional knowledge on process level. In the second part of this paper, we will discuss in more detail the different software components that are available in any graphic enterprise. In the last part, we will
Conditional graphical models for protein structural motif recognition.
Liu, Yan; Carbonell, Jaime; Gopalakrishnan, Vanathi; Weigele, Peter
2009-05-01
Determining protein structures is crucial to understanding the mechanisms of infection and designing drugs. However, the elucidation of protein folds by crystallographic experiments can be a bottleneck in the development process. In this article, we present a probabilistic graphical model framework, conditional graphical models, for predicting protein structural motifs. It represents the structure characteristics of a structural motif using a graph, where the nodes denote the secondary structure elements, and the edges indicate the side-chain interactions between the components either within one protein chain or between chains. Then the model defines the optimal segmentation of a protein sequence against the graph by maximizing its "conditional" probability so that it can take advantages of the discriminative training approach. Efficient approximate inference algorithms using reversible jump Markov Chain Monte Carlo (MCMC) algorithm are developed to handle the resulting complex graphical models. We test our algorithm on four important structural motifs, and our method outperforms other state-of-art algorithms for motif recognition. We also hypothesize potential membership proteins of target folds from Swiss-Prot, which further supports the evolutionary hypothesis about viral folds.
Detecting relationships between physiological variables using graphical models.
Imhoff, Michael; Fried, Ronald; Gather, Ursula
2002-01-01
In intensive care physiological variables of the critically ill are measured and recorded in short time intervals. The proper extraction and interpretation of the information contained in this flood of information can hardly be done by experience alone. Intelligent alarm systems are needed to provide suitable bedside decision support. So far there is no commonly accepted standard for detecting the actual clinical state from the patient record. We use the statistical methodology of graphical models based on partial correlations for detecting time-varying relationships between physiological variables. Graphical models provide information on the relationships among physiological variables that is helpful e.g. for variable selection. Separate analyses for different pathophysiological states show that distinct clinical states are characterized by distinct partial correlation structures. Hence, this technique can provide new insights into physiological mechanisms. PMID:12463843
Probabilistic graphic models applied to identification of diseases
Sato, Renato Cesar; Sato, Graziela Tiemy Kajita
2015-01-01
ABSTRACT Decision-making is fundamental when making diagnosis or choosing treatment. The broad dissemination of computed systems and databases allows systematization of part of decisions through artificial intelligence. In this text, we present basic use of probabilistic graphic models as tools to analyze causality in health conditions. This method has been used to make diagnosis of Alzheimer´s disease, sleep apnea and heart diseases. PMID:26154555
Probabilistic graphic models applied to identification of diseases.
Sato, Renato Cesar; Sato, Graziela Tiemy Kajita
2015-01-01
Decision-making is fundamental when making diagnosis or choosing treatment. The broad dissemination of computed systems and databases allows systematization of part of decisions through artificial intelligence. In this text, we present basic use of probabilistic graphic models as tools to analyze causality in health conditions. This method has been used to make diagnosis of Alzheimer´s disease, sleep apnea and heart diseases.
Identifying gene regulatory network rewiring using latent differential graphical models
Tian, Dechao; Gu, Quanquan; Ma, Jian
2016-01-01
Gene regulatory networks (GRNs) are highly dynamic among different tissue types. Identifying tissue-specific gene regulation is critically important to understand gene function in a particular cellular context. Graphical models have been used to estimate GRN from gene expression data to distinguish direct interactions from indirect associations. However, most existing methods estimate GRN for a specific cell/tissue type or in a tissue-naive way, or do not specifically focus on network rewiring between different tissues. Here, we describe a new method called Latent Differential Graphical Model (LDGM). The motivation of our method is to estimate the differential network between two tissue types directly without inferring the network for individual tissues, which has the advantage of utilizing much smaller sample size to achieve reliable differential network estimation. Our simulation results demonstrated that LDGM consistently outperforms other Gaussian graphical model based methods. We further evaluated LDGM by applying to the brain and blood gene expression data from the GTEx consortium. We also applied LDGM to identify network rewiring between cancer subtypes using the TCGA breast cancer samples. Our results suggest that LDGM is an effective method to infer differential network using high-throughput gene expression data to identify GRN dynamics among different cellular conditions. PMID:27378774
New probabilistic graphical models for genetic regulatory networks studies.
Wang, Junbai; Cheung, Leo Wang-Kit; Delabie, Jan
2005-12-01
This paper introduces two new probabilistic graphical models for reconstruction of genetic regulatory networks using DNA microarray data. One is an independence graph (IG) model with either a forward or a backward search algorithm and the other one is a Gaussian network (GN) model with a novel greedy search method. The performances of both models were evaluated on four MAPK pathways in yeast and three simulated data sets. Generally, an IG model provides a sparse graph but a GN model produces a dense graph where more information about gene-gene interactions may be preserved. The results of our proposed models were compared with several other commonly used models, and our models have shown to give superior performance. Additionally, we found the same common limitations in the prediction of genetic regulatory networks when using only DNA microarray data.
Graphical models of residue coupling in protein families.
Thomas, John; Ramakrishnan, Naren; Bailey-Kellogg, Chris
2008-01-01
Many statistical measures and algorithmic techniques have been proposed for studying residue coupling in protein families. Generally speaking, two residue positions are considered coupled if, in the sequence record, some of their amino acid type combinations are significantly more common than others. While the proposed approaches have proven useful in finding and describing coupling, a significant missing component is a formal probabilistic model that explicates and compactly represents the coupling, integrates information about sequence,structure, and function, and supports inferential procedures for analysis, diagnosis, and prediction.We present an approach to learning and using probabilistic graphical models of residue coupling. These models capture significant conservation and coupling constraints observable ina multiply-aligned set of sequences. Our approach can place a structural prior on considered couplings, so that all identified relationships have direct mechanistic explanations. It can also incorporate information about functional classes, and thereby learn a differential graphical model that distinguishes constraints common to all classes from those unique to individual classes. Such differential models separately account for class-specific conservation and family-wide coupling, two different sources of sequence covariation. They are then able to perform interpretable functional classification of new sequences, explaining classification decisions in terms of the underlying conservation and coupling constraints. We apply our approach in studies of both G protein-coupled receptors and PDZ domains, identifying and analyzing family-wide and class-specific constraints, and performing functional classification. The results demonstrate that graphical models of residue coupling provide a powerful tool for uncovering, representing, and utilizing significant sequence structure-function relationships in protein families.
Protein design by sampling an undirected graphical model of residue constraints.
Thomas, John; Ramakrishnan, Naren; Bailey-Kellogg, Chris
2009-01-01
This paper develops an approach for designing protein variants by sampling sequences that satisfy residue constraints encoded in an undirected probabilistic graphical model. Due to evolutionary pressures on proteins to maintain structure and function, the sequence record of a protein family contains valuable information regarding position-specific residue conservation and coupling (or covariation) constraints. Representing these constraints with a graphical model provides two key benefits for protein design: a probabilistic semantics enabling evaluation of possible sequences for consistency with the constraints, and an explicit factorization of residue dependence and independence supporting efficient exploration of the constrained sequence space. We leverage these benefits in developing two complementary MCMC algorithms for protein design: constrained shuffling mixes wild-type sequences positionwise and evaluates graphical model likelihood, while component sampling directly generates sequences by sampling clique values and propagating to other cliques. We apply our methods to design WW domains. We demonstrate that likelihood under a model of wild-type WWs is highly predictive of foldedness of new WWs. We then show both theoretical and rapid empirical convergence of our algorithms in generating high-likelihood, diverse new sequences. We further show that these sequences capture the original sequence constraints, yielding a model as predictive of foldedness as the original one.
SN_GUI: a graphical user interface for snowpack modeling
NASA Astrophysics Data System (ADS)
Spreitzhofer, G.; Fierz, C.; Lehning, M.
2004-10-01
SNOWPACK is a physical snow cover model. The model not only serves as a valuable research tool, but also runs operationally on a network of high Alpine automatic weather and snow measurement sites. In order to facilitate the operation of SNOWPACK and the interpretation of the results obtained by this model, a user-friendly graphical user interface for snowpack modeling, named SN_GUI, was created. This Java-based and thus platform-independent tool can be operated in two modes, one designed to fulfill the requirements of avalanche warning services (e.g. by providing information about critical layers within the snowpack that are closely related to the avalanche activity), and the other one offering a variety of additional options satisfying the needs of researchers. The user of SN_GUI is graphically guided through the entire process of creating snow cover simulations. The starting point is the efficient creation of input parameter files for SNOWPACK, followed by the launching of SNOWPACK with a variety of parameter settings. Finally, after the successful termination of the run, a number of interactive display options may be used to visualize the model output. Among these are vertical profiles and time profiles for many parameters. Besides other features, SN_GUI allows the use of various color, time and coordinate scales, and the comparison of measured and observed parameters.
De novo protein conformational sampling using a probabilistic graphical model.
Bhattacharya, Debswapna; Cheng, Jianlin
2015-11-06
Efficient exploration of protein conformational space remains challenging especially for large proteins when assembling discretized structural fragments extracted from a protein structure data database. We propose a fragment-free probabilistic graphical model, FUSION, for conformational sampling in continuous space and assess its accuracy using 'blind' protein targets with a length up to 250 residues from the CASP11 structure prediction exercise. The method reduces sampling bottlenecks, exhibits strong convergence, and demonstrates better performance than the popular fragment assembly method, ROSETTA, on relatively larger proteins with a length of more than 150 residues in our benchmark set. FUSION is freely available through a web server at http://protein.rnet.missouri.edu/FUSION/.
Implementing the lattice Boltzmann model on commodity graphics hardware
NASA Astrophysics Data System (ADS)
Kaufman, Arie; Fan, Zhe; Petkov, Kaloian
2009-06-01
Modern graphics processing units (GPUs) can perform general-purpose computations in addition to the native specialized graphics operations. Due to the highly parallel nature of graphics processing, the GPU has evolved into a many-core coprocessor that supports high data parallelism. Its performance has been growing at a rate of squared Moore's law, and its peak floating point performance exceeds that of the CPU by an order of magnitude. Therefore, it is a viable platform for time-sensitive and computationally intensive applications. The lattice Boltzmann model (LBM) computations are carried out via linear operations at discrete lattice sites, which can be implemented efficiently using a GPU-based architecture. Our simulations produce results comparable to the CPU version while improving performance by an order of magnitude. We have demonstrated that the GPU is well suited for interactive simulations in many applications, including simulating fire, smoke, lightweight objects in wind, jellyfish swimming in water, and heat shimmering and mirage (using the hybrid thermal LBM). We further advocate the use of a GPU cluster for large scale LBM simulations and for high performance computing. The Stony Brook Visual Computing Cluster has been the platform for several applications, including simulations of real-time plume dispersion in complex urban environments and thermal fluid dynamics in a pressurized water reactor. Major GPU vendors have been targeting the high performance computing market with GPU hardware implementations. Software toolkits such as NVIDIA CUDA provide a convenient development platform that abstracts the GPU and allows access to its underlying stream computing architecture. However, software programming for a GPU cluster remains a challenging task. We have therefore developed the Zippy framework to simplify GPU cluster programming. Zippy is based on global arrays combined with the stream programming model and it hides the low-level details of the
Dimension reduction for physiological variables using graphical modeling.
Imhoff, Michael; Fried, Roland; Gather, Ursula; Lanius, Vivian
2003-01-01
In intensive care, physiological variables of the critically ill are measured and recorded in short time intervals. The proper extraction and interpretation of the essential information contained in this flood of data can hardly be done by experience alone. Typically, decision making in intensive care is based on only a few selected variables. Alternatively, for a dimension reduction statistical latent variable techniques like principal component analysis or factor analysis can be applied. However, the interpretation of latent components extracted by these methods may be difficult. A more refined analysis is needed to provide suitable bedside decision support. Graphical models based on partial correlations provide information on the relationships among physiological variables that is helpful for variable selection and for identifying interpretable latent components. In a comparative study we investigate how much of the variability of the observed multivariate physiological time series can be explained by variable selection, by standard principal component analysis and by extracting latent compo-nents from groups of variables identified in a graphical model.
Ice-sheet modelling accelerated by graphics cards
NASA Astrophysics Data System (ADS)
Brædstrup, Christian Fredborg; Damsgaard, Anders; Egholm, David Lundbek
2014-11-01
Studies of glaciers and ice sheets have increased the demand for high performance numerical ice flow models over the past decades. When exploring the highly non-linear dynamics of fast flowing glaciers and ice streams, or when coupling multiple flow processes for ice, water, and sediment, researchers are often forced to use super-computing clusters. As an alternative to conventional high-performance computing hardware, the Graphical Processing Unit (GPU) is capable of massively parallel computing while retaining a compact design and low cost. In this study, we present a strategy for accelerating a higher-order ice flow model using a GPU. By applying the newest GPU hardware, we achieve up to 180× speedup compared to a similar but serial CPU implementation. Our results suggest that GPU acceleration is a competitive option for ice-flow modelling when compared to CPU-optimised algorithms parallelised by the OpenMP or Message Passing Interface (MPI) protocols.
An Accurate and Dynamic Computer Graphics Muscle Model
NASA Technical Reports Server (NTRS)
Levine, David Asher
1997-01-01
A computer based musculo-skeletal model was developed at the University in the departments of Mechanical and Biomedical Engineering. This model accurately represents human shoulder kinematics. The result of this model is the graphical display of bones moving through an appropriate range of motion based on inputs of EMGs and external forces. The need existed to incorporate a geometric muscle model in the larger musculo-skeletal model. Previous muscle models did not accurately represent muscle geometries, nor did they account for the kinematics of tendons. This thesis covers the creation of a new muscle model for use in the above musculo-skeletal model. This muscle model was based on anatomical data from the Visible Human Project (VHP) cadaver study. Two-dimensional digital images from the VHP were analyzed and reconstructed to recreate the three-dimensional muscle geometries. The recreated geometries were smoothed, reduced, and sliced to form data files defining the surfaces of each muscle. The muscle modeling function opened these files during run-time and recreated the muscle surface. The modeling function applied constant volume limitations to the muscle and constant geometry limitations to the tendons.
Non-convex Statistical Optimization for Sparse Tensor Graphical Model
Sun, Wei; Wang, Zhaoran; Liu, Han; Cheng, Guang
2016-01-01
We consider the estimation of sparse graphical models that characterize the dependency structure of high-dimensional tensor-valued data. To facilitate the estimation of the precision matrix corresponding to each way of the tensor, we assume the data follow a tensor normal distribution whose covariance has a Kronecker product structure. The penalized maximum likelihood estimation of this model involves minimizing a non-convex objective function. In spite of the non-convexity of this estimation problem, we prove that an alternating minimization algorithm, which iteratively estimates each sparse precision matrix while fixing the others, attains an estimator with the optimal statistical rate of convergence as well as consistent graph recovery. Notably, such an estimator achieves estimation consistency with only one tensor sample, which is unobserved in previous work. Our theoretical results are backed by thorough numerical studies.
De novo protein conformational sampling using a probabilistic graphical model
NASA Astrophysics Data System (ADS)
Bhattacharya, Debswapna; Cheng, Jianlin
2015-11-01
Efficient exploration of protein conformational space remains challenging especially for large proteins when assembling discretized structural fragments extracted from a protein structure data database. We propose a fragment-free probabilistic graphical model, FUSION, for conformational sampling in continuous space and assess its accuracy using ‘blind’ protein targets with a length up to 250 residues from the CASP11 structure prediction exercise. The method reduces sampling bottlenecks, exhibits strong convergence, and demonstrates better performance than the popular fragment assembly method, ROSETTA, on relatively larger proteins with a length of more than 150 residues in our benchmark set. FUSION is freely available through a web server at http://protein.rnet.missouri.edu/FUSION/.
MixSIAR: advanced stable isotope mixing models in R
Background/Question/Methods The development of stable isotope mixing models has coincided with modeling products (e.g. IsoSource, MixSIR, SIAR), where methodological advances are published in parity with software packages. However, while mixing model theory has recently been ex...
Handling geophysical flows: Numerical modelling using Graphical Processing Units
NASA Astrophysics Data System (ADS)
Garcia-Navarro, Pilar; Lacasta, Asier; Juez, Carmelo; Morales-Hernandez, Mario
2016-04-01
Computational tools may help engineers in the assessment of sediment transport during the decision-making processes. The main requirements are that the numerical results have to be accurate and simulation models must be fast. The present work is based on the 2D shallow water equations in combination with the 2D Exner equation [1]. The resulting numerical model accuracy was already discussed in previous work. Regarding the speed of the computation, the Exner equation slows down the already costly 2D shallow water model as the number of variables to solve is increased and the numerical stability is more restrictive. On the other hand, the movement of poorly sorted material over steep areas constitutes a hazardous environmental problem. Computational tools help in the predictions of such landslides [2]. In order to overcome this problem, this work proposes the use of Graphical Processing Units (GPUs) for decreasing significantly the simulation time [3, 4]. The numerical scheme implemented in GPU is based on a finite volume scheme. The mathematical model and the numerical implementation are compared against experimental and field data. In addition, the computational times obtained with the Graphical Hardware technology are compared against Single-Core (sequential) and Multi-Core (parallel) CPU implementations. References [Juez et al.(2014)] Juez, C., Murillo, J., & Garca-Navarro, P. (2014) A 2D weakly-coupled and efficient numerical model for transient shallow flow and movable bed. Advances in Water Resources. 71 93-109. [Juez et al.(2013)] Juez, C., Murillo, J., & Garca-Navarro, P. (2013) . 2D simulation of granular flow over irregular steep slopes using global and local coordinates. Journal of Computational Physics. 225 166-204. [Lacasta et al.(2014)] Lacasta, A., Morales-Hernndez, M., Murillo, J., & Garca-Navarro, P. (2014) An optimized GPU implementation of a 2D free surface simulation model on unstructured meshes Advances in Engineering Software. 78 1-15. [Lacasta
Dynamics of Mental Model Construction from Text and Graphics
ERIC Educational Resources Information Center
Hochpöchler, Ulrike; Schnotz, Wolfgang; Rasch, Thorsten; Ullrich, Mark; Horz, Holger; McElvany, Nele; Baumert, Jürgen
2013-01-01
When students read for learning, they frequently are required to integrate text and graphics information into coherent knowledge structures. The following study aimed at analyzing how students deal with texts and how they deal with graphics when they try to integrate the two sources of information. Furthermore, the study investigated differences…
Graphic-based musculoskeletal model for biomechanical analyses and animation.
Chao, Edmund Y S
2003-04-01
The ability to combine physiology and engineering analyses with computer sciences has opened the door to the possibility of creating the 'Virtual Human' reality. This paper presents a broad foundation for a full-featured biomechanical simulator for the human musculoskeletal system physiology. This simulation technology unites the expertise in biomechanical analysis and graphic modeling to investigate joint and connective tissue mechanics at the structural level and to visualize the results in both static and animated forms together with the model. Adaptable anatomical models including prosthetic implants and fracture fixation devices and a robust computational infrastructure for static, kinematic, kinetic, and stress analyses under varying boundary and loading conditions are incorporated on a common platform, the VIMS (Virtual Interactive Musculoskeletal System). Within this software system, a manageable database containing long bone dimensions, connective tissue material properties and a library of skeletal joint system functional activities and loading conditions are also available and they can easily be modified, updated and expanded. Application software is also available to allow end-users to perform biomechanical analyses interactively. This paper details the design, capabilities, and features of the VIMS development at Johns Hopkins University, an effort possible only through academic and commercial collaborations. Examples using these models and the computational algorithms in a virtual laboratory environment are used to demonstrate the utility of this unique database and simulation technology. This integrated system will impact on medical education, basic research, device development and application, and clinical patient care related to musculoskeletal diseases, trauma, and rehabilitation.
Modeling Mix in ICF Implosions
NASA Astrophysics Data System (ADS)
Weber, C. R.; Clark, D. S.; Chang, B.; Eder, D. C.; Haan, S. W.; Jones, O. S.; Marinak, M. M.; Peterson, J. L.; Robey, H. F.
2014-10-01
The observation of ablator material mixing into the hot spot of ICF implosions correlates with reduced yield in National Ignition Campaign (NIC) experiments. Higher Z ablator material radiatively cools the central hot spot, inhibiting thermonuclear burn. This talk focuses on modeling a ``high-mix'' implosion from the NIC, where greater than 1000 ng of ablator material was inferred to have mixed into the hot spot. Standard post-shot modeling of this implosion does not predict the large amounts of ablator mix necessary to explain the data. Other issues are explored in this talk and sensitivity to the method of radiation transport is found. Compared with radiation diffusion, Sn transport can increase ablation front growth and alter the blow-off dynamics of capsule dust. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
A Graphical Method for Assessing the Identification of Linear Structural Equation Models
ERIC Educational Resources Information Center
Eusebi, Paolo
2008-01-01
A graphical method is presented for assessing the state of identifiability of the parameters in a linear structural equation model based on the associated directed graph. We do not restrict attention to recursive models. In the recent literature, methods based on graphical models have been presented as a useful tool for assessing the state of…
Semi-Supervised Video Segmentation Using Tree Structured Graphical Models.
Badrinarayanan, Vijay; Budvytis, Ignas; Cipolla, Roberto
2013-03-06
We present a novel patch-based probabilistic graphical model for semi-supervised video segmentation. At the heart of our model is a temporal tree structure which links patches in adjacent frames through the video sequence. This permits exact inference of pixel labels without resorting to traditional short time-window based video processing or instantaneous decision making. The input to our algorithm are labelled key frame(s) of a video sequence and the output is pixel-wise labels along with their confidences. We propose an efficient inference scheme that performs exact inference over the temporal tree, and optionally a per frame label smoothing step using loopy BP, to estimate pixel-wise labels and their posteriors. These posteriors are used to learn pixel unaries by training a Random Decision Forest in a semi-supervised manner. These unaries are used in a second iteration of label inference to improve the segmentation quality. We demonstrate the efficacy of our proposed algorithm using several qualitative and quantitative tests on both foreground/background and multi-class video segmentation problems using publicly available and our own datasets.
Semi-supervised video segmentation using tree structured graphical models.
Badrinarayanan, Vijay; Budvytis, Ignas; Cipolla, Roberto
2013-11-01
We present a novel patch-based probabilistic graphical model for semi-supervised video segmentation. At the heart of our model is a temporal tree structure that links patches in adjacent frames through the video sequence. This permits exact inference of pixel labels without resorting to traditional short time window-based video processing or instantaneous decision making. The input to our algorithm is labeled key frame(s) of a video sequence and the output is pixel-wise labels along with their confidences. We propose an efficient inference scheme that performs exact inference over the temporal tree, and optionally a per frame label smoothing step using loopy BP, to estimate pixel-wise labels and their posteriors. These posteriors are used to learn pixel unaries by training a Random Decision Forest in a semi-supervised manner. These unaries are used in a second iteration of label inference to improve the segmentation quality. We demonstrate the efficacy of our proposed algorithm using several qualitative and quantitative tests on both foreground/background and multiclass video segmentation problems using publicly available and our own datasets.
Graphical User Interface for Simulink Integrated Performance Analysis Model
NASA Technical Reports Server (NTRS)
Durham, R. Caitlyn
2009-01-01
The J-2X Engine (built by Pratt & Whitney Rocketdyne,) in the Upper Stage of the Ares I Crew Launch Vehicle, will only start within a certain range of temperature and pressure for Liquid Hydrogen and Liquid Oxygen propellants. The purpose of the Simulink Integrated Performance Analysis Model is to verify that in all reasonable conditions the temperature and pressure of the propellants are within the required J-2X engine start boxes. In order to run the simulation, test variables must be entered at all reasonable values of parameters such as heat leak and mass flow rate. To make this testing process as efficient as possible in order to save the maximum amount of time and money, and to show that the J-2X engine will start when it is required to do so, a graphical user interface (GUI) was created to allow the input of values to be used as parameters in the Simulink Model, without opening or altering the contents of the model. The GUI must allow for test data to come from Microsoft Excel files, allow those values to be edited before testing, place those values into the Simulink Model, and get the output from the Simulink Model. The GUI was built using MATLAB, and will run the Simulink simulation when the Simulate option is activated. After running the simulation, the GUI will construct a new Microsoft Excel file, as well as a MATLAB matrix file, using the output values for each test of the simulation so that they may graphed and compared to other values.
2016-01-01
Over recent years, several alternative relaxed clock models have been proposed in the context of Bayesian dating. These models fall in two distinct categories: uncorrelated and autocorrelated across branches. The choice between these two classes of relaxed clocks is still an open question. More fundamentally, the true process of rate variation may have both long-term trends and short-term fluctuations, suggesting that more sophisticated clock models unfolding over multiple time scales should ultimately be developed. Here, a mixed relaxed clock model is introduced, which can be mechanistically interpreted as a rate variation process undergoing short-term fluctuations on the top of Brownian long-term trends. Statistically, this mixed clock represents an alternative solution to the problem of choosing between autocorrelated and uncorrelated relaxed clocks, by proposing instead to combine their respective merits. Fitting this model on a dataset of 105 placental mammals, using both node-dating and tip-dating approaches, suggests that the two pure clocks, Brownian and white noise, are rejected in favour of a mixed model with approximately equal contributions for its uncorrelated and autocorrelated components. The tip-dating analysis is particularly sensitive to the choice of the relaxed clock model. In this context, the classical pure Brownian relaxed clock appears to be overly rigid, leading to biases in divergence time estimation. By contrast, the use of a mixed clock leads to more recent and more reasonable estimates for the crown ages of placental orders and superorders. Altogether, the mixed clock introduced here represents a first step towards empirically more adequate models of the patterns of rate variation across phylogenetic trees. This article is part of the themed issue ‘Dating species divergences using rocks and clocks’. PMID:27325829
Lartillot, Nicolas; Phillips, Matthew J; Ronquist, Fredrik
2016-07-19
Over recent years, several alternative relaxed clock models have been proposed in the context of Bayesian dating. These models fall in two distinct categories: uncorrelated and autocorrelated across branches. The choice between these two classes of relaxed clocks is still an open question. More fundamentally, the true process of rate variation may have both long-term trends and short-term fluctuations, suggesting that more sophisticated clock models unfolding over multiple time scales should ultimately be developed. Here, a mixed relaxed clock model is introduced, which can be mechanistically interpreted as a rate variation process undergoing short-term fluctuations on the top of Brownian long-term trends. Statistically, this mixed clock represents an alternative solution to the problem of choosing between autocorrelated and uncorrelated relaxed clocks, by proposing instead to combine their respective merits. Fitting this model on a dataset of 105 placental mammals, using both node-dating and tip-dating approaches, suggests that the two pure clocks, Brownian and white noise, are rejected in favour of a mixed model with approximately equal contributions for its uncorrelated and autocorrelated components. The tip-dating analysis is particularly sensitive to the choice of the relaxed clock model. In this context, the classical pure Brownian relaxed clock appears to be overly rigid, leading to biases in divergence time estimation. By contrast, the use of a mixed clock leads to more recent and more reasonable estimates for the crown ages of placental orders and superorders. Altogether, the mixed clock introduced here represents a first step towards empirically more adequate models of the patterns of rate variation across phylogenetic trees.This article is part of the themed issue 'Dating species divergences using rocks and clocks'.
Overview of Neutrino Mixing Models and Their Mixing Angle Predictions
Albright, Carl H.
2009-11-01
An overview of neutrino-mixing models is presented with emphasis on the types of horizontal flavor and vertical family symmetries that have been invoked. Distributions for the mixing angles of many models are displayed. Ways to differentiate among the models and to narrow the list of viable models are discussed.
JACK - ANTHROPOMETRIC MODELING SYSTEM FOR SILICON GRAPHICS WORKSTATIONS
NASA Technical Reports Server (NTRS)
Smith, B.
1994-01-01
JACK is an interactive graphics program developed at the University of Pennsylvania that displays and manipulates articulated geometric figures. JACK is typically used to observe how a human mannequin interacts with its environment and what effects body types will have upon the performance of a task in a simulated environment. Any environment can be created, and any number of mannequins can be placed anywhere in that environment. JACK includes facilities to construct limited geometric objects, position figures, perform a variety of analyses on the figures, describe the motion of the figures and specify lighting and surface property information for rendering high quality images. JACK is supplied with a variety of body types pre-defined and known to the system. There are both male and female bodies, ranging from the 5th to the 95th percentile, based on NASA Standard 3000. Each mannequin is fully articulated and reflects the joint limitations of a normal human. JACK is an editor for manipulating previously defined objects known as "Peabody" objects. Used to describe the figures as well as the internal data structure for representing them, Peabody is a language with a powerful and flexible mechanism for representing connectivity between objects, both the joints between individual segments within a figure and arbitrary connections between different figures. Peabody objects are generally comprised of several individual figures, each one a collection of segments. Each segment has a geometry represented by PSURF files that consist of polygons or curved surface patches. Although JACK does not have the capability to create new objects, objects may be created by other geometric modeling programs and then translated into the PSURF format. Environment files are a collection of figures and attributes that may be dynamically moved under the control of an animation file. The animation facilities allow the user to create a sequence of commands that duplicate the movements of a
Design of multispecific protein sequences using probabilistic graphical modeling.
Fromer, Menachem; Yanover, Chen; Linial, Michal
2010-02-15
In nature, proteins partake in numerous protein- protein interactions that mediate their functions. Moreover, proteins have been shown to be physically stable in multiple structures, induced by cellular conditions, small ligands, or covalent modifications. Understanding how protein sequences achieve this structural promiscuity at the atomic level is a fundamental step in the drug design pipeline and a critical question in protein physics. One way to investigate this subject is to computationally predict protein sequences that are compatible with multiple states, i.e., multiple target structures or binding to distinct partners. The goal of engineering such proteins has been termed multispecific protein design. We develop a novel computational framework to efficiently and accurately perform multispecific protein design. This framework utilizes recent advances in probabilistic graphical modeling to predict sequences with low energies in multiple target states. Furthermore, it is also geared to specifically yield positional amino acid probability profiles compatible with these target states. Such profiles can be used as input to randomly bias high-throughput experimental sequence screening techniques, such as phage display, thus providing an alternative avenue for elucidating the multispecificity of natural proteins and the synthesis of novel proteins with specific functionalities. We prove the utility of such multispecific design techniques in better recovering amino acid sequence diversities similar to those resulting from millions of years of evolution. We then compare the approaches of prediction of low energy ensembles and of amino acid profiles and demonstrate their complementarity in providing more robust predictions for protein design.
A Gaussian graphical model approach to climate networks
Zerenner, Tanja; Friederichs, Petra; Hense, Andreas; Lehnertz, Klaus
2014-06-15
Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately.
Alternating direction methods for latent variable gaussian graphical model selection.
Ma, Shiqian; Xue, Lingzhou; Zou, Hui
2013-08-01
Chandrasekaran, Parrilo, and Willsky (2012) proposed a convex optimization problem for graphical model selection in the presence of unobserved variables. This convex optimization problem aims to estimate an inverse covariance matrix that can be decomposed into a sparse matrix minus a low-rank matrix from sample data. Solving this convex optimization problem is very challenging, especially for large problems. In this letter, we propose two alternating direction methods for solving this problem. The first method is to apply the classic alternating direction method of multipliers to solve the problem as a consensus problem. The second method is a proximal gradient-based alternating-direction method of multipliers. Our methods take advantage of the special structure of the problem and thus can solve large problems very efficiently. A global convergence result is established for the proposed methods. Numerical results on both synthetic data and gene expression data show that our methods usually solve problems with 1 million variables in 1 to 2 minutes and are usually 5 to 35 times faster than a state-of-the-art Newton-CG proximal point algorithm.
Understanding of Relation Structures of Graphical Models by Lower Secondary Students
ERIC Educational Resources Information Center
van Buuren, Onne; Heck, André; Ellermeijer, Ton
2016-01-01
A learning path has been developed on system dynamical graphical modelling, integrated into the Dutch lower secondary physics curriculum. As part of the developmental research for this learning path, students' understanding of the relation structures shown in the diagrams of graphical system dynamics based models has been investigated. One of our…
Bayesian stable isotope mixing models
In this paper we review recent advances in Stable Isotope Mixing Models (SIMMs) and place them into an over-arching Bayesian statistical framework which allows for several useful extensions. SIMMs are used to quantify the proportional contributions of various sources to a mixtur...
Viscoelastic Finite Difference Modeling Using Graphics Processing Units
NASA Astrophysics Data System (ADS)
Fabien-Ouellet, G.; Gloaguen, E.; Giroux, B.
2014-12-01
Full waveform seismic modeling requires a huge amount of computing power that still challenges today's technology. This limits the applicability of powerful processing approaches in seismic exploration like full-waveform inversion. This paper explores the use of Graphics Processing Units (GPU) to compute a time based finite-difference solution to the viscoelastic wave equation. The aim is to investigate whether the adoption of the GPU technology is susceptible to reduce significantly the computing time of simulations. The code presented herein is based on the freely accessible software of Bohlen (2002) in 2D provided under a General Public License (GNU) licence. This implementation is based on a second order centred differences scheme to approximate time differences and staggered grid schemes with centred difference of order 2, 4, 6, 8, and 12 for spatial derivatives. The code is fully parallel and is written using the Message Passing Interface (MPI), and it thus supports simulations of vast seismic models on a cluster of CPUs. To port the code from Bohlen (2002) on GPUs, the OpenCl framework was chosen for its ability to work on both CPUs and GPUs and its adoption by most of GPU manufacturers. In our implementation, OpenCL works in conjunction with MPI, which allows computations on a cluster of GPU for large-scale model simulations. We tested our code for model sizes between 1002 and 60002 elements. Comparison shows a decrease in computation time of more than two orders of magnitude between the GPU implementation run on a AMD Radeon HD 7950 and the CPU implementation run on a 2.26 GHz Intel Xeon Quad-Core. The speed-up varies depending on the order of the finite difference approximation and generally increases for higher orders. Increasing speed-ups are also obtained for increasing model size, which can be explained by kernel overheads and delays introduced by memory transfers to and from the GPU through the PCI-E bus. Those tests indicate that the GPU memory size
Graphics development of DCOR: Deterministic combat model of Oak Ridge
Hunt, G.; Azmy, Y.Y.
1992-10-01
DCOR is a user-friendly computer implementation of a deterministic combat model developed at ORNL. To make the interpretation of the results more intuitive, a conversion of the numerical solution to a graphic animation sequence of battle evolution is desirable. DCOR uses a coarse computational spatial mesh superimposed on the battlefield. This research is aimed at developing robust methods for computing the position of the combative units over the continuum (and also pixeled) battlefield, from DCOR`s discrete-variable solution representing the density of each force type evaluated at gridpoints. Three main problems have been identified and solutions have been devised and implemented in a new visualization module of DCOR. First, there is the problem of distributing the total number of objects, each representing a combative unit of each force type, among the gridpoints at each time level of the animation. This problem is solved by distributing, for each force type, the total number of combative units, one by one, to the gridpoint with the largest calculated number of units. Second, there is the problem of distributing the number of units assigned to each computational gridpoint over the battlefield area attributed to that point. This problem is solved by distributing the units within that area by taking into account the influence of surrounding gridpoints using linear interpolation. Finally, time interpolated solutions must be generated to produce a sufficient number of frames to create a smooth animation sequence. Currently, enough frames may be generated either by direct computation via the PDE solver or by using linear programming techniques to linearly interpolate intermediate frames between calculated frames.
A Graphical Analysis of the Cournot-Nash and Stackelberg Models.
ERIC Educational Resources Information Center
Fulton, Murray
1997-01-01
Shows how the Cournot-Nash and Stackelberg equilibria can be represented in the familiar supply-demand graphical framework, allowing a direct comparison with the monopoly, competitive, and industrial organization models. This graphical analysis is represented throughout the article. (MJP)
An Item Response Unfolding Model for Graphic Rating Scales
ERIC Educational Resources Information Center
Liu, Ying
2009-01-01
The graphic rating scale, a measurement tool used in many areas of psychology, usually takes a form of a fixed-length line segment, with both ends bounded and labeled as extreme responses. The raters mark somewhere on the line, and the length of the line segment from one endpoint to the mark is taken as the measure. An item response unfolding…
A probabilistic graphical model approach to stochastic multiscale partial differential equations
Wan, Jiang; Zabaras, Nicholas
2013-10-01
We develop a probabilistic graphical model based methodology to efficiently perform uncertainty quantification in the presence of both stochastic input and multiple scales. Both the stochastic input and model responses are treated as random variables in this framework. Their relationships are modeled by graphical models which give explicit factorization of a high-dimensional joint probability distribution. The hyperparameters in the probabilistic model are learned using sequential Monte Carlo (SMC) method, which is superior to standard Markov chain Monte Carlo (MCMC) methods for multi-modal distributions. Finally, we make predictions from the probabilistic graphical model using the belief propagation algorithm. Numerical examples are presented to show the accuracy and efficiency of the predictive capability of the developed graphical model.
A graphical representation model for telemedicine and telehealth center sustainability.
Gundim, Rosângela Simões; Chao, Wen Lung
2011-04-01
This study shows the creation of a graphical representation after the application of a questionnaire to evaluate the indicative factors of a sustainable telemedicine and telehealth center in São Paulo, Brazil. We categorized the factors into seven domain areas: institutional, functional, economic-financial, renewal, academic-scientific, partnerships, and social welfare, which were plotted into a graphical representation. The developed graph was shown to be useful when used in the same institution over a long period and complemented with secondary information from publications, archives, and administrative documents to support the numerical indicators. Its use may contribute toward monitoring the factors that define telemedicine and telehealth center sustainability. When systematically applied, it may also be useful for identifying the specific characteristics of the telemedicine and telehealth center, to support its organizational development.
Top View of a Computer Graphic Model of the Opportunity Lander and Rover
NASA Technical Reports Server (NTRS)
2004-01-01
[figure removed for brevity, see original site] PIA05265
A computer graphics model of the Opportunity lander and rover are super-imposed on top of the martian terrain where Opportunity landed.
Graphics-based intelligent search and abstracting using Data Modeling
NASA Astrophysics Data System (ADS)
Jaenisch, Holger M.; Handley, James W.; Case, Carl T.; Songy, Claude G.
2002-11-01
This paper presents an autonomous text and context-mining algorithm that converts text documents into point clouds for visual search cues. This algorithm is applied to the task of data-mining a scriptural database comprised of the Old and New Testaments from the Bible and the Book of Mormon, Doctrine and Covenants, and the Pearl of Great Price. Results are generated which graphically show the scripture that represents the average concept of the database and the mining of the documents down to the verse level.
A computer graphical user interface for survival mixture modelling of recurrent infections.
Lee, Andy H; Zhao, Yun; Yau, Kelvin K W; Ng, S K
2009-03-01
Recurrent infections data are commonly encountered in medical research, where the recurrent events are characterised by an acute phase followed by a stable phase after the index episode. Two-component survival mixture models, in both proportional hazards and accelerated failure time settings, are presented as a flexible method of analysing such data. To account for the inherent dependency of the recurrent observations, random effects are incorporated within the conditional hazard function, in the manner of generalised linear mixed models. Assuming a Weibull or log-logistic baseline hazard in both mixture components of the survival mixture model, an EM algorithm is developed for the residual maximum quasi-likelihood estimation of fixed effect and variance component parameters. The methodology is implemented as a graphical user interface coded using Microsoft visual C++. Application to model recurrent urinary tract infections for elderly women is illustrated, where significant individual variations are evident at both acute and stable phases. The survival mixture methodology developed enable practitioners to identify pertinent risk factors affecting the recurrent times and to draw valid conclusions inferred from these correlated and heterogeneous survival data.
NASA Technical Reports Server (NTRS)
Perucchio, R.; Ingraffea, A. R.
1984-01-01
The establishment of the boundary element method (BEM) as a valid tool for solving problems in structural mechanics and in other fields of applied physics is discussed. The development of an integrated interactive computer graphic system for the application of the BEM to three dimensional problems in elastostatics is described. The integration of interactive computer graphic techniques and the BEM takes place at the preprocessing and postprocessing stages of the analysis process, when, respectively, the data base is generated and the results are interpreted. The interactive computer graphic modeling techniques used for generating and discretizing the boundary surfaces of a solid domain are outlined.
NASA Technical Reports Server (NTRS)
Bidasaria, Hari
1989-01-01
Ultra network is a recently installed very high speed graphic hardware at NASA Langley Research Center. The Ultra Network interfaced to Voyager through its HSX channel is capable of transmitting up to 800 million bits of information per second. It is capable of displaying fifteen to twenty frames of precomputed images of size 1024 x 2368 with 24 bits of color information per pixel per second. Modeling and rendering techniques are being developed in computer graphics and implemented on Ultra hardware. A ray tracer is being developed for use at the Flight Software and Graphic branch. Changes were made to make the ray tracer compatible with Voyager.
Höhna, Sebastian; Landis, Michael J; Heath, Tracy A; Boussau, Bastien; Lartillot, Nicolas; Moore, Brian R; Huelsenbeck, John P; Ronquist, Fredrik
2016-07-01
Programs for Bayesian inference of phylogeny currently implement a unique and ﬁxed suite of models. Consequently, users of these software packages are simultaneously forced to use a number of programs for a given study, while also lacking the freedom to explore models that have not been implemented by the developers of those programs. We developed a new open-source software package, RevBayes, to address these problems. RevBayes is entirely based on probabilistic graphical models, a powerful generic framework for specifying and analyzing statistical models. Phylogenetic-graphical models can be speciﬁed interactively in RevBayes, piece by piece, using a new succinct and intuitive language called Rev. Rev is similar to the R language and the BUGS model-speciﬁcation language, and should be easy to learn for most users. The strength of RevBayes is the simplicity with which one can design, specify, and implement new and complex models. Fortunately, this tremendous ﬂexibility does not come at the cost of slower computation; as we demonstrate, RevBayes outperforms competing software for several standard analyses. Compared with other programs, RevBayes has fewer black-box elements. Users need to explicitly specify each part of the model and analysis. Although this explicitness may initially be unfamiliar, we are convinced that this transparency will improve understanding of phylogenetic models in our ﬁeld. Moreover, it will motivate the search for improvements to existing methods by brazenly exposing the model choices that we make to critical scrutiny. RevBayes is freely available at http://www.RevBayes.com [Bayesian inference; Graphical models; MCMC; statistical phylogenetics.].
Höhna, Sebastian; Landis, Michael J.
2016-01-01
Programs for Bayesian inference of phylogeny currently implement a unique and ﬁxed suite of models. Consequently, users of these software packages are simultaneously forced to use a number of programs for a given study, while also lacking the freedom to explore models that have not been implemented by the developers of those programs. We developed a new open-source software package, RevBayes, to address these problems. RevBayes is entirely based on probabilistic graphical models, a powerful generic framework for specifying and analyzing statistical models. Phylogenetic-graphical models can be speciﬁed interactively in RevBayes, piece by piece, using a new succinct and intuitive language called Rev. Rev is similar to the R language and the BUGS model-speciﬁcation language, and should be easy to learn for most users. The strength of RevBayes is the simplicity with which one can design, specify, and implement new and complex models. Fortunately, this tremendous ﬂexibility does not come at the cost of slower computation; as we demonstrate, RevBayes outperforms competing software for several standard analyses. Compared with other programs, RevBayes has fewer black-box elements. Users need to explicitly specify each part of the model and analysis. Although this explicitness may initially be unfamiliar, we are convinced that this transparency will improve understanding of phylogenetic models in our ﬁeld. Moreover, it will motivate the search for improvements to existing methods by brazenly exposing the model choices that we make to critical scrutiny. RevBayes is freely available at http://www.RevBayes.com. [Bayesian inference; Graphical models; MCMC; statistical phylogenetics.] PMID:27235697
Model Verification of Mixed Dynamic Systems
NASA Technical Reports Server (NTRS)
Evensen, D. A.; Chrostowski, J. D.; Hasselman, T. K.
1982-01-01
MOVER uses experimental data to verify mathematical models of "mixed" dynamic systems. The term "mixed" refers to interactive mechanical, hydraulic, electrical, and other components. Program compares analytical transfer functions with experiment.
Understanding of Relation Structures of Graphical Models by Lower Secondary Students
NASA Astrophysics Data System (ADS)
van Buuren, Onne; Heck, André; Ellermeijer, Ton
2016-10-01
A learning path has been developed on system dynamical graphical modelling, integrated into the Dutch lower secondary physics curriculum. As part of the developmental research for this learning path, students' understanding of the relation structures shown in the diagrams of graphical system dynamics based models has been investigated. One of our main findings is that only some students understand these structures correctly. Reality-based interpretation of the diagrams can conceal an incorrect understanding of diagram structures. As a result, students seemingly have no problems interpreting the diagrams until they are asked to construct a graphical model. Misconceptions have been identified that are the consequence of the fact that the equations are not clearly communicated by the diagrams or because the icons used in the diagrams mislead novice modellers. Suggestions are made for improvements.
Word-level language modeling for P300 spellers based on discriminative graphical models
NASA Astrophysics Data System (ADS)
Delgado Saa, Jaime F.; de Pesters, Adriana; McFarland, Dennis; Çetin, Müjdat
2015-04-01
Objective. In this work we propose a probabilistic graphical model framework that uses language priors at the level of words as a mechanism to increase the performance of P300-based spellers. Approach. This paper is concerned with brain-computer interfaces based on P300 spellers. Motivated by P300 spelling scenarios involving communication based on a limited vocabulary, we propose a probabilistic graphical model framework and an associated classification algorithm that uses learned statistical models of language at the level of words. Exploiting such high-level contextual information helps reduce the error rate of the speller. Main results. Our experimental results demonstrate that the proposed approach offers several advantages over existing methods. Most importantly, it increases the classification accuracy while reducing the number of times the letters need to be flashed, increasing the communication rate of the system. Significance. The proposed approach models all the variables in the P300 speller in a unified framework and has the capability to correct errors in previous letters in a word, given the data for the current one. The structure of the model we propose allows the use of efficient inference algorithms, which in turn makes it possible to use this approach in real-time applications.
Graphical modelling of carbon nanotube field effect transistor
NASA Astrophysics Data System (ADS)
Sahoo, R.; Mishra, R. R.
2015-02-01
Carbon nanotube Field Effect Transistors (CNTFET) are found to be one of the most promising successors to conventional Si-MOSFET. This paper presents a novel modelling for planar CNTFET based on curve fitting method. The results obtained from the model are compared with the simulated results obtained by using the nanohub simulator. Finally the accuracy of the model is discussed by calculating the normalized root mean square difference between the nanohub simulation results and those obtained from the proposed model.
Graphical Means for Inspecting Qualitative Models of System Behaviour
ERIC Educational Resources Information Center
Bouwer, Anders; Bredeweg, Bert
2010-01-01
This article presents the design and evaluation of a tool for inspecting conceptual models of system behaviour. The basis for this research is the Garp framework for qualitative simulation. This framework includes modelling primitives, such as entities, quantities and causal dependencies, which are combined into model fragments and scenarios.…
Use and abuse of mixing models (MixSIAR)
Background/Question/MethodsCharacterizing trophic links in food webs is a fundamental ecological question. In our efforts to quantify energy flow through food webs, ecologists have increasingly used mixing models to analyze biological tracer data, often from stable isotopes. Whil...
PRay - A graphical user interface for interactive visualization and modification of rayinvr models
NASA Astrophysics Data System (ADS)
Fromm, T.
2016-01-01
PRay is a graphical user interface for interactive displaying and editing of velocity models for seismic refraction. It is optimized for editing rayinvr models but can also be used as a dynamic viewer for ray tracing results from other software. The main features are the graphical editing of nodes and fast adjusting of the display (stations and phases). It can be extended by user-defined shell scripts and links to phase picking software. PRay is open source software written in the scripting language Perl, runs on Unix-like operating systems including Mac OS X and provides a version controlled source code repository for community development.
Three-dimensional interactive graphics for displaying and modelling microscopic data.
Basinski, M; Deatherage, J F
1990-09-01
EUCLID is a three-dimensional (3D) general purpose graphics display package for interactive manipulation of vector, surface and solid drawings on Evans and Sutherland PS300 series graphics processors. It is useful for displaying, comparing, measuring and modelling 3D microscopic images in real time. EUCLID can assemble groups of drawings into a composite drawing, while retaining the ability to operate upon the individual drawings within the composite drawing separately. EUCLID is capable of real time geometrical transformations (scaling, translation and rotation in two coordinate frames) and stereo and perspective viewing transformations. Because of its flexibility, EUCLID is especially useful for fitting models into 3D microscopic images.
Greiner, Matthias; Smid, Joost; Havelaar, Arie H; Müller-Graf, Christine
2013-05-15
Quantitative microbiological risk assessment (QMRA) models are used to reflect knowledge about complex real-world scenarios for the propagation of microbiological hazards along the feed and food chain. The aim is to provide insight into interdependencies among model parameters, typically with an interest to characterise the effect of risk mitigation measures. A particular requirement is to achieve clarity about the reliability of conclusions from the model in the presence of uncertainty. To this end, Monte Carlo (MC) simulation modelling has become a standard in so-called probabilistic risk assessment. In this paper, we elaborate on the application of Bayesian computational statistics in the context of QMRA. It is useful to explore the analogy between MC modelling and Bayesian inference (BI). This pertains in particular to the procedures for deriving prior distributions for model parameters. We illustrate using a simple example that the inability to cope with feedback among model parameters is a major limitation of MC modelling. However, BI models can be easily integrated into MC modelling to overcome this limitation. We refer a BI submodel integrated into a MC model to as a "Bayes domain". We also demonstrate that an entire QMRA model can be formulated as Bayesian graphical model (BGM) and discuss the advantages of this approach. Finally, we show example graphs of MC, BI and BGM models, highlighting the similarities among the three approaches.
Variational upper and lower bounds for probabilistic graphical models.
Wexler, Ydo; Geiger, Dan
2008-09-01
Probabilistic phylogenetic models which relax the site independence evolution assumption often face the problem of infeasible likelihood computations, for example, for the task of selecting suitable parameters for the model. We present a new approximation method, applicable for a wide range of probabilistic models, which guarantees to upper and lower bound the true likelihood of data, and apply it to the problem of probabilistic phylogenetic models. The new method is complementary to known variational methods that lower bound the likelihood, and it uses similar methods to optimize the bounds from above and below. We applied our method to aligned DNA sequences of various lengths from human in the region of the CFTR gene and homologous from eight mammals, and found the bounds to be appreciably close to the true likelihood whenever it could be computed. When computing the exact likelihood was not feasible, we demonstrated the proximity of the upper and lower variational bounds, implying a tight approximation of the likelihood.
A graphical vector autoregressive modelling approach to the analysis of electronic diary data
2010-01-01
Background In recent years, electronic diaries are increasingly used in medical research and practice to investigate patients' processes and fluctuations in symptoms over time. To model dynamic dependence structures and feedback mechanisms between symptom-relevant variables, a multivariate time series method has to be applied. Methods We propose to analyse the temporal interrelationships among the variables by a structural modelling approach based on graphical vector autoregressive (VAR) models. We give a comprehensive description of the underlying concepts and explain how the dependence structure can be recovered from electronic diary data by a search over suitable constrained (graphical) VAR models. Results The graphical VAR approach is applied to the electronic diary data of 35 obese patients with and without binge eating disorder (BED). The dynamic relationships for the two subgroups between eating behaviour, depression, anxiety and eating control are visualized in two path diagrams. Results show that the two subgroups of obese patients with and without BED are distinguishable by the temporal patterns which influence their respective eating behaviours. Conclusion The use of the graphical VAR approach for the analysis of electronic diary data leads to a deeper insight into patient's dynamics and dependence structures. An increasing use of this modelling approach could lead to a better understanding of complex psychological and physiological mechanisms in different areas of medical care and research. PMID:20359333
Automatic Construction of Anomaly Detectors from Graphical Models
Ferragut, Erik M; Darmon, David M; Shue, Craig A; Kelley, Stephen
2011-01-01
Detection of rare or previously unseen attacks in cyber security presents a central challenge: how does one search for a sufficiently wide variety of types of anomalies and yet allow the process to scale to increasingly complex data? In particular, creating each anomaly detector manually and training each one separately presents untenable strains on both human and computer resources. In this paper we propose a systematic method for constructing a potentially very large number of complementary anomaly detectors from a single probabilistic model of the data. Only one model needs to be trained, but numerous detectors can then be implemented. This approach promises to scale better than manual methods to the complex heterogeneity of real-life data. As an example, we develop a Latent Dirichlet Allocation probability model of TCP connections entering Oak Ridge National Laboratory. We show that several detectors can be automatically constructed from the model and will provide anomaly detection at flow, sub-flow, and host (both server and client) levels. This demonstrates how the fundamental connection between anomaly detection and probabilistic modeling can be exploited to develop more robust operational solutions.
C4: Exploring Multiple Solutions in Graphical Models by Cluster Sampling.
Porway, Jake; Zhu, Song-Chun
2011-09-01
This paper presents a novel Markov Chain Monte Carlo (MCMC) inference algorithm called C(4)--Clustering with Cooperative and Competitive Constraints--for computing multiple solutions from posterior probabilities defined on graphical models, including Markov random fields (MRF), conditional random fields (CRF), and hierarchical models. The graphs may have both positive and negative edges for cooperative and competitive constraints. C(4) is a probabilistic clustering algorithm in the spirit of Swendsen-Wang. By turning the positive edges on/off probabilistically, C(4) partitions the graph into a number of connected components (ccps) and each ccp is a coupled subsolution with nodes connected by positive edges. Then, by turning the negative edges on/off probabilistically, C(4) obtains composite ccps (called cccps) with competing ccps connected by negative edges. At each step, C(4) flips the labels of all nodes in a cccp so that nodes in each ccp keep the same label while different ccps are assigned different labels to observe both positive and negative constraints. Thus, the algorithm can jump between multiple competing solutions (or modes of the posterior probability) in a single or a few steps. It computes multiple distinct solutions to preserve the intrinsic ambiguities and avoids premature commitments to a single solution that may not be valid given later context. C(4) achieves a mixing rate faster than existing MCMC methods, such as various Gibbs samplers and Swendsen-Wang cuts. It is also more "dynamic" than common optimization methods such as ICM, LBP, and graph cuts. We demonstrate the C(4) algorithm in line drawing interpretation, scene labeling, and object recognition.
Probabilistic assessment of agricultural droughts using graphical models
NASA Astrophysics Data System (ADS)
Ramadas, Meenu; Govindaraju, Rao S.
2015-07-01
Agricultural droughts are often characterized by soil moisture in the root zone of the soil, but crop needs are rarely factored into the analysis. Since water needs vary with crops, agricultural drought incidences in a region can be characterized better if crop responses to soil water deficits are also accounted for in the drought index. This study investigates agricultural droughts driven by plant stress due to soil moisture deficits using crop stress functions available in the literature. Crop water stress is assumed to begin at the soil moisture level corresponding to incipient stomatal closure, and reaches its maximum at the crop's wilting point. Using available location-specific crop acreage data, a weighted crop water stress function is computed. A new probabilistic agricultural drought index is then developed within a hidden Markov model (HMM) framework that provides model uncertainty in drought classification and accounts for time dependence between drought states. The proposed index allows probabilistic classification of the drought states and takes due cognizance of the stress experienced by the crop due to soil moisture deficit. The capabilities of HMM model formulations for assessing agricultural droughts are compared to those of current drought indices such as standardized precipitation evapotranspiration index (SPEI) and self-calibrating Palmer drought severity index (SC-PDSI). The HMM model identified critical drought events and several drought occurrences that are not detected by either SPEI or SC-PDSI, and shows promise as a tool for agricultural drought studies.
A Monthly Water-Balance Model Driven By a Graphical User Interface
McCabe, Gregory J.; Markstrom, Steven L.
2007-01-01
This report describes a monthly water-balance model driven by a graphical user interface, referred to as the Thornthwaite monthly water-balance program. Computations of monthly water-balance components of the hydrologic cycle are made for a specified location. The program can be used as a research tool, an assessment tool, and a tool for classroom instruction.
Parallelized CCHE2D flow model with CUDA Fortran on Graphics Process Units
Technology Transfer Automated Retrieval System (TEKTRAN)
This paper presents the CCHE2D implicit flow model parallelized using CUDA Fortran programming technique on Graphics Processing Units (GPUs). A parallelized implicit Alternating Direction Implicit (ADI) solver using Parallel Cyclic Reduction (PCR) algorithm on GPU is developed and tested. This solve...
A Practical Probabilistic Graphical Modeling Tool for Weighing ...
Past weight-of-evidence frameworks for adverse ecological effects have provided soft-scoring procedures for judgments based on the quality and measured attributes of evidence. Here, we provide a flexible probabilistic structure for weighing and integrating lines of evidence for ecological risk determinations. Probabilistic approaches can provide both a quantitative weighing of lines of evidence and methods for evaluating risk and uncertainty. The current modeling structure wasdeveloped for propagating uncertainties in measured endpoints and their influence on the plausibility of adverse effects. To illustrate the approach, we apply the model framework to the sediment quality triad using example lines of evidence for sediment chemistry measurements, bioassay results, and in situ infauna diversity of benthic communities using a simplified hypothetical case study. We then combine the three lines evidence and evaluate sensitivity to the input parameters, and show how uncertainties are propagated and how additional information can be incorporated to rapidly update the probability of impacts. The developed network model can be expanded to accommodate additional lines of evidence, variables and states of importance, and different types of uncertainties in the lines of evidence including spatial and temporal as well as measurement errors. We provide a flexible Bayesian network structure for weighing and integrating lines of evidence for ecological risk determinations
Quantifying uncertainty in stable isotope mixing models
Davis, Paul; Syme, James; Heikoop, Jeffrey; Fessenden-Rahn, Julianna; Perkins, George; Newman, Brent; Chrystal, Abbey E.; Hagerty, Shannon B.
2015-05-19
Mixing models are powerful tools for identifying biogeochemical sources and determining mixing fractions in a sample. However, identification of actual source contributors is often not simple, and source compositions typically vary or even overlap, significantly increasing model uncertainty in calculated mixing fractions. This study compares three probabilistic methods, SIAR [Parnell et al., 2010] a pure Monte Carlo technique (PMC), and Stable Isotope Reference Source (SIRS) mixing model, a new technique that estimates mixing in systems with more than three sources and/or uncertain source compositions. In this paper, we use nitrate stable isotope examples (δ^{15}N and δ^{18}O) but all methods tested are applicable to other tracers. In Phase I of a three-phase blind test, we compared methods for a set of six-source nitrate problems. PMC was unable to find solutions for two of the target water samples. The Bayesian method, SIAR, experienced anchoring problems, and SIRS calculated mixing fractions that most closely approximated the known mixing fractions. For that reason, SIRS was the only approach used in the next phase of testing. In Phase II, the problem was broadened where any subset of the six sources could be a possible solution to the mixing problem. Results showed a high rate of Type I errors where solutions included sources that were not contributing to the sample. In Phase III some sources were eliminated based on assumed site knowledge and assumed nitrate concentrations, substantially reduced mixing fraction uncertainties and lowered the Type I error rate. These results demonstrate that valuable insights into stable isotope mixing problems result from probabilistic mixing model approaches like SIRS. The results also emphasize the importance of identifying a minimal set of potential sources and quantifying uncertainties in source isotopic composition as well as demonstrating the value of additional information in reducing the
Quantifying uncertainty in stable isotope mixing models
Davis, Paul; Syme, James; Heikoop, Jeffrey; ...
2015-05-19
Mixing models are powerful tools for identifying biogeochemical sources and determining mixing fractions in a sample. However, identification of actual source contributors is often not simple, and source compositions typically vary or even overlap, significantly increasing model uncertainty in calculated mixing fractions. This study compares three probabilistic methods, SIAR [Parnell et al., 2010] a pure Monte Carlo technique (PMC), and Stable Isotope Reference Source (SIRS) mixing model, a new technique that estimates mixing in systems with more than three sources and/or uncertain source compositions. In this paper, we use nitrate stable isotope examples (δ15N and δ18O) but all methods testedmore » are applicable to other tracers. In Phase I of a three-phase blind test, we compared methods for a set of six-source nitrate problems. PMC was unable to find solutions for two of the target water samples. The Bayesian method, SIAR, experienced anchoring problems, and SIRS calculated mixing fractions that most closely approximated the known mixing fractions. For that reason, SIRS was the only approach used in the next phase of testing. In Phase II, the problem was broadened where any subset of the six sources could be a possible solution to the mixing problem. Results showed a high rate of Type I errors where solutions included sources that were not contributing to the sample. In Phase III some sources were eliminated based on assumed site knowledge and assumed nitrate concentrations, substantially reduced mixing fraction uncertainties and lowered the Type I error rate. These results demonstrate that valuable insights into stable isotope mixing problems result from probabilistic mixing model approaches like SIRS. The results also emphasize the importance of identifying a minimal set of potential sources and quantifying uncertainties in source isotopic composition as well as demonstrating the value of additional information in reducing the uncertainty in calculated
Quantifying uncertainty in stable isotope mixing models
NASA Astrophysics Data System (ADS)
Davis, Paul; Syme, James; Heikoop, Jeffrey; Fessenden-Rahn, Julianna; Perkins, George; Newman, Brent; Chrystal, Abbey E.; Hagerty, Shannon B.
2015-05-01
Mixing models are powerful tools for identifying biogeochemical sources and determining mixing fractions in a sample. However, identification of actual source contributors is often not simple, and source compositions typically vary or even overlap, significantly increasing model uncertainty in calculated mixing fractions. This study compares three probabilistic methods, Stable Isotope Analysis in R (SIAR), a pure Monte Carlo technique (PMC), and Stable Isotope Reference Source (SIRS) mixing model, a new technique that estimates mixing in systems with more than three sources and/or uncertain source compositions. In this paper, we use nitrate stable isotope examples (δ15N and δ18O) but all methods tested are applicable to other tracers. In Phase I of a three-phase blind test, we compared methods for a set of six-source nitrate problems. PMC was unable to find solutions for two of the target water samples. The Bayesian method, SIAR, experienced anchoring problems, and SIRS calculated mixing fractions that most closely approximated the known mixing fractions. For that reason, SIRS was the only approach used in the next phase of testing. In Phase II, the problem was broadened where any subset of the six sources could be a possible solution to the mixing problem. Results showed a high rate of Type I errors where solutions included sources that were not contributing to the sample. In Phase III some sources were eliminated based on assumed site knowledge and assumed nitrate concentrations, substantially reduced mixing fraction uncertainties and lowered the Type I error rate. These results demonstrate that valuable insights into stable isotope mixing problems result from probabilistic mixing model approaches like SIRS. The results also emphasize the importance of identifying a minimal set of potential sources and quantifying uncertainties in source isotopic composition as well as demonstrating the value of additional information in reducing the uncertainty in calculated
Transition mixing study empirical model report
NASA Technical Reports Server (NTRS)
Srinivasan, R.; White, C.
1988-01-01
The empirical model developed in the NASA Dilution Jet Mixing Program has been extended to include the curvature effects of transition liners. This extension is based on the results of a 3-D numerical model generated under this contract. The empirical model results agree well with the numerical model results for all tests cases evaluated. The empirical model shows faster mixing rates compared to the numerical model. Both models show drift of jets toward the inner wall of a turning duct. The structure of the jets from the inner wall does not exhibit the familiar kidney-shaped structures observed for the outer wall jets or for jets injected in rectangular ducts.
Austin, Peter C; Steyerberg, Ewout W
2014-02-10
Predicting the probability of the occurrence of a binary outcome or condition is important in biomedical research. While assessing discrimination is an essential issue in developing and validating binary prediction models, less attention has been paid to methods for assessing model calibration. Calibration refers to the degree of agreement between observed and predicted probabilities and is often assessed by testing for lack-of-fit. The objective of our study was to examine the ability of graphical methods to assess the calibration of logistic regression models. We examined lack of internal calibration, which was related to misspecification of the logistic regression model, and external calibration, which was related to an overfit model or to shrinkage of the linear predictor. We conducted an extensive set of Monte Carlo simulations with a locally weighted least squares regression smoother (i.e., the loess algorithm) to examine the ability of graphical methods to assess model calibration. We found that loess-based methods were able to provide evidence of moderate departures from linearity and indicate omission of a moderately strong interaction. Misspecification of the link function was harder to detect. Visual patterns were clearer with higher sample sizes, higher incidence of the outcome, or higher discrimination. Loess-based methods were also able to identify the lack of calibration in external validation samples when an overfit regression model had been used. In conclusion, loess-based smoothing methods are adequate tools to graphically assess calibration and merit wider application.
Experiments with a low-cost system for computer graphics material model acquisition
NASA Astrophysics Data System (ADS)
Rushmeier, Holly; Lockerman, Yitzhak; Cartwright, Luke; Pitera, David
2015-03-01
We consider the design of an inexpensive system for acquiring material models for computer graphics rendering applications in animation, games and conceptual design. To be useful in these applications a system must be able to model a rich range of appearances in a computationally tractable form. The range of appearance of interest in computer graphics includes materials that have spatially varying properties, directionality, small-scale geometric structure, and subsurface scattering. To be computationally tractable, material models for graphics must be compact, editable, and efficient to numerically evaluate for ray tracing importance sampling. To construct appropriate models for a range of interesting materials, we take the approach of separating out directly and indirectly scattered light using high spatial frequency patterns introduced by Nayar et al. in 2006. To acquire the data at low cost, we use a set of Raspberry Pi computers and cameras clamped to miniature projectors. We explore techniques to separate out surface and subsurface indirect lighting. This separation would allow the fitting of simple, and so tractable, analytical models to features of the appearance model. The goal of the system is to provide models for physically accurate renderings that are visually equivalent to viewing the original physical materials.
VISUAL PLUMES MIXING ZONE MODELING SOFTWARE
The U.S. Environmental Protection Agency has a long history of both supporting plume model development and providing mixing zone modeling software. The Visual Plumes model is the most recent addition to the suite of public-domain models available through the EPA-Athens Center f...
Extended Generalized Linear Latent and Mixed Model
ERIC Educational Resources Information Center
Segawa, Eisuke; Emery, Sherry; Curry, Susan J.
2008-01-01
The generalized linear latent and mixed modeling (GLLAMM framework) includes many models such as hierarchical and structural equation models. However, GLLAMM cannot currently accommodate some models because it does not allow some parameters to be random. GLLAMM is extended to overcome the limitation by adding a submodel that specifies a…
ERIC Educational Resources Information Center
Crow, Wendell C.
This paper suggests ways in which manifest, physical attributes of graphic elements can be described and measured. It also proposes a preliminary conceptual model that accounts for the readily apparent, measurable variables in a visual message. The graphic elements that are described include format, typeface, and photographs/artwork. The…
From least squares to multilevel modeling: A graphical introduction to Bayesian inference
NASA Astrophysics Data System (ADS)
Loredo, Thomas J.
2016-01-01
This tutorial presentation will introduce some of the key ideas and techniques involved in applying Bayesian methods to problems in astrostatistics. The focus will be on the big picture: understanding the foundations (interpreting probability, Bayes's theorem, the law of total probability and marginalization), making connections to traditional methods (propagation of errors, least squares, chi-squared, maximum likelihood, Monte Carlo simulation), and highlighting problems where a Bayesian approach can be particularly powerful (Poisson processes, density estimation and curve fitting with measurement error). The "graphical" component of the title reflects an emphasis on pictorial representations of some of the math, but also on the use of graphical models (multilevel or hierarchical models) for analyzing complex data. Code for some examples from the talk will be available to participants, in Python and in the Stan probabilistic programming language.
A semiparametric graphical modelling approach for large-scale equity selection
Liu, Han; Mulvey, John; Zhao, Tianqi
2016-01-01
We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption. PMID:28316507
Pecevski, Dejan; Buesing, Lars; Maass, Wolfgang
2011-12-01
An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows ("explaining away") and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons.
Learned graphical models for probabilistic planning provide a new class of movement primitives.
Rückert, Elmar A; Neumann, Gerhard; Toussaint, Marc; Maass, Wolfgang
2012-01-01
BIOLOGICAL MOVEMENT GENERATION COMBINES THREE INTERESTING ASPECTS: its modular organization in movement primitives (MPs), its characteristics of stochastic optimality under perturbations, and its efficiency in terms of learning. A common approach to motor skill learning is to endow the primitives with dynamical systems. Here, the parameters of the primitive indirectly define the shape of a reference trajectory. We propose an alternative MP representation based on probabilistic inference in learned graphical models with new and interesting properties that complies with salient features of biological movement control. Instead of endowing the primitives with dynamical systems, we propose to endow MPs with an intrinsic probabilistic planning system, integrating the power of stochastic optimal control (SOC) methods within a MP. The parameterization of the primitive is a graphical model that represents the dynamics and intrinsic cost function such that inference in this graphical model yields the control policy. We parameterize the intrinsic cost function using task-relevant features, such as the importance of passing through certain via-points. The system dynamics as well as intrinsic cost function parameters are learned in a reinforcement learning (RL) setting. We evaluate our approach on a complex 4-link balancing task. Our experiments show that our movement representation facilitates learning significantly and leads to better generalization to new task settings without re-learning.
Surles, M. C.; Richardson, J. S.; Richardson, D. C.; Brooks, F. P.
1994-01-01
We describe a new paradigm for modeling proteins in interactive computer graphics systems--continual maintenance of a physically valid representation, combined with direct user control and visualization. This is achieved by a fast algorithm for energy minimization, capable of real-time performance on all atoms of a small protein, plus graphically specified user tugs. The modeling system, called Sculpt, rigidly constrains bond lengths, bond angles, and planar groups (similar to existing interactive modeling programs), while it applies elastic restraints to minimize the potential energy due to torsions, hydrogen bonds, and van der Waals and electrostatic interactions (similar to existing batch minimization programs), and user-specified springs. The graphical interface can show bad and/or favorable contacts, and individual energy terms can be turned on or off to determine their effects and interactions. Sculpt finds a local minimum of the total energy that satisfies all the constraints using an augmented Lagrange-multiplier method; calculation time increases only linearly with the number of atoms because the matrix of constraint gradients is sparse and banded. On a 100-MHz MIPS R4000 processor (Silicon Graphics Indigo), Sculpt achieves 11 updates per second on a 20-residue fragment and 2 updates per second on an 80-residue protein, using all atoms except non-H-bonding hydrogens, and without electrostatic interactions. Applications of Sculpt are described: to reverse the direction of bundle packing in a designed 4-helix bundle protein, to fold up a 2-stranded beta-ribbon into an approximate beta-barrel, and to design the sequence and conformation of a 30-residue peptide that mimics one partner of a protein subunit interaction. Computer models that are both interactive and physically realistic (within the limitations of a given force field) have 2 significant advantages: (1) they make feasible the modeling of very large changes (such as needed for de novo design), and
Surles, M C; Richardson, J S; Richardson, D C; Brooks, F P
1994-02-01
We describe a new paradigm for modeling proteins in interactive computer graphics systems--continual maintenance of a physically valid representation, combined with direct user control and visualization. This is achieved by a fast algorithm for energy minimization, capable of real-time performance on all atoms of a small protein, plus graphically specified user tugs. The modeling system, called Sculpt, rigidly constrains bond lengths, bond angles, and planar groups (similar to existing interactive modeling programs), while it applies elastic restraints to minimize the potential energy due to torsions, hydrogen bonds, and van der Waals and electrostatic interactions (similar to existing batch minimization programs), and user-specified springs. The graphical interface can show bad and/or favorable contacts, and individual energy terms can be turned on or off to determine their effects and interactions. Sculpt finds a local minimum of the total energy that satisfies all the constraints using an augmented Lagrange-multiplier method; calculation time increases only linearly with the number of atoms because the matrix of constraint gradients is sparse and banded. On a 100-MHz MIPS R4000 processor (Silicon Graphics Indigo), Sculpt achieves 11 updates per second on a 20-residue fragment and 2 updates per second on an 80-residue protein, using all atoms except non-H-bonding hydrogens, and without electrostatic interactions. Applications of Sculpt are described: to reverse the direction of bundle packing in a designed 4-helix bundle protein, to fold up a 2-stranded beta-ribbon into an approximate beta-barrel, and to design the sequence and conformation of a 30-residue peptide that mimics one partner of a protein subunit interaction. Computer models that are both interactive and physically realistic (within the limitations of a given force field) have 2 significant advantages: (1) they make feasible the modeling of very large changes (such as needed for de novo design), and
Cylindrical Mixing Layer Model in Stellar Jet
NASA Astrophysics Data System (ADS)
Choe, Seung-Urn; Yu, Kyoung Hee
1994-12-01
We have developed a cylindrical mixing layer model of a stellar jet including cooling effect in order to understand an optical emission mechanism along collimated high velocity stellar jets associated with young stellar objects. The cylindrical results have been calculated to be the same as the 2D ones presented by Canto & Raga(1991) because the entrainment efficiency in our cylindrical model has been obtained to be the same value as the 2D model has given. We have discussed the morphological and physical characteristics of the mixing layers by the cooling effect. As the jet Mach number increases, the initial temperature of the mixing layer goes high because the kinetic energy of the jet partly converts to the thermal energy of the mixing layer. The initial cooling of the mixing layer is very severe, changing its outer boundary radius. A subsequent change becomes adiabatic. The number of the Mach disks in the stellar jet and the total radiative luminosity of the mixing layer, based on our cylindrical calculation, have quite agreed with the observation.
NASA Technical Reports Server (NTRS)
Treinish, Lloyd A.; Gough, Michael L.; Wildenhain, W. David
1987-01-01
The capability was developed of rapidly producing visual representations of large, complex, multi-dimensional space and earth sciences data sets via the implementation of computer graphics modeling techniques on the Massively Parallel Processor (MPP) by employing techniques recently developed for typically non-scientific applications. Such capabilities can provide a new and valuable tool for the understanding of complex scientific data, and a new application of parallel computing via the MPP. A prototype system with such capabilities was developed and integrated into the National Space Science Data Center's (NSSDC) Pilot Climate Data System (PCDS) data-independent environment for computer graphics data display to provide easy access to users. While developing these capabilities, several problems had to be solved independently of the actual use of the MPP, all of which are outlined.
The effects of a dynamic graphical model during simulation-based training of console operation skill
NASA Technical Reports Server (NTRS)
Farquhar, John D.; Regian, J. Wesley
1993-01-01
LOADER is a Windows-based simulation of a complex procedural task. The task requires subjects to execute long sequences of console-operation actions (e.g., button presses, switch actuations, dial rotations) to accomplish specific goals. The LOADER interface is a graphical computer-simulated console which controls railroad cars, tracks, and cranes in a fictitious railroad yard. We hypothesized that acquisition of LOADER performance skill would be supported by the representation of a dynamic graphical model linking console actions to goal and goal states in the 'railroad yard'. Twenty-nine subjects were randomly assigned to one of two treatments (i.e., dynamic model or no model). During training, both groups received identical text-based instruction in an instructional-window above the LOADER interface. One group, however, additionally saw a dynamic version of the bird's-eye view of the railroad yard. After training, both groups were tested under identical conditions. They were asked to perform the complete procedure without guidance and without access to either type of railroad yard representation. Results indicate that rather than becoming dependent on the animated rail yard model, subjects in the dynamic model condition apparently internalized the model, as evidenced by their performance after the model was removed.
A Module for Graphical Display of Model Results with the CBP Toolbox
Smith, F.
2015-04-21
This report describes work performed by the Savannah River National Laboratory (SRNL) in fiscal year 2014 to add enhanced graphical capabilities to display model results in the Cementitious Barriers Project (CBP) Toolbox. Because Version 2.0 of the CBP Toolbox has just been released, the graphing enhancements described in this report have not yet been integrated into a new version of the Toolbox. Instead they have been tested using a standalone GoldSim model and, while they are substantially complete, may undergo further refinement before full implementation. Nevertheless, this report is issued to document the FY14 development efforts which will provide a basis for further development of the CBP Toolbox.
Praveen, Paurush; Fröhlich, Holger
2013-01-01
Inferring regulatory networks from experimental data via probabilistic graphical models is a popular framework to gain insights into biological systems. However, the inherent noise in experimental data coupled with a limited sample size reduces the performance of network reverse engineering. Prior knowledge from existing sources of biological information can address this low signal to noise problem by biasing the network inference towards biologically plausible network structures. Although integrating various sources of information is desirable, their heterogeneous nature makes this task challenging. We propose two computational methods to incorporate various information sources into a probabilistic consensus structure prior to be used in graphical model inference. Our first model, called Latent Factor Model (LFM), assumes a high degree of correlation among external information sources and reconstructs a hidden variable as a common source in a Bayesian manner. The second model, a Noisy-OR, picks up the strongest support for an interaction among information sources in a probabilistic fashion. Our extensive computational studies on KEGG signaling pathways as well as on gene expression data from breast cancer and yeast heat shock response reveal that both approaches can significantly enhance the reconstruction accuracy of Bayesian Networks compared to other competing methods as well as to the situation without any prior. Our framework allows for using diverse information sources, like pathway databases, GO terms and protein domain data, etc. and is flexible enough to integrate new sources, if available.
Spike-based probabilistic inference in analog graphical models using interspike-interval coding.
Steimer, Andreas; Douglas, Rodney
2013-09-01
Temporal spike codes play a crucial role in neural information processing. In particular, there is strong experimental evidence that interspike intervals (ISIs) are used for stimulus representation in neural systems. However, very few algorithmic principles exploit the benefits of such temporal codes for probabilistic inference of stimuli or decisions. Here, we describe and rigorously prove the functional properties of a spike-based processor that uses ISI distributions to perform probabilistic inference. The abstract processor architecture serves as a building block for more concrete, neural implementations of the belief-propagation (BP) algorithm in arbitrary graphical models (e.g., Bayesian networks and factor graphs). The distributed nature of graphical models matches well with the architectural and functional constraints imposed by biology. In our model, ISI distributions represent the BP messages exchanged between factor nodes, leading to the interpretation of a single spike as a random sample that follows such a distribution. We verify the abstract processor model by numerical simulation in full graphs, and demonstrate that it can be applied even in the presence of analog variables. As a particular example, we also show results of a concrete, neural implementation of the processor, although in principle our approach is more flexible and allows different neurobiological interpretations. Furthermore, electrophysiological data from area LIP during behavioral experiments are assessed in light of ISI coding, leading to concrete testable, quantitative predictions and a more accurate description of these data compared to hitherto existing models.
The Mixed Effects Trend Vector Model
ERIC Educational Resources Information Center
de Rooij, Mark; Schouteden, Martijn
2012-01-01
Maximum likelihood estimation of mixed effect baseline category logit models for multinomial longitudinal data can be prohibitive due to the integral dimension of the random effects distribution. We propose to use multidimensional unfolding methodology to reduce the dimensionality of the problem. As a by-product, readily interpretable graphical…
Mixed deterministic and probabilistic networks.
Mateescu, Robert; Dechter, Rina
2008-11-01
The paper introduces mixed networks, a new graphical model framework for expressing and reasoning with probabilistic and deterministic information. The motivation to develop mixed networks stems from the desire to fully exploit the deterministic information (constraints) that is often present in graphical models. Several concepts and algorithms specific to belief networks and constraint networks are combined, achieving computational efficiency, semantic coherence and user-interface convenience. We define the semantics and graphical representation of mixed networks, and discuss the two main types of algorithms for processing them: inference-based and search-based. A preliminary experimental evaluation shows the benefits of the new model.
Mixed deterministic and probabilistic networks
Dechter, Rina
2010-01-01
The paper introduces mixed networks, a new graphical model framework for expressing and reasoning with probabilistic and deterministic information. The motivation to develop mixed networks stems from the desire to fully exploit the deterministic information (constraints) that is often present in graphical models. Several concepts and algorithms specific to belief networks and constraint networks are combined, achieving computational efficiency, semantic coherence and user-interface convenience. We define the semantics and graphical representation of mixed networks, and discuss the two main types of algorithms for processing them: inference-based and search-based. A preliminary experimental evaluation shows the benefits of the new model. PMID:20981243
Wavelet-based functional mixed models
Morris, Jeffrey S.; Carroll, Raymond J.
2009-01-01
Summary Increasingly, scientific studies yield functional data, in which the ideal units of observation are curves and the observed data consist of sets of curves that are sampled on a fine grid. We present new methodology that generalizes the linear mixed model to the functional mixed model framework, with model fitting done by using a Bayesian wavelet-based approach. This method is flexible, allowing functions of arbitrary form and the full range of fixed effects structures and between-curve covariance structures that are available in the mixed model framework. It yields nonparametric estimates of the fixed and random-effects functions as well as the various between-curve and within-curve covariance matrices. The functional fixed effects are adaptively regularized as a result of the non-linear shrinkage prior that is imposed on the fixed effects’ wavelet coefficients, and the random-effect functions experience a form of adaptive regularization because of the separately estimated variance components for each wavelet coefficient. Because we have posterior samples for all model quantities, we can perform pointwise or joint Bayesian inference or prediction on the quantities of the model. The adaptiveness of the method makes it especially appropriate for modelling irregular functional data that are characterized by numerous local features like peaks. PMID:19759841
2008-04-07
interest in brain -like computing architectures. In July of 2005, Toin De’an, the principal investigator for this grant presented a papir at AAAI...Hintlon gave his Research Excellince Aw;rd lecture entitled "\\ht kind of a graphical model is the brain ?" In all three cases, the visual cortex is cast...distinctive features. There are cells in the retina, lateral genlat eandii p6imaxy visual corex whose rmqA[&tv lields s"an space andh timle and are
NASA Technical Reports Server (NTRS)
Goel, Narendra S.; Rozehnal, Ivan; Thompson, Richard L.
1991-01-01
A computer-graphics-based model, named DIANA, is presented for generation of objects of arbitrary shape and for calculating bidirectional reflectances and scattering from them, in the visible and infrared region. The computer generation is based on a modified Lindenmayer system approach which makes it possible to generate objects of arbitrary shapes and to simulate their growth, dynamics, and movement. Rendering techniques are used to display an object on a computer screen with appropriate shading and shadowing and to calculate the scattering and reflectance from the object. The technique is illustrated with scattering from canopies of simulated corn plants.
Simplified models of mixed dark matter
Cheung, Clifford; Sanford, David E-mail: dsanford@caltech.edu
2014-02-01
We explore simplified models of mixed dark matter (DM), defined here to be a stable relic composed of a singlet and an electroweak charged state. Our setup describes a broad spectrum of thermal DM candidates that can naturally accommodate the observed DM abundance but are subject to substantial constraints from current and upcoming direct detection experiments. We identify ''blind spots'' at which the DM-Higgs coupling is identically zero, thus nullifying direct detection constraints on spin independent scattering. Furthermore, we characterize the fine-tuning in mixing angles, i.e. well-tempering, required for thermal freeze-out to accommodate the observed abundance. Present and projected limits from LUX and XENON1T force many thermal relic models into blind spot tuning, well-tempering, or both. This simplified model framework generalizes bino-Higgsino DM in the MSSM, singlino-Higgsino DM in the NMSSM, and scalar DM candidates that appear in models of extended Higgs sectors.
Optimizing ion channel models using a parallel genetic algorithm on graphical processors.
Ben-Shalom, Roy; Aviv, Amit; Razon, Benjamin; Korngreen, Alon
2012-01-01
We have recently shown that we can semi-automatically constrain models of voltage-gated ion channels by combining a stochastic search algorithm with ionic currents measured using multiple voltage-clamp protocols. Although numerically successful, this approach is highly demanding computationally, with optimization on a high performance Linux cluster typically lasting several days. To solve this computational bottleneck we converted our optimization algorithm for work on a graphical processing unit (GPU) using NVIDIA's CUDA. Parallelizing the process on a Fermi graphic computing engine from NVIDIA increased the speed ∼180 times over an application running on an 80 node Linux cluster, considerably reducing simulation times. This application allows users to optimize models for ion channel kinetics on a single, inexpensive, desktop "super computer," greatly reducing the time and cost of building models relevant to neuronal physiology. We also demonstrate that the point of algorithm parallelization is crucial to its performance. We substantially reduced computing time by solving the ODEs (Ordinary Differential Equations) so as to massively reduce memory transfers to and from the GPU. This approach may be applied to speed up other data intensive applications requiring iterative solutions of ODEs.
Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing.
Yoshida, Ryo; West, Mike
2010-05-01
We describe a class of sparse latent factor models, called graphical factor models (GFMs), and relevant sparse learning algorithms for posterior mode estimation. Linear, Gaussian GFMs have sparse, orthogonal factor loadings matrices, that, in addition to sparsity of the implied covariance matrices, also induce conditional independence structures via zeros in the implied precision matrices. We describe the models and their use for robust estimation of sparse latent factor structure and data/signal reconstruction. We develop computational algorithms for model exploration and posterior mode search, addressing the hard combinatorial optimization involved in the search over a huge space of potential sparse configurations. A mean-field variational technique coupled with annealing is developed to successively generate "artificial" posterior distributions that, at the limiting temperature in the annealing schedule, define required posterior modes in the GFM parameter space. Several detailed empirical studies and comparisons to related approaches are discussed, including analyses of handwritten digit image and cancer gene expression data.
Anquez, Jérémie; Boubekeur, Tamy; Bibin, Lazar; Angelini, Elsa; Bloch, Isabelle
2009-01-01
Potential sanitary effects related to electromagnetic fields exposure raise public concerns, especially for fetuses during pregnancy. Human fetus exposure can only be assessed through simulated dosimetry studies, performed on anthropomorphic models of pregnant women. In this paper, we propose a new methodology to generate a set of detailed utero-fetal unit (UFU) 3D models during the first and third trimesters of pregnancy, based on segmented 3D ultrasound and MRI data. UFU models are built using recent geometry processing methods derived from mesh-based computer graphics techniques and embedded in a synthetic woman body. Nine pregnant woman models have been generated using this approach and validated by obstetricians, for anatomical accuracy and representativeness.
Modified graphical autocatalytic set model of combustion process in circulating fluidized bed boiler
NASA Astrophysics Data System (ADS)
Yusof, Nurul Syazwani; Bakar, Sumarni Abu; Ismail, Razidah
2014-07-01
Circulating Fluidized Bed Boiler (CFB) is a device for generating steam by burning fossil fuels in a furnace operating under a special hydrodynamic condition. Autocatalytic Set has provided a graphical model of chemical reactions that occurred during combustion process in CFB. Eight important chemical substances known as species were represented as nodes and catalytic relationships between nodes are represented by the edges in the graph. In this paper, the model is extended and modified by considering other relevant chemical reactions that also exist during the process. Catalytic relationship among the species in the model is discussed. The result reveals that the modified model is able to gives more explanation of the relationship among the species during the process at initial time t.
ERIC Educational Resources Information Center
Halpern, Jeanne W.
1970-01-01
Computer graphics have been called the most exciting development in computer technology. At the University of Michigan, three kinds of graphics output equipment are now being used: symbolic printers, line plotters or drafting devices, and cathode-ray tubes (CRT). Six examples are given that demonstrate the range of graphics use at the University.…
2011-01-01
Background Machine learning has a vast range of applications. In particular, advanced machine learning methods are routinely and increasingly used in quantitative structure activity relationship (QSAR) modeling. QSAR data sets often encompass tens of thousands of compounds and the size of proprietary, as well as public data sets, is rapidly growing. Hence, there is a demand for computationally efficient machine learning algorithms, easily available to researchers without extensive machine learning knowledge. In granting the scientific principles of transparency and reproducibility, Open Source solutions are increasingly acknowledged by regulatory authorities. Thus, an Open Source state-of-the-art high performance machine learning platform, interfacing multiple, customized machine learning algorithms for both graphical programming and scripting, to be used for large scale development of QSAR models of regulatory quality, is of great value to the QSAR community. Results This paper describes the implementation of the Open Source machine learning package AZOrange. AZOrange is specially developed to support batch generation of QSAR models in providing the full work flow of QSAR modeling, from descriptor calculation to automated model building, validation and selection. The automated work flow relies upon the customization of the machine learning algorithms and a generalized, automated model hyper-parameter selection process. Several high performance machine learning algorithms are interfaced for efficient data set specific selection of the statistical method, promoting model accuracy. Using the high performance machine learning algorithms of AZOrange does not require programming knowledge as flexible applications can be created, not only at a scripting level, but also in a graphical programming environment. Conclusions AZOrange is a step towards meeting the needs for an Open Source high performance machine learning platform, supporting the efficient development of
Pecevski, Dejan; Buesing, Lars; Maass, Wolfgang
2011-01-01
An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows (“explaining away”) and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons. PMID:22219717
Jackson, M E; Gnadt, J W
1999-03-01
The object-oriented graphical programming language LabView was used to implement the numerical solution to a computational model of saccade generation in primates. The computational model simulates the activity and connectivity of anatomical strictures known to be involved in saccadic eye movements. The LabView program provides a graphical user interface to the model that makes it easy to observe and modify the behavior of each element of the model. Essential elements of the source code of the LabView program are presented and explained. A copy of the model is available for download from the internet.
Raster graphics extensions to the core system
NASA Technical Reports Server (NTRS)
Foley, J. D.
1984-01-01
A conceptual model of raster graphics systems was developed. The model integrates core-like graphics package concepts with contemporary raster display architectures. The conceptual model of raster graphics introduces multiple pixel matrices with associated index tables.
ModelMuse - A Graphical User Interface for MODFLOW-2005 and PHAST
Winston, Richard B.
2009-01-01
ModelMuse is a graphical user interface (GUI) for the U.S. Geological Survey (USGS) models MODFLOW-2005 and PHAST. This software package provides a GUI for creating the flow and transport input file for PHAST and the input files for MODFLOW-2005. In ModelMuse, the spatial data for the model is independent of the grid, and the temporal data is independent of the stress periods. Being able to input these data independently allows the user to redefine the spatial and temporal discretization at will. This report describes the basic concepts required to work with ModelMuse. These basic concepts include the model grid, data sets, formulas, objects, the method used to assign values to data sets, and model features. The ModelMuse main window has a top, front, and side view of the model that can be used for editing the model, and a 3-D view of the model that can be used to display properties of the model. ModelMuse has tools to generate and edit the model grid. It also has a variety of interpolation methods and geographic functions that can be used to help define the spatial variability of the model. ModelMuse can be used to execute both MODFLOW-2005 and PHAST and can also display the results of MODFLOW-2005 models. An example of using ModelMuse with MODFLOW-2005 is included in this report. Several additional examples are described in the help system for ModelMuse, which can be accessed from the Help menu.
Configuration mixing calculations in soluble models
NASA Astrophysics Data System (ADS)
Cambiaggio, M. C.; Plastino, A.; Szybisz, L.; Miller, H. G.
1983-07-01
Configuration mixing calculations have been performed in two quasi-spin models using basis states which are solutions of a particular set of Hartree-Fock equations. Each of these solutions, even those which do not correspond to the global minimum, is found to contain interesting physical information. Relatively good agreement with the exact lowest-lying states has been obtained. In particular, one obtains a better approximation to the ground state than that provided by Hartree-Fock.
A random distribution reacting mixing layer model
NASA Technical Reports Server (NTRS)
Jones, Richard A.
1994-01-01
A methodology for simulation of molecular mixing and the resulting velocity and temperature fields has been developed. The ideas are applied to the flow conditions present in the NASA Lewis Planar Reacting Shear Layer (PRSL) facility, and results compared to experimental data. A gaussian transverse turbulent velocity distribution is used in conjunction with a linearly increasing time scale to describe the mixing of different regions of the flow. Equilibrium reaction calculations are then performed on the mix to arrive at a new species composition and temperature. Velocities are determined through summation of momentum contributions. The analysis indicates a combustion efficiency of the order of 80 percent for the reacting mixing layer, and a turbulent Schmidt number of 2/3. The success of the model is attributed to the simulation of large-scale transport of fluid. The favorable comparison shows that a relatively quick and simple PC calculation is capable of simulating the basic flow structure in the reacting and non-reacting shear layer present in the facility given basic assumptions about turbulence properties.
A random distribution reacting mixing layer model
NASA Technical Reports Server (NTRS)
Jones, Richard A.; Marek, C. John; Myrabo, Leik N.; Nagamatsu, Henry T.
1994-01-01
A methodology for simulation of molecular mixing, and the resulting velocity and temperature fields has been developed. The ideas are applied to the flow conditions present in the NASA Lewis Research Center Planar Reacting Shear Layer (PRSL) facility, and results compared to experimental data. A gaussian transverse turbulent velocity distribution is used in conjunction with a linearly increasing time scale to describe the mixing of different regions of the flow. Equilibrium reaction calculations are then performed on the mix to arrive at a new species composition and temperature. Velocities are determined through summation of momentum contributions. The analysis indicates a combustion efficiency of the order of 80 percent for the reacting mixing layer, and a turbulent Schmidt number of 2/3. The success of the model is attributed to the simulation of large-scale transport of fluid. The favorable comparison shows that a relatively quick and simple PC calculation is capable of simulating the basic flow structure in the reacting and nonreacting shear layer present in the facility given basic assumptions about turbulence properties.
CFD Modeling of Mixed-Phase Icing
NASA Astrophysics Data System (ADS)
Zhang, Lifen; Liu, Zhenxia; Zhang, Fei
2016-12-01
Ice crystal ingestion at high altitude has been reported to be a threat for safe operation of aero-engine in recently. Ice crystals do not accrete on external surface because of cold environment. But when they enter the core flow of aero-engine, ice crystals melt partially into droplets due to higher temperature. Air-droplets-ice crystal is the mixed-phase, which will give rise to ice accretion on static and rotating components in compressor. Subsequently, compressor surge and engine shutdowns may occur. To provide a numerical tool to analyze this in detail, a numerical method was developed in this study. The mixed phase flow was solved using Eulerian-Lagrangian method. The dispersed phase was represented by one-way coupling. A thermodynamic model that considers mass and energy balance with ice crystals and droplets was presented as well. The icing code was implemented by the user-defined function of Fluent. The method of ice accretion under mixed-phase conditions was validated by comparing the results simulated on a cylinder with experimental data derived from literature. The predicted ice shape and mass agree with these data, thereby confirming the validity of the numerical method developed in this research for mixed-phase conditions.
ASAMgpu V1.0 - a moist fully compressible atmospheric model using graphics processing units (GPUs)
NASA Astrophysics Data System (ADS)
Horn, S.
2012-03-01
In this work the three dimensional compressible moist atmospheric model ASAMgpu is presented. The calculations are done using graphics processing units (GPUs). To ensure platform independence OpenGL and GLSL are used, with that the model runs on any hardware supporting fragment shaders. The MPICH2 library enables interprocess communication allowing the usage of more than one GPU through domain decomposition. Time integration is done with an explicit three step Runge-Kutta scheme with a time-splitting algorithm for the acoustic waves. The results for four test cases are shown in this paper. A rising dry heat bubble, a cold bubble induced density flow, a rising moist heat bubble in a saturated environment, and a DYCOMS-II case.
ASAMgpu V1.0 - a moist fully compressible atmospheric model using graphics processing units (GPUs)
NASA Astrophysics Data System (ADS)
Horn, S.
2011-10-01
In this work the three dimensional compressible moist atmospheric model ASAMgpu is presented. The calculations are done using graphics processing units (GPUs). To ensure platform independence OpenGL and GLSL is used, with that the model runs on any hardware supporting fragment shaders. The MPICH2 library enables interprocess communication allowing the usage of more than one GPU through domain decomposition. Time integration is done with an explicit three step Runge-Kutta scheme with a timesplitting algorithm for the acoustic waves. The results for four test cases are shown in this paper. A rising dry heat bubble, a cold bubble induced density flow, a rising moist heat bubble in a saturated environment and a DYCOMS-II case.
Fuzzy Edge Connectivity of Graphical Fuzzy State Space Model in Multi-connected System
NASA Astrophysics Data System (ADS)
Harish, Noor Ainy; Ismail, Razidah; Ahmad, Tahir
2010-11-01
Structured networks of interacting components illustrate complex structure in a direct or intuitive way. Graph theory provides a mathematical modeling for studying interconnection among elements in natural and man-made systems. On the other hand, directed graph is useful to define and interpret the interconnection structure underlying the dynamics of the interacting subsystem. Fuzzy theory provides important tools in dealing various aspects of complexity, imprecision and fuzziness of the network structure of a multi-connected system. Initial development for systems of Fuzzy State Space Model (FSSM) and a fuzzy algorithm approach were introduced with the purpose of solving the inverse problems in multivariable system. In this paper, fuzzy algorithm is adapted in order to determine the fuzzy edge connectivity between subsystems, in particular interconnected system of Graphical Representation of FSSM. This new approach will simplify the schematic diagram of interconnection of subsystems in a multi-connected system.
BDA special care case mix model.
Bateman, P; Arnold, C; Brown, R; Foster, L V; Greening, S; Monaghan, N; Zoitopoulos, L
2010-04-10
Routine dental care provided in special care dentistry is complicated by patient specific factors which increase the time taken and costs of treatment. The BDA have developed and conducted a field trial of a case mix tool to measure this complexity. For each episode of care the case mix tool assesses the following on a four point scale: 'ability to communicate', 'ability to cooperate', 'medical status', 'oral risk factors', 'access to oral care' and 'legal and ethical barriers to care'. The tool is reported to be easy to use and captures sufficient detail to discriminate between types of service and special care dentistry provided. It offers potential as a simple to use and clinically relevant source of performance management and commissioning data. This paper describes the model, demonstrates how it is currently being used, and considers future developments in its use.
A graphical model approach to systematically missing data in meta-analysis of observational studies.
Kovačić, Jelena; Varnai, Veda Marija
2016-10-30
When studies in meta-analysis include different sets of confounders, simple analyses can cause a bias (omitting confounders that are missing in certain studies) or precision loss (omitting studies with incomplete confounders, i.e. a complete-case meta-analysis). To overcome these types of issues, a previous study proposed modelling the high correlation between partially and fully adjusted regression coefficient estimates in a bivariate meta-analysis. When multiple differently adjusted regression coefficient estimates are available, we propose exploiting such correlations in a graphical model. Compared with a previously suggested bivariate meta-analysis method, such a graphical model approach is likely to reduce the number of parameters in complex missing data settings by omitting the direct relationships between some of the estimates. We propose a structure-learning rule whose justification relies on the missingness pattern being monotone. This rule was tested using epidemiological data from a multi-centre survey. In the analysis of risk factors for early retirement, the method showed a smaller difference from a complete data odds ratio and greater precision than a commonly used complete-case meta-analysis. Three real-world applications with monotone missing patterns are provided, namely, the association between (1) the fibrinogen level and coronary heart disease, (2) the intima media thickness and vascular risk and (3) allergic asthma and depressive episodes. The proposed method allows for the inclusion of published summary data, which makes it particularly suitable for applications involving both microdata and summary data. Copyright © 2016 John Wiley & Sons, Ltd.
NASA Technical Reports Server (NTRS)
Jones, R. H.
1984-01-01
The hardware and software developments in computer graphics are discussed. Major topics include: system capabilities, hardware design, system compatibility, and software interface with the data base management system.
Model Selection with the Linear Mixed Model for Longitudinal Data
ERIC Educational Resources Information Center
Ryoo, Ji Hoon
2011-01-01
Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…
Two graphical user interfaces for managing and analyzing MODFLOW groundwater-model scenarios
Banta, Edward R.
2014-01-01
Scenario Manager and Scenario Analyzer are graphical user interfaces that facilitate the use of calibrated, MODFLOW-based groundwater models for investigating possible responses to proposed stresses on a groundwater system. Scenario Manager allows a user, starting with a calibrated model, to design and run model scenarios by adding or modifying stresses simulated by the model. Scenario Analyzer facilitates the process of extracting data from model output and preparing such display elements as maps, charts, and tables. Both programs are designed for users who are familiar with the science on which groundwater modeling is based but who may not have a groundwater modeler’s expertise in building and calibrating a groundwater model from start to finish. With Scenario Manager, the user can manipulate model input to simulate withdrawal or injection wells, time-variant specified hydraulic heads, recharge, and such surface-water features as rivers and canals. Input for stresses to be simulated comes from user-provided geographic information system files and time-series data files. A Scenario Manager project can contain multiple scenarios and is self-documenting. Scenario Analyzer can be used to analyze output from any MODFLOW-based model; it is not limited to use with scenarios generated by Scenario Manager. Model-simulated values of hydraulic head, drawdown, solute concentration, and cell-by-cell flow rates can be presented in display elements. Map data can be represented as lines of equal value (contours) or as a gradated color fill. Charts and tables display time-series data obtained from output generated by a transient-state model run or from user-provided text files of time-series data. A display element can be based entirely on output of a single model run, or, to facilitate comparison of results of multiple scenarios, an element can be based on output from multiple model runs. Scenario Analyzer can export display elements and supporting metadata as a Portable
Gray component replacement using color mixing models
NASA Astrophysics Data System (ADS)
Kang, Henry R.
1994-05-01
A new approach to the gray component replacement (GCR) has been developed. It employs the color mixing theory for modeling the spectral fit between the 3-color and 4-color prints. To achieve this goal, we first examine the accuracy of the models with respect to the experimental results by applying them to the prints made by a Canon Color Laser Copier-500 (CLC-500). An empirical halftone correction factor is used for improving the data fitting. Among the models tested, the halftone corrected Kubelka-Munk theory gives the closest fit, followed by the halftone corrected Beer-Bouguer law and the Yule-Neilsen approach. We then apply the halftone corrected BB law to GCR. The main feature of this GCR approach is based on the spectral measurements of the primary color step wedges and a software package implementing the color mixing model. The software determines the amount of the gray component to be removed, then adjusts each primary color until a good match of the peak wavelengths between the 3-color and 4-color spectra is obtained. Results indicate that the average (Delta) Eab between cmy and cmyk renditions of 64 color patches is 3.11 (Delta) Eab. Eighty-seven percent of the patches has (Delta) Eab less than 5 units. The advantage of this approach is its simplicity; there is no need for the black printer and under color addition. Because this approach is based on the spectral reproduction, it minimizes the metamerism.
Toward Better Modeling of Supercritical Turbulent Mixing
NASA Technical Reports Server (NTRS)
Selle, Laurent; Okongo'o, Nora; Bellan, Josette; Harstad, Kenneth
2008-01-01
study was done as part of an effort to develop computational models representing turbulent mixing under thermodynamic supercritical (here, high pressure) conditions. The question was whether the large-eddy simulation (LES) approach, developed previously for atmospheric-pressure compressible-perfect-gas and incompressible flows, can be extended to real-gas non-ideal (including supercritical) fluid mixtures. [In LES, the governing equations are approximated such that the flow field is spatially filtered and subgrid-scale (SGS) phenomena are represented by models.] The study included analyses of results from direct numerical simulation (DNS) of several such mixing layers based on the Navier-Stokes, total-energy, and conservation- of-chemical-species governing equations. Comparison of LES and DNS results revealed the need to augment the atmospheric- pressure LES equations with additional SGS momentum and energy terms. These new terms are the direct result of high-density-gradient-magnitude regions found in the DNS and observed experimentally under fully turbulent flow conditions. A model has been derived for the new term in the momentum equation and was found to perform well at small filter size but to deteriorate with increasing filter size. Several alternative models were derived for the new SGS term in the energy equation that would need further investigations to determine if they are too computationally intensive in LES.
Robust Depth Image Acquisition Using Modulated Pattern Projection and Probabilistic Graphical Models
Kravanja, Jaka; Žganec, Mario; Žganec-Gros, Jerneja; Dobrišek, Simon; Štruc, Vitomir
2016-01-01
Depth image acquisition with structured light approaches in outdoor environments is a challenging problem due to external factors, such as ambient sunlight, which commonly affect the acquisition procedure. This paper presents a novel structured light sensor designed specifically for operation in outdoor environments. The sensor exploits a modulated sequence of structured light projected onto the target scene to counteract environmental factors and estimate a spatial distortion map in a robust manner. The correspondence between the projected pattern and the estimated distortion map is then established using a probabilistic framework based on graphical models. Finally, the depth image of the target scene is reconstructed using a number of reference frames recorded during the calibration process. We evaluate the proposed sensor on experimental data in indoor and outdoor environments and present comparative experiments with other existing methods, as well as commercial sensors. PMID:27775570
Kravanja, Jaka; Žganec, Mario; Žganec-Gros, Jerneja; Dobrišek, Simon; Štruc, Vitomir
2016-10-19
Depth image acquisition with structured light approaches in outdoor environments is a challenging problem due to external factors, such as ambient sunlight, which commonly affect the acquisition procedure. This paper presents a novel structured light sensor designed specifically for operation in outdoor environments. The sensor exploits a modulated sequence of structured light projected onto the target scene to counteract environmental factors and estimate a spatial distortion map in a robust manner. The correspondence between the projected pattern and the estimated distortion map is then established using a probabilistic framework based on graphical models. Finally, the depth image of the target scene is reconstructed using a number of reference frames recorded during the calibration process. We evaluate the proposed sensor on experimental data in indoor and outdoor environments and present comparative experiments with other existing methods, as well as commercial sensors.
Asymptotically Normal and Efficient Estimation of Covariate-Adjusted Gaussian Graphical Model
Chen, Mengjie; Ren, Zhao; Zhao, Hongyu; Zhou, Harrison
2015-01-01
A tuning-free procedure is proposed to estimate the covariate-adjusted Gaussian graphical model. For each finite subgraph, this estimator is asymptotically normal and efficient. As a consequence, a confidence interval can be obtained for each edge. The procedure enjoys easy implementation and efficient computation through parallel estimation on subgraphs or edges. We further apply the asymptotic normality result to perform support recovery through edge-wise adaptive thresholding. This support recovery procedure is called ANTAC, standing for Asymptotically Normal estimation with Thresholding after Adjusting Covariates. ANTAC outperforms other methodologies in the literature in a range of simulation studies. We apply ANTAC to identify gene-gene interactions using an eQTL dataset. Our result achieves better interpretability and accuracy in comparison with CAMPE. PMID:27499564
Graphical representation of life paths to better convey results of decision models to patients.
Rubrichi, Stefania; Rognoni, Carla; Sacchi, Lucia; Parimbelli, Enea; Napolitano, Carlo; Mazzanti, Andrea; Quaglini, Silvana
2015-04-01
The inclusion of patients' perspectives in clinical practice has become an important matter for health professionals, in view of the increasing attention to patient-centered care. In this regard, this report illustrates a method for developing a visual aid that supports the physician in the process of informing patients about a critical decisional problem. In particular, we focused on interpretation of the results of decision trees embedding Markov models implemented with the commercial tool TreeAge Pro. Starting from patient-level simulations and exploiting some advanced functionalities of TreeAge Pro, we combined results to produce a novel graphical output that represents the distributions of outcomes over the lifetime for the different decision options, thus becoming a more informative decision support in a context of shared decision making. The training example used to illustrate the method is a decision tree for thromboembolism risk prevention in patients with nonvalvular atrial fibrillation.
Glossiness of Colored Papers based on Computer Graphics Model and Its Measuring Method
NASA Astrophysics Data System (ADS)
Aida, Teizo
In the case of colored papers, the color of surface effects strongly upon the gloss of its paper. The new glossiness for such a colored paper is suggested in this paper. First, using the Achromatic and Chromatic Munsell colored chips, the author obtained experimental equation which represents the relation between lightness V ( or V and saturation C ) and psychological glossiness Gph of these chips. Then, the author defined a new glossiness G for the colored papers, based on the above mentioned experimental equations Gph and Cook-Torrance's reflection model which are widely used in the filed of Computer Graphics. This new glossiness is shown to be nearly proportional to the psychological glossiness Gph. The measuring system for the new glossiness G is furthermore descrived. The measuring time for one specimen is within 1 minute.
NASA Astrophysics Data System (ADS)
Kornfeld, A.; Van der Tol, C.; Berry, J. A.
2015-12-01
Recent advances in optical remote sensing of photosynthesis offer great promise for estimating gross primary productivity (GPP) at leaf, canopy and even global scale. These methods -including solar-induced chlorophyll fluorescence (SIF) emission, fluorescence spectra, and hyperspectral features such as the red edge and the photochemical reflectance index (PRI) - can be used to greatly enhance the predictive power of global circulation models (GCMs) by providing better constraints on GPP. The way to use measured optical data to parameterize existing models such as SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) is not trivial, however. We have therefore extended a biochemical model to include fluorescence and other parameters in a coupled treatment. To help parameterize the model, we then use nonlinear curve-fitting routines to determine the parameter set that enables model results to best fit leaf-level gas exchange and optical data measurements. To make the tool more accessible to all practitioners, we have further designed a graphical user interface (GUI) based front-end to allow researchers to analyze data with a minimum of effort while, at the same time, allowing them to change parameters interactively to visualize how variation in model parameters affect predicted outcomes such as photosynthetic rates, electron transport, and chlorophyll fluorescence. Here we discuss the tool and its effectiveness, using recently-gathered leaf-level data.
Graphics Processing Unit (GPU) Acceleration of the Goddard Earth Observing System Atmospheric Model
NASA Technical Reports Server (NTRS)
Putnam, Williama
2011-01-01
The Goddard Earth Observing System 5 (GEOS-5) is the atmospheric model used by the Global Modeling and Assimilation Office (GMAO) for a variety of applications, from long-term climate prediction at relatively coarse resolution, to data assimilation and numerical weather prediction, to very high-resolution cloud-resolving simulations. GEOS-5 is being ported to a graphics processing unit (GPU) cluster at the NASA Center for Climate Simulation (NCCS). By utilizing GPU co-processor technology, we expect to increase the throughput of GEOS-5 by at least an order of magnitude, and accelerate the process of scientific exploration across all scales of global modeling, including: The large-scale, high-end application of non-hydrostatic, global, cloud-resolving modeling at 10- to I-kilometer (km) global resolutions Intermediate-resolution seasonal climate and weather prediction at 50- to 25-km on small clusters of GPUs Long-range, coarse-resolution climate modeling, enabled on a small box of GPUs for the individual researcher After being ported to the GPU cluster, the primary physics components and the dynamical core of GEOS-5 have demonstrated a potential speedup of 15-40 times over conventional processor cores. Performance improvements of this magnitude reduce the required scalability of 1-km, global, cloud-resolving models from an unfathomable 6 million cores to an attainable 200,000 GPU-enabled cores.
Model Selection and Accounting for Model Uncertainty in Graphical Models Using OCCAM’s Window
1991-07-22
There are also approaches based on information criteria and discrepancy measures (Gokhale and Kullback, 1978; Sakamoto, 1984; Linhart and Zucchini , 1986...Statistical Society (Series B), 50,157-224. Linhart, H. and Zucchini , W. (1986) Model Selection. New York: Wiley. Miller, A.J. (1984) Selection of
Inference of ICF implosion core mix using experimental data and theoretical mix modeling
Sherrill, Leslie Welser; Haynes, Donald A; Cooley, James H; Sherrill, Manolo E; Mancini, Roberto C; Tommasini, Riccardo; Golovkin, Igor E; Haan, Steven W
2009-01-01
The mixing between fuel and shell materials in Inertial Confinement Fusion (lCF) implosion cores is a current topic of interest. The goal of this work was to design direct-drive ICF experiments which have varying levels of mix, and subsequently to extract information on mixing directly from the experimental data using spectroscopic techniques. The experimental design was accomplished using hydrodynamic simulations in conjunction with Haan's saturation model, which was used to predict the mix levels of candidate experimental configurations. These theoretical predictions were then compared to the mixing information which was extracted from the experimental data, and it was found that Haan's mix model predicted trends in the width of the mix layer as a function of initial shell thickness. These results contribute to an assessment of the range of validity and predictive capability of the Haan saturation model, as well as increasing confidence in the methods used to extract mixing information from experimental data.
Developing a multiscale, multi-resolution agent-based brain tumor model by graphics processing units
2011-01-01
Multiscale agent-based modeling (MABM) has been widely used to simulate Glioblastoma Multiforme (GBM) and its progression. At the intracellular level, the MABM approach employs a system of ordinary differential equations to describe quantitatively specific intracellular molecular pathways that determine phenotypic switches among cells (e.g. from migration to proliferation and vice versa). At the intercellular level, MABM describes cell-cell interactions by a discrete module. At the tissue level, partial differential equations are employed to model the diffusion of chemoattractants, which are the input factors of the intracellular molecular pathway. Moreover, multiscale analysis makes it possible to explore the molecules that play important roles in determining the cellular phenotypic switches that in turn drive the whole GBM expansion. However, owing to limited computational resources, MABM is currently a theoretical biological model that uses relatively coarse grids to simulate a few cancer cells in a small slice of brain cancer tissue. In order to improve this theoretical model to simulate and predict actual GBM cancer progression in real time, a graphics processing unit (GPU)-based parallel computing algorithm was developed and combined with the multi-resolution design to speed up the MABM. The simulated results demonstrated that the GPU-based, multi-resolution and multiscale approach can accelerate the previous MABM around 30-fold with relatively fine grids in a large extracellular matrix. Therefore, the new model has great potential for simulating and predicting real-time GBM progression, if real experimental data are incorporated. PMID:22176732
Integrating diagnostic data analysis for W7-AS using Bayesian graphical models
Svensson, J.; Dinklage, A.; Geiger, J.; Werner, A.; Fischer, R
2004-10-01
Analysis of diagnostic data in fusion experiments is usually dealt with separately for each diagnostic, in spite of the existence of a large number of interdependencies between global physics parameters and measurements from different diagnostics. In this article, we demonstrate an integrated data analysis model, applied to the W7-AS stellarator, where diagnostic interdependencies have been modeled in a novel way by using so called Bayesian graphical models. A Thomson scattering system, interferometer, diamagnetic loop, and neutral particle analyzer are combined with an equilibrium reconstruction, forming together one single model for the determination of quantities such as density and temperature profiles, directly in magnetic coordinates. The magnetic coordinate transformation is itself inferred from the measurements. Influence of both statistical and systematic uncertainties on quantities from equilibrium calculations, such as position of flux surfaces, can therefore be readily estimated together with uncertainties of profile estimates. The model allows for modular addition of further diagnostics. A software architecture for such integrated analysis where possibly large number of diagnostic and theoretical codes need to be combined, will also be discussed.
Higher-order ice-sheet modelling accelerated by multigrid on graphics cards
NASA Astrophysics Data System (ADS)
Brædstrup, Christian; Egholm, David
2013-04-01
Higher-order ice flow modelling is a very computer intensive process owing primarily to the nonlinear influence of the horizontal stress coupling. When applied for simulating long-term glacial landscape evolution, the ice-sheet models must consider very long time series, while both high temporal and spatial resolution is needed to resolve small effects. The use of higher-order and full stokes models have therefore seen very limited usage in this field. However, recent advances in graphics card (GPU) technology for high performance computing have proven extremely efficient in accelerating many large-scale scientific computations. The general purpose GPU (GPGPU) technology is cheap, has a low power consumption and fits into a normal desktop computer. It could therefore provide a powerful tool for many glaciologists working on ice flow models. Our current research focuses on utilising the GPU as a tool in ice-sheet and glacier modelling. To this extent we have implemented the Integrated Second-Order Shallow Ice Approximation (iSOSIA) equations on the device using the finite difference method. To accelerate the computations, the GPU solver uses a non-linear Red-Black Gauss-Seidel iterator coupled with a Full Approximation Scheme (FAS) multigrid setup to further aid convergence. The GPU finite difference implementation provides the inherent parallelization that scales from hundreds to several thousands of cores on newer cards. We demonstrate the efficiency of the GPU multigrid solver using benchmark experiments.
Mixing parametrizations for ocean climate modelling
NASA Astrophysics Data System (ADS)
Gusev, Anatoly; Moshonkin, Sergey; Diansky, Nikolay; Zalesny, Vladimir
2016-04-01
The algorithm is presented of splitting the total evolutionary equations for the turbulence kinetic energy (TKE) and turbulence dissipation frequency (TDF), which is used to parameterize the viscosity and diffusion coefficients in ocean circulation models. The turbulence model equations are split into the stages of transport-diffusion and generation-dissipation. For the generation-dissipation stage, the following schemes are implemented: the explicit-implicit numerical scheme, analytical solution and the asymptotic behavior of the analytical solutions. The experiments were performed with different mixing parameterizations for the modelling of Arctic and the Atlantic climate decadal variability with the eddy-permitting circulation model INMOM (Institute of Numerical Mathematics Ocean Model) using vertical grid refinement in the zone of fully developed turbulence. The proposed model with the split equations for turbulence characteristics is similar to the contemporary differential turbulence models, concerning the physical formulations. At the same time, its algorithm has high enough computational efficiency. Parameterizations with using the split turbulence model make it possible to obtain more adequate structure of temperature and salinity at decadal timescales, compared to the simpler Pacanowski-Philander (PP) turbulence parameterization. Parameterizations with using analytical solution or numerical scheme at the generation-dissipation step of the turbulence model leads to better representation of ocean climate than the faster parameterization using the asymptotic behavior of the analytical solution. At the same time, the computational efficiency left almost unchanged relative to the simple PP parameterization. Usage of PP parametrization in the circulation model leads to realistic simulation of density and circulation with violation of T,S-relationships. This error is majorly avoided with using the proposed parameterizations containing the split turbulence model
NASA Technical Reports Server (NTRS)
1987-01-01
Genigraphics Corporation's Masterpiece 8770 FilmRecorder is an advanced high resolution system designed to improve and expand a company's in-house graphics production. GRAFTIME/software package was designed to allow office personnel with minimal training to produce professional level graphics for business communications and presentations. Products are no longer being manufactured.
ERIC Educational Resources Information Center
Thompson, John
2009-01-01
Graphic storytelling is a medium that allows students to make and share stories, while developing their art communication skills. American comics today are more varied in genre, approach, and audience than ever before. When considering the impact of Japanese manga on the youth, graphic storytelling emerges as a powerful player in pop culture. In…
Guo, Hongbin; Renaut, Rosemary A; Chen, Kewei; Reiman, Eric M
2010-01-01
Graphical analysis methods are widely used in positron emission tomography quantification because of their simplicity and model independence. But they may, particularly for reversible kinetics, lead to bias in the estimated parameters. The source of the bias is commonly attributed to noise in the data. Assuming a two-tissue compartmental model, we investigate the bias that originates from modeling error. This bias is an intrinsic property of the simplified linear models used for limited scan durations, and it is exaggerated by random noise and numerical quadrature error. Conditions are derived under which Logan's graphical method either over- or under-estimates the distribution volume in the noise-free case. The bias caused by modeling error is quantified analytically. The presented analysis shows that the bias of graphical methods is inversely proportional to the dissociation rate. Furthermore, visual examination of the linearity of the Logan plot is not sufficient for guaranteeing that equilibrium has been reached. A new model which retains the elegant properties of graphical analysis methods is presented, along with a numerical algorithm for its solution. We perform simulations with the fibrillar amyloid β radioligand [11C] benzothiazole-aniline using published data from the University of Pittsburgh and Rotterdam groups. The results show that the proposed method significantly reduces the bias due to modeling error. Moreover, the results for data acquired over a 70 minutes scan duration are at least as good as those obtained using existing methods for data acquired over a 90 minutes scan duration. PMID:20493196
Mixed Membership Distributions with Applications to Modeling Multiple Strategy Usage
ERIC Educational Resources Information Center
Galyardt, April
2012-01-01
This dissertation examines two related questions. "How do mixed membership models work?" and "Can mixed membership be used to model how students use multiple strategies to solve problems?". Mixed membership models have been used in thousands of applications from text and image processing to genetic microarray analysis. Yet…
Modeling populations of rotationally mixed massive stars
NASA Astrophysics Data System (ADS)
Brott, I.
2011-02-01
Massive stars can be considered as cosmic engines. With their high luminosities, strong stellar winds and violent deaths they drive the evolution of galaxies through-out the history of the universe. Despite the importance of massive stars, their evolution is still poorly understood. Two major issues have plagued evolutionary models of massive stars until today: mixing and mass loss On the main sequence, the effects of mass loss remain limited in the considered mass and metallicity range, this thesis concentrates on the role of mixing in massive stars. This thesis approaches this problem just on the cross road between observations and simulations. The main question: Do evolutionary models of single stars, accounting for the effects of rotation, reproduce the observed properties of real stars. In particular we are interested if the evolutionary models can reproduce the surface abundance changes during the main-sequence phase. To constrain our models we build a population synthesis model for the sample of the VLT-FLAMES Survey of Massive stars, for which star-formation history and rotational velocity distribution are well constrained. We consider the four main regions of the Hunter diagram. Nitrogen un-enriched slow rotators and nitrogen enriched fast rotators that are predicted by theory. Nitrogen enriched slow rotators and nitrogen unenriched fast rotators that are not predicted by our model. We conclude that currently these comparisons are not sufficient to verify the theory of rotational mixing. Physical processes in addition to rotational mixing appear necessary to explain the stars in the later two regions. The chapters of this Thesis have been published in the following Journals: Ch. 2: ``Rotating Massive Main-Sequence Stars I: Grids of Evolutionary Models and Isochrones'', I. Brott, S. E. de Mink, M. Cantiello, N. Langer, A. de Koter, C. J. Evans, I. Hunter, C. Trundle, J.S. Vink submitted to Astronomy & Astrop hysics Ch. 3: ``The VLT-FLAMES Survey of Massive
Structural and Functional Model of Organization of Geometric and Graphic Training of the Students
ERIC Educational Resources Information Center
Poluyanov, Valery B.; Pyankova, Zhanna A.; Chukalkina, Marina I.; Smolina, Ekaterina S.
2016-01-01
The topicality of the investigated problem is stipulated by the social need for training competitive engineers with a high level of graphical literacy; especially geometric and graphic training of students and its projected results in a competence-based approach; individual characteristics and interests of the students, as well as methodological…
ERIC Educational Resources Information Center
Meznarich, R. A.; Shava, R. C.; Lightner, S. L.
2009-01-01
Engineering design graphics courses taught in colleges or universities should provide and equip students preparing for employment with the basic occupational graphics skill competences required by engineering and technology disciplines. Academic institutions should introduce and include topics that cover the newer and more efficient graphics…
A Comparison of Learning Style Models and Assessment Instruments for University Graphics Educators
ERIC Educational Resources Information Center
Harris, La Verne Abe; Sadowski, Mary S.; Birchman, Judy A.
2006-01-01
Kolb (2004) and others have defined learning style as a preference by which students learn and remember what they have learned. This presentation will include a summary of learning style research published in the "Engineering Design Graphics Journal" over the past 15 years on the topic of learning styles and graphics education. The…
NASA Astrophysics Data System (ADS)
Stork, David G.; Nagy, Gabor
2010-02-01
We explored the working methods of the Italian Baroque master Caravaggio through computer graphics reconstruction of his studio, with special focus on his use of lighting and illumination in The calling of St. Matthew. Although he surely took artistic liberties while constructing this and other works and did not strive to provide a "photographic" rendering of the tableau before him, there are nevertheless numerous visual clues to the likely studio conditions and working methods within the painting: the falloff of brightness along the rear wall, the relative brightness of the faces of figures, and the variation in sharpness of cast shadows (i.e., umbrae and penumbrae). We explored two studio lighting hypotheses: that the primary illumination was local (and hence artificial) and that it was distant solar. We find that the visual evidence can be consistent with local (artificial) illumination if Caravaggio painted his figures separately, adjusting the brightness on each to compensate for the falloff in illumination. Alternatively, the evidence is consistent with solar illumination only if the rear wall had particular reflectance properties, as described by a bi-directional reflectance distribution function, BRDF. (Ours is the first research applying computer graphics to the understanding of artists' praxis that models subtle reflectance properties of surfaces through BRDFs, a technique that may find use in studies of other artists.) A somewhat puzzling visual feature-unnoted in the scholarly literature-is the upward-slanting cast shadow in the upper-right corner of the painting. We found this shadow is naturally consistent with a local illuminant passing through a small window perpendicular to the viewer's line of sight, but could also be consistent with solar illumination if the shadow was due to a slanted, overhanging section of a roof outside the artist's studio. Our results place likely conditions upon any hypotheses concerning Caravaggio's working methods and
Joint conditional Gaussian graphical models with multiple sources of genomic data
Chun, Hyonho; Chen, Min; Li, Bing; Zhao, Hongyu
2013-01-01
It is challenging to identify meaningful gene networks because biological interactions are often condition-specific and confounded with external factors. It is necessary to integrate multiple sources of genomic data to facilitate network inference. For example, one can jointly model expression datasets measured from multiple tissues with molecular marker data in so-called genetical genomic studies. In this paper, we propose a joint conditional Gaussian graphical model (JCGGM) that aims for modeling biological processes based on multiple sources of data. This approach is able to integrate multiple sources of information by adopting conditional models combined with joint sparsity regularization. We apply our approach to a real dataset measuring gene expression in four tissues (kidney, liver, heart, and fat) from recombinant inbred rats. Our approach reveals that the liver tissue has the highest level of tissue-specific gene regulations among genes involved in insulin responsive facilitative sugar transporter mediated glucose transport pathway, followed by heart and fat tissues, and this finding can only be attained from our JCGGM approach. PMID:24381584
Kizilkaya, Kadir; Tempelman, Robert J
2005-01-01
We propose a general Bayesian approach to heteroskedastic error modeling for generalized linear mixed models (GLMM) in which linked functions of conditional means and residual variances are specified as separate linear combinations of fixed and random effects. We focus on the linear mixed model (LMM) analysis of birth weight (BW) and the cumulative probit mixed model (CPMM) analysis of calving ease (CE). The deviance information criterion (DIC) was demonstrated to be useful in correctly choosing between homoskedastic and heteroskedastic error GLMM for both traits when data was generated according to a mixed model specification for both location parameters and residual variances. Heteroskedastic error LMM and CPMM were fitted, respectively, to BW and CE data on 8847 Italian Piemontese first parity dams in which residual variances were modeled as functions of fixed calf sex and random herd effects. The posterior mean residual variance for male calves was over 40% greater than that for female calves for both traits. Also, the posterior means of the standard deviation of the herd-specific variance ratios (relative to a unitary baseline) were estimated to be 0.60 ± 0.09 for BW and 0.74 ± 0.14 for CE. For both traits, the heteroskedastic error LMM and CPMM were chosen over their homoskedastic error counterparts based on DIC values. PMID:15588567
Ortiz, Andrés; Munilla, Jorge; Álvarez-Illán, Ignacio; Górriz, Juan M.; Ramírez, Javier
2015-01-01
Alzheimer's Disease (AD) is the most common neurodegenerative disease in elderly people. Its development has been shown to be closely related to changes in the brain connectivity network and in the brain activation patterns along with structural changes caused by the neurodegenerative process. Methods to infer dependence between brain regions are usually derived from the analysis of covariance between activation levels in the different areas. However, these covariance-based methods are not able to estimate conditional independence between variables to factor out the influence of other regions. Conversely, models based on the inverse covariance, or precision matrix, such as Sparse Gaussian Graphical Models allow revealing conditional independence between regions by estimating the covariance between two variables given the rest as constant. This paper uses Sparse Inverse Covariance Estimation (SICE) methods to learn undirected graphs in order to derive functional and structural connectivity patterns from Fludeoxyglucose (18F-FDG) Position Emission Tomography (PET) data and segmented Magnetic Resonance images (MRI), drawn from the ADNI database, for Control, MCI (Mild Cognitive Impairment Subjects), and AD subjects. Sparse computation fits perfectly here as brain regions usually only interact with a few other areas. The models clearly show different metabolic covariation patters between subject groups, revealing the loss of strong connections in AD and MCI subjects when compared to Controls. Similarly, the variance between GM (Gray Matter) densities of different regions reveals different structural covariation patterns between the different groups. Thus, the different connectivity patterns for controls and AD are used in this paper to select regions of interest in PET and GM images with discriminative power for early AD diagnosis. Finally, functional an structural models are combined to leverage the classification accuracy. The results obtained in this work show the
NASA Astrophysics Data System (ADS)
Le Grand, Scott; Götz, Andreas W.; Walker, Ross C.
2013-02-01
A new precision model is proposed for the acceleration of all-atom classical molecular dynamics (MD) simulations on graphics processing units (GPUs). This precision model replaces double precision arithmetic with fixed point integer arithmetic for the accumulation of force components as compared to a previously introduced model that uses mixed single/double precision arithmetic. This significantly boosts performance on modern GPU hardware without sacrificing numerical accuracy. We present an implementation for NVIDIA GPUs of both generalized Born implicit solvent simulations as well as explicit solvent simulations using the particle mesh Ewald (PME) algorithm for long-range electrostatics using this precision model. Tests demonstrate both the performance of this implementation as well as its numerical stability for constant energy and constant temperature biomolecular MD as compared to a double precision CPU implementation and double and mixed single/double precision GPU implementations.
Heinzer, T.; Hansen, D.T.; Greer, W.; Sebhat, M.
1996-12-31
A geographic information system (GIS) was used in developing a graphical user interface (GUI) for use with the US Geological Survey`s finite difference ground-water flow model, MODFLOW. The GUI permits the construction of a MODFLOW based ground-water flow model from scratch in a GIS environment. The model grid, input data and output are stored as separate raster data sets which may be viewed, edited, and manipulated in a graphic environment. Other GIS data sets can be displayed with the model data sets for reference and evaluation. The GUI sets up a directory structure for storage of the files associated with the ground-water model and the raster data sets created by the interface. The GUI stores model coefficients and model output as raster values. Values stored by these raster data sets are formatted for use with the ground-water flow model code.
Thomas, John; Ramakrishnan, Naren; Bailey-Kellogg, Chris
2009-09-01
Protein-protein interactions are mediated by complementary amino acids defining complementary surfaces. Typically not all members of a family of related proteins interact equally well with all members of a partner family; thus analysis of the sequence record can reveal the complementary amino acid partners that confer interaction specificity. This article develops methods for learning and using probabilistic graphical models of such residue "cross-coupling" constraints between interacting protein families, based on multiple sequence alignments and information about which pairs of proteins are known to interact. Our models generalize traditional consensus sequence binding motifs, and provide a probabilistic semantics enabling sound evaluation of the plausibility of new possible interactions. Furthermore, predictions made by the models can be explained in terms of the underlying residue interactions. Our approach supports different levels of prior knowledge regarding interactions, including both one-to-one (e.g., pairs of proteins from the same organism) and many-to-many (e.g., experimentally identified interactions), and we present a technique to account for possible bias in the represented interactions. We apply our approach in studies of PDZ domains and their ligands, fundamental building blocks in a number of protein assemblies. Our algorithms are able to identify biologically interesting cross-coupling constraints, to successfully identify known interactions, and to make explainable predictions about novel interactions.
Donkin, S.G.
1997-09-01
A new method of performing soil toxicity tests with free-living nematodes exposed to several metals and soil types has been adapted to the Langmuir sorption model in an attempt at bridging the gap between physico-chemical and biological data gathered in the complex soil matrix. Pseudo-Langmuir sorption isotherms have been developed using nematode toxic responses (lethality, in this case) in place of measured solvated metal, in order to more accurately model bioavailability. This method allows the graphical determination of Langmuir coefficients describing maximum sorption capacities and sorption affinities of various metal-soil combinations in the context of real biological responses of indigenous organisms. Results from nematode mortality tests with zinc, cadmium, copper, and lead in four soil types and water were used for isotherm construction. The level of agreement between these results and available literature data on metal sorption behavior in soils suggests that biologically relevant data may be successfully fitted to sorption models such as the Langmuir. This would allow for accurate prediction of soil contaminant concentrations which have minimal effect on indigenous invertebrates.
NASA Astrophysics Data System (ADS)
Skataric, Maja; Bose, Sandip; Zeroug, Smaine; Tilke, Peter
2017-02-01
It is not uncommon in the field of non-destructive evaluation that multiple measurements encompassing a variety of modalities are available for analysis and interpretation for determining the underlying states of nature of the materials or parts being tested. Despite and sometimes due to the richness of data, significant challenges arise in the interpretation manifested as ambiguities and inconsistencies due to various uncertain factors in the physical properties (inputs), environment, measurement device properties, human errors, and the measurement data (outputs). Most of these uncertainties cannot be described by any rigorous mathematical means, and modeling of all possibilities is usually infeasible for many real time applications. In this work, we will discuss an approach based on Hierarchical Bayesian Graphical Models (HBGM) for the improved interpretation of complex (multi-dimensional) problems with parametric uncertainties that lack usable physical models. In this setting, the input space of the physical properties is specified through prior distributions based on domain knowledge and expertise, which are represented as Gaussian mixtures to model the various possible scenarios of interest for non-destructive testing applications. Forward models are then used offline to generate the expected distribution of the proposed measurements which are used to train a hierarchical Bayesian network. In Bayesian analysis, all model parameters are treated as random variables, and inference of the parameters is made on the basis of posterior distribution given the observed data. Learned parameters of the posterior distribution obtained after the training can therefore be used to build an efficient classifier for differentiating new observed data in real time on the basis of pre-trained models. We will illustrate the implementation of the HBGM approach to ultrasonic measurements used for cement evaluation of cased wells in the oil industry.
Stricker, C.; Fernando, R. L.; Elston, R. C.
1995-01-01
This paper presents an extension of the finite polygenic mixed model of FERNANDO et al. (1994) to linkage analysis. The finite polygenic mixed model, extended for linkage analysis, leads to a likelihood that can be calculated using efficient algorithms developed for oligogenic models. For comparison, linkage analysis of 5 simulated 4021-member pedigrees was performed using the usual mixed model of inheritance, approximated by HASSTEDT (1982), and the finite polygenic mixed model extended for linkage analysis presented here. Maximum likelihood estimates of the finite polygenic mixed model could be inferred to be closer to the simulated values in these pedigrees. PMID:8601502
Nonequilibrium antiferromagnetic mixed-spin Ising model.
Godoy, Mauricio; Figueiredo, Wagner
2002-09-01
We studied an antiferromagnetic mixed-spin Ising model on the square lattice subject to two competing stochastic processes. The model system consists of two interpenetrating sublattices of spins sigma=1/2 and S=1, and we take only nearest neighbor interactions between pairs of spins. The system is in contact with a heat bath at temperature T, and the exchange of energy with the heat bath occurs via one-spin flip (Glauber dynamics). Besides, the system interacts with an external agency of energy, which supplies energy to it whenever two nearest neighboring spins are simultaneously flipped. By employing Monte Carlo simulations and a dynamical pair approximation, we found the phase diagram for the stationary states of the model in the plane temperature T versus the competition parameter between one- and two-spin flips p. We observed the appearance of three distinct phases, that are separated by continuous transition lines. We also determined the static critical exponents along these lines and we showed that this nonequilibrium model belongs to the universality class of the two-dimensional equilibrium Ising model.
Donovan, Courtney
2014-09-01
This paper focuses on the graphic pathogeographies in David B.'s Epileptic and David Small's Stitches: A Memoir to highlight the significance of geographic concepts in graphic novels of health and disease. Despite its importance in such works, few scholars have examined the role of geography in their narrative and structure. I examine the role of place in Epileptic and Stitches to extend the academic discussion on graphic novels of health and disease and identify how such works bring attention to the role of geography in the individual's engagement with health, disease, and related settings.
Extended model for Richtmyer-Meshkov mix
Mikaelian, K O
2009-11-18
We examine four Richtmyer-Meshkov (RM) experiments on shock-generated turbulent mix and find them to be in good agreement with our earlier simple model in which the growth rate h of the mixing layer following a shock or reshock is constant and given by 2{alpha}A{Delta}v, independent of initial conditions h{sub 0}. Here A is the Atwood number ({rho}{sub B}-{rho}{sub A})/({rho}{sub B} + {rho}{sub A}), {rho}{sub A,B} are the densities of the two fluids, {Delta}V is the jump in velocity induced by the shock or reshock, and {alpha} is the constant measured in Rayleigh-Taylor (RT) experiments: {alpha}{sup bubble} {approx} 0.05-0.07, {alpha}{sup spike} {approx} (1.8-2.5){alpha}{sup bubble} for A {approx} 0.7-1.0. In the extended model the growth rate beings to day after a time t*, when h = h*, slowing down from h = h{sub 0} + 2{alpha}A{Delta}vt to h {approx} t{sup {theta}} behavior, with {theta}{sup bubble} {approx} 0.25 and {theta}{sup spike} {approx} 0.36 for A {approx} 0.7. They ascribe this change-over to loss of memory of the direction of the shock or reshock, signaling transition from highly directional to isotropic turbulence. In the simplest extension of the model h*/h{sub 0} is independent of {Delta}v and depends only on A. They find that h*/h{sub 0} {approx} 2.5-3.5 for A {approx} 0.7-1.0.
Awate, Suyash P; Radhakrishnan, Thyagarajan
2015-01-01
In microscopy imaging, colocalization between two biological entities (e.g., protein-protein or protein-cell) refers to the (stochastic) dependencies between the spatial locations of the two entities in the biological specimen. Measuring colocalization between two entities relies on fluorescence imaging of the specimen using two fluorescent chemicals, each of which indicates the presence/absence of one of the entities at any pixel location. State-of-the-art methods for estimating colocalization rely on post-processing image data using an adhoc sequence of algorithms with many free parameters that are tuned visually. This leads to loss of reproducibility of the results. This paper proposes a brand-new framework for estimating the nature and strength of colocalization directly from corrupted image data by solving a single unified optimization problem that automatically deals with noise, object labeling, and parameter tuning. The proposed framework relies on probabilistic graphical image modeling and a novel inference scheme using variational Bayesian expectation maximization for estimating all model parameters, including colocalization, from data. Results on simulated and real-world data demonstrate improved performance over the state of the art.
Liu, Quan
2016-01-01
Learning a Gaussian graphical model with latent variables is ill posed when there is insufficient sample complexity, thus having to be appropriately regularized. A common choice is convex ℓ1 plus nuclear norm to regularize the searching process. However, the best estimator performance is not always achieved with these additive convex regularizations, especially when the sample complexity is low. In this paper, we consider a concave additive regularization which does not require the strong irrepresentable condition. We use concave regularization to correct the intrinsic estimation biases from Lasso and nuclear penalty as well. We establish the proximity operators for our concave regularizations, respectively, which induces sparsity and low rankness. In addition, we extend our method to also allow the decomposition of fused structure-sparsity plus low rankness, providing a powerful tool for models with temporal information. Specifically, we develop a nontrivial modified alternating direction method of multipliers with at least local convergence. Finally, we use both synthetic and real data to validate the excellence of our method. In the application of reconstructing two-stage cancer networks, “the Warburg effect” can be revealed directly. PMID:27843485
Configuring a Graphical User Interface for Managing Local HYSPLIT Model Runs Through AWIPS
NASA Technical Reports Server (NTRS)
Wheeler, mark M.; Blottman, Peter F.; Sharp, David W.; Hoeth, Brian; VanSpeybroeck, Kurt M.
2009-01-01
Responding to incidents involving the release of harmful airborne pollutants is a continual challenge for Weather Forecast Offices in the National Weather Service. When such incidents occur, current protocol recommends forecaster-initiated requests of NOAA's Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model output through the National Centers of Environmental Prediction to obtain critical dispersion guidance. Individual requests are submitted manually through a secured web site, with desired multiple requests submitted in sequence, for the purpose of obtaining useful trajectory and concentration forecasts associated with the significant release of harmful chemical gases, radiation, wildfire smoke, etc., into local the atmosphere. To help manage the local HYSPLIT for both routine and emergency use, a graphical user interface was designed for operational efficiency. The interface allows forecasters to quickly determine the current HYSPLIT configuration for the list of predefined sites (e.g., fixed sites and floating sites), and to make any necessary adjustments to key parameters such as Input Model. Number of Forecast Hours, etc. When using the interface, forecasters will obtain desired output more confidently and without the danger of corrupting essential configuration files.
Computer graphics in aerodynamic analysis
NASA Technical Reports Server (NTRS)
Cozzolongo, J. V.
1984-01-01
The use of computer graphics and its application to aerodynamic analyses on a routine basis is outlined. The mathematical modelling of the aircraft geometries and the shading technique implemented are discussed. Examples of computer graphics used to display aerodynamic flow field data and aircraft geometries are shown. A future need in computer graphics for aerodynamic analyses is addressed.
NASA Technical Reports Server (NTRS)
1990-01-01
A mathematician, David R. Hedgley, Jr. developed a computer program that considers whether a line in a graphic model of a three-dimensional object should or should not be visible. Known as the Hidden Line Computer Code, the program automatically removes superfluous lines and displays an object from a specific viewpoint, just as the human eye would see it. An example of how one company uses the program is the experience of Birdair which specializes in production of fabric skylights and stadium covers. The fabric called SHEERFILL is a Teflon coated fiberglass material developed in cooperation with DuPont Company. SHEERFILL glazed structures are either tension structures or air-supported tension structures. Both are formed by patterned fabric sheets supported by a steel or aluminum frame or cable network. Birdair uses the Hidden Line Computer Code, to illustrate a prospective structure to an architect or owner. The program generates a three- dimensional perspective with the hidden lines removed. This program is still used by Birdair and continues to be commercially available to the public.
Estimation of growth parameters using a nonlinear mixed Gompertz model.
Wang, Z; Zuidhof, M J
2004-06-01
In order to maximize the utility of simulation models for decision making, accurate estimation of growth parameters and associated variances is crucial. A mixed Gompertz growth model was used to account for between-bird variation and heterogeneous variance. The mixed model had several advantages over the fixed effects model. The mixed model partitioned BW variation into between- and within-bird variation, and the covariance structure assumed with the random effect accounted for part of the BW correlation across ages in the same individual. The amount of residual variance decreased by over 55% with the mixed model. The mixed model reduced estimation biases that resulted from selective sampling. For analysis of longitudinal growth data, the mixed effects growth model is recommended.
MixSIAR: A Bayesian stable isotope mixing model for characterizing intrapopulation niche variation
Background/Question/Methods The science of stable isotope mixing models has tended towards the development of modeling products (e.g. IsoSource, MixSIR, SIAR), where methodological advances or syntheses of the current state of the art are published in parity with software packa...
Kim, Won Hwa; Kim, Hyunwoo J; Adluru, Nagesh; Singh, Vikas
2016-06-01
A major goal of imaging studies such as the (ongoing) Human Connectome Project (HCP) is to characterize the structural network map of the human brain and identify its associations with covariates such as genotype, risk factors, and so on that correspond to an individual. But the set of image derived measures and the set of covariates are both large, so we must first estimate a 'parsimonious' set of relations between the measurements. For instance, a Gaussian graphical model will show conditional independences between the random variables, which can then be used to setup specific downstream analyses. But most such data involve a large list of 'latent' variables that remain unobserved, yet affect the 'observed' variables sustantially. Accounting for such latent variables is not directly addressed by standard precision matrix estimation, and is tackled via highly specialized optimization methods. This paper offers a unique harmonic analysis view of this problem. By casting the estimation of the precision matrix in terms of a composition of low-frequency latent variables and high-frequency sparse terms, we show how the problem can be formulated using a new wavelet-type expansion in non-Euclidean spaces. Our formulation poses the estimation problem in the frequency space and shows how it can be solved by a simple sub-gradient scheme. We provide a set of scientific results on ~500 scans from the recently released HCP data where our algorithm recovers highly interpretable and sparse conditional dependencies between brain connectivity pathways and well-known covariates.
Extremely large-scale simulation of a Kardar-Parisi-Zhang model using graphics cards.
Kelling, Jeffrey; Ódo, Géza
2011-12-01
The octahedron model introduced recently has been implemented onto graphics cards, which permits extremely large-scale simulations via binary lattice gases and bit-coded algorithms. We confirm scaling behavior belonging to the two-dimensional Kardar-Parisi-Zhang universality class and find a surface growth exponent: β = 0.2415(15) on 2(17) × 2(17) systems, ruling out β = 1/4 suggested by field theory. The maximum speedup with respect to a single CPU is 240. The steady state has been analyzed by finite-size scaling and a growth exponent α = 0.393(4) is found. Correction-to-scaling-exponent are computed and the power-spectrum density of the steady state is determined. We calculate the universal scaling functions and cumulants and show that the limit distribution can be obtained by the sizes considered. We provide numerical fitting for the small and large tail behavior of the steady-state scaling function of the interface width.
Lee, Mikyung; Huang, Ruili; Tong, Weida
2016-03-01
Nuclear receptors (NRs) are ligand-activated transcriptional regulators that play vital roles in key biological processes such as growth, differentiation, metabolism, reproduction, and morphogenesis. Disruption of NRs can result in adverse health effects such as NR-mediated endocrine disruption. A comprehensive understanding of core transcriptional targets regulated by NRs helps to elucidate their key biological processes in both toxicological and therapeutic aspects. In this study, we applied a probabilistic graphical model to identify the transcriptional targets of NRs and the biological processes they govern. The Tox21 program profiled a collection of approximate 10 000 environmental chemicals and drugs against a panel of human NRs in a quantitative high-throughput screening format for their NR disruption potential. The Japanese Toxicogenomics Project, one of the most comprehensive efforts in the field of toxicogenomics, generated large-scale gene expression profiles on the effect of 131 compounds (in its first phase of study) at various doses, and different durations, and their combinations. We applied author-topic model to these 2 toxicological datasets, which consists of 11 NRs run in either agonist and/or antagonist mode (18 assays total) and 203 in vitro human gene expression profiles connected by 52 shared drugs. As a result, a set of clusters (topics), which consists of a set of NRs and their associated target genes were determined. Various transcriptional targets of the NRs were identified by assays run in either agonist or antagonist mode. Our results were validated by functional analysis and compared with TRANSFAC data. In summary, our approach resulted in effective identification of associated/affected NRs and their target genes, providing biologically meaningful hypothesis embedded in their relationships.
Ward-Garrison, Christian; Markstrom, Steven L.; Hay, Lauren E.
2009-01-01
The U.S. Geological Survey Downsizer is a computer application that selects, downloads, verifies, and formats station-based time-series data for environmental-resource models, particularly the Precipitation-Runoff Modeling System. Downsizer implements the client-server software architecture. The client presents a map-based, graphical user interface that is intuitive to modelers; the server provides streamflow and climate time-series data from over 40,000 measurement stations across the United States. This report is the Downsizer user's manual and provides (1) an overview of the software design, (2) installation instructions, (3) a description of the graphical user interface, (4) a description of selected output files, and (5) troubleshooting information.
Robot graphic simulation testbed
NASA Technical Reports Server (NTRS)
Cook, George E.; Sztipanovits, Janos; Biegl, Csaba; Karsai, Gabor; Springfield, James F.
1991-01-01
The objective of this research was twofold. First, the basic capabilities of ROBOSIM (graphical simulation system) were improved and extended by taking advantage of advanced graphic workstation technology and artificial intelligence programming techniques. Second, the scope of the graphic simulation testbed was extended to include general problems of Space Station automation. Hardware support for 3-D graphics and high processing performance make high resolution solid modeling, collision detection, and simulation of structural dynamics computationally feasible. The Space Station is a complex system with many interacting subsystems. Design and testing of automation concepts demand modeling of the affected processes, their interactions, and that of the proposed control systems. The automation testbed was designed to facilitate studies in Space Station automation concepts.
Probabilistic graphical models to deal with age estimation of living persons.
Sironi, Emanuele; Gallidabino, Matteo; Weyermann, Céline; Taroni, Franco
2016-03-01
Due to the rise of criminal, civil and administrative judicial situations involving people lacking valid identity documents, age estimation of living persons has become an important operational procedure for numerous forensic and medicolegal services worldwide. The chronological age of a given person is generally estimated from the observed degree of maturity of some selected physical attributes by means of statistical methods. However, their application in the forensic framework suffers from some conceptual and practical drawbacks, as recently claimed in the specialised literature. The aim of this paper is therefore to offer an alternative solution for overcoming these limits, by reiterating the utility of a probabilistic Bayesian approach for age estimation. This approach allows one to deal in a transparent way with the uncertainty surrounding the age estimation process and to produce all the relevant information in the form of posterior probability distribution about the chronological age of the person under investigation. Furthermore, this probability distribution can also be used for evaluating in a coherent way the possibility that the examined individual is younger or older than a given legal age threshold having a particular legal interest. The main novelty introduced by this work is the development of a probabilistic graphical model, i.e. a Bayesian network, for dealing with the problem at hand. The use of this kind of probabilistic tool can significantly facilitate the application of the proposed methodology: examples are presented based on data related to the ossification status of the medial clavicular epiphysis. The reliability and the advantages of this probabilistic tool are presented and discussed.
The Effectiveness of an Interactive 3-Dimensional Computer Graphics Model for Medical Education
Konishi, Takeshi; Tamura, Yoko; Moriguchi, Hiroki
2012-01-01
Background Medical students often have difficulty achieving a conceptual understanding of 3-dimensional (3D) anatomy, such as bone alignment, muscles, and complex movements, from 2-dimensional (2D) images. To this end, animated and interactive 3-dimensional computer graphics (3DCG) can provide better visual information to users. In medical fields, research on the advantages of 3DCG in medical education is relatively new. Objective To determine the educational effectiveness of interactive 3DCG. Methods We divided 100 participants (27 men, mean (SD) age 17.9 (0.6) years, and 73 women, mean (SD) age 18.1 (1.1) years) from the Health Sciences University of Mongolia (HSUM) into 3DCG (n = 50) and textbook-only (control) (n = 50) groups. The control group used a textbook and 2D images, while the 3DCG group was trained to use the interactive 3DCG shoulder model in addition to a textbook. We conducted a questionnaire survey via an encrypted satellite network between HSUM and Tokushima University. The questionnaire was scored on a 5-point Likert scale from strongly disagree (score 1) to strongly agree (score 5). Results Interactive 3DCG was effective in undergraduate medical education. Specifically, there was a significant difference in mean (SD) scores between the 3DCG and control groups in their response to questionnaire items regarding content (4.26 (0.69) vs 3.85 (0.68), P = .001) and teaching methods (4.33 (0.65) vs 3.74 (0.79), P < .001), but no significant difference in the Web category. Participants also provided meaningful comments on the advantages of interactive 3DCG. Conclusions Interactive 3DCG materials have positive effects on medical education when properly integrated into conventional education. In particular, our results suggest that interactive 3DCG is more efficient than textbooks alone in medical education and can motivate students to understand complex anatomical structures. PMID:23611759
Kim, Won Hwa; Kim, Hyunwoo J.; Adluru, Nagesh; Singh, Vikas
2016-01-01
A major goal of imaging studies such as the (ongoing) Human Connectome Project (HCP) is to characterize the structural network map of the human brain and identify its associations with covariates such as genotype, risk factors, and so on that correspond to an individual. But the set of image derived measures and the set of covariates are both large, so we must first estimate a ‘parsimonious’ set of relations between the measurements. For instance, a Gaussian graphical model will show conditional independences between the random variables, which can then be used to setup specific downstream analyses. But most such data involve a large list of ‘latent’ variables that remain unobserved, yet affect the ‘observed’ variables sustantially. Accounting for such latent variables is not directly addressed by standard precision matrix estimation, and is tackled via highly specialized optimization methods. This paper offers a unique harmonic analysis view of this problem. By casting the estimation of the precision matrix in terms of a composition of low-frequency latent variables and high-frequency sparse terms, we show how the problem can be formulated using a new wavelet-type expansion in non-Euclidean spaces. Our formulation poses the estimation problem in the frequency space and shows how it can be solved by a simple sub-gradient scheme. We provide a set of scientific results on ~500 scans from the recently released HCP data where our algorithm recovers highly interpretable and sparse conditional dependencies between brain connectivity pathways and well-known covariates. PMID:28255221
Perception in statistical graphics
NASA Astrophysics Data System (ADS)
VanderPlas, Susan Ruth
There has been quite a bit of research on statistical graphics and visualization, generally focused on new types of graphics, new software to create graphics, interactivity, and usability studies. Our ability to interpret and use statistical graphics hinges on the interface between the graph itself and the brain that perceives and interprets it, and there is substantially less research on the interplay between graph, eye, brain, and mind than is sufficient to understand the nature of these relationships. The goal of the work presented here is to further explore the interplay between a static graph, the translation of that graph from paper to mental representation (the journey from eye to brain), and the mental processes that operate on that graph once it is transferred into memory (mind). Understanding the perception of statistical graphics should allow researchers to create more effective graphs which produce fewer distortions and viewer errors while reducing the cognitive load necessary to understand the information presented in the graph. Taken together, these experiments should lay a foundation for exploring the perception of statistical graphics. There has been considerable research into the accuracy of numerical judgments viewers make from graphs, and these studies are useful, but it is more effective to understand how errors in these judgments occur so that the root cause of the error can be addressed directly. Understanding how visual reasoning relates to the ability to make judgments from graphs allows us to tailor graphics to particular target audiences. In addition, understanding the hierarchy of salient features in statistical graphics allows us to clearly communicate the important message from data or statistical models by constructing graphics which are designed specifically for the perceptual system.
Shin, Woong-Hee; Kang, Xuejiao; Zhang, Jian; Kihara, Daisuke
2017-01-01
Protein tertiary structure prediction methods have matured in recent years. However, some proteins defy accurate prediction due to factors such as inadequate template structures. While existing model quality assessment methods predict global model quality relatively well, there is substantial room for improvement in local quality assessment, i.e. assessment of the error at each residue position in a model. Local quality is a very important information for practical applications of structure models such as interpreting/designing site-directed mutagenesis of proteins. We have developed a novel local quality assessment method for protein tertiary structure models. The method, named Graph-based Model Quality assessment method (GMQ), explicitly considers the predicted quality of spatially neighboring residues using a graph representation of a query protein structure model. GMQ uses conditional random field as its core of the algorithm, and performs a binary prediction of the quality of each residue in a model, indicating if a residue position is likely to be within an error cutoff or not. The accuracy of GMQ was improved by considering larger graphs to include quality information of more surrounding residues. Moreover, we found that using different edge weights in graphs reflecting different secondary structures further improves the accuracy. GMQ showed competitive performance on a benchmark for quality assessment of structure models from the Critical Assessment of Techniques for Protein Structure Prediction (CASP). PMID:28074879
Shin, Woong-Hee; Kang, Xuejiao; Zhang, Jian; Kihara, Daisuke
2017-01-11
Protein tertiary structure prediction methods have matured in recent years. However, some proteins defy accurate prediction due to factors such as inadequate template structures. While existing model quality assessment methods predict global model quality relatively well, there is substantial room for improvement in local quality assessment, i.e. assessment of the error at each residue position in a model. Local quality is a very important information for practical applications of structure models such as interpreting/designing site-directed mutagenesis of proteins. We have developed a novel local quality assessment method for protein tertiary structure models. The method, named Graph-based Model Quality assessment method (GMQ), explicitly considers the predicted quality of spatially neighboring residues using a graph representation of a query protein structure model. GMQ uses conditional random field as its core of the algorithm, and performs a binary prediction of the quality of each residue in a model, indicating if a residue position is likely to be within an error cutoff or not. The accuracy of GMQ was improved by considering larger graphs to include quality information of more surrounding residues. Moreover, we found that using different edge weights in graphs reflecting different secondary structures further improves the accuracy. GMQ showed competitive performance on a benchmark for quality assessment of structure models from the Critical Assessment of Techniques for Protein Structure Prediction (CASP).
ERIC Educational Resources Information Center
Towler, Alan L.
This guide to teaching graphic arts, one in a series of instructional materials for junior high industrial arts education, is designed to assist teachers as they plan and implement new courses of study and as they make revisions and improvements in existing courses in order to integrate classroom learning with real-life experiences. This graphic…
Reacting to Graphic Horror: A Model of Empathy and Emotional Behavior.
ERIC Educational Resources Information Center
Tamborini, Ron; And Others
1990-01-01
Studies viewer response to graphic horror films. Reports that undergraduate mass communication students viewed clips from two horror films and a scientific television program. Concludes that people who score high on measures for wandering imagination, fictional involvement, humanistic orientation, and emotional contagion tend to find horror films…
Implementing a Multiple Criteria Model Base in Co-Op with a Graphical User Interface Generator
1993-09-23
Decision Support System (Co-op) for Windows. The algorithms and the graphical user interfaces for these modules are implemented using Microsoft Visual ... Basic under the Windows based environment operating in a IBM compatible microcomputer. Design of the MCDM programs interface is based on general interface design principles of user control, screen design, and layout.
Radiolysis Model Formulation for Integration with the Mixed Potential Model
Buck, Edgar C.; Wittman, Richard S.
2014-07-10
The U.S. Department of Energy Office of Nuclear Energy (DOE-NE), Office of Fuel Cycle Technology has established the Used Fuel Disposition Campaign (UFDC) to conduct the research and development activities related to storage, transportation, and disposal of used nuclear fuel (UNF) and high-level radioactive waste. Within the UFDC, the components for a general system model of the degradation and subsequent transport of UNF is being developed to analyze the performance of disposal options [Sassani et al., 2012]. Two model components of the near-field part of the problem are the ANL Mixed Potential Model and the PNNL Radiolysis Model. This report is in response to the desire to integrate the two models as outlined in [Buck, E.C, J.L. Jerden, W.L. Ebert, R.S. Wittman, (2013) “Coupling the Mixed Potential and Radiolysis Models for Used Fuel Degradation,” FCRD-UFD-2013-000290, M3FT-PN0806058
ModelMuse: A U.S. Geological Survey Open-Source, Graphical User Interface for Groundwater Models
NASA Astrophysics Data System (ADS)
Winston, R. B.
2013-12-01
ModelMuse is a free publicly-available graphical preprocessor used to generate the input and display the output for several groundwater models. It is written in Object Pascal and the source code is available on the USGS software web site. Supported models include the MODFLOW family of models, PHAST (version 1), and SUTRA version 2.2. With MODFLOW and PHAST, the user generates a grid and uses 'objects' (points, lines, and polygons) to define boundary conditions and the spatial variation in aquifer properties. Because the objects define the spatial variation, the grid can be changed without the user needing to re-enter spatial data. The same paradigm is used with SUTRA except that the user generates a quadrilateral finite-element mesh instead of a rectangular grid. The user interacts with the model in a top view and in a vertical cross section. The cross section can be at any angle or location. There is also a three-dimensional view of the model. For SUTRA, a new method of visualizing the permeability and related properties has been introduced. In three dimensional SUTRA models, the user specifies the permeability tensor by specifying permeability in three mutually orthogonal directions that can be oriented in space in any direction. Because it is important for the user to be able to check both the magnitudes and directions of the permeabilities, ModelMuse displays the permeabilities as either a two-dimensional or a three-dimensional vector plot. Color is used to differentiate the maximum, middle, and minimum permeability vectors. The magnitude of the permeability is shown by the vector length. The vector angle shows the direction of the maximum, middle, or minimum permeability. Contour and color plots can also be used to display model input and output data.
Computer graphics and the graphic artist
NASA Technical Reports Server (NTRS)
Taylor, N. L.; Fedors, E. G.; Pinelli, T. E.
1985-01-01
A centralized computer graphics system is being developed at the NASA Langley Research Center. This system was required to satisfy multiuser needs, ranging from presentation quality graphics prepared by a graphic artist to 16-mm movie simulations generated by engineers and scientists. While the major thrust of the central graphics system was directed toward engineering and scientific applications, hardware and software capabilities to support the graphic artists were integrated into the design. This paper briefly discusses the importance of computer graphics in research; the central graphics system in terms of systems, software, and hardware requirements; the application of computer graphics to graphic arts, discussed in terms of the requirements for a graphic arts workstation; and the problems encountered in applying computer graphics to the graphic arts. The paper concludes by presenting the status of the central graphics system.
Models of neutrino mass, mixing and CP violation
NASA Astrophysics Data System (ADS)
King, Stephen F.
2015-12-01
In this topical review we argue that neutrino mass and mixing data motivates extending the Standard Model (SM) to include a non-Abelian discrete flavour symmetry in order to accurately predict the large leptonic mixing angles and {C}{P} violation. We begin with an overview of the SM puzzles, followed by a description of some classic lepton mixing patterns. Lepton mixing may be regarded as a deviation from tri-bimaximal mixing, with charged lepton corrections leading to solar mixing sum rules, or tri-maximal lepton mixing leading to atmospheric mixing rules. We survey neutrino mass models, using a roadmap based on the open questions in neutrino physics. We then focus on the seesaw mechanism with right-handed neutrinos, where sequential dominance (SD) can account for large lepton mixing angles and {C}{P} violation, with precise predictions emerging from constrained SD (CSD). We define the flavour problem and discuss progress towards a theory of favour using GUTs and discrete family symmetry. We classify models as direct, semidirect or indirect, according to the relation between the Klein symmetry of the mass matrices and the discrete family symmetry, in all cases focussing on spontaneous {C}{P} violation. Finally we give two examples of realistic and highly predictive indirect models with CSD, namely an A to Z of flavour with Pati-Salam and a fairly complete A 4 × SU(5) SUSY GUT of flavour, where both models have interesting implications for leptogenesis.
Nigam, Ravi; Schlosser, Ralf W; Lloyd, Lyle L
2006-09-01
Matrix strategies employing parts of speech arranged in systematic language matrices and milieu language teaching strategies have been successfully used to teach word combining skills to children who have cognitive disabilities and some functional speech. The present study investigated the acquisition and generalized production of two-term semantic relationships in a new population using new types of symbols. Three children with cognitive disabilities and little or no functional speech were taught to combine graphic symbols. The matrix strategy and the mand-model procedure were used concomitantly as intervention procedures. A multiple probe design across sets of action-object combinations with generalization probes of untrained combinations was used to teach the production of graphic symbol combinations. Results indicated that two of the three children learned the early syntactic-semantic rule of combining action-object symbols and demonstrated generalization to untrained action-object combinations and generalization across trainers. The results and future directions for research are discussed.
A multifluid mix model with material strength effects
Chang, C. H.; Scannapieco, A. J.
2012-04-23
We present a new multifluid mix model. Its features include material strength effects and pressure and temperature nonequilibrium between mixing materials. It is applicable to both interpenetration and demixing of immiscible fluids and diffusion of miscible fluids. The presented model exhibits the appropriate smooth transition in mathematical form as the mixture evolves from multiphase to molecular mixing, extending its applicability to the intermediate stages in which both types of mixing are present. Virtual mass force and momentum exchange have been generalized for heterogeneous multimaterial mixtures. The compression work has been extended so that the resulting species energy equations are consistent with the pressure force and material strength.
2013-01-01
Background Until now, no kinetic model was described for the oncologic tracer [18F]fluoromethylcholine ([18F]FCho), so it was aimed to validate a proper model, which is easy to implement and allows tracer quantification in tissues. Methods Based on the metabolic profile, two types of compartmental models were evaluated. One is a 3C2i model, which contains three tissue compartments and two input functions and corrects for possible [18F]fluorobetaine ([18F]FBet) uptake by the tissues. On the other hand, a two-tissue-compartment model (2C1i) was evaluated. Moreover, a comparison, based on intra-observer variability, was made between kinetic modelling and graphical analysis. Results Determination of the [18F]FCho-to-[18F]FBet uptake ratios in tissues and evaluation of the fitting of both kinetic models indicated that corrections for [18F]FBet uptake are not mandatory. In addition, [18F]FCho uptake is well described by the 2C1i model and by graphical analysis by means of the Patlak plot. Conclusions The Patlak plot is a reliable, precise, and robust method to quantify [18F]FCho uptake independent of scan time or plasma clearance. In addition, it is easily implemented, even under non-equilibrium conditions and without creating additional errors. PMID:24034278
Modeling a Rain-Induced Mixed Layer
1990-06-01
te -)-A-- e e -2)- . (7) ’&Z AZ Az D Using the exponential relations with trigonometry , equation (7) becomes, Ok n) 3 (I- cos2ikAz)+ D (1- cos ikAz...completely unknown because there are no prior studies which predict what portion of total energy may go into subsurface mixing. The biggest obstacle
ERIC Educational Resources Information Center
Holladay, Jennifer
2009-01-01
Since 2002, Teaching Tolerance's Mix It Up at Lunch Day program has helped millions of students cross social boundaries and create more inclusive school communities. Its goal is to create a safe, purposeful opportunity for students to break down the patterns of social self-segregation that too often plague schools. Research conducted in 2006 by…
Imaging and quantifying mixing in a model droplet micromixer
NASA Astrophysics Data System (ADS)
Stone, Z. B.; Stone, H. A.
2005-06-01
Rapid mixing is essential in a variety of microfluidic applications but is often difficult to achieve at low Reynolds numbers. Inspired by a recently developed microdevice that mixes reagents in droplets, which simply flow along a periodic serpentine channel [H. Song, J. D. Tice, and R. F. Ismagilov, "A microfluidic system for controlling reaction networks in time," Angew. Chem. Int. Ed. 42, 767 (2003)], we investigate a model "droplet mixer." The model consists of a spherical droplet immersed in a periodic sequence of distinct external flows, which are superpositions of uniform and shear flows. We label the fluid inside the droplet with two colors and visualize mixing with a method we call "backtrace imaging," which allows us to render cross sections of the droplet at arbitrary times during the mixing cycle. To analyze our results, we present a novel scalar measure of mixing that permits us to locate sets of parameters that optimize mixing over a small number of flow cycles.
Analysis and modeling of subgrid scalar mixing using numerical data
NASA Technical Reports Server (NTRS)
Girimaji, Sharath S.; Zhou, YE
1995-01-01
Direct numerical simulations (DNS) of passive scalar mixing in isotropic turbulence is used to study, analyze and, subsequently, model the role of small (subgrid) scales in the mixing process. In particular, we attempt to model the dissipation of the large scale (supergrid) scalar fluctuations caused by the subgrid scales by decomposing it into two parts: (1) the effect due to the interaction among the subgrid scales; and (2) the effect due to interaction between the supergrid and the subgrid scales. Model comparisons with DNS data show good agreement. This model is expected to be useful in the large eddy simulations of scalar mixing and reaction.
Souza, W.R.
1987-01-01
This report documents a graphical display program for the U. S. Geological Survey finite-element groundwater flow and solute transport model. Graphic features of the program, SUTRA-PLOT (SUTRA-PLOT = saturated/unsaturated transport), include: (1) plots of the finite-element mesh, (2) velocity vector plots, (3) contour plots of pressure, solute concentration, temperature, or saturation, and (4) a finite-element interpolator for gridding data prior to contouring. SUTRA-PLOT is written in FORTRAN 77 on a PRIME 750 computer system, and requires Version 9.0 or higher of the DISSPLA graphics library. The program requires two input files: the SUTRA input data list and the SUTRA simulation output listing. The program is menu driven and specifications for individual types of plots are entered and may be edited interactively. Installation instruction, a source code listing, and a description of the computer code are given. Six examples of plotting applications are used to demonstrate various features of the plotting program. (Author 's abstract)
An Investigation of Item Fit Statistics for Mixed IRT Models
ERIC Educational Resources Information Center
Chon, Kyong Hee
2009-01-01
The purpose of this study was to investigate procedures for assessing model fit of IRT models for mixed format data. In this study, various IRT model combinations were fitted to data containing both dichotomous and polytomous item responses, and the suitability of the chosen model mixtures was evaluated based on a number of model fit procedures.…
On the coalescence-dispersion modeling of turbulent molecular mixing
NASA Technical Reports Server (NTRS)
Givi, Peyman; Kosaly, George
1987-01-01
The general coalescence-dispersion (C/D) closure provides phenomenological modeling of turbulent molecular mixing. The models of Curl and Dopazo and O'Brien appear as two limiting C/D models that bracket the range of results one can obtain by various models. This finding is used to investigate the sensitivtiy of the results to the choice of the model. Inert scalar mixing is found to be less model-sensitive than mixing accompanied by chemical reaction. Infinitely fast chemistry approximation is used to relate the C/D approach to Toor's earlier results. Pure mixing and infinite rate chemistry calculations are compared to study further a recent result of Hsieh and O'Brien who found that higher concentration moments are not sensitive to chemistry.
A Non-Fickian Mixing Model for Stratified Turbulent Flows
2011-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. A Non-Fickian Mixing Model for Stratified Turbulent Flows...would be to improve the predictive skill of the Navy numerical models for submesoscale transport in the ocean. OBJECTIVES My main objective...COVERED 00-00-2011 to 00-00-2011 4. TITLE AND SUBTITLE A Non-Fickian Mixing Model for Stratified Turbulent Flows 5a. CONTRACT NUMBER 5b. GRANT
Simulation model for urban ternary mix-traffic flow
NASA Astrophysics Data System (ADS)
Deo, Lalit; Akkawi, Faisal; Deo, Puspita
2007-12-01
A two-lane two-way traffic light controlled X-intersection for ternary mix traffic (cars + buses (equivalent vehicles) + very large trucks/ buses) is developed based on cellular automata model. This model can provide different matrices such as throughput, queue length and delay time. This paper will describe how the model works and how composition of traffic mix effects the throughput (numbers of vehicles navigate through the intersection per unit of time (vph)) and also compare the result with homogeneous counterpart.
Development of a Medicaid Behavioral Health Case-Mix Model
ERIC Educational Resources Information Center
Robst, John
2009-01-01
Many Medicaid programs have either fully or partially carved out mental health services. The evaluation of carve-out plans requires a case-mix model that accounts for differing health status across Medicaid managed care plans. This article develops a diagnosis-based case-mix adjustment system specific to Medicaid behavioral health care. Several…
Diagnostic tools for mixing models of stream water chemistry
Hooper, R.P.
2003-01-01
Mixing models provide a useful null hypothesis against which to evaluate processes controlling stream water chemical data. Because conservative mixing of end-members with constant concentration is a linear process, a number of simple mathematical and multivariate statistical methods can be applied to this problem. Although mixing models have been most typically used in the context of mixing soil and groundwater end-members, an extension of the mathematics of mixing models is presented that assesses the "fit" of a multivariate data set to a lower dimensional mixing subspace without the need for explicitly identified end-members. Diagnostic tools are developed to determine the approximate rank of the data set and to assess lack of fit of the data. This permits identification of processes that violate the assumptions of the mixing model and can suggest the dominant processes controlling stream water chemical variation. These same diagnostic tools can be used to assess the fit of the chemistry of one site into the mixing subspace of a different site, thereby permitting an assessment of the consistency of controlling end-members across sites. This technique is applied to a number of sites at the Panola Mountain Research Watershed located near Atlanta, Georgia.
Graphics processing unit implementation of lattice Boltzmann models for flowing soft systems.
Bernaschi, Massimo; Rossi, Ludovico; Benzi, Roberto; Sbragaglia, Mauro; Succi, Sauro
2009-12-01
A graphic processing unit (GPU) implementation of the multicomponent lattice Boltzmann equation with multirange interactions for soft-glassy materials ["glassy" lattice Boltzmann (LB)] is presented. Performance measurements for flows under shear indicate a GPU/CPU speed up in excess of 10 for 1024(2) grids. Such significant speed up permits to carry out multimillion time-steps simulations of 1024(2) grids within tens of hours of GPU time, thereby considerably expanding the scope of the glassy LB toward the investigation of long-time relaxation properties of soft-flowing glassy materials.
On the uniqueness of quantitative DNA difference descriptors in 2D graphical representation models
NASA Astrophysics Data System (ADS)
Nandy, A.; Nandy, P.
2003-01-01
The rapid growth in additions to databases of DNA primary sequence data have led to searches for methods to numerically characterize these data and help in fast identification and retrieval of relevant sequences. The DNA descriptors derived from the 2D graphical representation technique have already been proposed to index chemical toxicity and single nucleotide polymorphic (SNP) genes but the inherent degeneracies in this representation have given rise to doubts about their suitability. We prove in this paper that such degeneracies will exist only in very restricted cases and that the method can be relied upon to provide unique descriptors for, in particular, the SNP genes and several other classes of DNA sequences.
NASA Astrophysics Data System (ADS)
Roy, S. G.; Koons, P. O.; Gerbi, C. C.; Capps, D. K.; Tucker, G. E.; Rogers, Z. A.
2014-12-01
Sophisticated numerical tools exist for modeling geomorphic processes and linking them to tectonic and climatic systems, but they are often seen as inaccessible for users with an exploratory level of interest. We have improved the accessibility of landscape evolution models by producing a simple graphics user interface (GUI) that takes advantage of the Channel-Hillslope Integrated Landscape Development (CHILD) model. Model access is flexible: the user can edit values for basic geomorphic, tectonic, and climate parameters, or obtain greater control by defining the spatiotemporal distributions of those parameters. Users can make educated predictions by choosing their own parametric values for the governing equations and interpreting the results immediately through model graphics. This method of modeling allows users to iteratively build their understanding through experimentation. Use of this GUI is intended for inquiry and discovery-based learning activities. We discuss a number of examples of how the GUI can be used at the upper high school, introductory university, and advanced university level. Effective teaching modules initially focus on an inquiry-based example guided by the instructor. As students become familiar with the GUI and the CHILD model, the class can shift to more student-centered exploration and experimentation. To make model interpretations more robust, digital elevation models can be imported and direct comparisons can be made between CHILD model results and natural topography. The GUI is available online through the University of Maine's Earth and Climate Sciences website, through the Community Surface Dynamics Modeling System (CSDMS) model repository, or by contacting the corresponding author.
Shell model of optimal passive-scalar mixing
NASA Astrophysics Data System (ADS)
Miles, Christopher; Doering, Charles
2015-11-01
Optimal mixing is significant to process engineering within industries such as food, chemical, pharmaceutical, and petrochemical. An important question in this field is ``How should one stir to create a homogeneous mixture while being energetically efficient?'' To answer this question, we consider an initially unmixed scalar field representing some concentration within a fluid on a periodic domain. This passive-scalar field is advected by the velocity field, our control variable, constrained by a physical quantity such as energy or enstrophy. We consider two objectives: local-in-time (LIT) optimization (what will maximize the mixing rate now?) and global-in-time (GIT) optimization (what will maximize mixing at the end time?). Throughout this work we use the H-1 mix-norm to measure mixing. To gain a better understanding, we provide a simplified mixing model by using a shell model of passive-scalar advection. LIT optimization in this shell model gives perfect mixing in finite time for the energy-constrained case and exponential decay to the perfect-mixed state for the enstrophy-constrained case. Although we only enforce that the time-average energy (or enstrophy) equals a chosen value in GIT optimization, interestingly, the optimal control keeps this value constant over time.
VISUAL PLUMES MIXING ZONE MODELING SOFTWARE
The US Environmental Protection Agency has a history of developing plume models and providing technical assistance. The Visual Plumes model (VP) is a recent addition to the public-domain models available on the EPA Center for Exposure Assessment Modeling (CEAM) web page. The Wind...
Graphical programming of telerobotic tasks
Small, D.E.; McDonald, M.J.
1996-11-01
With a goal of producing faster, safer, and cheaper technologies for nuclear waste cleanup, Sandia is actively developing and extending intelligent systems technologies through the US Department of Energy Office of Technology Development (DOE OTD) Robotic Technology Development Program (RTDP). Graphical programming is a key technology for robotic waste cleanup that Sandia is developing for this goal. Graphical programming uses simulation such as TELEGRIP `on-line` to program and control robots. Characterized by its model-based control architecture, integrated simulation, `point-and-click` graphical user interfaces, task and path planning software, and network communications, Sandia`s Graphical Programming systems allow operators to focus on high-level robotic tasks rather than the low-level details. Use of scripted tasks, rather than customized programs minimizes the necessity of recompiling supervisory control systems and enhances flexibility. Rapid world-modelling technologies allow Graphical Programming to be used in dynamic and unpredictable environments including digging and pipe-cutting. This paper describes Sancho, Sandia`s most advanced graphical programming supervisory software. Sancho, now operational on several robot systems, incorporates all of Sandia`s recent advances in supervisory control. Graphical programming uses 3-D graphics models as intuitive operator interfaces to program and control complex robotic systems. The goal of the paper is to help the reader understand how Sandia implements graphical programming systems and which key features in Sancho have proven to be most effective.
Scaled tests and modeling of effluent stack sampling location mixing.
Recknagle, Kurtis P; Yokuda, Satoru T; Ballinger, Marcel Y; Barnett, J Matthew
2009-02-01
A three-dimensional computational fluid dynamics computer model was used to evaluate the mixing at a sampling system for radioactive air emissions. Researchers sought to determine whether the location would meet the criteria for uniform air velocity and contaminant concentration as prescribed in the American National Standards Institute standard, Sampling and Monitoring Releases of Airborne Radioactive Substances from the Stacks and Ducts of Nuclear Facilities. This standard requires that the sampling location be well-mixed and stipulates specific tests to verify the extent of mixing. The exhaust system for the Radiochemical Processing Laboratory was modeled with a computational fluid dynamics code to better understand the flow and contaminant mixing and to predict mixing test results. The modeled results were compared to actual measurements made at a scale-model stack and to the limited data set for the full-scale facility stack. Results indicated that the computational fluid dynamics code provides reasonable predictions for velocity, cyclonic flow, gas, and aerosol uniformity, although the code predicts greater improvement in mixing as the injection point is moved farther away from the sampling location than is actually observed by measurements. In expanding from small to full scale, the modeled predictions for full-scale measurements show similar uniformity values as in the scale model. This work indicated that a computational fluid dynamics code can be a cost-effective aid in designing or retrofitting a facility's stack sampling location that will be required to meet standard ANSI/HPS N13.1-1999.
Souza, W.R.
1999-01-01
This report documents a graphical display post-processor (SutraPlot) for the U.S. Geological Survey Saturated-Unsaturated flow and solute or energy TRAnsport simulation model SUTRA, Version 2D3D.1. This version of SutraPlot is an upgrade to SutraPlot for the 2D-only SUTRA model (Souza, 1987). It has been modified to add 3D functionality, a graphical user interface (GUI), and enhanced graphic output options. Graphical options for 2D SUTRA (2-dimension) simulations include: drawing the 2D finite-element mesh, mesh boundary, and velocity vectors; plots of contours for pressure, saturation, concentration, and temperature within the model region; 2D finite-element based gridding and interpolation; and 2D gridded data export files. Graphical options for 3D SUTRA (3-dimension) simulations include: drawing the 3D finite-element mesh; plots of contours for pressure, saturation, concentration, and temperature in 2D sections of the 3D model region; 3D finite-element based gridding and interpolation; drawing selected regions of velocity vectors (projected on principal coordinate planes); and 3D gridded data export files. Installation instructions and a description of all graphic options are presented. A sample SUTRA problem is described and three step-by-step SutraPlot applications are provided. In addition, the methodology and numerical algorithms for the 2D and 3D finite-element based gridding and interpolation, developed for SutraPlot, are described. 1
2010-05-10
Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/6180--10-9244 User Manual for Graphical User Interface Version 2.10 with Fire and Smoke...ABSTRACT User Manual for Graphical User Interface Version 2.10 with Fire and Smoke Simulation Model (FSSIM) Version 1.2 Tomasz A. Haupt,* Gregory J...runtime environment for a third-party simulation package, Fire and Smoke Simulation (FSSIM) developed by HAI. This updated user’s manual for the
Weakly nonlinear models for turbulent mixing in a plane mixing layer
NASA Technical Reports Server (NTRS)
Liou, William W.; Morris, Philip J.
1992-01-01
New closure models for turbulent free shear flows are presented in this paper. They are based on a weakly nonlinear theory with a description of the dominant large-scale structures as instability waves. Two models are presented that describe the evolution of the free shear flows in terms of the time-averaged mean flow and the dominant large-scale turbulent structure. The local characteristics of the large-scale motions are described using linear theory. Their amplitude is determined from an energy integral analysis. The models have been applied to the study of an incompressible mixing layer. For both models, predictions of the mean flow developed are made. In the second model, predictions of the time-dependent motion of the large-scale structures in the mixing layer are made. The predictions show good agreement with experimental observations.
Mixing Model Performance in Non-Premixed Turbulent Combustion
NASA Astrophysics Data System (ADS)
Pope, Stephen B.; Ren, Zhuyin
2002-11-01
In order to shed light on their qualitative and quantitative performance, three different turbulent mixing models are studied in application to non-premixed turbulent combustion. In previous works, PDF model calculations with detailed kinetics have been shown to agree well with experimental data for non-premixed piloted jet flames. The calculations from two different groups using different descriptions of the chemistry and turbulent mixing are capable of producing the correct levels of local extinction and reignition. The success of these calculations raises several questions, since it is not clear that the mixing models used contain an adequate description of the processes involved. To address these questions, three mixing models (IEM, modified Curl and EMST) are applied to a partially-stirred reactor burning hydrogen in air. The parameters varied are the residence time and the mixing time scale. For small relative values of the mixing time scale (approaching the perfectly-stirred limit) the models yield the same extinction behavior. But for larger values, the behavior is distictly different, with EMST being must resistant to extinction.
A Comparison of Item Fit Statistics for Mixed IRT Models
ERIC Educational Resources Information Center
Chon, Kyong Hee; Lee, Won-Chan; Dunbar, Stephen B.
2010-01-01
In this study we examined procedures for assessing model-data fit of item response theory (IRT) models for mixed format data. The model fit indices used in this study include PARSCALE's G[superscript 2], Orlando and Thissen's S-X[superscript 2] and S-G[superscript 2], and Stone's chi[superscript 2*] and G[superscript 2*]. To investigate the…
A Bayesian Semiparametric Latent Variable Model for Mixed Responses
ERIC Educational Resources Information Center
Fahrmeir, Ludwig; Raach, Alexander
2007-01-01
In this paper we introduce a latent variable model (LVM) for mixed ordinal and continuous responses, where covariate effects on the continuous latent variables are modelled through a flexible semiparametric Gaussian regression model. We extend existing LVMs with the usual linear covariate effects by including nonparametric components for nonlinear…
Regional Conference on the Analysis of the Unbalanced Mixed Model.
1987-12-31
this complicated problem. Paper titles: The Present Status of Confidence Interval Estimation on Variance Components in Balanced and Unbalanced Random...Models; Prediction-Interval Procedures and (Fixed Effects) Confidence - Interval Procedures for Mixed Linear Models; The Use of Equivalent linear Models
Zierer, Jonas; Pallister, Tess; Tsai, Pei-Chien; Krumsiek, Jan; Bell, Jordana T.; Lauc, Gordan; Spector, Tim D; Menni, Cristina; Kastenmüller, Gabi
2016-01-01
Although association studies have unveiled numerous correlations of biochemical markers with age and age-related diseases, we still lack an understanding of their mutual dependencies. To find molecular pathways that underlie age-related diseases as well as their comorbidities, we integrated aging markers from four different high-throughput omics datasets, namely epigenomics, transcriptomics, glycomics and metabolomics, with a comprehensive set of disease phenotypes from 510 participants of the TwinsUK cohort. We used graphical random forests to assess conditional dependencies between omics markers and phenotypes while eliminating mediated associations. Applying this novel approach for multi-omics data integration yields a model consisting of seven modules that represent distinct aspects of aging. These modules are connected by hubs that potentially trigger comorbidities of age-related diseases. As an example, we identified urate as one of these key players mediating the comorbidity of renal disease with body composition and obesity. Body composition variables are in turn associated with inflammatory IgG markers, mediated by the expression of the hormone oxytocin. Thus, oxytocin potentially contributes to the development of chronic low-grade inflammation, which often accompanies obesity. Our multi-omics graphical model demonstrates the interconnectivity of age-related diseases and highlights molecular markers of the aging process that might drive disease comorbidities. PMID:27886242
Hunt, G. ); Azmy, Y.Y. )
1992-10-01
DCOR is a user-friendly computer implementation of a deterministic combat model developed at ORNL. To make the interpretation of the results more intuitive, a conversion of the numerical solution to a graphic animation sequence of battle evolution is desirable. DCOR uses a coarse computational spatial mesh superimposed on the battlefield. This research is aimed at developing robust methods for computing the position of the combative units over the continuum (and also pixeled) battlefield, from DCOR's discrete-variable solution representing the density of each force type evaluated at gridpoints. Three main problems have been identified and solutions have been devised and implemented in a new visualization module of DCOR. First, there is the problem of distributing the total number of objects, each representing a combative unit of each force type, among the gridpoints at each time level of the animation. This problem is solved by distributing, for each force type, the total number of combative units, one by one, to the gridpoint with the largest calculated number of units. Second, there is the problem of distributing the number of units assigned to each computational gridpoint over the battlefield area attributed to that point. This problem is solved by distributing the units within that area by taking into account the influence of surrounding gridpoints using linear interpolation. Finally, time interpolated solutions must be generated to produce a sufficient number of frames to create a smooth animation sequence. Currently, enough frames may be generated either by direct computation via the PDE solver or by using linear programming techniques to linearly interpolate intermediate frames between calculated frames.
Mixing by barotropic instability in a nonlinear model
NASA Technical Reports Server (NTRS)
Bowman, Kenneth P.; Chen, Ping
1994-01-01
A global, nonlinear, equivalent barotropic model is used to study the isentropic mixing of passive tracers by barotropic instability. Basic states are analytical zonal-mean jets representative of the zonal-mean flow in the upper stratosphere, where the observed 4-day wave is thought to be a result of barotropic, and possibly baroclinic, instability. As is known from previous studies, the phase speed and growth rate of the unstable waves is fairly sensitive to the shape of the zonal-mean jet; and the dominant wave mode at saturation is not necessarily the fastest growing mode; but the unstable modes share many features of the observed 4-day wave. Lagrangian trajectories computed from model winds are used to characterize the mixing by the flow. For profiles with both midlatitude and polar modes, mixing is stronger in midlatitude than inside the vortex; but there is little exchange of air across the vortex boundary. There is a minimum in the Lyapunov exponents of the flow and the particle dispersion at the jet maximum. For profiles with only polar unstable modes, there is weak mixing inside the vortex, no mixing outside the vortex, and no exchange of air across the vortex boundary. These results support the theoretical arguments that, whether wave disturbances are generated by local instability or propagate from other regions, the mixing properties of the total flow are determined by the locations of the wave critical lines and that strong gradients of potential vorticity are very resistant to mixing.
New mixing angles in the left-right symmetric model
NASA Astrophysics Data System (ADS)
Kokado, Akira; Saito, Takesi
2015-12-01
In the left-right symmetric model neutral gauge fields are characterized by three mixing angles θ12,θ23,θ13 between three gauge fields Bμ,WLμ 3,WRμ 3, which produce mass eigenstates Aμ,Zμ,Zμ', when G =S U (2 )L×S U (2 )R×U (1 )B-L×D is spontaneously broken down until U (1 )em . We find a new mixing angle θ', which corresponds to the Weinberg angle θW in the standard model with the S U (2 )L×U (1 )Y gauge symmetry, from these mixing angles. It is then shown that any mixing angle θi j can be expressed by ɛ and θ', where ɛ =gL/gR is a ratio of running left-right gauge coupling strengths. We observe that light gauge bosons are described by θ' only, whereas heavy gauge bosons are described by two parameters ɛ and θ'.
NASA Astrophysics Data System (ADS)
Fourtakas, G.; Rogers, B. D.
2016-06-01
A two-phase numerical model using Smoothed Particle Hydrodynamics (SPH) is applied to two-phase liquid-sediments flows. The absence of a mesh in SPH is ideal for interfacial and highly non-linear flows with changing fragmentation of the interface, mixing and resuspension. The rheology of sediment induced under rapid flows undergoes several states which are only partially described by previous research in SPH. This paper attempts to bridge the gap between the geotechnics, non-Newtonian and Newtonian flows by proposing a model that combines the yielding, shear and suspension layer which are needed to predict accurately the global erosion phenomena, from a hydrodynamics prospective. The numerical SPH scheme is based on the explicit treatment of both phases using Newtonian and the non-Newtonian Bingham-type Herschel-Bulkley-Papanastasiou constitutive model. This is supplemented by the Drucker-Prager yield criterion to predict the onset of yielding of the sediment surface and a concentration suspension model. The multi-phase model has been compared with experimental and 2-D reference numerical models for scour following a dry-bed dam break yielding satisfactory results and improvements over well-known SPH multi-phase models. With 3-D simulations requiring a large number of particles, the code is accelerated with a graphics processing unit (GPU) in the open-source DualSPHysics code. The implementation and optimisation of the code achieved a speed up of x58 over an optimised single thread serial code. A 3-D dam break over a non-cohesive erodible bed simulation with over 4 million particles yields close agreement with experimental scour and water surface profiles.
Graphic engine resource management
NASA Astrophysics Data System (ADS)
Bautin, Mikhail; Dwarakinath, Ashok; Chiueh, Tzi-cker
2008-01-01
Modern consumer-grade 3D graphic cards boast a computation/memory resource that can easily rival or even exceed that of standard desktop PCs. Although these cards are mainly designed for 3D gaming applications, their enormous computational power has attracted developers to port an increasing number of scientific computation programs to these cards, including matrix computation, collision detection, cryptography, database sorting, etc. As more and more applications run on 3D graphic cards, there is a need to allocate the computation/memory resource on these cards among the sharing applications more fairly and efficiently. In this paper, we describe the design, implementation and evaluation of a Graphic Processing Unit (GPU) scheduler based on Deficit Round Robin scheduling that successfully allocates to every process an equal share of the GPU time regardless of their demand. This scheduler, called GERM, estimates the execution time of each GPU command group based on dynamically collected statistics, and controls each process's GPU command production rate through its CPU scheduling priority. Measurements on the first GERM prototype show that this approach can keep the maximal GPU time consumption difference among concurrent GPU processes consistently below 5% for a variety of application mixes.
A Mixed Effects Randomized Item Response Model
ERIC Educational Resources Information Center
Fox, J.-P.; Wyrick, Cheryl
2008-01-01
The randomized response technique ensures that individual item responses, denoted as true item responses, are randomized before observing them and so-called randomized item responses are observed. A relationship is specified between randomized item response data and true item response data. True item response data are modeled with a (non)linear…
Regression models for mixed Poisson and continuous longitudinal data.
Yang, Ying; Kang, Jian; Mao, Kai; Zhang, Jie
2007-09-10
In this article we develop flexible regression models in two respects to evaluate the influence of the covariate variables on the mixed Poisson and continuous responses and to evaluate how the correlation between Poisson response and continuous response changes over time. A scenario for dealing with regression models of mixed continuous and Poisson responses when the heterogeneous variance and correlation changing over time exist is proposed. Our general approach is first to jointly build marginal model and to check whether the variance and correlation change over time via likelihood ratio test. If the variance and correlation change over time, we will do a suitable data transformation to properly evaluate the influence of the covariates on the mixed responses. The proposed methods are applied to the interstitial cystitis data base (ICDB) cohort study, and we find that the positive correlations significantly change over time, which suggests heterogeneous variances should not be ignored in modelling and inference.
Generalized Dynamic Factor Models for Mixed-Measurement Time Series
Cui, Kai; Dunson, David B.
2013-01-01
In this article, we propose generalized Bayesian dynamic factor models for jointly modeling mixed-measurement time series. The framework allows mixed-scale measurements associated with each time series, with different measurements having different distributions in the exponential family conditionally on time-varying latent factor(s). Efficient Bayesian computational algorithms are developed for posterior inference on both the latent factors and model parameters, based on a Metropolis Hastings algorithm with adaptive proposals. The algorithm relies on a Greedy Density Kernel Approximation (GDKA) and parameter expansion with latent factor normalization. We tested the framework and algorithms in simulated studies and applied them to the analysis of intertwined credit and recovery risk for Moody’s rated firms from 1982–2008, illustrating the importance of jointly modeling mixed-measurement time series. The article has supplemental materials available online. PMID:24791133
Generalized Dynamic Factor Models for Mixed-Measurement Time Series.
Cui, Kai; Dunson, David B
2014-02-12
In this article, we propose generalized Bayesian dynamic factor models for jointly modeling mixed-measurement time series. The framework allows mixed-scale measurements associated with each time series, with different measurements having different distributions in the exponential family conditionally on time-varying latent factor(s). Efficient Bayesian computational algorithms are developed for posterior inference on both the latent factors and model parameters, based on a Metropolis Hastings algorithm with adaptive proposals. The algorithm relies on a Greedy Density Kernel Approximation (GDKA) and parameter expansion with latent factor normalization. We tested the framework and algorithms in simulated studies and applied them to the analysis of intertwined credit and recovery risk for Moody's rated firms from 1982-2008, illustrating the importance of jointly modeling mixed-measurement time series. The article has supplemental materials available online.
MULTIVARIATE LINEAR MIXED MODELS FOR MULTIPLE OUTCOMES. (R824757)
We propose a multivariate linear mixed (MLMM) for the analysis of multiple outcomes, which generalizes the latent variable model of Sammel and Ryan. The proposed model assumes a flexible correlation structure among the multiple outcomes, and allows a global test of the impact of ...
Teaching Service Modelling to a Mixed Class: An Integrated Approach
ERIC Educational Resources Information Center
Deng, Jeremiah D.; Purvis, Martin K.
2015-01-01
Service modelling has become an increasingly important area in today's telecommunications and information systems practice. We have adapted a Network Design course in order to teach service modelling to a mixed class of both the telecommunication engineering and information systems backgrounds. An integrated approach engaging mathematics teaching…
Teaching the Mixed Model Design: A Flowchart to Facilitate Understanding.
ERIC Educational Resources Information Center
Mills, Jamie D.
2005-01-01
The Mixed Model (MM) design, sometimes known as a Split-Plot design, is very popular in educational research. This model can be used to examine the effects of several independent variables on a dependent variable and it offers a more powerful alternative to the completely randomized design. The MM design considers both a between-subjects factor,…
Temperature Chaos in Some Spherical Mixed p-Spin Models
NASA Astrophysics Data System (ADS)
Chen, Wei-Kuo; Panchenko, Dmitry
2017-03-01
We give two types of examples of the spherical mixed even- p-spin models for which chaos in temperature holds. These complement some known results for the spherical pure p-spin models and for models with Ising spins. For example, in contrast to a recent result of Subag who showed absence of chaos in temperature in the spherical pure p-spin models for p≥3, we show that even a smaller order perturbation induces temperature chaos.
Modeling the iron cycling in the mixed layer
NASA Astrophysics Data System (ADS)
Weber, L.; Voelker, C.; Schartau, M.; Wolf-Gladrow, D.
2003-04-01
We present a comprehensive model of the iron cycling within the mixed layer of the ocean, which predicts the time course of iron concentration and speciation. The speciation of iron within the mixed layer is heavily influenced by photochemistry, organic complexation, colloid formation and aggregation, as well as uptake and release by marine biota. The model is driven by mixed layer dynamics, dust deposition and insolation, as well as coupled to a simple ecosystem model (based on Schartau at al.2001: Deep-Sea Res.II.48,1769-1800) and applied to the site of the Bermuda Atlantic Time-series Study (BATS). Parameters in the model were chosen to reproduce the small number of available speciation measurements resolving a daily cycle. The model clearly reproduces the available Fe concentration at the BATS station but the annual balance of Fe fluxes at BATS is less constrained, due to uncertainties in the model parameters. Hence we discuss the model's sensitivity to parameter uncertainties and which observations might help to better constrain the relevant model parameters. Futher we discuss how the most important model parameters are constrained by the data. The mixed layer cycle in the model strongly influences seasonality of primary production as well as light dependency of photoreductive processes and therefore controlls iron speciation. Futhermore short events within a day (e.g. heavy rain, change of irradiance, intense dust deposition and temporary deepening of the mixed layer) may push processes like colloidal aggregation. For this reason we compare two versions of the model: The first one is forced by monthly averaged climatological variables, the second one by daily climatological variabilities.
Hybrid configuration mixing model for odd nuclei
NASA Astrophysics Data System (ADS)
Colò, G.; Bortignon, P. F.; Bocchi, G.
2017-03-01
In this work, we introduce a new approach which is meant to be a first step towards complete self-consistent low-lying spectroscopy of odd nuclei. So far, we essentially limit ourselves to the description of a double-magic core plus an extra nucleon. The model does not contain any free adjustable parameter and is instead based on a Hartree-Fock (HF) description of the particle states in the core, together with self-consistent random-phase approximation (RPA) calculations for the core excitations. We include both collective and noncollective excitations, with proper care of the corrections due to the overlap between them (i.e., due to the nonorthonormality of the basis). As a consequence, with respect to traditional particle-vibration coupling calculations in which one can only address single-nucleon states and particle-vibration multiplets, we can also describe states of shell-model types like 2 particle-1 hole. We will report results for 49Ca and 133Sb and discuss future perspectives.
Mix Model Comparison of Low Feed-Through Implosions
NASA Astrophysics Data System (ADS)
Pino, Jesse; MacLaren, S.; Greenough, J.; Casey, D.; Dewald, E.; Dittrich, T.; Khan, S.; Ma, T.; Sacks, R.; Salmonson, J.; Smalyuk, V.; Tipton, R.; Kyrala, G.
2016-10-01
The CD Mix campaign previously demonstrated the use of nuclear diagnostics to study the mix of separated reactants in plastic capsule implosions at the NIF. Recently, the separated reactants technique has been applied to the Two Shock (TS) implosion platform, which is designed to minimize this feed-through and isolate local mix at the gas-ablator interface and produce core yields in good agreement with 1D clean simulations. The effects of both inner surface roughness and convergence ratio have been probed. The TT, DT, and DD neutron signals respectively give information about core gas performance, gas-shell atomic mix, and heating of the shell. In this talk, we describe efforts to model these implosions using high-resolution 2D ARES simulations. Various methods of interfacial mix will be considered, including the Reynolds-Averaged Navier Stokes (RANS) KL method as well as and a multicomponent enhanced diffusivity model with species, thermal, and pressure gradient terms. We also give predictions of a upcoming campaign to investigate Mid-Z mixing by adding a Ge dopant to the CD layer. LLNL-ABS-697251 This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
The salinity effect in a mixed layer ocean model
NASA Technical Reports Server (NTRS)
Miller, J. R.
1976-01-01
A model of the thermally mixed layer in the upper ocean as developed by Kraus and Turner and extended by Denman is further extended to investigate the effects of salinity. In the tropical and subtropical Atlantic Ocean rapid increases in salinity occur at the bottom of a uniformly mixed surface layer. The most significant effects produced by the inclusion of salinity are the reduction of the deepening rate and the corresponding change in the heating characteristics of the mixed layer. If the net surface heating is positive, but small, salinity effects must be included to determine whether the mixed layer temperature will increase or decrease. Precipitation over tropical oceans leads to the development of a shallow stable layer accompanied by a decrease in the temperature and salinity at the sea surface.
A 3D Bubble Merger Model for RTI Mixing
NASA Astrophysics Data System (ADS)
Cheng, Baolian
2015-11-01
In this work we present a model for the merger processes of bubbles at the edge of an unstable acceleration driven mixing layer. Steady acceleration defines a self-similar mixing process, with a time-dependent inverse cascade of structures of increasing size. The time evolution is itself a renormalization group evolution. The model predicts the growth rate of a Rayleigh-Taylor chaotic fluid-mixing layer. The 3-D model differs from the 2-D merger model in several important ways. Beyond the extension of the model to three dimensions, the model contains one phenomenological parameter, the variance of the bubble radii at fixed time. The model also predicts several experimental numbers: the bubble mixing rate, the mean bubble radius, and the bubble height separation at the time of merger. From these we also obtain the bubble height to the radius aspect ratio, which is in good agreement with experiments. Applications to recent NIF and Omega experiments will be discussed. This work was performed under the auspices of the U.S. Department of Energy by the Los Alamos National Laboratory under Contract No. W-7405-ENG-36.
Modeling and Analysis of Mixed Synchronous/Asynchronous Systems
NASA Technical Reports Server (NTRS)
Driscoll, Kevin R.; Madl. Gabor; Hall, Brendan
2012-01-01
Practical safety-critical distributed systems must integrate safety critical and non-critical data in a common platform. Safety critical systems almost always consist of isochronous components that have synchronous or asynchronous interface with other components. Many of these systems also support a mix of synchronous and asynchronous interfaces. This report presents a study on the modeling and analysis of asynchronous, synchronous, and mixed synchronous/asynchronous systems. We build on the SAE Architecture Analysis and Design Language (AADL) to capture architectures for analysis. We present preliminary work targeted to capture mixed low- and high-criticality data, as well as real-time properties in a common Model of Computation (MoC). An abstract, but representative, test specimen system was created as the system to be modeled.
Villeneuve, Daniel L.; Larkin, Patrick; Knoebl, Iris; Miracle, Ann L.; Kahl, Michael D.; Jensen, Kathleen M.; Makynen, Elizabeth A.; Durhan, Elizabeth J.; Carter, Barbara J.; Denslow, Nancy D.; Ankley, Gerald T.
2007-01-01
Conceptual or graphical systems models are powerful tools that can help facilitate hypothesis-based ecotoxicogenomic research and aid mechanistic interpretation of toxicogenomic results. This paper presents a novel conceptual model of the teleost brain-pituitary-gonadal axis designed to aid ecotoxigenomics research on endocrine-disrupting chemicals using small fish models. Application of the model to toxicogenomics research was illustrated in the context of a recent study that examined the effects of the competitive aromatase inhibitor, fadrozole, on mRNA transcript abundance in gonad, brain, and liver tissue of exposed fathead minnows using a novel fathead minnow oligonucleotide microarray and quantitative real-time polymerase chain reaction. Changes in transcript abundance observed in the ovaries of females exposed to 6.3 ug fadrozole/L for 7 d were functionally consistent with fadrozole’s mechanism of action, and expected compensatory responses of the BPG-axis to fadrozole’s effects. Furthermore, array results helped identify additional elements (genes/proteins) that could be included in the model to potentially increase it’s predictive capacity. However, model-based predictions did not readily explain the lack of differential mRNA expression (relative to controls) observed in the ovary of females exposed to 60 ug fadrozole/L for 7 d. Both the utility and limitations of conceptual systems models as tools for hypothesis-driven ecotoxicogenomics research are discussed.
Graphics Career Ladder AFSC 231X1
1992-01-01
paints , other than watercolor , casein, or tempera paints F224 Mix watercolor , casein, or tempera paints F235 Produce preliminary...color schemes for graphics F223 Mix paints , other than watercolor , casein, or tempera paints F224 Mix watercolor , casein, or tempera paints P392...TASK STATEMENTS: F191 Clean airbrush parts F194 Clean paint brushes F223 Mix paints , other than watercolor , casein, or tempera paints F224 Mix
Computer modeling of ORNL storage tank sludge mobilization and mixing
Terrones, G.; Eyler, L.L.
1993-09-01
This report presents and analyzes the results of the computer modeling of mixing and mobilization of sludge in horizontal, cylindrical storage tanks using submerged liquid jets. The computer modeling uses the TEMPEST computational fluid dynamics computer program. The horizontal, cylindrical storage tank configuration is similar to the Melton Valley Storage Tanks (MVST) at Oak Ridge National (ORNL). The MVST tank contents exhibit non-homogeneous, non-Newtonian rheology characteristics. The eventual goals of the simulations are to determine under what conditions sludge mobilization using submerged liquid jets is feasible in tanks of this configuration, and to estimate mixing times required to approach homogeneity of the contents of the tanks.
Mixed waste treatment model: Basis and analysis
Palmer, B.A.
1995-09-01
The Department of Energy`s Programmatic Environmental Impact Statement (PEIS) required treatment system capacities for risk and cost calculation. Los Alamos was tasked with providing these capacities to the PEIS team. This involved understanding the Department of Energy (DOE) Complex waste, making the necessary changes to correct for problems, categorizing the waste for treatment, and determining the treatment system requirements. The treatment system requirements depended on the incoming waste, which varied for each PEIS case. The treatment system requirements also depended on the type of treatment that was desired. Because different groups contributing to the PEIS needed specific types of results, we provided the treatment system requirements in a variety of forms. In total, some 40 data files were created for the TRU cases, and for the MLLW case, there were 105 separate data files. Each data file represents one treatment case consisting of the selected waste from various sites, a selected treatment system, and the reporting requirements for such a case. The treatment system requirements in their most basic form are the treatment process rates for unit operations in the desired treatment system, based on a 10-year working life and 20-year accumulation of the waste. These results were reported in cubic meters and for the MLLW case, in kilograms as well. The treatment system model consisted of unit operations that are linked together. Each unit operation`s function depended on the input waste streams, waste matrix, and contaminants. Each unit operation outputs one or more waste streams whose matrix, contaminants, and volume/mass may have changed as a result of the treatment. These output streams are then routed to the appropriate unit operation for additional treatment until the output waste stream meets the treatment requirements for disposal. The total waste for each unit operation was calculated as well as the waste for each matrix treated by the unit.
Spread in model climate sensitivity traced to atmospheric convective mixing.
Sherwood, Steven C; Bony, Sandrine; Dufresne, Jean-Louis
2014-01-02
Equilibrium climate sensitivity refers to the ultimate change in global mean temperature in response to a change in external forcing. Despite decades of research attempting to narrow uncertainties, equilibrium climate sensitivity estimates from climate models still span roughly 1.5 to 5 degrees Celsius for a doubling of atmospheric carbon dioxide concentration, precluding accurate projections of future climate. The spread arises largely from differences in the feedback from low clouds, for reasons not yet understood. Here we show that differences in the simulated strength of convective mixing between the lower and middle tropical troposphere explain about half of the variance in climate sensitivity estimated by 43 climate models. The apparent mechanism is that such mixing dehydrates the low-cloud layer at a rate that increases as the climate warms, and this rate of increase depends on the initial mixing strength, linking the mixing to cloud feedback. The mixing inferred from observations appears to be sufficiently strong to imply a climate sensitivity of more than 3 degrees for a doubling of carbon dioxide. This is significantly higher than the currently accepted lower bound of 1.5 degrees, thereby constraining model projections towards relatively severe future warming.
NASA Astrophysics Data System (ADS)
Runge, J.; Petoukhov, V.; Kurths, J.
2013-12-01
The analysis of time delays using lagged cross correlations is commonly used to gain insights into interaction mechanisms between climatological processes, also to quantify the strength of a mechanism. Especially ENSOs teleconnections have been investigated with this approach. Here we critically evaluate how justified this method is, i.e., what aspect of a climatic mechanism such an inferred time lag actually measures. We find a strong dependence on serial dependencies or autocorrelation which can lead to misleading conclusions about the time delays and also obscures a quantification of the interaction mechanism. To overcome these possible artifacts, we propose a two-step procedure based on the concept of graphical models recently introduced to climate research. In the first step, graphical models are used to detect the existence of (Granger-) causal interactions which determines the time delays of a mechanism. In the second step a certain partial correlation is introduced that allows to specifically quantify the strength of an interaction mechanism in a well interpretable way that enables to exclude misleading effects of serial correlation as well as more general dependencies. With this approach we find novel interpretations of the time delays and strengths of ENSOs teleconnections. The potential of the approach to quantify interactions also between more than two variables is demonstrated by investigating the mechanism of the Walker circulation. Overview over important teleconnections. The black dashed lines denote the regions used in the bivariate analyses, while the gray boxes show the three regions analyzed to study the Walker circulation (see the inset). The arrows indicate the direction with the gray shading roughly corresponding to the novel partial correlation measure strength. The label gives the value and time lag in months in brackets.
Statistical basis and outputs of stable isotope mixing models: Comment on Fry (2013)
A recent article by Fry (2013; Mar Ecol Prog Ser 472:1−13) reviewed approaches to solving underdetermined stable isotope mixing systems, and presented a new graphical approach and set of summary statistics for the analysis of such systems. In his review, Fry (2013) mis-characteri...
Sensitivity of fine sediment source apportionment to mixing model assumptions
NASA Astrophysics Data System (ADS)
Cooper, Richard; Krueger, Tobias; Hiscock, Kevin; Rawlins, Barry
2015-04-01
Mixing models have become increasingly common tools for quantifying fine sediment redistribution in river catchments. The associated uncertainties may be modelled coherently and flexibly within a Bayesian statistical framework (Cooper et al., 2015). However, there is more than one way to represent these uncertainties because the modeller has considerable leeway in making error assumptions and model structural choices. In this presentation, we demonstrate how different mixing model setups can impact upon fine sediment source apportionment estimates via a one-factor-at-a-time (OFAT) sensitivity analysis. We formulate 13 versions of a mixing model, each with different error assumptions and model structural choices, and apply them to sediment geochemistry data from the River Blackwater, Norfolk, UK, to apportion suspended particulate matter (SPM) contributions from three sources (arable topsoils, road verges and subsurface material) under base flow conditions between August 2012 and August 2013 (Cooper et al., 2014). Whilst all 13 models estimate subsurface sources to be the largest contributor of SPM (median ~76%), comparison of apportionment estimates reveals varying degrees of sensitivity to changing prior parameter distributions, inclusion of covariance terms, incorporation of time-variant distributions and methods of proportion characterisation. We also demonstrate differences in apportionment results between a full and an empirical Bayesian setup and between a Bayesian and a popular Least Squares optimisation approach. Our OFAT sensitivity analysis reveals that mixing model structural choices and error assumptions can significantly impact upon fine sediment source apportionment results, with estimated median contributions in this study varying by up to 21% between model versions. Users of mixing models are therefore strongly advised to carefully consider and justify their choice of model setup prior to conducting fine sediment source apportionment investigations
Was the Hadean Earth stagnant? Constraints from dynamic mixing models
NASA Astrophysics Data System (ADS)
O'Neill, C.; Debaille, V.; Griffin, W. L.
2013-12-01
As a result of high internal heat production, high rates of impact bombardment, and primordial heat from accretion, a result a strong case is made for extremely high internal temperatures, low internal viscosities, and extremely vigorous mantle convection in the Hadean mantle. Previous studies of mixing of high-Rayleigh number convection indicates that chemically heterogeneous mantle anomalies should have efficiently remixed into the mantle on timescales of less than 100Myr. However, 142Nd and 182W isotope studies indicate that heterogeneous mantle domains survived, without mixing, for over 2Gyr - at odds with mixing rates expected. Similarly, platinum group elements concentrations in Archaean komatiites, purported due to the later veneer of meteoritic addition on the Earth, only achieve current levels at 2.7Ga - indicating a time lag of almost 1-2Gyr in mixing this material thoroughly in the mantle. Whilst previous studies have sought to understand slow Archaean mantle mixing via mantle layering due to endothermic phase changes, or anomalously viscous blobs of material, these have demonstrated limited efficacy. Here we pursue another explanation for inefficient mantle mixing in the Hadean: tectonic regime. A number of lines of evidence suggest resurfacing in the Archaean was episodic, and extending these models to Hadean times implies the Hadean was characterized by long periods of tectonic quiescence. We explore mixing times in 3D spherical-cap models of mantle convection, which incorporate vertically stratified and temperature-dependent viscosities. At an extreme, we show that mixing in stagnant lid regimes is over an order of magnitude less efficient than mobile lid mixing, and for plausible Rayleigh numbers and internal heat production, the lag in Hadean convective recycling can be explained. The attractiveness of this explanation is that it not only explains the long-lived 142Nd and 182W mantle anomalies, but also 1) posits an explanation for the delay
Multikernel linear mixed models for complex phenotype prediction
Weissbrod, Omer; Geiger, Dan; Rosset, Saharon
2016-01-01
Linear mixed models (LMMs) and their extensions have recently become the method of choice in phenotype prediction for complex traits. However, LMM use to date has typically been limited by assuming simple genetic architectures. Here, we present multikernel linear mixed model (MKLMM), a predictive modeling framework that extends the standard LMM using multiple-kernel machine learning approaches. MKLMM can model genetic interactions and is particularly suitable for modeling complex local interactions between nearby variants. We additionally present MKLMM-Adapt, which automatically infers interaction types across multiple genomic regions. In an analysis of eight case-control data sets from the Wellcome Trust Case Control Consortium and more than a hundred mouse phenotypes, MKLMM-Adapt consistently outperforms competing methods in phenotype prediction. MKLMM is as computationally efficient as standard LMMs and does not require storage of genotypes, thus achieving state-of-the-art predictive power without compromising computational feasibility or genomic privacy. PMID:27302636
COMBINING SOURCES IN STABLE ISOTOPE MIXING MODELS: ALTERNATIVE METHODS
Stable isotope mixing models are often used to quantify source contributions to a mixture. Examples include pollution source identification; trophic web studies; analysis of water sources for soils, plants, or water bodies; and many others. A common problem is having too many s...
The Worm Process for the Ising Model is Rapidly Mixing
NASA Astrophysics Data System (ADS)
Collevecchio, Andrea; Garoni, Timothy M.; Hyndman, Timothy; Tokarev, Daniel
2016-09-01
We prove rapid mixing of the worm process for the zero-field ferromagnetic Ising model, on all finite connected graphs, and at all temperatures. As a corollary, we obtain a fully-polynomial randomized approximation scheme for the Ising susceptibility, and for a certain restriction of the two-point correlation function.
Development of stable isotope mixing models in ecology - Sydney
More than 40 years ago, stable isotope analysis methods used in geochemistry began to be applied to ecological studies. One common application is using mathematical mixing models to sort out the proportional contributions of various sources to a mixture. Examples include contri...
Development of stable isotope mixing models in ecology - Perth
More than 40 years ago, stable isotope analysis methods used in geochemistry began to be applied to ecological studies. One common application is using mathematical mixing models to sort out the proportional contributions of various sources to a mixture. Examples include contri...
Sensitivity Analysis of Mixed Models for Incomplete Longitudinal Data
ERIC Educational Resources Information Center
Xu, Shu; Blozis, Shelley A.
2011-01-01
Mixed models are used for the analysis of data measured over time to study population-level change and individual differences in change characteristics. Linear and nonlinear functions may be used to describe a longitudinal response, individuals need not be observed at the same time points, and missing data, assumed to be missing at random (MAR),…
Historical development of stable isotope mixing models in ecology
More than 40 years ago, stable isotope analysis methods used in geochemistry began to be applied to ecological studies. One common application is using mathematical mixing models to sort out the proportional contributions of various sources to a mixture. Examples include contri...
INCORPORATING CONCENTRATION DEPENDENCE IN STABLE ISOTOPE MIXING MODELS
Stable isotopes are frequently used to quantify the contributions of multiple sources to a mixture; e.g., C and N isotopic signatures can be used to determine the fraction of three food sources in a consumer's diet. The standard dual isotope, three source linear mixing model ass...
Confidence Intervals for Assessing Heterogeneity in Generalized Linear Mixed Models
ERIC Educational Resources Information Center
Wagler, Amy E.
2014-01-01
Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for…
Dynamics and Modeling of Turbulent Mixing in Oceanic Flows
2010-09-30
channel flow (for a nice theoretical discussion, see Armenio and Sarkar 2002), the mixing properties of each of the Prt formulations might not be...to incorporate effects of inhomogeneity into turblence models. REFERENCES Armenio , V. and Sarkar, S. 2002. An investigation of stably stratified
A Nonlinear Mixed Effects Model for Latent Variables
ERIC Educational Resources Information Center
Harring, Jeffrey R.
2009-01-01
The nonlinear mixed effects model for continuous repeated measures data has become an increasingly popular and versatile tool for investigating nonlinear longitudinal change in observed variables. In practice, for each individual subject, multiple measurements are obtained on a single response variable over time or condition. This structure can be…
Development of stable isotope mixing models in ecology - Fremantle
More than 40 years ago, stable isotope analysis methods used in geochemistry began to be applied to ecological studies. One common application is using mathematical mixing models to sort out the proportional contributions of various sources to a mixture. Examples include contri...
Development of stable isotope mixing models in ecology - Dublin
More than 40 years ago, stable isotope analysis methods used in geochemistry began to be applied to ecological studies. One common application is using mathematical mixing models to sort out the proportional contributions of various sources to a mixture. Examples include contri...
Cross-Validation for Nonlinear Mixed Effects Models
Colby, Emily; Bair, Eric
2013-01-01
Cross-validation is frequently used for model selection in a variety of applications. However, it is difficult to apply cross-validation to mixed effects models (including nonlinear mixed effects models or NLME models) due to the fact that cross-validation requires “out-of-sample” predictions of the outcome variable, which cannot be easily calculated when random effects are present. We describe two novel variants of cross-validation that can be applied to nonlinear mixed effects models. One variant, where out-of-sample predictions are based on post hoc estimates of the random effects, can be used to select the overall structural model. Another variant, where cross-validation seeks to minimize the estimated random effects rather than the estimated residuals, can be used to select covariates to include in the model. We show that these methods produce accurate results in a variety of simulated data sets and apply them to two publicly available population pharmacokinetic data sets. PMID:23532511
Probabilistic graphical models for effective connectivity extraction in the brain using FMRI data.
Ali Safari, Mohammad; Mohammadbeigi, Majid
2012-01-01
In this study using Bayesian network method to learn the structure of effective connectivity among brain regions involved in a functional MRI. The approach is exploratory in the sense that it does not require a priori model as in the earlier approaches, such as the Structural Equation Modeling or Dynamic Causal Modeling, which can only affirm or refute the connectivity of a previously known anatomical model or a hypothesized model. The conditional probabilities that render the interactions among brain regions in Bayesian networks represent the connectivity in the complete statistical sense. This method is applicable even when the number of regions involved in the cognitive network is large or unknown. In this study, we demonstrated the present approach using synthetic data and fMRI data collected in attention to motion in the visual system task.
Logit-normal mixed model for Indian monsoon precipitation
NASA Astrophysics Data System (ADS)
Dietz, L. R.; Chatterjee, S.
2014-09-01
Describing the nature and variability of Indian monsoon precipitation is a topic of much debate in the current literature. We suggest the use of a generalized linear mixed model (GLMM), specifically, the logit-normal mixed model, to describe the underlying structure of this complex climatic event. Four GLMM algorithms are described and simulations are performed to vet these algorithms before applying them to the Indian precipitation data. The logit-normal model was applied to light, moderate, and extreme rainfall. Findings indicated that physical constructs were preserved by the models, and random effects were significant in many cases. We also found GLMM estimation methods were sensitive to tuning parameters and assumptions and therefore, recommend use of multiple methods in applications. This work provides a novel use of GLMM and promotes its addition to the gamut of tools for analysis in studying climate phenomena.
An epidemic model to evaluate the homogeneous mixing assumption
NASA Astrophysics Data System (ADS)
Turnes, P. P.; Monteiro, L. H. A.
2014-11-01
Many epidemic models are written in terms of ordinary differential equations (ODE). This approach relies on the homogeneous mixing assumption; that is, the topological structure of the contact network established by the individuals of the host population is not relevant to predict the spread of a pathogen in this population. Here, we propose an epidemic model based on ODE to study the propagation of contagious diseases conferring no immunity. The state variables of this model are the percentages of susceptible individuals, infectious individuals and empty space. We show that this dynamical system can experience transcritical and Hopf bifurcations. Then, we employ this model to evaluate the validity of the homogeneous mixing assumption by using real data related to the transmission of gonorrhea, hepatitis C virus, human immunodeficiency virus, and obesity.
Low-order models of biogenic ocean mixing
NASA Astrophysics Data System (ADS)
Dabiri, J. O.; Rosinelli, D.; Koumoutsakos, P.
2009-12-01
Biogenic ocean mixing, the process whereby swimming animals may affect ocean circulation, has primarily been studied using order-of-magnitude theoretical estimates and a small number of field observations. We describe numerical simulations of arrays of simplified animal shapes migrating in inviscid fluid and at finite Reynolds numbers. The effect of density stratification is modeled in the fluid dynamic equations of motion by a buoyancy acceleration term, which arises due to perturbations to the density field by the migrating bodies. The effects of fluid viscosity, body spacing, and array configuration are investigated to identify scenarios in which a meaningful contribution to ocean mixing by swimming animals is plausible.
An explicit mixed numerical method for mesoscale model
NASA Technical Reports Server (NTRS)
Hsu, H.-M.
1981-01-01
A mixed numerical method has been developed for mesoscale models. The technique consists of a forward difference scheme for time tendency terms, an upstream scheme for advective terms, and a central scheme for the other terms in a physical system. It is shown that the mixed method is conditionally stable and highly accurate for approximating the system of either shallow-water equations in one dimension or primitive equations in three dimensions. Since the technique is explicit and two time level, it conserves computer and programming resources.
Quasi 1D Modeling of Mixed Compression Supersonic Inlets
NASA Technical Reports Server (NTRS)
Kopasakis, George; Connolly, Joseph W.; Paxson, Daniel E.; Woolwine, Kyle J.
2012-01-01
The AeroServoElasticity task under the NASA Supersonics Project is developing dynamic models of the propulsion system and the vehicle in order to conduct research for integrated vehicle dynamic performance. As part of this effort, a nonlinear quasi 1-dimensional model of the 2-dimensional bifurcated mixed compression supersonic inlet is being developed. The model utilizes computational fluid dynamics for both the supersonic and subsonic diffusers. The oblique shocks are modeled utilizing compressible flow equations. This model also implements variable geometry required to control the normal shock position. The model is flexible and can also be utilized to simulate other mixed compression supersonic inlet designs. The model was validated both in time and in the frequency domain against the legacy LArge Perturbation INlet code, which has been previously verified using test data. This legacy code written in FORTRAN is quite extensive and complex in terms of the amount of software and number of subroutines. Further, the legacy code is not suitable for closed loop feedback controls design, and the simulation environment is not amenable to systems integration. Therefore, a solution is to develop an innovative, more simplified, mixed compression inlet model with the same steady state and dynamic performance as the legacy code that also can be used for controls design. The new nonlinear dynamic model is implemented in MATLAB Simulink. This environment allows easier development of linear models for controls design for shock positioning. The new model is also well suited for integration with a propulsion system model to study inlet/propulsion system performance, and integration with an aero-servo-elastic system model to study integrated vehicle ride quality, vehicle stability, and efficiency.
Application of large eddy interaction model to a mixing layer
NASA Technical Reports Server (NTRS)
Murthy, S. N. B.
1989-01-01
The large eddy interaction model (LEIM) is a statistical model of turbulence based on the interaction of selected eddies with the mean flow and all of the eddies in a turbulent shear flow. It can be utilized as the starting point for obtaining physical structures in the flow. The possible application of the LEIM to a mixing layer formed between two parallel, incompressible flows with a small temperature difference is developed by invoking a detailed similarity between the spectra of velocity and temperature.
Seismic tests for solar models with tachocline mixing
NASA Astrophysics Data System (ADS)
Brun, A. S.; Antia, H. M.; Chitre, S. M.; Zahn, J.-P.
2002-08-01
We have computed accurate 1-D solar models including both a macroscopic mixing process in the solar tachocline as well as up-to-date microscopic physical ingredients. Using sound speed and density profiles inferred through primary inversion of the solar oscillation frequencies coupled with the equation of thermal equilibrium, we have extracted the temperature and hydrogen abundance profiles. These inferred quantities place strong constraints on our theoretical models in terms of the extent and strength of our macroscopic mixing, on the photospheric heavy elements abundance, on the nuclear reaction rates such as S11 and S34 and on the efficiency of the microscopic diffusion. We find a good overall agreement between the seismic Sun and our models if we introduce a macroscopic mixing in the tachocline and allow for variation within their uncertainties of the main physical ingredients. From our study we deduce that the solar hydrogen abundance at the solar age is Xinv=0.732+/- 0.001 and that based on the 9Be photospheric depletion, the maximum extent of mixing in the tachocline is 5% of the solar radius. The nuclear reaction rate for the fundamental pp reaction is found to be S11(0)=4.06+/- 0.07 10-25 MeV barns, i.e., 1.5% higher than the present theoretical determination. The predicted solar neutrino fluxes are discussed in the light of the new SNO/SuperKamiokande results.
Logistic Mixed Models to Investigate Implicit and Explicit Belief Tracking
Lages, Martin; Scheel, Anne
2016-01-01
We investigated the proposition of a two-systems Theory of Mind in adults’ belief tracking. A sample of N = 45 participants predicted the choice of one of two opponent players after observing several rounds in an animated card game. Three matches of this card game were played and initial gaze direction on target and subsequent choice predictions were recorded for each belief task and participant. We conducted logistic regressions with mixed effects on the binary data and developed Bayesian logistic mixed models to infer implicit and explicit mentalizing in true belief and false belief tasks. Although logistic regressions with mixed effects predicted the data well a Bayesian logistic mixed model with latent task- and subject-specific parameters gave a better account of the data. As expected explicit choice predictions suggested a clear understanding of true and false beliefs (TB/FB). Surprisingly, however, model parameters for initial gaze direction also indicated belief tracking. We discuss why task-specific parameters for initial gaze directions are different from choice predictions yet reflect second-order perspective taking. PMID:27853440
Graphical Technique to Support the Teaching/Learning Process of Software Process Reference Models
NASA Astrophysics Data System (ADS)
Espinosa-Curiel, Ismael Edrein; Rodríguez-Jacobo, Josefina; Fernández-Zepeda, José Alberto
In this paper, we propose a set of diagrams to visualize software process reference models (PRM). The diagrams, called dimods, are the combination of some visual and process modeling techniques such as rich pictures, mind maps, IDEF and RAD diagrams. We show the use of this technique by designing a set of dimods for the Mexican Software Industry Process Model (MoProSoft). Additionally, we perform an evaluation of the usefulness of dimods. The result of the evaluation shows that dimods may be a support tool that facilitates the understanding, memorization, and learning of software PRMs in both, software development organizations and universities. The results also show that dimods may have advantages over the traditional description methods for these types of models.
Probabilistic Graphical Models for the Analysis and Synthesis of Musical Audio
NASA Astrophysics Data System (ADS)
Hoffmann, Matthew Douglas
Content-based Music Information Retrieval (MIR) systems seek to automatically extract meaningful information from musical audio signals. This thesis applies new and existing generative probabilistic models to several content-based MIR tasks: timbral similarity estimation, semantic annotation and retrieval, and latent source discovery and separation. In order to estimate how similar two songs sound to one another, we employ a Hierarchical Dirichlet Process (HDP) mixture model to discover a shared representation of the distribution of timbres in each song. Comparing songs under this shared representation yields better query-by-example retrieval quality and scalability than previous approaches. To predict what tags are likely to apply to a song (e.g., "rap," "happy," or "driving music"), we develop the Codeword Bernoulli Average (CBA) model, a simple and fast mixture-of-experts model. Despite its simplicity, CBA performs at least as well as state-of-the-art approaches at automatically annotating songs and finding to what songs in a database a given tag most applies. Finally, we address the problem of latent source discovery and separation by developing two Bayesian nonparametric models, the Shift-Invariant HDP and Gamma Process NMF. These models allow us to discover what sounds (e.g. bass drums, guitar chords, etc.) are present in a song or set of songs and to isolate or suppress individual source. These models' ability to decide how many latent sources are necessary to model the data is particularly valuable in this application, since it is impossible to guess a priori how many sounds will appear in a given song or set of songs. Once they have been fit to data, probabilistic models can also be used to drive the synthesis of new musical audio, both for creative purposes and to qualitatively diagnose what information a model does and does not capture. We also adapt the SIHDP model to create new versions of input audio with arbitrary sample sets, for example, to create
Upscaling of Mixing Processes using a Spatial Markov Model
NASA Astrophysics Data System (ADS)
Bolster, Diogo; Sund, Nicole; Porta, Giovanni
2016-11-01
The Spatial Markov model is a model that has been used to successfully upscale transport behavior across a broad range of spatially heterogeneous flows, with most examples to date coming from applications relating to porous media. In its most common current forms the model predicts spatially averaged concentrations. However, many processes, including for example chemical reactions, require an adequate understanding of mixing below the averaging scale, which means that knowledge of subscale fluctuations, or closures that adequately describe them, are needed. Here we present a framework, consistent with the Spatial Markov modeling framework, that enables us to do this. We apply and present it as applied to a simple example, a spatially periodic flow at low Reynolds number. We demonstrate that our upscaled model can successfully predict mixing by comparing results from direct numerical simulations to predictions with our upscaled model. To this end we focus on predicting two common metrics of mixing: the dilution index and the scalar dissipation. For both metrics our upscaled predictions very closely match observed values from the DNS. This material is based upon work supported by NSF Grants EAR-1351625 and EAR-1417264.
Gill, Peter; Curran, James; Elliot, Keith
2005-01-01
The use of expert systems to interpret short tandem repeat DNA profiles in forensic, medical and ancient DNA applications is becoming increasingly prevalent as high-throughput analytical systems generate large amounts of data that are time-consuming to process. With special reference to low copy number (LCN) applications, we use a graphical model to simulate stochastic variation associated with the entire DNA process starting with extraction of sample, followed by the processing associated with the preparation of a PCR reaction mixture and PCR itself. Each part of the process is modelled with input efficiency parameters. Then, the key output parameters that define the characteristics of a DNA profile are derived, namely heterozygote balance (Hb) and the probability of allelic drop-out p(D). The model can be used to estimate the unknown efficiency parameters, such as pi(extraction). 'What-if' scenarios can be used to improve and optimize the entire process, e.g. by increasing the aliquot forwarded to PCR, the improvement expected to a given DNA profile can be reliably predicted. We demonstrate that Hb and drop-out are mainly a function of stochastic effect of pre-PCR molecular selection. Whole genome amplification is unlikely to give any benefit over conventional PCR for LCN.
Gill, Peter; Curran, James; Elliot, Keith
2005-01-01
The use of expert systems to interpret short tandem repeat DNA profiles in forensic, medical and ancient DNA applications is becoming increasingly prevalent as high-throughput analytical systems generate large amounts of data that are time-consuming to process. With special reference to low copy number (LCN) applications, we use a graphical model to simulate stochastic variation associated with the entire DNA process starting with extraction of sample, followed by the processing associated with the preparation of a PCR reaction mixture and PCR itself. Each part of the process is modelled with input efficiency parameters. Then, the key output parameters that define the characteristics of a DNA profile are derived, namely heterozygote balance (Hb) and the probability of allelic drop-out p(D). The model can be used to estimate the unknown efficiency parameters, such as πextraction. ‘What-if’ scenarios can be used to improve and optimize the entire process, e.g. by increasing the aliquot forwarded to PCR, the improvement expected to a given DNA profile can be reliably predicted. We demonstrate that Hb and drop-out are mainly a function of stochastic effect of pre-PCR molecular selection. Whole genome amplification is unlikely to give any benefit over conventional PCR for LCN. PMID:15681615
Graphic comparison of reserve-growth models for conventional oil and accumulation
Klett, T.R.
2003-01-01
The U.S. Geological Survey (USGS) periodically assesses crude oil, natural gas, and natural gas liquids resources of the world. The assessment procedure requires estimated recover-able oil and natural gas volumes (field size, cumulative production plus remaining reserves) in discovered fields. Because initial reserves are typically conservative, subsequent estimates increase through time as these fields are developed and produced. The USGS assessment of petroleum resources makes estimates, or forecasts, of the potential additions to reserves in discovered oil and gas fields resulting from field development, and it also estimates the potential fully developed sizes of undiscovered fields. The term ?reserve growth? refers to the commonly observed upward adjustment of reserve estimates. Because such additions are related to increases in the total size of a field, the USGS uses field sizes to model reserve growth. Future reserve growth in existing fields is a major component of remaining U.S. oil and natural gas resources and has therefore become a necessary element of U.S. petroleum resource assessments. Past and currently proposed reserve-growth models compared herein aid in the selection of a suitable set of forecast functions to provide an estimate of potential additions to reserves from reserve growth in the ongoing National Oil and Gas Assessment Project (NOGA). Reserve growth is modeled by construction of a curve that represents annual fractional changes of recoverable oil and natural gas volumes (for fields and reservoirs), which provides growth factors. Growth factors are used to calculate forecast functions, which are sets of field- or reservoir-size multipliers. Comparisons of forecast functions were made based on datasets used to construct the models, field type, modeling method, and length of forecast span. Comparisons were also made between forecast functions based on field-level and reservoir- level growth, and between forecast functions based on older
A Probabilistic Graphical Model for Individualizing Prognosis in Chronic, Complex Diseases.
Schulam, Peter; Saria, Suchi
Making accurate prognoses in chronic, complex diseases is challenging due to the wide variation in expression across individuals. In many such diseases, the notion of subtypes-subpopulations that share similar symptoms and patterns of progression-have been proposed. We develop a probabilistic model that exploits the concept of subtypes to individualize prognoses of disease trajectories. These subtypes are learned automatically from data. On a new individual, our model incorporates static and time-varying markers to dynamically update predictions of subtype membership and provide individualized predictions of disease trajectory. We use our model to tackle the problem of predicting lung function trajectories in scleroderma, an autoimmune disease, and demonstrate improved predictive performance over existing approaches.
A graphical interface based model for wind turbine drive train dynamics
Manwell, J.F.; McGowan, J.G.; Abdulwahid, U.; Rogers, A.; McNiff, B.
1996-12-31
This paper presents a summary of a wind turbine drive train dynamics code that has been under development at the University of Massachusetts, under National Renewable Energy Laboratory (NREL) support. The code is intended to be used to assist in the proper design and selection of drive train components. This work summarizes the development of the equations of motion for the model, and discusses the method of solution. In addition, a number of comparisons with analytical solutions and experimental field data are given. The summary includes conclusions and suggestions for future work on the model. 13 refs., 10 figs.
NASA Technical Reports Server (NTRS)
Nelson, D. P.
1981-01-01
A graphical presentation of the aerodynamic data acquired during coannular nozzle performance wind tunnel tests is given. The graphical data consist of plots of nozzle gross thrust coefficient, fan nozzle discharge coefficient, and primary nozzle discharge coefficient. Normalized model component static pressure distributions are presented as a function of primary total pressure, fan total pressure, and ambient static pressure for selected operating conditions. In addition, the supersonic cruise configuration data include plots of nozzle efficiency and secondary-to-fan total pressure pumping characteristics. Supersonic and subsonic cruise data are given.
Logit-normal mixed model for Indian Monsoon rainfall extremes
NASA Astrophysics Data System (ADS)
Dietz, L. R.; Chatterjee, S.
2014-03-01
Describing the nature and variability of Indian monsoon rainfall extremes is a topic of much debate in the current literature. We suggest the use of a generalized linear mixed model (GLMM), specifically, the logit-normal mixed model, to describe the underlying structure of this complex climatic event. Several GLMM algorithms are described and simulations are performed to vet these algorithms before applying them to the Indian precipitation data procured from the National Climatic Data Center. The logit-normal model was applied with fixed covariates of latitude, longitude, elevation, daily minimum and maximum temperatures with a random intercept by weather station. In general, the estimation methods concurred in their suggestion of a relationship between the El Niño Southern Oscillation (ENSO) and extreme rainfall variability estimates. This work provides a valuable starting point for extending GLMM to incorporate the intricate dependencies in extreme climate events.
A comparison of algorithms for inference and learning in probabilistic graphical models.
Frey, Brendan J; Jojic, Nebojsa
2005-09-01
Research into methods for reasoning under uncertainty is currently one of the most exciting areas of artificial intelligence, largely because it has recently become possible to record, store, and process large amounts of data. While impressive achievements have been made in pattern classification problems such as handwritten character recognition, face detection, speaker identification, and prediction of gene function, it is even more exciting that researchers are on the verge of introducing systems that can perform large-scale combinatorial analyses of data, decomposing the data into interacting components. For example, computational methods for automatic scene analysis are now emerging in the computer vision community. These methods decompose an input image into its constituent objects, lighting conditions, motion patterns, etc. Two of the main challenges are finding effective representations and models in specific applications and finding efficient algorithms for inference and learning in these models. In this paper, we advocate the use of graph-based probability models and their associated inference and learning algorithms. We review exact techniques and various approximate, computationally efficient techniques, including iterated conditional modes, the expectation maximization (EM) algorithm, Gibbs sampling, the mean field method, variational techniques, structured variational techniques and the sum-product algorithm ("loopy" belief propagation). We describe how each technique can be applied in a vision model of multiple, occluding objects and contrast the behaviors and performances of the techniques using a unifying cost function, free energy.
NASA Technical Reports Server (NTRS)
Phillips, D. T.; Manseur, B.; Foster, J. W.
1982-01-01
Alternate definitions of system failure create complex analysis for which analytic solutions are available only for simple, special cases. The GRASP methodology is a computer simulation approach for solving all classes of problems in which both failure and repair events are modeled according to the probability laws of the individual components of the system.
Perry, Nicholas S; Baucom, Katherine J W; Bourne, Stacia; Butner, Jonathan; Crenshaw, Alexander O; Hogan, Jasara N; Imel, Zac E; Wiltshire, Travis J; Baucom, Brian R W
2017-02-27
Researchers commonly use repeated-measures actor-partner interdependence models (RM-APIM) to understand how romantic partners change in relation to one another over time. However, traditional interpretations of the results of these models do not fully or correctly capture the dyadic temporal patterns estimated in RM-APIM. Interpretation of results from these models largely focuses on the meaning of single-parameter estimates in isolation from all the others. However, considering individual coefficients separately impedes the understanding of how these associations combine to produce an interdependent pattern that emerges over time. Additionally, positive within-person, or actor, effects are commonly misinterpreted as indicating growth from one time point to the next when they actually represent decline. We suggest that change-as-outcome RM-APIMs and vector field diagrams (VFDs) can be used to improve the understanding and presentation of dyadic patterns of association described by standard RM-APIMs. The current article briefly reviews the conceptual foundations of RM-APIMs, demonstrates how change-as-outcome RM-APIMs and VFDs can aid interpretation of standard RM-APIMs, and provides a tutorial in making VFDs using multilevel modeling. (PsycINFO Database Record
Yaghouby, Farid; O'Hara, Bruce F; Sunderam, Sridhar
2016-06-01
The proportion, number of bouts, and mean bout duration of different vigilance states (Wake, NREM, REM) are useful indices of dynamics in experimental sleep research. These metrics are estimated by first scoring state, sometimes using an algorithm, based on electrophysiological measurements such as the electroencephalogram (EEG) and electromyogram (EMG), and computing their values from the score sequence. Isolated errors in the scores can lead to large discrepancies in the estimated sleep metrics. But most algorithms score sleep by classifying the state from EEG/EMG features independently in each time epoch without considering the dynamics across epochs, which could provide contextual information. The objective here is to improve estimation of sleep metrics by fitting a probabilistic dynamical model to mouse EEG/EMG data and then predicting the metrics from the model parameters. Hidden Markov models (HMMs) with multivariate Gaussian observations and Markov state transitions were fitted to unlabeled 24-h EEG/EMG feature time series from 20 mice to model transitions between the latent vigilance states; a similar model with unbiased transition probabilities served as a reference. Sleep metrics predicted from the HMM parameters did not deviate significantly from manual estimates except for rapid eye movement sleep (REM) ([Formula: see text]; Wilcoxon signed-rank test). Changes in value from Light to Dark conditions correlated well with manually estimated differences (Spearman's rho 0.43-0.84) except for REM. HMMs also scored vigilance state with over 90% accuracy. HMMs of EEG/EMG features can therefore characterize sleep dynamics from EEG/EMG measurements, a prerequisite for characterizing the effects of perturbation in sleep monitoring and control applications.
Kierzek, Andrzej M; Zhou, Lu; Wanner, Barry L
2010-03-01
Two-component systems (TCSs) are prevalent signal transduction systems in bacteria that control innumerable adaptive responses to environmental cues and host-pathogen interactions. We constructed a detailed stochastic kinetic model of two component signalling based on published data. Our model has been validated with flow cytometry data and used to examine reporter gene expression in response to extracellular signal strength. The model shows that, depending on the actual kinetic parameters, TCSs exhibit all-or-none, graded or mixed mode responses. In accordance with other studies, positively autoregulated TCSs exhibit all-or-none responses. Unexpectedly, our model revealed that TCSs lacking a positive feedback loop exhibit not only graded but also mixed mode responses, in which variation of the signal strength alters the level of gene expression in induced cells while the regulated gene continues to be expressed at the basal level in a substantial fraction of cells. The graded response of the TCS changes to mixed mode response by an increase of the translation initiation rate of the histidine kinase. Thus, a TCS is an evolvable design pattern capable of implementing deterministic regulation and stochastic switches associated with both graded and threshold responses. This has implications for understanding the emergence of population diversity in pathogenic bacteria and the design of genetic circuits in synthetic biology applications. The model is available in systems biology markup language (SBML) and systems biology graphical notation (SBGN) formats and can be used as a component of large-scale biochemical reaction network models.
ERIC Educational Resources Information Center
Kriston, Levente; Melchior, Hanne; Hergert, Anika; Bergelt, Corinna; Watzke, Birgit; Schulz, Holger; von Wolff, Alessa
2011-01-01
The aim of our study was to develop a graphical tool that can be used in addition to standard statistical criteria to support decisions on the number of classes in explorative categorical latent variable modeling for rehabilitation research. Data from two rehabilitation research projects were used. In the first study, a latent profile analysis was…
Modeling of Low Feed-Through CD Mix Implosions
NASA Astrophysics Data System (ADS)
Pino, Jesse; MacLaren, Steven; Greenough, Jeff; Casey, Daniel; Dittrich, Tom; Kahn, Shahab; Kyrala, George; Ma, Tammy; Salmonson, Jay; Smalyuk, Vladimir; Tipton, Robert
2015-11-01
The CD Mix campaign previously demonstrated the use of nuclear diagnostics to study the mix of separated reactants in plastic capsule implosions at the National Ignition Facility. However, the previous implosions suffered from large instability growth seeded from perturbations on the outside of the capsule. Recently, the separated reactants technique has been applied to two platforms designed to minimize this feed-through and isolate local mix at the gas-ablator interface: the Two Shock (TS) and Adiabat-Shaped (AS) Platforms. Additionally, the background contamination of Deuterium in the gas has been greatly reduced, allowing for simultaneous observation of TT, DT, and DD neutrons, which respectively give information about core gas performance, gas-shell atomic mix, and heating of the shell. In this talk, we describe efforts to model these implosions using high-resolution 2D ARES simulations with both a Reynolds-Averaged Navier Stokes method and an enhanced diffusivity model. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-674867.
Uncertainty in mixing models: a blessing in disguise?
NASA Astrophysics Data System (ADS)
Delsman, J. R.; Oude Essink, G. H. P.
2012-04-01
Despite the abundance of tracer-based studies in catchment hydrology over the past decades, relatively few studies have addressed the uncertainty associated with these studies in much detail. This uncertainty stems from analytical error, spatial and temporal variance in end-member composition, and from not incorporating all relevant processes in the necessarily simplistic mixing models. Instead of applying standard EMMA methodology, we used end-member mixing model analysis within a Monte Carlo framework to quantify the uncertainty surrounding our analysis. Borrowing from the well-known GLUE methodology, we discarded mixing models that could not satisfactorily explain sample concentrations and analyzed the posterior parameter set. This use of environmental tracers aided in disentangling hydrological pathways in a Dutch polder catchment. This 10 km2 agricultural catchment is situated in the coastal region of the Netherlands. Brackish groundwater seepage, originating from Holocene marine transgressions, adversely affects water quality in this catchment. Current water management practice is aimed at improving water quality by flushing the catchment with fresh water from the river Rhine. Climate change is projected to decrease future fresh water availability, signifying the need for a more sustainable water management practice and a better understanding of the functioning of the catchment. The end-member mixing analysis increased our understanding of the hydrology of the studied catchment. The use of a GLUE-like framework for applying the end-member mixing analysis not only quantified the uncertainty associated with the analysis, the analysis of the posterior parameter set also identified the existence of catchment processes otherwise overlooked.
Huang, Xiao-Tai; Zhu, Yuan; Chan, Leanne Lai Hang; Zhao, Zhongying; Yan, Hong
2016-01-01
In Caenorhabditis elegans, a large number of protein-protein interactions (PPIs) are identified by different experiments. However, a comprehensive weighted PPI network, which is essential for signaling pathway inference, is not yet available in this model organism. Therefore, we firstly construct an integrative PPI network in C. elegans with 12,951 interactions involving 5039 proteins from seven molecular interaction databases. Then, a reliability score based on a probabilistic graphical model (RSPGM) is proposed to assess PPIs. It assumes that the random number of interactions between two proteins comes from the Bernoulli distribution to avoid multi-links. The main parameter of the RSPGM score contains a few latent variables which can be considered as several common properties between two proteins. Validations on high-confidence yeast datasets show that RSPGM provides more accurate evaluation than other approaches, and the PPIs in the reconstructed PPI network have higher biological relevance than that in the original network in terms of gene ontology, gene expression, essentiality and the prediction of known protein complexes. Furthermore, this weighted integrative PPI network in C. elegans is employed on inferring interaction path of the canonical Wnt/β-catenin pathway as well. Most genes on the inferred interaction path have been validated to be Wnt pathway components. Therefore, RSPGM is essential and effective for evaluating PPIs and inferring interaction path. Finally, the PPI network with RSPGM scores can be queried and visualized on a user interactive website, which is freely available at .
Fierro, Andrew Dickens, James; Neuber, Andreas
2014-12-15
A 3-dimensional particle-in-cell/Monte Carlo collision simulation that is fully implemented on a graphics processing unit (GPU) is described and used to determine low-temperature plasma characteristics at high reduced electric field, E/n, in nitrogen gas. Details of implementation on the GPU using the NVIDIA Compute Unified Device Architecture framework are discussed with respect to efficient code execution. The software is capable of tracking around 10 × 10{sup 6} particles with dynamic weighting and a total mesh size larger than 10{sup 8} cells. Verification of the simulation is performed by comparing the electron energy distribution function and plasma transport parameters to known Boltzmann Equation (BE) solvers. Under the assumption of a uniform electric field and neglecting the build-up of positive ion space charge, the simulation agrees well with the BE solvers. The model is utilized to calculate plasma characteristics of a pulsed, parallel plate discharge. A photoionization model provides the simulation with additional electrons after the initial seeded electron density has drifted towards the anode. Comparison of the performance benefits between the GPU-implementation versus a CPU-implementation is considered, and a speed-up factor of 13 for a 3D relaxation Poisson solver is obtained. Furthermore, a factor 60 speed-up is realized for parallelization of the electron processes.
Wilderjans, Tom F; Ceulemans, Eva; Van Mechelen, Iven; Depril, Dirk
2011-03-01
In many areas of psychology, one is interested in disclosing the underlying structural mechanisms that generated an object by variable data set. Often, based on theoretical or empirical arguments, it may be expected that these underlying mechanisms imply that the objects are grouped into clusters that are allowed to overlap (i.e., an object may belong to more than one cluster). In such cases, analyzing the data with Mirkin's additive profile clustering model may be appropriate. In this model: (1) each object may belong to no, one or several clusters, (2) there is a specific variable profile associated with each cluster, and (3) the scores of the objects on the variables can be reconstructed by adding the cluster-specific variable profiles of the clusters the object in question belongs to. Until now, however, no software program has been publicly available to perform an additive profile clustering analysis. For this purpose, in this article, the ADPROCLUS program, steered by a graphical user interface, is presented. We further illustrate its use by means of the analysis of a patient by symptom data matrix.
Learning a Tracking and Estimation Integrated Graphical Model for Human Pose Tracking.
Zhao, Lin; Gao, Xinbo; Tao, Dacheng; Li, Xuelong
2015-12-01
We investigate the tracking of 2-D human poses in a video stream to determine the spatial configuration of body parts in each frame, but this is not a trivial task because people may wear different kinds of clothing and may move very quickly and unpredictably. The technology of pose estimation is typically applied, but it ignores the temporal context and cannot provide smooth, reliable tracking results. Therefore, we develop a tracking and estimation integrated model (TEIM) to fully exploit temporal information by integrating pose estimation with visual tracking. However, joint parsing of multiple articulated parts over time is difficult, because a full model with edges capturing all pairwise relationships within and between frames is loopy and intractable. In previous models, approximate inference was usually resorted to, but it cannot promise good results and the computational cost is large. We overcome these problems by exploring the idea of divide and conquer, which decomposes the full model into two much simpler tractable submodels. In addition, a novel two-step iteration strategy is proposed to efficiently conquer the joint parsing problem. Algorithmically, we design TEIM very carefully so that: 1) it enables pose estimation and visual tracking to compensate for each other to achieve desirable tracking results; 2) it is able to deal with the problem of tracking loss; and 3) it only needs past information and is capable of tracking online. Experiments are conducted on two public data sets in the wild with ground truth layout annotations, and the experimental results indicate the effectiveness of the proposed TEIM framework.
Graphical Models for Recovering Probabilistic and Causal Queries from Missing Data
2014-11-01
employ a formal representation called ‘Missingness Graphs ’ (m- graphs , for short) to explicitly portray the missingness process as well as the...exists any theoretical impediment to estimability of queries of interest, m- graphs can also provide a means for communication and refinement of...assumptions about the missingness process. Furthermore, m- graphs permit us to detect violations in modeling assumptions even when the dataset is
Overview of the Graphical User Interface for the GERM Code (GCR Event-Based Risk Model
NASA Technical Reports Server (NTRS)
Kim, Myung-Hee; Cucinotta, Francis A.
2010-01-01
The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERM code calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERM code also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERM code accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERM code for application to thick target experiments. The GERM code provides scientists participating in NSRL experiments with the data needed for the interpretation of their
Overview of the Graphical User Interface for the GERMcode (GCR Event-Based Risk Model)
NASA Technical Reports Server (NTRS)
Kim, Myung-Hee Y.; Cucinotta, Francis A.
2010-01-01
The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERMcode calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERMcode also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERMcode for application to thick target experiments. The GERMcode provides scientists participating in NSRL experiments with the data needed for the interpretation of their
Measurements and Models for Hazardous chemical and Mixed Wastes
Laurel A. Watts; Cynthia D. Holcomb; Stephanie L. Outcalt; Beverly Louie; Michael E. Mullins; Tony N. Rogers
2002-08-21
Mixed solvent aqueous waste of various chemical compositions constitutes a significant fraction of the total waste produced by industry in the United States. Not only does the chemical process industry create large quantities of aqueous waste, but the majority of the waste inventory at the DOE sites previously used for nuclear weapons production is mixed solvent aqueous waste. In addition, large quantities of waste are expected to be generated in the clean-up of those sites. In order to effectively treat, safely handle, and properly dispose of these wastes, accurate and comprehensive knowledge of basic thermophysical properties is essential. The goal of this work is to develop a phase equilibrium model for mixed solvent aqueous solutions containing salts. An equation of state was sought for these mixtures that (a) would require a minimum of adjustable parameters and (b) could be obtained from a available data or data that were easily measured. A model was developed to predict vapor composition and pressure given the liquid composition and temperature. It is based on the Peng-Robinson equation of state, adapted to include non-volatile and salt components. The model itself is capable of predicting the vapor-liquid equilibria of a wide variety of systems composed of water, organic solvents, salts, nonvolatile solutes, and acids or bases. The representative system o water + acetone + 2-propanol + NaNo3 was selected to test and verify the model. Vapor-liquid equilibrium and phase density measurements were performed for this system and its constituent binaries.
Fermion masses and mixing in general warped extra dimensional models
NASA Astrophysics Data System (ADS)
Frank, Mariana; Hamzaoui, Cherif; Pourtolami, Nima; Toharia, Manuel
2015-06-01
We analyze fermion masses and mixing in a general warped extra dimensional model, where all the Standard Model (SM) fields, including the Higgs, are allowed to propagate in the bulk. In this context, a slightly broken flavor symmetry imposed universally on all fermion fields, without distinction, can generate the full flavor structure of the SM, including quarks, charged leptons and neutrinos. For quarks and charged leptons, the exponential sensitivity of their wave functions to small flavor breaking effects yield hierarchical masses and mixing as it is usual in warped models with fermions in the bulk. In the neutrino sector, the exponential wave-function factors can be flavor blind and thus insensitive to the small flavor symmetry breaking effects, directly linking their masses and mixing angles to the flavor symmetric structure of the five-dimensional neutrino Yukawa couplings. The Higgs must be localized in the bulk and the model is more successful in generalized warped scenarios where the metric background solution is different than five-dimensional anti-de Sitter (AdS5 ). We study these features in two simple frameworks, flavor complimentarity and flavor democracy, which provide specific predictions and correlations between quarks and leptons, testable as more precise data in the neutrino sector becomes available.
A mixed model reduction method for preserving selected physical information
NASA Astrophysics Data System (ADS)
Zhang, Jing; Zheng, Gangtie
2017-03-01
A new model reduction method in the frequency domain is presented. By mixedly using the model reduction techniques from both the time domain and the frequency domain, the dynamic model is condensed to selected physical coordinates, and the contribution of slave degrees of freedom is taken as a modification to the model in the form of effective modal mass of virtually constrained modes. The reduced model can preserve the physical information related to the selected physical coordinates such as physical parameters and physical space positions of corresponding structure components. For the cases of non-classical damping, the method is extended to the model reduction in the state space but still only contains the selected physical coordinates. Numerical results are presented to validate the method and show the effectiveness of the model reduction.
Extension of the stochastic mixing model to cumulonimbus clouds
Raymond, D.J.; Blyth, A.M. )
1992-11-01
The stochastic mixing model of cumulus clouds is extended to the case in which ice and precipitation form. A simple cloud microphysical model is adopted in which ice crystals and aggregates are carried along with the updraft, whereas raindrops, graupel, and hail are assumed to immediately fall out. The model is then applied to the 2 August 1984 case study of convection over the Magdalena Mountains of central New Mexico, with excellent results. The formation of ice and precipitation can explain the transition of this system from a cumulus congestus cloud to thunderstorm. 28 refs.
Analysis of mixed model in gear transmission based on ADAMS
NASA Astrophysics Data System (ADS)
Li, Xiufeng; Wang, Yabin
2012-09-01
The traditional method of mechanical gear driving simulation includes gear pair method and solid to solid contact method. The former has higher solving efficiency but lower results accuracy; the latter usually obtains higher precision of results while the calculation process is complex, also it is not easy to converge. Currently, most of the researches are focused on the description of geometric models and the definition of boundary conditions. However, none of them can solve the problems fundamentally. To improve the simulation efficiency while ensure the results with high accuracy, a mixed model method which uses gear tooth profiles to take the place of the solid gear to simulate gear movement is presented under these circumstances. In the process of modeling, build the solid models of the mechanism in the SolidWorks firstly; Then collect the point coordinates of outline curves of the gear using SolidWorks API and create fit curves in Adams based on the point coordinates; Next, adjust the position of those fitting curves according to the position of the contact area; Finally, define the loading conditions, boundary conditions and simulation parameters. The method provides gear shape information by tooth profile curves; simulates the mesh process through tooth profile curve to curve contact and offer mass as well as inertia data via solid gear models. This simulation process combines the two models to complete the gear driving analysis. In order to verify the validity of the method presented, both theoretical derivation and numerical simulation on a runaway escapement are conducted. The results show that the computational efficiency of the mixed model method is 1.4 times over the traditional method which contains solid to solid contact. Meanwhile, the simulation results are more closely to theoretical calculations. Consequently, mixed model method has a high application value regarding to the study of the dynamics of gear mechanism.
PVA in Igneous Petrology: The Rosetta Stone for Testing Mixing and Fractionation Models
NASA Astrophysics Data System (ADS)
Vogel, T. A.; Ehrlich, R.
2006-05-01
One of the major goals of igneous petrology is to evaluate the relative contributions of fractional crystallization and magma mixing (or assimilation) that produce the chemical variations within related igneous units (plutons, sills and dikes, ash-flow tuffs, lavas etc). Mixing and fractional crystallization have often been evaluated by selecting a few variables (major elements, trace elements, isotopes) and modeling the trends. EC-AFC models have been developed to include energy constraints along with selected trace elements and isotopes. Polytopic Vector Analysis (PVA) is a technique that uses all of the chemical variations (major elements and trace elements) in all the samples to determine: (1) the number of end member compositions present in the system, (2) the chemical composition of each end member, and (3) the relative contribution of each end member in each sample from the igneous unit. Each sample in the dataset is described as the sum of some fraction of each end member; therefore each sample is uniquely described by a specific amount of each of the end members. Each end member is defined in the same non negative units as the sample values. Graphical analysis of the output allows the recognition of trends either due to crystal fraction or mixing of separate magma batches (assimilation), as samples form discrete clusters or trends with different variations in end member proportions. Mixing of discrete magma batches is immediately apparent, as samples representing mixed magmas plot between the parent magmas. PVA has been used successfully to identify end members in aqueous geochemistry and petroleum. However, even though it was originally developed in part by igneous petrologists, it has not been thoroughly tested on petrologic problems. In order to evaluate PVA, we selected three igneous units in which fractionation and mixing processes had been identified: (1) glasses from Kilauea Iki drilling, which are unquestionably due to crystal fractionation; (2
Juan, H F; Hung, C C; Wang, K T; Chiou, S H
1999-04-13
We present a systematic structure comparison of three major classes of postsynaptic snake toxins, which include short and long chain alpha-type neurotoxins plus one angusticeps-type toxin of black mamba snake family. Two novel alpha-type neurotoxins isolated from Taiwan cobra (Naja naja atra) possessing distinct primary sequences and different postsynaptic neurotoxicities were taken as exemplars for short and long chain neurotoxins and compared with the major lethal short-chain neurotoxin in the same venom, i.e., cobrotoxin, based on the derived three-dimensional structure of this toxin in solution by NMR spectroscopy. A structure comparison among these two alpha-neurotoxins and angusticeps-type toxin (denoted as FS2) was carried out by the secondary-structure prediction together with computer homology-modeling based on multiple sequence alignment of their primary sequences and established NMR structures of cobrotoxin and FS2. It is of interest to find that upon pairwise superpositions of these modeled three-dimensional polypeptide chains, distinct differences in the overall peptide flexibility and interior microenvironment between these toxins can be detected along the three constituting polypeptide loops, which may reflect some intrinsic differences in the surface hydrophobicity of several hydrophobic peptide segments present on the surface loops of these toxin molecules as revealed by hydropathy profiles. Construction of a phylogenetic tree for these structurally related and functionally distinct toxins corroborates that all long and short toxins present in diverse snake families are evolutionarily related to each other, supposedly derived from an ancestral polypeptide by gene duplication and subsequent mutational substitutions leading to divergence of multiple three-loop toxin peptides.
A Non-Fickian Mixing Model for Stratified Turbulent Flows
2012-09-30
center particle at each grid point and 4 satellite ones, displaced by 500 m along the four cardinal directions. Drifter trajectories were integrated...type of submesoscale instabilities exist, how they are connected to both larger scale and smaller scale motions, and to what extent they influence...been to model upper ocean mixed layer instabilities , investigate their behavior and try to develop sampling strategies using synthetic drifters and
Continuum Modeling of Mixed Conductors: a Study of Ceria
NASA Astrophysics Data System (ADS)
Ciucci, Francesco
In this thesis we have derived a new way to analyze the impedance response of mixed conducting materials for use in solid oxide fuel cells (SOFCs), with the main focus on anodic materials, in particular cerium oxides. First we have analyzed the impact of mixed conductivity coupled to electrocatalytic behavior in the linear time-independent domain for a thick ceria sample. We have derived that, for a promising fuel cell material, Samarium Doped Ceria, chemical reactions are the determining component of the polarization resistance. As a second step we have extended the previous model to the time-dependent case, where we focused on single harmonic excitation, the impedance spectroscopy conditions. We extended the model to the case where some input diffusivities are spatially nonuniform. For instance we considered the case where diffusivities change significantly in the vicinity of the electrocatalytic region. As a third and final step we use to model to capture the two dimensional behavior of mixed conducting thin films, where the electronic motion from one side of the sample to the other is impeded. Such conditions are similar to those encountered in fuel cells where an electrolyte conducting exclusively oxygen ions is placed between the anode and the cathode. The framework developed was also extended to study a popular cathodic material, Lanthanum Manganite. The model is used to give unprecedented insight in SOFC polarization resistance analysis of mixed conductors. It helps elucidate rigorously rate determining steps and to address the interplay of diffusion with diffusion losses. Electrochemical surface losses dominate for most experimental conditions of Samarium Doped Ceria and they are shown to be strongly dependent on geometry.
Shell Model Depiction of Isospin Mixing in sd Shell
Lam, Yi Hua; Smirnova, Nadya A.; Caurier, Etienne
2011-11-30
We constructed a new empirical isospin-symmetry breaking (ISB) Hamiltonian in the sd(1s{sub 1/2}, 0d{sub 5/2} and 0d{sub 3/2}) shell-model space. In this contribution, we present its application to two important case studies: (i){beta}-delayed proton emission from {sup 22}Al and (ii) isospin-mixing correction to superallowed 0{sup +}{yields}0{sup +}{beta}-decay ft-values.
Estimating Preferential Flow in Karstic Aquifers Using Statistical Mixed Models
Anaya, Angel A.; Padilla, Ingrid; Macchiavelli, Raul; Vesper, Dorothy J.; Meeker, John D.; Alshawabkeh, Akram N.
2013-01-01
Karst aquifers are highly productive groundwater systems often associated with conduit flow. These systems can be highly vulnerable to contamination, resulting in a high potential for contaminant exposure to humans and ecosystems. This work develops statistical models to spatially characterize flow and transport patterns in karstified limestone and determines the effect of aquifer flow rates on these patterns. A laboratory-scale Geo-HydroBed model is used to simulate flow and transport processes in a karstic limestone unit. The model consists of stainless-steel tanks containing a karstified limestone block collected from a karst aquifer formation in northern Puerto Rico. Experimental work involves making a series of flow and tracer injections, while monitoring hydraulic and tracer response spatially and temporally. Statistical mixed models are applied to hydraulic data to determine likely pathways of preferential flow in the limestone units. The models indicate a highly heterogeneous system with dominant, flow-dependent preferential flow regions. Results indicate that regions of preferential flow tend to expand at higher groundwater flow rates, suggesting a greater volume of the system being flushed by flowing water at higher rates. Spatial and temporal distribution of tracer concentrations indicates the presence of conduit-like and diffuse flow transport in the system, supporting the notion of both combined transport mechanisms in the limestone unit. The temporal response of tracer concentrations at different locations in the model coincide with, and confirms the preferential flow distribution generated with the statistical mixed models used in the study. PMID:23802921
Effects of mixing in threshold models of social behavior
NASA Astrophysics Data System (ADS)
Akhmetzhanov, Andrei R.; Worden, Lee; Dushoff, Jonathan
2013-07-01
We consider the dynamics of an extension of the influential Granovetter model of social behavior, where individuals are affected by their personal preferences and observation of the neighbors’ behavior. Individuals are arranged in a network (usually the square lattice), and each has a state and a fixed threshold for behavior changes. We simulate the system asynchronously by picking a random individual and we either update its state or exchange it with another randomly chosen individual (mixing). We describe the dynamics analytically in the fast-mixing limit by using the mean-field approximation and investigate it mainly numerically in the case of finite mixing. We show that the dynamics converge to a manifold in state space, which determines the possible equilibria, and show how to estimate the projection of this manifold by using simulated trajectories, emitted from different initial points. We show that the effects of considering the network can be decomposed into finite-neighborhood effects, and finite-mixing-rate effects, which have qualitatively similar effects. Both of these effects increase the tendency of the system to move from a less-desired equilibrium to the “ground state.” Our findings can be used to probe shifts in behavioral norms and have implications for the role of information flow in determining when social norms that have become unpopular in particular communities (such as foot binding or female genital cutting) persist or vanish.
Effects of mixing in threshold models of social behavior.
Akhmetzhanov, Andrei R; Worden, Lee; Dushoff, Jonathan
2013-07-01
We consider the dynamics of an extension of the influential Granovetter model of social behavior, where individuals are affected by their personal preferences and observation of the neighbors' behavior. Individuals are arranged in a network (usually the square lattice), and each has a state and a fixed threshold for behavior changes. We simulate the system asynchronously by picking a random individual and we either update its state or exchange it with another randomly chosen individual (mixing). We describe the dynamics analytically in the fast-mixing limit by using the mean-field approximation and investigate it mainly numerically in the case of finite mixing. We show that the dynamics converge to a manifold in state space, which determines the possible equilibria, and show how to estimate the projection of this manifold by using simulated trajectories, emitted from different initial points. We show that the effects of considering the network can be decomposed into finite-neighborhood effects, and finite-mixing-rate effects, which have qualitatively similar effects. Both of these effects increase the tendency of the system to move from a less-desired equilibrium to the "ground state." Our findings can be used to probe shifts in behavioral norms and have implications for the role of information flow in determining when social norms that have become unpopular in particular communities (such as foot binding or female genital cutting) persist or vanish.
Modeling and diagnosing interface mix in layered ICF implosions
NASA Astrophysics Data System (ADS)
Weber, C. R.; Berzak Hopkins, L. F.; Clark, D. S.; Haan, S. W.; Ho, D. D.; Meezan, N. B.; Milovich, J. L.; Robey, H. F.; Smalyuk, V. A.; Thomas, C. A.
2015-11-01
Mixing at the fuel-ablator interface of an inertial confinement fusion (ICF) implosion can arise from an unfavorable in-flight Atwood number between the cryogenic DT fuel and the ablator. High-Z dopant is typically added to the ablator to control the Atwood number, but recent high-density carbon (HDC) capsules have been shot at the National Ignition Facility (NIF) without this added dopant. Highly resolved post-shot modeling of these implosions shows that there was significant mixing of ablator material into the dense DT fuel. This mix lowers the fuel density and results in less overall compression, helping to explain the measured ratio of down scattered-to-primary neutrons. Future experimental designs will seek to improve this issue through adding dopant and changing the x-ray spectra with a different hohlraum wall material. To test these changes, we are designing an experimental platform to look at the growth of this mixing layer. This technique uses side-on radiography to measure the spatial extent of an embedded high-Z tracer layer near the interface. Work performed under the auspices of the U.S. D.O.E. by Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344.
Study on system dynamics of evolutionary mix-game models
NASA Astrophysics Data System (ADS)
Gou, Chengling; Guo, Xiaoqian; Chen, Fang
2008-11-01
Mix-game model is ameliorated from an agent-based MG model, which is used to simulate the real financial market. Different from MG, there are two groups of agents in Mix-game: Group 1 plays a majority game and Group 2 plays a minority game. These two groups of agents have different bounded abilities to deal with historical information and to count their own performance. In this paper, we modify Mix-game model by assigning the evolution abilities to agents: if the winning rates of agents are smaller than a threshold, they will copy the best strategies the other agent has; and agents will repeat such evolution at certain time intervals. Through simulations this paper finds: (1) the average winning rates of agents in Group 1 and the mean volatilities increase with the increases of the thresholds of Group 1; (2) the average winning rates of both groups decrease but the mean volatilities of system increase with the increase of the thresholds of Group 2; (3) the thresholds of Group 2 have greater impact on system dynamics than the thresholds of Group 1; (4) the characteristics of system dynamics under different time intervals of strategy change are similar to each other qualitatively, but they are different quantitatively; (5) As the time interval of strategy change increases from 1 to 20, the system behaves more and more stable and the performances of agents in both groups become better also.
Lecca, Paola; Casiraghi, Nicola; Demichelis, Francesca
2015-01-01
Somatic mutations arise and accumulate both during tumor genesis and progression. However, the order in which mutations occur is an open question and the inference of the temporal ordering at the gene level could potentially impact on patient treatment. Thus, exploiting recent observations suggesting that the occurrence of mutations is a non-memoryless process, we developed a computational approach to infer timed oncogenetic directed acyclic graphs (TO-DAGs) from human tumor mutation data. Such graphs represent the path and the waiting times of alterations during tumor evolution. The probability of occurrence of each alteration in a path is the probability that the alteration occurs when all alterations prior to it have occurred. The waiting time between an alteration and the subsequent is modeled as a stochastic function of the conditional probability of the event given the occurrence of the previous one. TO-DAG performances have been evaluated both on synthetic data and on somatic non-silent mutations from prostate cancer and melanoma patients and then compared with those of current well-established approaches. TO-DAG shows high performance scores on synthetic data and recognizes mutations in gatekeeper tumor suppressor genes as trigger for several downstream mutational events in the human tumor data.
A novel bayesian graphical model for genome-wide multi-SNP association mapping.
Zhang, Yu
2012-01-01
Most disease association mapping algorithms are based on hypothesis testing procedures that test one variant at a time. Those methods lose power when the disease mutations are jointly tagged by multiple variants, or when gene-gene interaction exist. Nearby variants are also correlated, for which procedures ignoring the dependence between variants will inevitably produce redundant results. With a large number of variants genotyped in current genome-wide disease association studies, simultaneous multivariant association mapping algorithms are strongly desired. We present a novel Bayesian method for automatic detection of multivariant joint association in genome-wide case-control studies. Our method has improved power and specificity over existing tools. We fit a joint probabilistic model to the entire data and identify disease variants simultaneously. The method dynamically accounts for the strong linkage disequilibrium (LD) between variants. As a result, only the primary disease variants will be identified, with all secondary associations due to LD effects filtered out. Our method better pinpoints the disease variants with improved resolution. The method is also computationally efficient for genome-wide studies. When applied to a real data set of inflammatory bowel disease (IBD) containing 401,473 variants in 4,720 individuals, our method detected all previously reported IBD loci in the same data, and recovered two missed loci. We further detected two novel interchromosome interactions. The first is between STAT3 and PARD6G, and the second is between DLG5 and an intergenic region at 5p14. We further validated the two interactions in an independent study.
Analysis and simulation of industrial distillation processes using a graphical system design model
NASA Astrophysics Data System (ADS)
Boca, Maria Loredana; Dobra, Remus; Dragos, Pasculescu; Ahmad, Mohammad Ayaz
2016-12-01
The separation column used for experimentations one model can be configured in two ways: one - two columns of different diameters placed one within the other extension, and second way, one column with set diameter [1], [2]. The column separates the carbon isotopes based on the cryogenic distillation of pure carbon monoxide, which is fed at a constant flow rate as a gas through the feeding system [1],[2]. Based on numerical control systems used in virtual instrumentation was done some simulations of the distillation process in order to obtain of the isotope 13C at high concentrations. The experimental installation for cryogenic separation can be configured from the point of view of the separation column in two ways: Cascade - two columns of different diameters and placed one in the extension of the other column, and second one column with a set diameter. It is proposed that this installation is controlled to achieve data using a data acquisition tool and professional software that will process information from the isotopic column based on a logical dedicated algorithm. Classical isotopic column will be controlled automatically, and information about the main parameters will be monitored and properly display using one program. Take in consideration the very-low operating temperature, an efficient thermal isolation vacuum jacket is necessary. Since the "elementary separation ratio" [2] is very close to unity in order to raise the (13C) isotope concentration up to a desired level, a permanent counter current of the liquid-gaseous phases of the carbon monoxide is created by the main elements of the equipment: the boiler in the bottom-side of the column and the condenser in the top-side.
WE-E-BRE-05: Ensemble of Graphical Models for Predicting Radiation Pneumontis Risk
Lee, S; Ybarra, N; Jeyaseelan, K; El Naqa, I; Faria, S; Kopek, N
2014-06-15
Purpose: We propose a prior knowledge-based approach to construct an interaction graph of biological and dosimetric radiation pneumontis (RP) covariates for the purpose of developing a RP risk classifier. Methods: We recruited 59 NSCLC patients who received curative radiotherapy with minimum 6 month follow-up. 16 RP events was observed (CTCAE grade ≥2). Blood serum was collected from every patient before (pre-RT) and during RT (mid-RT). From each sample the concentration of the following five candidate biomarkers were taken as covariates: alpha-2-macroglobulin (α2M), angiotensin converting enzyme (ACE), transforming growth factor β (TGF-β), interleukin-6 (IL-6), and osteopontin (OPN). Dose-volumetric parameters were also included as covariates. The number of biological and dosimetric covariates was reduced by a variable selection scheme implemented by L1-regularized logistic regression (LASSO). Posterior probability distribution of interaction graphs between the selected variables was estimated from the data under the literature-based prior knowledge to weight more heavily the graphs that contain the expected associations. A graph ensemble was formed by averaging the most probable graphs weighted by their posterior, creating a Bayesian Network (BN)-based RP risk classifier. Results: The LASSO selected the following 7 RP covariates: (1) pre-RT concentration level of α2M, (2) α2M level mid- RT/pre-RT, (3) pre-RT IL6 level, (4) IL6 level mid-RT/pre-RT, (5) ACE mid-RT/pre-RT, (6) PTV volume, and (7) mean lung dose (MLD). The ensemble BN model achieved the maximum sensitivity/specificity of 81%/84% and outperformed univariate dosimetric predictors as shown by larger AUC values (0.78∼0.81) compared with MLD (0.61), V20 (0.65) and V30 (0.70). The ensembles obtained by incorporating the prior knowledge improved classification performance for the ensemble size 5∼50. Conclusion: We demonstrated a probabilistic ensemble method to detect robust associations between
NASA Technical Reports Server (NTRS)
Menon, Suresh
1992-01-01
An advanced gas turbine engine to power supersonic transport aircraft is currently under study. In addition to high combustion efficiency requirements, environmental concerns have placed stringent restrictions on the pollutant emissions from these engines. A combustor design with the potential for minimizing pollutants such as NO(x) emissions is undergoing experimental evaluation. A major technical issue in the design of this combustor is how to rapidly mix the hot, fuel-rich primary zone product with the secondary diluent air to obtain a fuel-lean mixture for combustion in the second stage. Numerical predictions using steady-state methods cannot account for the unsteady phenomena in the mixing region. Therefore, to evaluate the effect of unsteady mixing and combustion processes, a novel unsteady mixing model is demonstrated here. This model has been used to study multispecies mixing as well as propane-air and hydrogen-air jet nonpremixed flames, and has been used to predict NO(x) production in the mixing region. Comparison with available experimental data show good agreement, thereby providing validation of the mixing model. With this demonstration, this mixing model is ready to be implemented in conjunction with steady-state prediction methods and provide an improved engineering design analysis tool.
A Mixed Exponential Time Series Model. NMEARMA(p,q).
1980-03-01
AD-AO85 316 NAVAL POSTGRADUATE SCHOOL MONTEREY CA F/G 12/1 A MIXED EXPONENTIAL TIME SERIES MODEL. NMEARMA(P,Q).(U MAR GO A .J LAWRANCE , P A LEWIS...This report was prepared by: A. J. Lawrance University of Birmingham Birmingham, England Reviewed by: Released by- Michael G. Sover’ign, Chirman...MODEL, NMEARMA(p,q) by A. J. Lawrance P. A. W. Lewis University of Birmingham Naval Postgraduate School Birmingham, England Monterey, California, USA
Baldi, Pierre; Rosen-Zvi, Michal
2005-10-01
Machine learning methods that can handle variable-size structured data such as sequences and graphs include Bayesian networks (BNs) and Recursive Neural Networks (RNNs). In both classes of models, the data is modeled using a set of observed and hidden variables associated with the nodes of a directed acyclic graph. In BNs, the conditional relationships between parent and child variables are probabilistic, whereas in RNNs they are deterministic and parameterized by neural networks. Here, we study the formal relationship between both classes of models and show that when the source nodes variables are observed, RNNs can be viewed as limits, both in distribution and probability, of BNs with local conditional distributions that have vanishing covariance matrices and converge to delta functions. Conditions for uniform convergence are also given together with an analysis of the behavior and exactness of Belief Propagation (BP) in 'deterministic' BNs. Implications for the design of mixed architectures and the corresponding inference algorithms are briefly discussed.
The dependence of global ocean modeling on background diapycnal mixing.
Deng, Zengan
2014-01-01
The Argo-derived background diapycnal mixing (BDM) proposed by Deng et al. (in publish) is introduced to and applied in Hybrid Coordinate Ocean Model (HYCOM). Sensitive experiments are carried out using HYCOM to detect the responses of ocean surface temperature and Meridional Overturning Circulation (MOC) to BDM in a global context. Preliminary results show that utilizing a constant BDM, with the same order of magnitude as the realistic one, may cause significant deviation in temperature and MOC. It is found that the dependence of surface temperature and MOC on BDM is prominent. Surface temperature is decreased with the increase of BDM, because diapycnal mixing can promote the deep cold water return to the upper ocean. Comparing to the control run, more striking MOC changes can be caused by the larger variation in BDM.
Nonlinear spectral mixing theory to model multispectral signatures
Borel, C.C.
1996-02-01
Nonlinear spectral mixing occurs due to multiple reflections and transmissions between discrete surfaces, e.g. leaves or facets of a rough surface. The radiosity method is an energy conserving computational method used in thermal engineering and it models nonlinear spectral mixing realistically and accurately. In contrast to the radiative transfer method the radiosity method takes into account the discreteness of the scattering surfaces (e.g. exact location, orientation and shape) such as leaves and includes mutual shading between them. An analytic radiosity-based scattering model for vegetation was developed and used to compute vegetation indices for various configurations. The leaf reflectance and transmittance was modeled using the PROSPECT model for various amounts of water, chlorophyll and variable leaf structure. The soil background was modeled using SOILSPEC with a linear mixture of reflectances of sand, clay and peat. A neural network and a geometry based retrieval scheme were used to retrieve leaf area index and chlorophyll concentration for dense canopies. Only simulated canopy reflectances in the 6 visible through short wave IR Landsat TM channels were used. The authors used an empirical function to compute the signal-to-noise ratio of a retrieved quantity.
Intercomparison of garnet barometers and implications for garnet mixing models
Anovitz, L.M.; Essene, E.J.
1985-01-01
Several well-calibrated barometers are available in the system Ca-Fe-Ti-Al-Si-O, including: Alm+3Ru-3Ilm+Sil+2Qtz (GRAIL), 2Alm+Grreverse arrow6Ru=6Ilm+3An+3Qtz (GRIPS); 2Alm+Gr=3Fa+3An (FAG); 3AnGr+Ky+Qtz (GASP); 2Fs-Fa+Qtz (FFQ); and Gr+Qtz=An+2Wo (WAGS). GRIPS, GRAIL and GASP form a linearly dependent set such that any two should yield the third given an a/X model for the grossular/almandine solid-solution. Application to barometry of garnet granulite assemblages from the Grenville in Ontario yields average pressures 0.1 kb lower for GRIPS and 0.4 kb higher for FAGS using our mixing model. Results from Parry Island, Ontario, yield 8.7 kb from GRAIL as opposed to 9.1 kb using Ganguly and Saxena's model. For GASP, Parry Island assemblages yield 8.4 kb with the authors calibration. Ganguly and Saxena's model gives 5.4 kb using Gasparik's reversals and 8.1 kb using the position of GASP calculated from GRIPS and GRAIL. These corrections allow GRIPS, GRAIL, GASP and FAGS to yield consistent pressures to +/- 0.5 kb in regional metamorphic terranes. Application of their mixing model outside of the fitted range 700-1000 K is not encouraged as extrapolation may yield erroneous results.
Subbanna, Nagesh; Precup, Doina; Arnold, Douglas; Arbel, Tal
2015-01-01
In this paper, we present IMaGe, a new, iterative two-stage probabilistic graphical model for detection and segmentation of Multiple Sclerosis (MS) lesions. Our model includes two levels of Markov Random Fields (MRFs). At the bottom level, a regular grid voxel-based MRF identifies potential lesion voxels, as well as other tissue classes, using local and neighbourhood intensities and class priors. Contiguous voxels of a particular tissue type are grouped into regions. A higher, non-lattice MRF is then constructed, in which each node corresponds to a region, and edges are defined based on neighbourhood relationships between regions. The goal of this MRF is to evaluate the probability of candidate lesions, based on group intensity, texture and neighbouring regions. The inferred information is then propagated to the voxel-level MRF. This process of iterative inference between the two levels repeats as long as desired. The iterations suppress false positives and refine lesion boundaries. The framework is trained on 660 MRI volumes of MS patients enrolled in clinical trials from 174 different centres, and tested on a separate multi-centre clinical trial data set with 535 MRI volumes. All data consists of T1, T2, PD and FLAIR contrasts. In comparison to other MRF methods, such as, and a traditional MRF, IMaGe is much more sensitive (with slightly better PPV). It outperforms its nearest competitor by around 20% when detecting very small lesions (3-10 voxels). This is a significant result, as such lesions constitute around 40% of the total number of lesions.
Companies can apply to use the voluntary new graphic on product labels of skin-applied insect repellents. This graphic is intended to help consumers easily identify the protection time for mosquitoes and ticks and select appropriately.
Application of a mixing-ratios based formulation to model mixing-driven dissolution experiments
NASA Astrophysics Data System (ADS)
Guadagnini, Alberto; Sanchez-Vila, Xavier; Saaltink, Maarten W.; Bussini, Michele; Berkowitz, Brian
2009-05-01
We address the question of how one can combine theoretical and numerical modeling approaches with limited measurements from laboratory flow cell experiments to realistically quantify salient features of complex mixing-driven multicomponent reactive transport problems in porous media. Flow cells are commonly used to examine processes affecting reactive transport through porous media, under controlled conditions. An advantage of flow cells is their suitability for relatively fast and reliable experiments, although measuring spatial distributions of a state variable within the cell is often difficult. In general, fluid is sampled only at the flow cell outlet, and concentration measurements are usually interpreted in terms of integrated reaction rates. In reactive transport problems, however, the spatial distribution of the reaction rates within the cell might be more important than the bulk integrated value. Recent advances in theoretical and numerical modeling of complex reactive transport problems [De Simoni M, Carrera J, Sanchez-Vila X, Guadagnini A. A procedure for the solution of multicomponent reactive transport problems. Water Resour Res 2005;41:W11410. doi: 10.1029/2005WR004056, De Simoni M, Sanchez-Vila X, Carrera J, Saaltink MW. A mixing ratios-based formulation for multicomponent reactive transport. Water Resour Res 2007;43:W07419. doi: 10.1029/2006WR005256] result in a methodology conducive to a simple exact expression for the space-time distribution of reaction rates in the presence of homogeneous or heterogeneous reactions in chemical equilibrium. The key points of the methodology are that a general reactive transport problem, involving a relatively high number of chemical species, can be formulated in terms of a set of decoupled partial differential equations, and the amount of reactants evolving into products depends on the rate at which solutions mix. The main objective of the current study is to show how this methodology can be used in conjunction
Box-Cox Mixed Logit Model for Travel Behavior Analysis
NASA Astrophysics Data System (ADS)
Orro, Alfonso; Novales, Margarita; Benitez, Francisco G.
2010-09-01
To represent the behavior of travelers when they are deciding how they are going to get to their destination, discrete choice models, based on the random utility theory, have become one of the most widely used tools. The field in which these models were developed was halfway between econometrics and transport engineering, although the latter now constitutes one of their principal areas of application. In the transport field, they have mainly been applied to mode choice, but also to the selection of destination, route, and other important decisions such as the vehicle ownership. In usual practice, the most frequently employed discrete choice models implement a fixed coefficient utility function that is linear in the parameters. The principal aim of this paper is to present the viability of specifying utility functions with random coefficients that are nonlinear in the parameters, in applications of discrete choice models to transport. Nonlinear specifications in the parameters were present in discrete choice theory at its outset, although they have seldom been used in practice until recently. The specification of random coefficients, however, began with the probit and the hedonic models in the 1970s, and, after a period of apparent little practical interest, has burgeoned into a field of intense activity in recent years with the new generation of mixed logit models. In this communication, we present a Box-Cox mixed logit model, original of the authors. It includes the estimation of the Box-Cox exponents in addition to the parameters of the random coefficients distribution. Probability of choose an alternative is an integral that will be calculated by simulation. The estimation of the model is carried out by maximizing the simulated log-likelihood of a sample of observed individual choices between alternatives. The differences between the predictions yielded by models that are inconsistent with real behavior have been studied with simulation experiments.
Modeling of Transient Flow Mixing of Streams Injected into a Mixing Chamber
NASA Technical Reports Server (NTRS)
Voytovych, Dmytro M.; Merkle, Charles L.; Lucht, Robert P.; Hulka, James R.; Jones, Gregg W.
2006-01-01
Ignition is recognized as one the critical drivers in the reliability of multiple-start rocket engines. Residual combustion products from previous engine operation can condense on valves and related structures thereby creating difficulties for subsequent starting procedures. Alternative ignition methods that require fewer valves can mitigate the valve reliability problem, but require improved understanding of the spatial and temporal propellant distribution in the pre-ignition chamber. Current design tools based mainly on one-dimensional analysis and empirical models cannot predict local details of the injection and ignition processes. The goal of this work is to evaluate the capability of the modern computational fluid dynamics (CFD) tools in predicting the transient flow mixing in pre-ignition environment by comparing the results with the experimental data. This study is a part of a program to improve analytical methods and methodologies to analyze reliability and durability of combustion devices. In the present paper we describe a series of detailed computational simulations of the unsteady mixing events as the cold propellants are first introduced into the chamber as a first step in providing this necessary environmental description. The present computational modeling represents a complement to parallel experimental simulations' and includes comparisons with experimental results from that effort. A large number of rocket engine ignition studies has been previously reported. Here we limit our discussion to the work discussed in Refs. 2, 3 and 4 which is both similar to and different from the present approach. The similarities arise from the fact that both efforts involve detailed experimental/computational simulations of the ignition problem. The differences arise from the underlying philosophy of the two endeavors. The approach in Refs. 2 to 4 is a classical ignition study in which the focus is on the response of a propellant mixture to an ignition source, with
Kriston, Levente; Melchior, Hanne; Hergert, Anika; Bergelt, Corinna; Watzke, Birgit; Schulz, Holger; von Wolff, Alessa
2011-06-01
The aim of our study was to develop a graphical tool that can be used in addition to standard statistical criteria to support decisions on the number of classes in explorative categorical latent variable modeling for rehabilitation research. Data from two rehabilitation research projects were used. In the first study, a latent profile analysis was carried out in patients with cancer receiving an inpatient rehabilitation program to identify prototypical combinations of treatment elements. In the second study, growth mixture modeling was used to identify latent trajectory classes based on weekly symptom severity measurements during inpatient treatment of patients with mental disorders. A graphical tool, the Class Evolution Tree, was developed, and its central components were described. The Class Evolution Tree can be used in addition to statistical criteria to systematically address the issue of number of classes in explorative categorical latent variable modeling.
MIXING MODELING ANALYSIS FOR SRS SALT WASTE DISPOSITION
Lee, S.
2011-01-18
Nuclear waste at Savannah River Site (SRS) waste tanks consists of three different types of waste forms. They are the lighter salt solutions referred to as supernate, the precipitated salts as salt cake, and heavier fine solids as sludge. The sludge is settled on the tank floor. About half of the residual waste radioactivity is contained in the sludge, which is only about 8 percentage of the total waste volume. Mixing study to be evaluated here for the Salt Disposition Integration (SDI) project focuses on supernate preparations in waste tanks prior to transfer to the Salt Waste Processing Facility (SWPF) feed tank. The methods to mix and blend the contents of the SRS blend tanks were evalutaed to ensure that the contents are properly blended before they are transferred from the blend tank such as Tank 50H to the SWPF feed tank. The work consists of two principal objectives to investigate two different pumps. One objective is to identify a suitable pumping arrangement that will adequately blend/mix two miscible liquids to obtain a uniform composition in the tank with a minimum level of sludge solid particulate in suspension. The other is to estimate the elevation in the tank at which the transfer pump inlet should be located where the solid concentration of the entrained fluid remains below the acceptance criterion (0.09 wt% or 1200 mg/liter) during transfer operation to the SWPF. Tank 50H is a Waste Tank that will be used to prepare batches of salt feed for SWPF. The salt feed must be a homogeneous solution satisfying the acceptance criterion of the solids entrainment during transfer operation. The work described here consists of two modeling areas. They are the mixing modeling analysis during miscible liquid blending operation, and the flow pattern analysis during transfer operation of the blended liquid. The modeling results will provide quantitative design and operation information during the mixing/blending process and the transfer operation of the blended
Measurement and Model for Hazardous Chemical and Mixed Waste
Michael E. Mullins; Tony N. Rogers; Stephanie L. Outcalt; Beverly Louie; Laurel A. Watts; Cynthia D. Holcomb
2002-07-30
Mixed solvent aqueous waste of various chemical compositions constitutes a significant fraction of the total waste produced by industry in the United States. Not only does the chemical process industry create large quantities of aqueous waste, but the majority of the waste inventory at the Department of Energy (DOE) sites previously used for nuclear weapons production is mixed solvent aqueous waste. In addition, large quantities of waste are expected to be generated in the clean-up of those sites. In order to effectively treat, safely handle, and properly dispose of these wastes, accurate and comprehensive knowledge of basic thermophysical properties is essential. The goal of this work is to develop a phase equilibrium model for mixed solvent aqueous solutions containing salts. An equation of state was sought for these mixtures that (a) would require a minimum of adjustable parameters and (b) could be obtained from a available data or data that were easily measured. A model was developed to predict vapor composition and pressure given the liquid composition and temperature. It is based on the Peng-Robinson equation of state, adapted to include non-volatile and salt components. The model itself is capable of predicting the vapor-liquid equilibria of a wide variety of systems composed of water, organic solvents, salts, nonvolatile solutes, and acids or bases. The representative system of water + acetone + 2-propanol + NaNO3 was selected to test and verify the model. Vapor-liquid equilibrium and phase density measurements were performed for this system and its constituent binaries.
Mixing and shocks in geophysical shallow water models
NASA Astrophysics Data System (ADS)
Jacobson, Tivon
In the first section, a reduced two-layer shallow water model for fluid mixing is described. The model is a nonlinear hyperbolic quasilinear system of partial differential equations, derived by taking the limit as the upper layer becomes infinitely deep. It resembles the shallow water equations, but with an active buoyancy. Fluid entrainment is supposed to occur from the upper layer to the lower. Several physically motivated closures are proposed, including a robust closure based on maximizing a mixing entropy (also defined and derived) at shocks. The structure of shock solutions is examined. The Riemann problem is solved by setting the shock speed to maximize the production of mixing entropy. Shock-resolving finite-volume numerical models are presented with and without topographic forcing. Explicit shock tracking is required for strong shocks. The constraint that turbulent energy production be positive is considered. The model has geophysical applications in studying the dynamics of dense sill overflows in the ocean. The second section discusses stationary shocks of the shallow water equations in a reentrant rotating channel with wind stress and topography. Asymptotic predictions for the shock location, strength, and associated energy dissipation are developed by taking the topographic perturbation to be small. The scaling arguments for the asymptotics are developed by demanding integrated energy and momentum balance, with the result that the free surface perturbation is of the order of the square root of the topographic perturbation. Shock formation requires that linear waves be nondispersive, which sets a solvability condition on the mean flow and which leads to a class of generalized Kelvin waves. Two-dimensional shock-resolving numerical simulations validate the asymptotic expressions and demonstrate the presence of stationary separated flow shocks in some cases. Geophysical applications are considered. Overview sections on shock-resolving numerical methods
Subgrid models for mass and thermal diffusion in turbulent mixing
Sharp, David H; Lim, Hyunkyung; Li, Xiao - Lin; Gilmm, James G
2008-01-01
We are concerned with the chaotic flow fields of turbulent mixing. Chaotic flow is found in an extreme form in multiply shocked Richtmyer-Meshkov unstable flows. The goal of a converged simulation for this problem is twofold: to obtain converged solutions for macro solution features, such as the trajectories of the principal shock waves, mixing zone edges, and mean densities and velocities within each phase, and also for such micro solution features as the joint probability distributions of the temperature and species concentration. We introduce parameterized subgrid models of mass and thermal diffusion, to define large eddy simulations (LES) that replicate the micro features observed in the direct numerical simulation (DNS). The Schmidt numbers and Prandtl numbers are chosen to represent typical liquid, gas and plasma parameter values. Our main result is to explore the variation of the Schmidt, Prandtl and Reynolds numbers by three orders of magnitude, and the mesh by a factor of 8 per linear dimension (up to 3200 cells per dimension), to allow exploration of both DNS and LES regimes and verification of the simulations for both macro and micro observables. We find mesh convergence for key properties describing the molecular level of mixing, including chemical reaction rates between the distinct fluid species. We find results nearly independent of Reynolds number for Re 300, 6000, 600K . Methodologically, the results are also new. In common with the shock capturing community, we allow and maintain sharp solution gradients, and we enhance these gradients through use of front tracking. In common with the turbulence modeling community, we include subgrid scale models with no adjustable parameters for LES. To the authors' knowledge, these two methodologies have not been previously combined. In contrast to both of these methodologies, our use of Front Tracking, with DNS or LES resolution of the momentum equation at or near the Kolmogorov scale, but without resolving the
Generalized linear mixed model for segregation distortion analysis
2011-01-01
Background Segregation distortion is a phenomenon that the observed genotypic frequencies of a locus fall outside the expected Mendelian segregation ratio. The main cause of segregation distortion is viability selection on linked marker loci. These viability selection loci can be mapped using genome-wide marker information. Results We developed a generalized linear mixed model (GLMM) under the liability model to jointly map all viability selection loci of the genome. Using a hierarchical generalized linear mixed model, we can handle the number of loci several times larger than the sample size. We used a dataset from an F2 mouse family derived from the cross of two inbred lines to test the model and detected a major segregation distortion locus contributing 75% of the variance of the underlying liability. Replicated simulation experiments confirm that the power of viability locus detection is high and the false positive rate is low. Conclusions Not only can the method be used to detect segregation distortion loci, but also used for mapping quantitative trait loci of disease traits using case only data in humans and selected populations in plants and animals. PMID:22078575
A Mixed Model for Real-Time, Interactive Simulation of a Cable Passing Through Several Pulleys
Garcia-Fernandez, Ignacio; Pla-Castells, Marta; Martinez-Dura, Rafael J.
2007-09-06
A model of a cable and pulleys is presented that can be used in Real Time Computer Graphics applications. The model is formulated by the coupling of a damped spring and a variable coefficient wave equation, and can be integrated in more complex mechanical models of lift systems, such as cranes, elevators, etc. with a high degree of interactivity.
Stochastic Mixing Model with Power Law Decay of Variance
NASA Technical Reports Server (NTRS)
Fedotov, S.; Ihme, M.; Pitsch, H.
2003-01-01
Here we present a simple stochastic mixing model based on the law of large numbers (LLN). The reason why the LLN is involved in our formulation of the mixing problem is that the random conserved scalar c = c(t,x(t)) appears to behave as a sample mean. It converges to the mean value mu, while the variance sigma(sup 2)(sub c) (t) decays approximately as t(exp -1). Since the variance of the scalar decays faster than a sample mean (typically is greater than unity), we will introduce some non-linear modifications into the corresponding pdf-equation. The main idea is to develop a robust model which is independent from restrictive assumptions about the shape of the pdf. The remainder of this paper is organized as follows. In Section 2 we derive the integral equation from a stochastic difference equation describing the evolution of the pdf of a passive scalar in time. The stochastic difference equation introduces an exchange rate gamma(sub n) which we model in a first step as a deterministic function. In a second step, we generalize gamma(sub n) as a stochastic variable taking fluctuations in the inhomogeneous environment into account. In Section 3 we solve the non-linear integral equation numerically and analyze the influence of the different parameters on the decay rate. The paper finishes with a conclusion.
Generalized linear mixed models for meta-analysis.
Platt, R W; Leroux, B G; Breslow, N
1999-03-30
We examine two strategies for meta-analysis of a series of 2 x 2 tables with the odds ratio modelled as a linear combination of study level covariates and random effects representing between-study variation. Penalized quasi-likelihood (PQL), an approximate inference technique for generalized linear mixed models, and a linear model fitted by weighted least squares to the observed log-odds ratios are used to estimate regression coefficients and dispersion parameters. Simulation results demonstrate that both methods perform adequate approximate inference under many conditions, but that neither method works well in the presence of highly sparse data. Under certain conditions with small cell frequencies the PQL method provides better inference.
Graphical programming at Sandia National Laboratories
McDonald, M.J.; Palmquist, R.D.; Desjarlais, L.
1993-09-01
Sandia has developed an advanced operational control system approach, called Graphical Programming, to design, program, and operate robotic systems. The Graphical Programming approach produces robot systems that are faster to develop and use, safer in operation, and cheaper overall than altemative teleoperation or autonomous robot control systems. Graphical Programming also provides an efficient and easy-to-use interface to traditional robot systems for use in setup and programming tasks. This paper provides an overview of the Graphical Programming approach and lists key features of Graphical Programming systems. Graphical Programming uses 3-D visualization and simulation software with intuitive operator interfaces for the programming and control of complex robotic systems. Graphical Programming Supervisor software modules allow an operator to command and simulate complex tasks in a graphic preview mode and, when acceptable, command the actual robots and monitor their motions with the graphic system. Graphical Programming Supervisors maintain registration with the real world and allow the robot to perform tasks that cannot be accurately represented with models alone by using a combination of model and sensor-based control.
ERIC Educational Resources Information Center
Louis, Linda
2013-01-01
This article reports on the most recent phase of an ongoing research program that examines the artistic graphic representational behavior and paintings of children between the ages of four and seven. The goal of this research program is to articulate a contemporary account of artistic growth and to illuminate how young children's changing…
NASA Technical Reports Server (NTRS)
Noor, A. K.; Peters, J. M.
1981-01-01
Simple mixed models are developed for use in the geometrically nonlinear analysis of deep arches. A total Lagrangian description of the arch deformation is used, the analytical formulation being based on a form of the nonlinear deep arch theory with the effects of transverse shear deformation included. The fundamental unknowns comprise the six internal forces and generalized displacements of the arch, and the element characteristic arrays are obtained by using Hellinger-Reissner mixed variational principle. The polynomial interpolation functions employed in approximating the forces are one degree lower than those used in approximating the displacements, and the forces are discontinuous at the interelement boundaries. Attention is given to the equivalence between the mixed models developed herein and displacement models based on reduced integration of both the transverse shear and extensional energy terms. The advantages of mixed models over equivalent displacement models are summarized. Numerical results are presented to demonstrate the high accuracy and effectiveness of the mixed models developed and to permit a comparison of their performance with that of other mixed models reported in the literature.
Estimating anatomical trajectories with Bayesian mixed-effects modeling.
Ziegler, G; Penny, W D; Ridgway, G R; Ourselin, S; Friston, K J
2015-11-01
We introduce a mass-univariate framework for the analysis of whole-brain structural trajectories using longitudinal Voxel-Based Morphometry data and Bayesian inference. Our approach to developmental and aging longitudinal studies characterizes heterogeneous structural growth/decline between and within groups. In particular, we propose a probabilistic generative model that parameterizes individual and ensemble average changes in brain structure using linear mixed-effects models of age and subject-specific covariates. Model inversion uses Expectation Maximization (EM), while voxelwise (empirical) priors on the size of individual differences are estimated from the data. Bayesian inference on individual and group trajectories is realized using Posterior Probability Maps (PPM). In addition to parameter inference, the framework affords comparisons of models with varying combinations of model order for fixed and random effects using model evidence. We validate the model in simulations and real MRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) project. We further demonstrate how subject specific characteristics contribute to individual differences in longitudinal volume changes in healthy subjects, Mild Cognitive Impairment (MCI), and Alzheimer's Disease (AD).
Instantiated mixed effects modeling of Alzheimer's disease markers.
Guerrero, R; Schmidt-Richberg, A; Ledig, C; Tong, T; Wolz, R; Rueckert, D
2016-11-15
The assessment and prediction of a subject's current and future risk of developing neurodegenerative diseases like Alzheimer's disease are of great interest in both the design of clinical trials as well as in clinical decision making. Exploring the longitudinal trajectory of markers related to neurodegeneration is an important task when selecting subjects for treatment in trials and the clinic, in the evaluation of early disease indicators and the monitoring of disease progression. Given that there is substantial intersubject variability, models that attempt to describe marker trajectories for a whole population will likely lack specificity for the representation of individual patients. Therefore, we argue here that individualized models provide a more accurate alternative that can be used for tasks such as population stratification and a subject-specific prognosis. In the work presented here, mixed effects modeling is used to derive global and individual marker trajectories for a training population. Test subject (new patient) specific models are then instantiated using a stratified "marker signature" that defines a subpopulation of similar cases within the training database. From this subpopulation, personalized models of the expected trajectory of several markers are subsequently estimated for unseen patients. These patient specific models of markers are shown to provide better predictions of time-to-conversion to Alzheimer's disease than population based models.
Estimating anatomical trajectories with Bayesian mixed-effects modeling
Ziegler, G.; Penny, W.D.; Ridgway, G.R.; Ourselin, S.; Friston, K.J.
2015-01-01
We introduce a mass-univariate framework for the analysis of whole-brain structural trajectories using longitudinal Voxel-Based Morphometry data and Bayesian inference. Our approach to developmental and aging longitudinal studies characterizes heterogeneous structural growth/decline between and within groups. In particular, we propose a probabilistic generative model that parameterizes individual and ensemble average changes in brain structure using linear mixed-effects models of age and subject-specific covariates. Model inversion uses Expectation Maximization (EM), while voxelwise (empirical) priors on the size of individual differences are estimated from the data. Bayesian inference on individual and group trajectories is realized using Posterior Probability Maps (PPM). In addition to parameter inference, the framework affords comparisons of models with varying combinations of model order for fixed and random effects using model evidence. We validate the model in simulations and real MRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) project. We further demonstrate how subject specific characteristics contribute to individual differences in longitudinal volume changes in healthy subjects, Mild Cognitive Impairment (MCI), and Alzheimer's Disease (AD). PMID:26190405
Maximal atmospheric neutrino mixing in an SU(5) model
NASA Astrophysics Data System (ADS)
Grimus, W.; Lavoura, L.
2003-05-01
We show that maximal atmospheric and large solar neutrino mixing can be implemented in SU(5) gauge theories, by making use of the U(1) F symmetry associated with a suitably defined family number F, together with a Z2 symmetry which does not commute with F. U(1) F is softly broken by the mass terms of the right-handed neutrino singlets, which are responsible for the seesaw mechanism; in additio n, U(1) F is also spontaneously broken at the electroweak scale. In our scenario, lepton mixing stems exclusively from the right-handed-neutrino Majorana mass matrix, whereas the CKM matrix originates solely in the up-type-quark sector. We show that, despite the non-supersymmetric character of our model, unification of the gauge couplings can be achieved at a scale 1016 GeV < m U < 1019 GeV; indeed, we have found a particula r solution to this problem which yields results almost identical to the ones of the minimal supersymmetric standard model.
A perspective view of the plane mixing layer
NASA Technical Reports Server (NTRS)
Jimenez, J.; Cogollos, M.; Bernal, L. P.
1984-01-01
A three-dimensional model of the plane mixing layer is constructed by applying digital image processing and computer graphic techniques to laser fluorescent motion pictures of its transversal sections. A system of streamwise vortex pairs is shown to exist on top of the classical spanwise eddies. Its influence on mixing is examined.
NASA Astrophysics Data System (ADS)
Watanabe, Tomoaki; Nagata, Koji
2016-11-01
The mixing volume model (MVM), which is a mixing model for molecular diffusion in Lagrangian simulations of turbulent mixing problems, is proposed based on the interactions among spatially distributed particles in a finite volume. The mixing timescale in the MVM is derived by comparison between the model and the subgrid scale scalar variance equation. A-priori test of the MVM is conducted based on the direct numerical simulations of planar jets. The MVM is shown to predict well the mean effects of the molecular diffusion under various conditions. However, a predicted value of the molecular diffusion term is positively correlated to the exact value in the DNS only when the number of the mixing particles is larger than two. Furthermore, the MVM is tested in the hybrid implicit large-eddy-simulation/Lagrangian-particle-simulation (ILES/LPS). The ILES/LPS with the present mixing model predicts well the decay of the scalar variance in planar jets. This work was supported by JSPS KAKENHI Nos. 25289030 and 16K18013. The numerical simulations presented in this manuscript were carried out on the high performance computing system (NEC SX-ACE) in the Japan Agency for Marine-Earth Science and Technology.
A mixing evolution model for bidirectional microblog user networks
NASA Astrophysics Data System (ADS)
Yuan, Wei-Guo; Liu, Yun
2015-08-01
Microblogs have been widely used as a new form of online social networking. Based on the user profile data collected from Sina Weibo, we find that the number of microblog user bidirectional friends approximately corresponds with the lognormal distribution. We then build two microblog user networks with real bidirectional relationships, both of which have not only small-world and scale-free but also some special properties, such as double power-law degree distribution, disassortative network, hierarchical and rich-club structure. Moreover, by detecting the community structures of the two real networks, we find both of their community scales follow an exponential distribution. Based on the empirical analysis, we present a novel evolution network model with mixed connection rules, including lognormal fitness preferential and random attachment, nearest neighbor interconnected in the same community, and global random associations in different communities. The simulation results show that our model is consistent with real network in many topology features.
Linear mixing model applied to coarse resolution satellite data
NASA Technical Reports Server (NTRS)
Holben, Brent N.; Shimabukuro, Yosio E.
1992-01-01
A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies.
Study of a mixed dispersal population dynamics model
Chugunova, Marina; Jadamba, Baasansuren; Kao, Chiu -Yen; ...
2016-08-27
In this study, we consider a mixed dispersal model with periodic and Dirichlet boundary conditions and its corresponding linear eigenvalue problem. This model describes the time evolution of a population which disperses both locally and non-locally. We investigate how long time dynamics depend on the parameter values. Furthermore, we study the minimization of the principal eigenvalue under the constraints that the resource function is bounded from above and below, and with a fixed total integral. Biologically, this minimization problem is motivated by the question of determining the optimal spatial arrangement of favorable and unfavorable regions for the species to diemore » out more slowly or survive more easily. Our numerical simulations indicate that the optimal favorable region tends to be a simply-connected domain. Numerous results are shown to demonstrate various scenarios of optimal favorable regions for periodic and Dirichlet boundary conditions.« less
Study of a mixed dispersal population dynamics model
Chugunova, Marina; Jadamba, Baasansuren; Kao, Chiu -Yen; Klymko, Christine F.; Thomas, Evelyn; Zhao, Bingyu
2016-08-27
In this study, we consider a mixed dispersal model with periodic and Dirichlet boundary conditions and its corresponding linear eigenvalue problem. This model describes the time evolution of a population which disperses both locally and non-locally. We investigate how long time dynamics depend on the parameter values. Furthermore, we study the minimization of the principal eigenvalue under the constraints that the resource function is bounded from above and below, and with a fixed total integral. Biologically, this minimization problem is motivated by the question of determining the optimal spatial arrangement of favorable and unfavorable regions for the species to die out more slowly or survive more easily. Our numerical simulations indicate that the optimal favorable region tends to be a simply-connected domain. Numerous results are shown to demonstrate various scenarios of optimal favorable regions for periodic and Dirichlet boundary conditions.
Clark, David W.; Skinner, Kenneth D.; Pollock, David W.
2006-01-01
A flow and transport model was created with a graphical user interface to simplify the evaluation of nitrogen loading and nitrate transport in the mid-Snake region in south-central Idaho. This model and interface package, the Snake River Nitrate Scenario Simulator, uses the U.S. Geological Survey's MODFLOW 2000 and MOC3D models. The interface, which is enabled for use with geographic information systems (GIS), was created using ESRI's royalty-free MapObjects LT software. The interface lets users view initial nitrogen-loading conditions (representing conditions as of 1998), alter the nitrogen loading within selected zones by specifying a multiplication factor and applying it to the initial condition, run the flow and transport model, and view a graphical representation of the modeling results. The flow and transport model of the Snake River Nitrate Scenario Simulator was created by rediscretizing and recalibrating a clipped portion of an existing regional flow model. The new subregional model was recalibrated with newly available water-level data and spring and ground-water nitrate concentration data for the study area. An updated nitrogen input GIS layer controls the application of nitrogen to the flow and transport model. Users can alter the nitrogen application to the flow and transport model by altering the nitrogen load in predefined spatial zones contained within similar political, hydrologic, and size-constrained boundaries.
Jackson, Andrew L; Inger, Richard; Bearhop, Stuart; Parnell, Andrew
2009-03-01
The application of Bayesian methods to stable isotopic mixing problems, including inference of diet has the potential to revolutionise ecological research. Using simulated data we show that a recently published model MixSIR fails to correctly identify the true underlying dietary proportions more than 50% of the time and fails with increasing frequency as additional unquantified error is added. While the source of the fundamental failure remains elusive, mitigating solutions are suggested for dealing with additional unquantified variation. Moreover, MixSIR uses a formulation for a prior distribution that results in an opaque and unintuitive covariance structure.
Linear models for sound from supersonic reacting mixing layers
NASA Astrophysics Data System (ADS)
Chary, P. Shivakanth; Samanta, Arnab
2016-12-01
We perform a linearized reduced-order modeling of the aeroacoustic sound sources in supersonic reacting mixing layers to explore their sensitivities to some of the flow parameters in radiating sound. Specifically, we investigate the role of outer modes as the effective flow compressibility is raised, when some of these are expected to dominate over the traditional Kelvin-Helmholtz (K-H) -type central mode. Although the outer modes are known to be of lesser importance in the near-field mixing, how these radiate to the far-field is uncertain, on which we focus. On keeping the flow compressibility fixed, the outer modes are realized via biasing the respective mean densities of the fast (oxidizer) or slow (fuel) side. Here the mean flows are laminar solutions of two-dimensional compressible boundary layers with an imposed composite (turbulent) spreading rate, which we show to significantly alter the growth of instability waves by saturating them earlier, similar to in nonlinear calculations, achieved here via solving the linear parabolized stability equations. As the flow parameters are varied, instability of the slow modes is shown to be more sensitive to heat release, potentially exceeding equivalent central modes, as these modes yield relatively compact sound sources with lesser spreading of the mixing layer, when compared to the corresponding fast modes. In contrast, the radiated sound seems to be relatively unaffected when the mixture equivalence ratio is varied, except for a lean mixture which is shown to yield a pronounced effect on the slow mode radiation by reducing its modal growth.
Mesoscale Modeling During Mixed-Phase Arctic Cloud Experiment
Avramov, A.; Harringston, J.Y.; Verlinde, J.
2005-03-18
Mixed-phase arctic stratus clouds are the predominant cloud type in the Arctic (Curry et al. 2000) and through various feedback mechanisms exert a strong influence on the Arctic climate. Perhaps one of the most intriguing of their features is that they tend to have liquid tops that precipitate ice. Despite the fact that this situation is colloidally unstable, these cloud systems are quite long lived - from a few days to over a couple of weeks. It has been hypothesized that mixed-phase clouds are maintained through a balance between liquid water condensation resulting from the cloud-top radiative cooling and ice removal by precipitation (Pinto 1998; Harrington et al. 1999). In their modeling study Harrington et al. (1999) found that the maintenance of this balance depends strongly on the ambient concentration of ice forming nucleus (IFN). In a follow-up study, Jiang et al. (2002), using only 30% of IFN concentration predicted by Meyers et al. (1992) IFN parameterization were able to obtain results similar to the observations reported by Pinto (1998). The IFN concentration measurements collected during the Mixed-Phase Arctic Cloud Experiment (M-PACE), conducted in October 2004 over the North Slope of Alaska and the Beaufort Sea (Verlinde et al. 2005), also showed much lower values then those predicted (Prenne, pers. comm.) by currently accepted ice nucleation parameterizations (e.g. Meyers et al. 1992). The goal of this study is to use the extensive IFN data taken during M-PACE to examine what effects low IFN concentrations have on mesoscale cloud structure and coastal dynamics.
ERIC Educational Resources Information Center
Ker, H. W.
2014-01-01
Multilevel data are very common in educational research. Hierarchical linear models/linear mixed-effects models (HLMs/LMEs) are often utilized to analyze multilevel data nowadays. This paper discusses the problems of utilizing ordinary regressions for modeling multilevel educational data, compare the data analytic results from three regression…
Modeling of mixed-mode chromatography of peptides.
Bernardi, Susanna; Gétaz, David; Forrer, Nicola; Morbidelli, Massimo
2013-03-29
Mixed-mode chromatographic materials are more and more often used for the purification of biomolecules, such as peptides and proteins. In many instances they in fact exhibit better selectivity values and therefore improve the purification efficiency compared to classical materials. In this work, a model to describe biomolecules retention in cation-exchange/reversed-phase (CIEX-RP) mixed-mode columns under diluted conditions has been developed. The model accounts for the effect of the salt and organic modifier concentration on the biomolecule Henry coefficient through three parameters: α, β and γ. The α parameter is related to the adsorption strength and ligand density, β represents the number of organic modifier molecules necessary to displace one adsorbed biomolecule and γ represents the number of salt molecules necessary to desorb one biomolecule. The latter parameter is strictly related to the number of charges on the biomolecule surface interacting with the ion-exchange ligands and it is shown experimentally that its value is close to the biomolecule net charge. The model reliability has been validated by a large set of experimental data including retention times of two different peptides (goserelin and insulin) on five columns: a reversed-phase C8 column and four CIEX-RP columns with different percentages of sulfonic groups and various concentration values of the salt and organic modifier. It has been found that the percentage of sulfonic groups on the surface strongly affects the peptides adsorption strength, and in particular, in the cases investigated, a CIEX ligand density around 0.04μmol/m(2) leads to optimal retention values.
Efficient material flow in mixed model assembly lines.
Alnahhal, Mohammed; Noche, Bernd
2013-01-01
In this study, material flow from decentralized supermarkets to stations in mixed model assembly lines using tow (tugger) trains is investigated. Train routing, scheduling, and loading problems are investigated in parallel to minimize the number of trains, variability in loading and in routes lengths, and line-side inventory holding costs. The general framework for solving these problems in parallel contains analytical equations, Dynamic Programming (DP), and Mixed Integer Programming (MIP). Matlab in conjunction with LP-solve software was used to formulate the problem. An example was presented to explain the idea. Results which were obtained in very short CPU time showed the effect of using time buffer among routes on the feasible space and on the optimal solution. Results also showed the effect of the objective, concerning reducing the variability in loading, on the results of routing, scheduling, and loading. Moreover, results showed the importance of considering the maximum line-side inventory beside the capacity of the train in the same time in finding the optimal solution.
Mixed-Effects Modeling with Crossed Random Effects for Subjects and Items
ERIC Educational Resources Information Center
Baayen, R. H.; Davidson, D. J.; Bates, D. M.
2008-01-01
This paper provides an introduction to mixed-effects models for the analysis of repeated measurement data with subjects and items as crossed random effects. A worked-out example of how to use recent software for mixed-effects modeling is provided. Simulation studies illustrate the advantages offered by mixed-effects analyses compared to…
NASA Technical Reports Server (NTRS)
Stockwell, Alan E.; Cooper, Paul A.
1991-01-01
The Integrated Multidisciplinary Analysis Tool (IMAT) consists of a menu driven executive system coupled with a relational database which links commercial structures, structural dynamics and control codes. The IMAT graphics system, a key element of the software, provides a common interface for storing, retrieving, and displaying graphical information. The IMAT Graphics Manual shows users of commercial analysis codes (MATRIXx, MSC/NASTRAN and I-DEAS) how to use the IMAT graphics system to obtain high quality graphical output using familiar plotting procedures. The manual explains the key features of the IMAT graphics system, illustrates their use with simple step-by-step examples, and provides a reference for users who wish to take advantage of the flexibility of the software to customize their own applications.
JACKSON VL
2011-08-31
The primary purpose of the tank mixing and sampling demonstration program is to mitigate the technical risks associated with the ability of the Hanford tank farm delivery and celtification systems to measure and deliver a uniformly mixed high-level waste (HLW) feed to the Waste Treatment and Immobilization Plant (WTP) Uniform feed to the WTP is a requirement of 24590-WTP-ICD-MG-01-019, ICD-19 - Interface Control Document for Waste Feed, although the exact definition of uniform is evolving in this context. Computational Fluid Dynamics (CFD) modeling has been used to assist in evaluating scaleup issues, study operational parameters, and predict mixing performance at full-scale.
Metabolic modeling of mixed substrate uptake for polyhydroxyalkanoate (PHA) production.
Jiang, Yang; Hebly, Marit; Kleerebezem, Robbert; Muyzer, Gerard; van Loosdrecht, Mark C M
2011-01-01
Polyhydroxyalkanoate (PHA) production by mixed microbial communities can be established in a two-stage process, consisting of a microbial enrichment step and a PHA accumulation step. In this study, a mathematical model was constructed for evaluating the influence of the carbon substrate composition on both steps of the PHA production process. Experiments were conducted with acetate, propionate, and acetate propionate mixtures. Microbial community analysis demonstrated that despite the changes in substrate composition the dominant microorganism was Plasticicumulans acidivorans in all experiments. A metabolic network model was established to investigate the processes observed. The model based analysis indicated that adaptation of the acetate and propionate uptake rate as a function of acetate and propionate concentrations in the substrate during cultivation occurred. The monomer composition of the PHA produced was found to be directly related to the composition of the substrate. Propionate induced mainly polyhydroxyvalerate (PHV) production whereas only polyhydroxybutyrate (PHB) was produced on acetate. Accumulation experiments with acetate-propionate mixtures yielded PHB/PHV mixtures in ratios directly related to the acetate and propionate uptake rate. The model developed can be used as a useful tool to predict the PHA composition as a function of the substrate composition for acetate-propionate mixtures.
Neutrino mixing in a left-right model
NASA Astrophysics Data System (ADS)
Martins Simões, J. A.; Ponciano, J. A.
We study the mixing among different generations of massive neutrino fields in a model can accommodate a consistent pattern for neutral fermion masses as well as neutrino oscillations. The left and right sectors can be connected by a new neutral current. PACS: 12.60.-i, 14.60.St, 14.60.Pq
Longitudinal Mixed Membership Trajectory Models for Disability Survey Data.
Manrique-Vallier, Daniel
2014-12-01
We develop new methods for analyzing discrete multivariate longitudinal data and apply them to functional disability data on U.S. elderly population from the National Long Term Care Survey (NLTCS), 1982-2004. Our models build on a mixed membership framework, in which individuals are allowed multiple membership on a set of extreme profiles characterized by time-dependent trajectories of progression into disability. We also develop an extension that allows us to incorporate birth-cohort effects, in order to assess inter-generational changes. Applying these methods we find that most individuals follow trajectories that imply a late onset of disability, and that younger cohorts tend to develop disabilities at a later stage in life compared to their elders.
Chemical geothermometers and mixing models for geothermal systems
Fournier, R.O.
1977-01-01
Qualitative chemical geothermometers utilize anomalous concentrations of various "indicator" elements in groundwaters, streams, soils, and soil gases to outline favorable places to explore for geothermal energy. Some of the qualitative methods, such as the delineation of mercury and helium anomalies in soil gases, do not require the presence of hot springs or fumaroles. However, these techniques may also outline fossil thermal areas that are now cold. Quantitative chemical geothermometers and mixing models can provide information about present probable minimum subsurface temperatures. Interpretation is easiest where several hot or warm springs are present in a given area. At this time the most widely used quantitative chemical geothermometers are silica, Na/K, and Na-K-Ca. ?? 1976.
Using Graphic Organizers in Intercultural Education
ERIC Educational Resources Information Center
Ciascai, Liliana
2009-01-01
Graphic organizers are instruments of representation, illustration and modeling of information. In the educational practice they are used for building, and systematization of knowledge. Graphic organizers are instruments that addressed mostly visual learning style, but their use is beneficial to all learners. In this paper we illustrate the use of…
Research on mixed network architecture collaborative application model
NASA Astrophysics Data System (ADS)
Jing, Changfeng; Zhao, Xi'an; Liang, Song
2009-10-01
When facing complex requirements of city development, ever-growing spatial data, rapid development of geographical business and increasing business complexity, collaboration between multiple users and departments is needed urgently, however conventional GIS software (such as Client/Server model or Browser/Server model) are not support this well. Collaborative application is one of the good resolutions. Collaborative application has four main problems to resolve: consistency and co-edit conflict, real-time responsiveness, unconstrained operation, spatial data recoverability. In paper, application model called AMCM is put forward based on agent and multi-level cache. AMCM can be used in mixed network structure and supports distributed collaborative. Agent is an autonomous, interactive, initiative and reactive computing entity in a distributed environment. Agent has been used in many fields such as compute science and automation. Agent brings new methods for cooperation and the access for spatial data. Multi-level cache is a part of full data. It reduces the network load and improves the access and handle of spatial data, especially, in editing the spatial data. With agent technology, we make full use of its characteristics of intelligent for managing the cache and cooperative editing that brings a new method for distributed cooperation and improves the efficiency.
NASA Astrophysics Data System (ADS)
Abas, Norzaida; Daud, Zalina M.; Yusof, Fadhilah
2014-11-01
A stochastic rainfall model is presented for the generation of hourly rainfall data in an urban area in Malaysia. In view of the high temporal and spatial variability of rainfall within the tropical rain belt, the Spatial-Temporal Neyman-Scott Rectangular Pulse model was used. The model, which is governed by the Neyman-Scott process, employs a reasonable number of parameters to represent the physical attributes of rainfall. A common approach is to attach each attribute to a mathematical distribution. With respect to rain cell intensity, this study proposes the use of a mixed exponential distribution. The performance of the proposed model was compared to a model that employs the Weibull distribution. Hourly and daily rainfall data from four stations in the Damansara River basin in Malaysia were used as input to the models, and simulations of hourly series were performed for an independent site within the basin. The performance of the models was assessed based on how closely the statistical characteristics of the simulated series resembled the statistics of the observed series. The findings obtained based on graphical representation revealed that the statistical characteristics of the simulated series for both models compared reasonably well with the observed series. However, a further assessment using the AIC, BIC and RMSE showed that the proposed model yields better results. The results of this study indicate that for tropical climates, the proposed model, using a mixed exponential distribution, is the best choice for generation of synthetic data for ungauged sites or for sites with insufficient data within the limit of the fitted region.
Cruise observation and numerical modeling of turbulent mixing in the Pearl River estuary in summer
NASA Astrophysics Data System (ADS)
Pan, Jiayi; Gu, Yanzhen
2016-06-01
The turbulent mixing in the Pearl River estuary and plume area is analyzed by using cruise data and simulation results of the Regional Ocean Model System (ROMS). The cruise observations reveal that strong mixing appeared in the bottom layer on larger ebb in the estuary. Modeling simulations are consistent with the observation results, and suggest that inside the estuary and in the near-shore water, the mixing is stronger on ebb than on flood. The mixing generation mechanism analysis based on modeling data reveals that bottom stress is responsible for the generation of turbulence in the estuary, for the re-circulating plume area, internal shear instability plays an important role in the mixing, and wind may induce the surface mixing in the plume far-field. The estuary mixing is controlled by the tidal strength, and in the re-circulating plume bulge, the wind stirring may reinforce the internal shear instability mixing.
Using Bayesian Stable Isotope Mixing Models to Enhance Marine Ecosystem Models
The use of stable isotopes in food web studies has proven to be a valuable tool for ecologists. We investigated the use of Bayesian stable isotope mixing models as constraints for an ecosystem model of a temperate seagrass system on the Atlantic coast of France. δ13C and δ15N i...
NASA Technical Reports Server (NTRS)
Taylor, Nancy L.; Randall, Donald P.; Bowen, John T.; Johnson, Mary M.; Roland, Vincent R.; Matthews, Christine G.; Gates, Raymond L.; Skeens, Kristi M.; Nolf, Scott R.; Hammond, Dana P.
1990-01-01
The computer graphics capabilities available at the Center are introduced and their use is explained. More specifically, the manual identifies and describes the various graphics software and hardware components, details the interfaces between these components, and provides information concerning the use of these components at LaRC.
Extended Mixed-Efects Item Response Models with the MH-RM Algorithm
ERIC Educational Resources Information Center
Chalmers, R. Philip
2015-01-01
A mixed-effects item response theory (IRT) model is presented as a logical extension of the generalized linear mixed-effects modeling approach to formulating explanatory IRT models. Fixed and random coefficients in the extended model are estimated using a Metropolis-Hastings Robbins-Monro (MH-RM) stochastic imputation algorithm to accommodate for…
Validation of hydrogen gas stratification and mixing models
Wu, Hsingtzu; Zhao, Haihua
2015-05-26
Two validation benchmarks confirm that the BMIX++ code is capable of simulating unintended hydrogen release scenarios efficiently. The BMIX++ (UC Berkeley mechanistic MIXing code in C++) code has been developed to accurately and efficiently predict the fluid mixture distribution and heat transfer in large stratified enclosures for accident analyses and design optimizations. The BMIX++ code uses a scaling based one-dimensional method to achieve large reduction in computational effort compared to a 3-D computational fluid dynamics (CFD) simulation. Two BMIX++ benchmark models have been developed. One is for a single buoyant jet in an open space and another is for a large sealed enclosure with both a jet source and a vent near the floor. Both of them have been validated by comparisons with experimental data. Excellent agreements are observed. The entrainment coefficients of 0.09 and 0.08 are found to fit the experimental data for hydrogen leaks with the Froude number of 99 and 268 best, respectively. In addition, the BIX++ simulation results of the average helium concentration for an enclosure with a vent and a single jet agree with the experimental data within a margin of about 10% for jet flow rates ranging from 1.21 × 10⁻⁴ to 3.29 × 10⁻⁴ m³/s. In conclusion, computing time for each BMIX++ model with a normal desktop computer is less than 5 min.
Validation of hydrogen gas stratification and mixing models
Wu, Hsingtzu; Zhao, Haihua
2015-05-26
Two validation benchmarks confirm that the BMIX++ code is capable of simulating unintended hydrogen release scenarios efficiently. The BMIX++ (UC Berkeley mechanistic MIXing code in C++) code has been developed to accurately and efficiently predict the fluid mixture distribution and heat transfer in large stratified enclosures for accident analyses and design optimizations. The BMIX++ code uses a scaling based one-dimensional method to achieve large reduction in computational effort compared to a 3-D computational fluid dynamics (CFD) simulation. Two BMIX++ benchmark models have been developed. One is for a single buoyant jet in an open space and another is for amore » large sealed enclosure with both a jet source and a vent near the floor. Both of them have been validated by comparisons with experimental data. Excellent agreements are observed. The entrainment coefficients of 0.09 and 0.08 are found to fit the experimental data for hydrogen leaks with the Froude number of 99 and 268 best, respectively. In addition, the BIX++ simulation results of the average helium concentration for an enclosure with a vent and a single jet agree with the experimental data within a margin of about 10% for jet flow rates ranging from 1.21 × 10⁻⁴ to 3.29 × 10⁻⁴ m³/s. In conclusion, computing time for each BMIX++ model with a normal desktop computer is less than 5 min.« less
Mixed dark matter in left-right symmetric models
Berlin, Asher; Fox, Patrick J.; Hooper, Dan; ...
2016-06-08
Motivated by the recently reported diboson and dijet excesses in Run 1 data at ATLAS and CMS, we explore models of mixed dark matter in left-right symmetric theories. In this study, we calculate the relic abundance and the elastic scattering cross section with nuclei for a number of dark matter candidates that appear within the fermionic multiplets of left-right symmetric models. In contrast to the case of pure multiplets, WIMP-nucleon scattering proceeds at tree-level, and hence the projected reach of future direct detection experiments such as LUX-ZEPLIN and XENON1T will cover large regions of parameter space for TeV-scale thermal darkmore » matter. Decays of the heavy charged W' boson to particles in the dark sector can potentially shift the right-handed gauge coupling to larger values when fixed to the rate of the Run 1 excesses, moving towards the theoretically attractive scenario, gR = gL. Furthermore, this region of parameter space may be probed by future collider searches for new Higgs bosons or electroweak fermions.« less
Mixed dark matter in left-right symmetric models
Berlin, Asher; Fox, Patrick J.; Hooper, Dan; Mohlabeng, Gopolang
2016-06-08
Motivated by the recently reported diboson and dijet excesses in Run 1 data at ATLAS and CMS, we explore models of mixed dark matter in left-right symmetric theories. In this study, we calculate the relic abundance and the elastic scattering cross section with nuclei for a number of dark matter candidates that appear within the fermionic multiplets of left-right symmetric models. In contrast to the case of pure multiplets, WIMP-nucleon scattering proceeds at tree-level, and hence the projected reach of future direct detection experiments such as LUX-ZEPLIN and XENON1T will cover large regions of parameter space for TeV-scale thermal dark matter. Decays of the heavy charged W' boson to particles in the dark sector can potentially shift the right-handed gauge coupling to larger values when fixed to the rate of the Run 1 excesses, moving towards the theoretically attractive scenario, g_{R} = g_{L}. Furthermore, this region of parameter space may be probed by future collider searches for new Higgs bosons or electroweak fermions.
Mixed dark matter in left-right symmetric models
Berlin, Asher; Fox, Patrick J.; Hooper, Dan; Mohlabeng, Gopolang
2016-06-08
Motivated by the recently reported diboson and dijet excesses in Run 1 data at ATLAS and CMS, we explore models of mixed dark matter in left-right symmetric theories. In this study, we calculate the relic abundance and the elastic scattering cross section with nuclei for a number of dark matter candidates that appear within the fermionic multiplets of left-right symmetric models. In contrast to the case of pure multiplets, WIMP-nucleon scattering proceeds at tree-level, and hence the projected reach of future direct detection experiments such as LUX-ZEPLIN and XENON1T will cover large regions of parameter space for TeV-scale thermal dark matter. Decays of the heavy charged W{sup ′} boson to particles in the dark sector can potentially shift the right-handed gauge coupling to larger values when fixed to the rate of the Run 1 excesses, moving towards the theoretically attractive scenario, g{sub R}=g{sub L}. This region of parameter space may be probed by future collider searches for new Higgs bosons or electroweak fermions.
Mixed dark matter in left-right symmetric models
NASA Astrophysics Data System (ADS)
Berlin, Asher; Fox, Patrick J.; Hooper, Dan; Mohlabeng, Gopolang
2016-06-01
Motivated by the recently reported diboson and dijet excesses in Run 1 data at ATLAS and CMS, we explore models of mixed dark matter in left-right symmetric theories. In this study, we calculate the relic abundance and the elastic scattering cross section with nuclei for a number of dark matter candidates that appear within the fermionic multiplets of left-right symmetric models. In contrast to the case of pure multiplets, WIMP-nucleon scattering proceeds at tree-level, and hence the projected reach of future direct detection experiments such as LUX-ZEPLIN and XENON1T will cover large regions of parameter space for TeV-scale thermal dark matter. Decays of the heavy charged W' boson to particles in the dark sector can potentially shift the right-handed gauge coupling to larger values when fixed to the rate of the Run 1 excesses, moving towards the theoretically attractive scenario, gR = gL. This region of parameter space may be probed by future collider searches for new Higgs bosons or electroweak fermions.
Numerical Modeling of Mixing and Venting from Explosions in Bunkers
NASA Astrophysics Data System (ADS)
Liu, Benjamin
2005-07-01
2D and 3D numerical simulations were performed to study the dynamic interaction of explosion products in a concrete bunker with ambient air, stored chemical or biological warfare (CBW) agent simulant, and the surrounding walls and structure. The simulations were carried out with GEODYN, a multi-material, Godunov-based Eulerian code, that employs adaptive mesh refinement and runs efficiently on massively parallel computer platforms. Tabular equations of state were used for all materials with the exception of any high explosives employed, which were characterized with conventional JWL models. An appropriate constitutive model was used to describe the concrete. Interfaces between materials were either tracked with a volume-of-fluid method that used high-order reconstruction to specify the interface location and orientation, or a capturing approach was employed with the assumption of local thermal and mechanical equilibrium. A major focus of the study was to estimate the extent of agent heating that could be obtained prior to venting of the bunker and resultant agent dispersal. Parameters investigated included the bunker construction, agent layout, energy density in the bunker and the yield-to-agent mass ratio. Turbulent mixing was found to be the dominant heat transfer mechanism for heating the agent.
Analytical model for heterogeneous reactions in mixed porous media
Hatfield, K.; Burris, D.R.; Wolfe, N.L.
1996-08-01
The funnel/gate system is a developing technology for passive ground-water plume management and treatment. This technology uses sheet pilings as a funnel to force polluted ground water through a highly permeable zone of reactive porous media (the gate) where contaminants are degraded by biotic or abiotic heterogeneous reactions. This paper presents a new analytical nonequilibrium model for solute transport in saturated, nonhomogeneous or mixed porous media that could assist efforts to design funnel/gate systems and predict their performance. The model incorporates convective/dispersion transport, dissolved constituent decay, surface-mediated degradation, and time-dependent mass transfer between phases. Simulation studies of equilibrium and nonequilibrium transport conditions reveal manifestations of rate-limited degradation when mass-transfer times are longer than system hydraulic residence times, or when surface-mediated reaction rates are faster than solute mass-transfer processes (i.e., sorption, film diffusion, or intraparticle diffusion). For example, steady-state contaminant concentrations will be higher under a nonequilibrium transport scenario than would otherwise be expected when assuming equilibrium conditions. Thus, a funnel/gate system may fail to achieve desired ground-water treatment if the possibility of mass-transfer-limited degradation is not considered.
Linear mixed effects models under inequality constraints with applications.
Farnan, Laura; Ivanova, Anastasia; Peddada, Shyamal D
2014-01-01
Constraints arise naturally in many scientific experiments/studies such as in, epidemiology, biology, toxicology, etc. and often researchers ignore such information when analyzing their data and use standard methods such as the analysis of variance (ANOVA). Such methods may not only result in a loss of power and efficiency in costs of experimentation but also may result poor interpretation of the data. In this paper we discuss constrained statistical inference in the context of linear mixed effects models that arise naturally in many applications, such as in repeated measurements designs, familial studies and others. We introduce a novel methodology that is broadly applicable for a variety of constraints on the parameters. Since in many applications sample sizes are small and/or the data are not necessarily normally distributed and furthermore error variances need not be homoscedastic (i.e. heterogeneity in the data) we use an empirical best linear unbiased predictor (EBLUP) type residual based bootstrap methodology for deriving critical values of the proposed test. Our simulation studies suggest that the proposed procedure maintains the desired nominal Type I error while competing well with other tests in terms of power. We illustrate the proposed methodology by re-analyzing a clinical trial data on blood mercury level. The methodology introduced in this paper can be easily extended to other settings such as nonlinear and generalized regression models.
SU(4) chiral quark model with configuration mixing
NASA Astrophysics Data System (ADS)
Dahiya, Harleen; Gupta, Manmohan
2003-04-01
The chiral quark model with configuration mixing and broken SU(3)×U(1) symmetry is extended to include the contribution from cc¯ fluctuations by considering broken SU(4) instead of SU(3). The implications of such a model are studied for quark flavor and spin distribution functions corresponding to E866 and the NMC data. The predicted parameters regarding the charm spin distribution functions, for example, Δc, Δc/ΔΣ, Δc/c as well as the charm quark distribution functions, for example, c¯, 2c¯/(ū+d¯), 2c¯/(u+d) and (c+c¯)/∑(q+q¯) are in agreement with other similar calculations. Specifically, we find Δc=-0.009, Δc/ΔΣ=-0.02, c¯=0.03 and (c+c¯)/∑(q+q¯)=0.02 for the χQM parameters a=0.1, α=0.4, β=0.7, ζE866=-1-2β, ζNMC=-2-2β and γ=0.3; the latter appears due to the extension of SU(3) to SU(4).
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.
A mixing timescale model for TPDF simulations of turbulent premixed flames
Kuron, Michael; Ren, Zhuyin; Hawkes, Evatt R.; ...
2017-02-06
Transported probability density function (TPDF) methods are an attractive modeling approach for turbulent flames as chemical reactions appear in closed form. However, molecular micro-mixing needs to be modeled and this modeling is considered a primary challenge for TPDF methods. In the present study, a new algebraic mixing rate model for TPDF simulations of turbulent premixed flames is proposed, which is a key ingredient in commonly used molecular mixing models. The new model aims to properly account for the transition in reactive scalar mixing rate behavior from the limit of turbulence-dominated mixing to molecular mixing behavior in flamelets. An a priorimore » assessment of the new model is performed using direct numerical simulation (DNS) data of a lean premixed hydrogen–air jet flame. The new model accurately captures the mixing timescale behavior in the DNS and is found to be a significant improvement over the commonly used constant mechanical-to-scalar mixing timescale ratio model. An a posteriori TPDF study is then performed using the same DNS data as a numerical test bed. The DNS provides the initial conditions and time-varying input quantities, including the mean velocity, turbulent diffusion coefficient, and modeled scalar mixing rate for the TPDF simulations, thus allowing an exclusive focus on the mixing model. Here, the new mixing timescale model is compared with the constant mechanical-to-scalar mixing timescale ratio coupled with the Euclidean Minimum Spanning Tree (EMST) mixing model, as well as a laminar flamelet closure. It is found that the laminar flamelet closure is unable to properly capture the mixing behavior in the thin reaction zones regime while the constant mechanical-to-scalar mixing timescale model under-predicts the flame speed. Furthermore, the EMST model coupled with the new mixing timescale model provides the best prediction of the flame structure and flame propagation among the models tested, as the dynamics of reactive
Engineering Graphics Educational Outcomes for the Global Engineer: An Update
ERIC Educational Resources Information Center
Barr, R. E.
2012-01-01
This paper discusses the formulation of educational outcomes for engineering graphics that span the global enterprise. Results of two repeated faculty surveys indicate that new computer graphics tools and techniques are now the preferred mode of engineering graphical communication. Specifically, 3-D computer modeling, assembly modeling, and model…
Computing Science and Statistics: Volume 24. Graphics and Visualization
1993-03-20
Considering this component customization, and project integration , approach, we choose BORLAND C+ + as programming i) Project Recognization language , which...1174. Pole, A. and West, M. (1990). Efficient bayesian learning 324 Posterior Integration in Dynamic Models in nonlinear dynamic models. Journal of... language is designed to integrate text and graphic mainly used for graphical printing in two dimensional images. Any graphics package which can
Linear mixed-effects modeling approach to FMRI group analysis
Chen, Gang; Saad, Ziad S.; Britton, Jennifer C.; Pine, Daniel S.; Cox, Robert W.
2013-01-01
Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance–covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance–covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the
Mathematical Modelling of Mixed-Model Assembly Line Balancing Problem with Resources Constraints
NASA Astrophysics Data System (ADS)
Magffierah Razali, Muhamad; Rashid, Mohd Fadzil Faisae Ab.; Razif Abdullah Make, Muhammad
2016-11-01
Modern manufacturing industries nowadays encounter with the challenges to provide a product variety in their production at a cheaper cost. This situation requires for a system that flexible with cost competent such as Mixed-Model Assembly Line. This paper developed a mathematical model for Mixed-Model Assembly Line Balancing Problem (MMALBP). In addition to the existing works that consider minimize cycle time, workstation and product rate variation, this paper also consider the resources constraint in the problem modelling. Based on the finding, the modelling results achieved by using computational method were in line with the manual calculation for the evaluated objective functions. Hence, it provided an evidence to verify the developed mathematical model for MMALBP. Implications of the results and future research directions were also presented in this paper.
Sugawara, Takuya; Ogihara, Yuki; Sakamoto, Yuji
2016-01-20
The point-based method and fast-Fourier-transform-based method are commonly used for calculation methods of computer-generation holograms. This paper proposes a novel fast calculation method for a patch model, which uses the point-based method. The method provides a calculation time that is proportional to the number of patches but not to that of the point light sources. This means that the method is suitable for calculating a wide area covered by patches quickly. Experiments using a graphics processing unit indicated that the proposed method is about 8 times or more faster than the ordinary point-based method.
Approximate Counting of Graphical Realizations.
Erdős, Péter L; Kiss, Sándor Z; Miklós, István; Soukup, Lajos
2015-01-01
In 1999 Kannan, Tetali and Vempala proposed a MCMC method to uniformly sample all possible realizations of a given graphical degree sequence and conjectured its rapidly mixing nature. Recently their conjecture was proved affirmative for regular graphs (by Cooper, Dyer and Greenhill, 2007), for regular directed graphs (by Greenhill, 2011) and for half-regular bipartite graphs (by Miklós, Erdős and Soukup, 2013). Several heuristics on counting the number of possible realizations exist (via sampling processes), and while they work well in practice, so far no approximation guarantees exist for such an approach. This paper is the first to develop a method for counting realizations with provable approximation guarantee. In fact, we solve a slightly more general problem; besides the graphical degree sequence a small set of forbidden edges is also given. We show that for the general problem (which contains the Greenhill problem and the Miklós, Erdős and Soukup problem as special cases) the derived MCMC process is rapidly mixing. Further, we show that this new problem is self-reducible therefore it provides a fully polynomial randomized approximation scheme (a.k.a. FPRAS) for counting of all realizations.
Approximate Counting of Graphical Realizations
2015-01-01
In 1999 Kannan, Tetali and Vempala proposed a MCMC method to uniformly sample all possible realizations of a given graphical degree sequence and conjectured its rapidly mixing nature. Recently their conjecture was proved affirmative for regular graphs (by Cooper, Dyer and Greenhill, 2007), for regular directed graphs (by Greenhill, 2011) and for half-regular bipartite graphs (by Miklós, Erdős and Soukup, 2013). Several heuristics on counting the number of possible realizations exist (via sampling processes), and while they work well in practice, so far no approximation guarantees exist for such an approach. This paper is the first to develop a method for counting realizations with provable approximation guarantee. In fact, we solve a slightly more general problem; besides the graphical degree sequence a small set of forbidden edges is also given. We show that for the general problem (which contains the Greenhill problem and the Miklós, Erdős and Soukup problem as special cases) the derived MCMC process is rapidly mixing. Further, we show that this new problem is self-reducible therefore it provides a fully polynomial randomized approximation scheme (a.k.a. FPRAS) for counting of all realizations. PMID:26161994
From linear to generalized linear mixed models: A case study in repeated measures
Technology Transfer Automated Retrieval System (TEKTRAN)
Compared to traditional linear mixed models, generalized linear mixed models (GLMMs) can offer better correspondence between response variables and explanatory models, yielding more efficient estimates and tests in the analysis of data from designed experiments. Using proportion data from a designed...
Not Available
1984-08-01
The Computing Services Department supports a number of graphics software packages on the VAX machines, primarily on the IGM VAX. These packages will drive a large variety of different graphical devices, terminals (including various Tektronix terminals, the AED 512 color raster terminal, the IMLAC Series II vector list processor terminal and others), various styles of plotters and the DICOMED D48 film recorder. We are going to present to you the following graphic software packages: Tell-A-Graf, Cuechart, Tell-A-Plan, Data Connection, DI-3000, Contouring, Grafmaker (including Grafeasy), Grafmaster, Movie.BYU, Grafpac, IDDS, UGS/HPLOT/HBOOK, and SDL/SGL.
Huh, Yeamin; Hynes, Scott M.; Smith, David E.
2013-01-01
Purpose To develop a population pharmacokinetic model to quantitate the distribution kinetics of glycylsarcosine (GlySar), a substrate of peptide transporter 2 (PEPT2), in blood, CSF and kidney in wild-type and PEPT2 knockout mice. Methods A stepwise compartment modeling approach was performed to describe the concentration profiles of GlySar in blood, CSF, and kidney simultaneously using nonlinear mixed effects modeling (NONMEM). The final model was selected based on the likelihood ratio test and graphical goodness-of-fit. Results The profiles of GlySar in blood, CSF, and kidney were best described by a four-compartment model. The estimated systemic elimination clearance, volume of distribution in the central and peripheral compartments were 0.236 vs 0.449 ml/min, 3.79 vs 4.75 ml, and 5.75 vs 9.18 ml for wild-type versus knockout mice. Total CSF efflux clearance was 4.3 fold higher for wild-type compared to knockout mice. NONMEM parameter estimates indicated that 77% of CSF efflux clearance was mediated by PEPT2 and the remaining 23% was mediated by the diffusional and bulk clearances. Conclusions Due to the availability of PEPT2 knockout mice, we were able to quantitatively determine the significance of PEPT2 in the efflux kinetics of GlySar at the blood-cerebrospinal fluid barrier. PMID:23371515
Age of stratospheric air and aging by mixing in global models
NASA Astrophysics Data System (ADS)
Garny, Hella; Dietmüller, Simone; Plöger, Felix; Birner, Thomas; Bönisch, Harald; Jöckel, Patrick
2016-04-01
The Brewer-Dobson circulation is often quantified by the integrated transport measure age of air (AoA). AoA is affected by all transport processes, including transport along the residual mean mass circulation and two-way mixing. A large spread in the simulation of AoA by current global models exists. Using CCMVal-2 and CCMI-1 global model data, we show that this spread can only in small parts be attributed to differences in the simulated residual circulation. Instead, large differences in the "mixing efficiency" strongly contribute to the differences in the simulated AoA. The "mixing efficiency" is defined as the ratio of the two-way mixing mass flux across the subtropical barrier to the net (residual) mass flux, and this mixing efficiency controls the relative increase in AoA by mixing. We derive the mixing efficiency from global model data using the analytical solution of a simplified version of the tropical leaky pipe (TLP) model, in which vertical diffusion is neglected. Thus, it is assumed that only residual mean transport and horizontal two-way mixing across the subtropical barrier controls AoA. However, in global models vertical mixing and numerical diffusion modify AoA, and these processes likely contribute to the differences in the mixing efficiency between models. We explore the contributions of diffusion and mixing on mean AoA by a) using simulations with the tropical leaky pipe model including vertical diffusion and b) explicit calculations of aging by mixing on resolved scales. Using the TLP model, we show that vertical diffusion leads to a decrease in tropical AoA, i.e. counteracts the increase in tropical mean AoA due to horizontal mixing. Thus, neglecting vertical diffusion leads to an underestimation of the mixing efficiency. With explicit calculations of aging by mixing via integration of daily local mixing tendencies along residual circulation trajectories, we explore the contributions of vertical and horizontal mixing for aging by mixing. The
Igarashi, Jun; Shouno, Osamu; Fukai, Tomoki; Tsujino, Hiroshi
2011-11-01
Real-time simulation of a biologically realistic spiking neural network is necessary for evaluation of its capacity to interact with real environments. However, the real-time simulation of such a neural network is difficult due to its high computational costs that arise from two factors: (1) vast network size and (2) the complicated dynamics of biologically realistic neurons. In order to address these problems, mainly the latter, we chose to use general purpose computing on graphics processing units (GPGPUs) for simulation of such a neural network, taking advantage of the powerful computational capability of a graphics processing unit (GPU). As a target for real-time simulation, we used a model of the basal ganglia that has been developed according to electrophysiological and anatomical knowledge. The model consists of heterogeneous populations of 370 spiking model neurons, including computationally heavy conductance-based models, connected by 11,002 synapses. Simulation of the model has not yet been performed in real-time using a general computing server. By parallelization of the model on the NVIDIA Geforce GTX 280 GPU in data-parallel and task-parallel fashion, faster-than-real-time simulation was robustly realized with only one-third of the GPU's total computational resources. Furthermore, we used the GPU's full computational resources to perform faster-than-real-time simulation of three instances of the basal ganglia model; these instances consisted of 1100 neurons and 33,006 synapses and were synchronized at each calculation step. Finally, we developed software for simultaneous visualization of faster-than-real-time simulation output. These results suggest the potential power of GPGPU techniques in real-time simulation of realistic neural networks.
Modeling of mixing processes: Fluids, particulates, and powders
Ottino, J.M.; Hansen, S.
1995-12-31
Work under this grant involves two main areas: (1) Mixing of Viscous Liquids, this first area comprising aggregation, fragmentation and dispersion, and (2) Mixing of Powders. In order to produce a coherent self-contained picture, we report primarily on results obtained under (1), and within this area, mostly on computational studies of particle aggregation in regular and chaotic flows. Numerical simulations show that the average cluster size of compact clusters grows algebraically, while the average cluster size of fractal clusters grows exponentially; companion mathematical arguments are used to describe the initial growth of average cluster size and polydispersity. It is found that when the system is well mixed and the capture radius independent of mass, the polydispersity is constant for long-times and the cluster size distribution is self-similar. Furthermore, our simulations indicate that the fractal nature of the clusters is dependent upon the mixing.
NASA Technical Reports Server (NTRS)
Desautel, Richard
1993-01-01
The objectives of this research include supporting the Aerothermodynamics Branch's research by developing graphical visualization tools for both the branch's adaptive grid code and flow field ray tracing code. The completed research for the reporting period includes development of a graphical user interface (GUI) and its implementation into the NAS Flowfield Analysis Software Tool kit (FAST), for both the adaptive grid code (SAGE) and the flow field ray tracing code (CISS).
GRAPS: Graphical Plotting System.
1985-07-01
stand-alone unit, but could (with a few modifications) be incorporated into a larger system; e.g., the IGUANA system (ref 3). The GRAPS system...the GRAPS software into another system (e.g., the IGUANA ) could possibly introduce additional requirements. I have simply listed those things...Graphics Utility For Army NEC Automation ( IGUANA ), May 1985. 4. Hewlett-Packard Corp., Interfacing and Programming Manual - HP 7470A Graphics Plotter
Some Recent Advances in Computer Graphics.
ERIC Educational Resources Information Center
Whitted, Turner
1982-01-01
General principles of computer graphics are reviewed, including discussions of display hardware, geometric modeling, algorithms, and applications in science, computer-aided design, flight training, communications, business, art, and entertainment. (JN)
Peacor, Scott D; Peckarsky, Barbara L; Trussell, Geoffrey C; Vonesh, James R
2013-01-01
Defensive modifications in prey traits that reduce predation risk can also have negative effects on prey fitness. Such nonconsumptive effects (NCEs) of predators are common, often quite strong, and can even dominate the net effect of predators. We develop an intuitive graphical model to identify and explore the conditions promoting strong NCEs. The model illustrates two conditions necessary and sufficient for large NCEs: (1) trait change has a large cost, and (2) the benefit of reduced predation outweighs the costs, such as reduced growth rate. A corollary condition is that potential predation in the absence of trait change must be large. In fact, the sum total of the consumptive effects (CEs) and NCEs may be any value bounded by the magnitude of the predation rate in the absence of the trait change. The model further illustrates how, depending on the effect of increased trait change on resulting costs and benefits, any combination of strong and weak NCEs and CEs is possible. The model can also be used to examine how changes in environmental factors (e.g., refuge safety) or variation among predator-prey systems (e.g., different benefits of a prey trait change) affect NCEs. Results indicate that simple rules of thumb may not apply; factors that increase the cost of trait change or that increase the degree to which an animal changes a trait, can actually cause smaller (rather than larger) NCEs. We provide examples of how this graphical model can provide important insights for empirical studies from two natural systems. Implementation of this approach will improve our understanding of how and when NCEs are expected to dominate the total effect of predators. Further, application of the models will likely promote a better linkage between experimental and theoretical studies of NCEs, and foster synthesis across systems.
Comparison of Mixed-Model Approaches for Association Mapping
Stich, Benjamin; Möhring, Jens; Piepho, Hans-Peter; Heckenberger, Martin; Buckler, Edward S.; Melchinger, Albrecht E.
2008-01-01
Association-mapping methods promise to overcome the limitations of linkage-mapping methods. The main objectives of this study were to (i) evaluate various methods for association mapping in the autogamous species wheat using an empirical data set, (ii) determine a marker-based kinship matrix using a restricted maximum-likelihood (REML) estimate of the probability of two alleles at the same locus being identical in state but not identical by descent, and (iii) compare the results of association-mapping approaches based on adjusted entry means (two-step approaches) with the results of approaches in which the phenotypic data analysis and the association analysis were performed in one step (one-step approaches). On the basis of the phenotypic and genotypic data of 303 soft winter wheat (Triticum aestivum L.) inbreds, various association-mapping methods were evaluated. Spearman's rank correlation between P-values calculated on the basis of one- and two-stage association-mapping methods ranged from 0.63 to 0.93. The mixed-model association-mapping approaches using a kinship matrix estimated by REML are more appropriate for association mapping than the recently proposed QK method with respect to (i) the adherence to the nominal α-level and (ii) the adjusted power for detection of quantitative trait loci. Furthermore, we showed that our data set could be analyzed by using two-step approaches of the proposed association-mapping method without substantially increasing the empirical type I error rate in comparison to the corresponding one-step approaches. PMID:18245847
Best practices for use of stable isotope mixing models in food-web studies
Stable isotope mixing models are increasingly used to quantify contributions of resources to consumers. While potentially powerful tools, these mixing models have the potential to be misused, abused, and misinterpreted. Here we draw on our collective experiences to address the qu...
The Analysis of Repeated Measurements with Mixed-Model Adjusted "F" Tests
ERIC Educational Resources Information Center
Kowalchuk, Rhonda K.; Keselman, H. J.; Algina, James; Wolfinger, Russell D.
2004-01-01
One approach to the analysis of repeated measures data allows researchers to model the covariance structure of their data rather than presume a certain structure, as is the case with conventional univariate and multivariate test statistics. This mixed-model approach, available through SAS PROC MIXED, was compared to a Welch-James type statistic.…
Item Purification in Differential Item Functioning Using Generalized Linear Mixed Models
ERIC Educational Resources Information Center
Liu, Qian
2011-01-01
For this dissertation, four item purification procedures were implemented onto the generalized linear mixed model for differential item functioning (DIF) analysis, and the performance of these item purification procedures was investigated through a series of simulations. Among the four procedures, forward and generalized linear mixed model (GLMM)…
CONVERTING ISOTOPE RATIOS TO DIET COMPOSITION - THE USE OF MIXING MODELS
Investigations of wildlife foraging ecology with stable isotope analysis are increasing. Converting isotope values to proportions of different foods in a consumer's diet requires the use of mixing models. Simple mixing models based on mass balance equations have been used for d...
A Proposed Model of Retransformed Qualitative Data within a Mixed Methods Research Design
ERIC Educational Resources Information Center
Palladino, John M.
2009-01-01
Most models of mixed methods research design provide equal emphasis of qualitative and quantitative data analyses and interpretation. Other models stress one method more than the other. The present article is a discourse about the investigator's decision to employ a mixed method design to examine special education teachers' advocacy and…
NASA Astrophysics Data System (ADS)
Binti Shamsuddin, Norsila
Technology advancement and development in a higher learning institution is a chance for students to be motivated to learn in depth in the information technology areas. Students should take hold of the opportunity to blend their skills towards these technologies as preparation for them when graduating. The curriculum itself can rise up the students' interest and persuade them to be directly involved in the evolvement of the technology. The aim of this study is to see how deep is the students' involvement as well as their acceptance towards the adoption of the technology used in Computer Graphics and Image Processing subjects. The study will be towards the Bachelor students in Faculty of Industrial Information Technology (FIIT), Universiti Industri Selangor (UNISEL); Bac. In Multimedia Industry, BSc. Computer Science and BSc. Computer Science (Software Engineering). This study utilizes the new Unified Theory of Acceptance and Use of Technology (UTAUT) to further validate the model and enhance our understanding of the adoption of Computer Graphics and Image Processing Technologies. Four (4) out of eight (8) independent factors in UTAUT will be studied towards the dependent factor.
NASA Astrophysics Data System (ADS)
Milani, G.; Milani, F.
A GUI software (GURU) for experimental data fitting of rheometer curves in Natural Rubber (NR) vulcanized with sulphur at different curing temperatures is presented. Experimental data are automatically loaded in GURU from an Excel spreadsheet coming from the output of the experimental machine (moving die rheometer). To fit the experimental data, the general reaction scheme proposed by Han and co-workers for NR vulcanized with sulphur is considered. From the simplified kinetic scheme adopted, a closed form solution can be found for the crosslink density, with the only limitation that the induction period is excluded from computations. Three kinetic constants must be determined in such a way to minimize the absolute error between normalized experimental data and numerical prediction. Usually, this result is achieved by means of standard least-squares data fitting. On the contrary, GURU works interactively by means of a Graphical User Interface (GUI) to minimize the error and allows an interactive calibration of the kinetic constants by means of sliders. A simple mouse click on the sliders allows the assignment of a value for each kinetic constant and a visual comparison between numerical and experimental curves. Users will thus find optimal values of the constants by means of a classic trial and error strategy. An experimental case of technical relevance is shown as benchmark.
Bleka, Øyvind; Storvik, Geir; Gill, Peter
2016-03-01
We have released a software named EuroForMix to analyze STR DNA profiles in a user-friendly graphical user interface. The software implements a model to explain the allelic peak height on a continuous scale in order to carry out weight-of-evidence calculations for profiles which could be from a mixture of contributors. Through a properly parameterized model we are able to do inference on mixture proportions, the peak height properties, stutter proportion and degradation. In addition, EuroForMix includes models for allele drop-out, allele drop-in and sub-population structure. EuroForMix supports two inference approaches for likelihood ratio calculations. The first approach uses maximum likelihood estimation of the unknown parameters. The second approach is Bayesian based which requires prior distributions to be specified for the parameters involved. The user may specify any number of known and unknown contributors in the model, however we find that there is a practical computing time limit which restricts the model to a maximum of four unknown contributors. EuroForMix is the first freely open source, continuous model (accommodating peak height, stutter, drop-in, drop-out, population substructure and degradation), to be reported in the literature. It therefore serves an important purpose to act as an unrestricted platform to compare different solutions that are available. The implementation of the continuous model used in the software showed close to identical results to the R-package DNAmixtures, which requires a HUGIN Expert license to be used. An additional feature in EuroForMix is the ability for the user to adapt the Bayesian inference framework by incorporating their own prior information.
Application of mixing-controlled combustion models to gas turbine combustors
NASA Technical Reports Server (NTRS)
Nguyen, Hung Lee
1990-01-01
Gas emissions were studied from a staged Rich Burn/Quick-Quench Mix/Lean Burn combustor were studied under test conditions encountered in High Speed Research engines. The combustor was modeled at conditions corresponding to different engine power settings, and the effect of primary dilution airflow split on emissions, flow field, flame size and shape, and combustion intensity, as well as mixing, was investigated. A mathematical model was developed from a two-equation model of turbulence, a quasi-global kinetics mechanism for the oxidation of propane, and the Zeldovich mechanism for nitric oxide formation. A mixing-controlled combustion model was used to account for turbulent mixing effects on the chemical reaction rate. This model assumes that the chemical reaction rate is much faster than the turbulent mixing rate.
A time-dependent Mixing Model for PDF Methods in Heterogeneous Aquifers
NASA Astrophysics Data System (ADS)
Schüler, Lennart; Suciu, Nicolae; Knabner, Peter; Attinger, Sabine
2016-04-01
Predicting the transport of groundwater contaminations remains a demanding task, especially with respect to the heterogeneity of the subsurface and the large measurement uncertainties. A risk analysis also includes the quantification of the uncertainty in order to evaluate how accurate the predictions are. Probability density function (PDF) methods are a promising alternative to predicting the transport of solutes in groundwater under uncertainty. They make it possible to derive the evolution equations of the mean concentration and the concentration variance, which can be used as a first measure of uncertainty. A mixing model, also known as a dissipation model, is essential for both methods. Finding a satisfactory mixing model is still an open question and due to the rather elaborate PDF methods, a difficult undertaking. Both the PDF equation and the concentration variance equation depend on the same mixing model. This connection is used to find and test an improved mixing model for the much easier to handle concentration variance. Subsequently, this mixing model is transferred to the PDF equation and tested. The newly proposed mixing model yields significantly improved results for both variance modelling and PDF modelling. The implications of the new mixing model for different kinds of flow conditions are discussed and some comments are made on efficiently handling spatially resolved higher moments.
2015-11-04
Gnuforplot Graphics is a Fortran90 program designed to generate two and three dimensional plots of data on a personal computer. The program uses calls to the open source code Gnuplot to generate the plots. Two Fortran90 programs have been written to use the Gnuplot graphics capabilities. The first program, named Plotsetup.f90 reads data from output files created by either the Stadium or LeachXS/Orchestra modeling codes and saves the data in arrays for plotting. This program then calls Gnuforplot which takes the data array along with user specified parameters to set plot specifications and issues Gnuplot commands that generate the screen plots. The user can view the plots and optionally save copies in jpeg format.
Winston, Richard B.; Voss, Clifford I.
2004-01-01
This report describes SutraGUI, a flexible graphical user-interface (GUI) that supports two-dimensional (2D) and three-dimensional (3D) simulation with the U.S. Geological Survey (USGS) SUTRA ground-water-flow and transport model (Voss and Provost, 2002). SutraGUI allows the user to create SUTRA ground-water models graphically. SutraGUI provides all of the graphical functionality required for setting up and running SUTRA simulations that range from basic to sophisticated, but it is also possible for advanced users to apply programmable features within Argus ONE to meet the unique demands of particular ground-water modeling projects. SutraGUI is a public-domain computer program designed to run with the proprietary Argus ONE? package, which provides 2D Geographic Information System (GIS) and meshing support. For 3D simulation, GIS and meshing support is provided by programming contained within SutraGUI. When preparing a 3D SUTRA model, the model and all of its features are viewed within Argus 1 in 2D projection. For 2D models, SutraGUI is only slightly changed in functionality from the previous 2D-only version (Voss and others, 1997) and it provides visualization of simulation results. In 3D, only model preparation is supported by SutraGUI, and 3D simulation results may be viewed in SutraPlot (Souza, 1999) or Model Viewer (Hsieh and Winston, 2002). A comprehensive online Help system is included in SutraGUI. For 3D SUTRA models, the 3D model domain is conceptualized as bounded on the top and bottom by 2D surfaces. The 3D domain may also contain internal surfaces extending across the model that divide the domain into tabular units, which can represent hydrogeologic strata or other features intended by the user. These surfaces can be non-planar and non-horizontal. The 3D mesh is defined by one or more 2D meshes at different elevations that coincide with these surfaces. If the nodes in the 3D mesh are vertically aligned, only a single 2D mesh is needed. For nonaligned
Prediction of microbial growth in mixed culture with a competition model.
Fujikawa, Hiroshi; Sakha, Mohammad Z
2014-01-01
Prediction of microbial growth in mixed culture was studied with a competition model that we had developed recently. The model, which is composed of the new logistic model and the Lotka-Volterra model, is shown to successfully describe the microbial growth of two species in mixed culture using Staphylococcus aureus, Escherichia coli, and Salmonella. With the parameter values of the model obtained from the experimental data on monoculture and mixed culture with two species, it then succeeded in predicting the simultaneous growth of the three species in mixed culture inoculated with various cell concentrations. To our knowledge, it is the first time for a prediction model for multiple (three) microbial species to be reported. The model, which is not built on any premise for specific microorganisms, may become a basic competition model for microorganisms in food and food materials.
Mixed Models: Combining incompatible scalar models in any space-time dimension
NASA Astrophysics Data System (ADS)
Klauder, John R.
2017-01-01
Traditionally, covariant scalar field theory models are either super renormalizable, strictly renormalizable, or nonrenormalizable. The goal of “Mixed Models” is to make sense of sums of these distinct examples, e.g. gφ34 + g‧φ 36 + g″φ 38, which includes an example of each kind for space-time dimension n = 3. We show how the several interactions such mixed models have may be turned on and off in any order without any difficulties. Analogous results are shown for gφn4 + g‧φ n138, etc. for all n ≥ 3. Different categories hold for n = 2 such as, e.g. gP(φ)2 + g‧NP(φ) 2, that involve polynomial (P) and suitable nonpolynomial (NP) interactions, etc. Analogous situations for n = 1 (time alone) offer simple “toy” examples of how such mixed models may be constructed. As a general rule, if the introduction of a specific interaction term reduces the domain of the free classical action, we invariably find that the introduction of the associated quantum interaction leads, effectively, to a “nonrenormalizable” quantum theory. However, in special cases, a classical interaction that does not reduce the domain of the classical free action may generate an “unsatisfactory” quantum theory, which generally involves a model-specific, different approach to become “satisfactory.” We will encounter both situations in our analysis.
NASA Astrophysics Data System (ADS)
Wood, Roy C.
2001-11-01
There has been a desire in recent years to introduce physics to students at the middle school, or freshmen high school level. However, traditional physics courses involve a great deal of mathematics, and this makes physics unattractive to many of them. In the last few decades, courses have been developed with a focus that is more conceptual than mathematical, and is generally referred to as conceptual physics. These two types of courses emphasize two methods that physicist use to solve physics problems. However, there is a third, graphical method that is also useful, and complements mathematical and verbal reasoning. A course emphasizing graphical methods would deal with quantitative graphical diagrams, as well as qualitative diagrams. Examples of quantitative graphical diagrams are scaled force diagrams and scaled optical ray-tracing diagrams. A course based on this type of approach would involve measurements and uncertainties, and would involve active (hands-on) student participation suitable for younger students. This talk will discuss a graphical physics course, and its benefits to younger students.
Graphical functions in parametric space
NASA Astrophysics Data System (ADS)
Golz, Marcel; Panzer, Erik; Schnetz, Oliver
2016-12-01
Graphical functions are positive functions on the punctured complex plane Csetminus {0,1} which arise in quantum field theory. We generalize a parametric integral representation for graphical functions due to Lam, Lebrun and Nakanishi, which implies the real analyticity of graphical functions. Moreover, we prove a formula that relates graphical functions of planar dual graphs.
General-Purpose Software For Computer Graphics
NASA Technical Reports Server (NTRS)
Rogers, Joseph E.
1992-01-01
NASA Device Independent Graphics Library (NASADIG) is general-purpose computer-graphics package for computer-based engineering and management applications which gives opportunity to translate data into effective graphical displays for presentation. Features include two- and three-dimensional plotting, spline and polynomial interpolation, control of blanking of areas, multiple log and/or linear axes, control of legends and text, control of thicknesses of curves, and multiple text fonts. Included are subroutines for definition of areas and axes of plots; setup and display of text; blanking of areas; setup of style, interpolation, and plotting of lines; control of patterns and of shading of colors; control of legends, blocks of text, and characters; initialization of devices; and setting of mixed alphabets. Written in FORTRAN 77.
Interactive computer graphics applications for compressible aerodynamics
NASA Technical Reports Server (NTRS)
Benson, Thomas J.
1994-01-01
Three computer applications have been developed to solve inviscid compressible fluids problems using interactive computer graphics. The first application is a compressible flow calculator which solves for isentropic flow, normal shocks, and oblique shocks or centered expansions produced by two dimensional ramps. The second application couples the solutions generated by the first application to a more graphical presentation of the results to produce a desk top simulator of three compressible flow problems: 1) flow past a single compression ramp; 2) flow past two ramps in series; and 3) flow past two opposed ramps. The third application extends the results of the second to produce a design tool which solves for the flow through supersonic external or mixed compression inlets. The applications were originally developed to run on SGI or IBM workstations running GL graphics. They are currently being extended to solve additional types of flow problems and modified to operate on any X-based workstation.
Comparative quantification of physically and numerically induced mixing in ocean models
NASA Astrophysics Data System (ADS)
Burchard, Hans; Rennau, Hannes
A diagnostic method for calculating physical and numerical mixing of tracers in ocean models is presented. The physical mixing is defined as the turbulent mean tracer variance decay rate. The numerical mixing due to discretisation errors of tracer advection schemes is shown to be the decay rate between the advected square of the tracer variance and the square of the advected tracer and can be easily implemented into any ocean model. The applicability of the method is demonstrated for four test cases: (i) a one-dimensional linear advection equation with periodic boundary conditions, (ii) a two-dimensional flat-bottom lock exchange test case without mixing, (iii) a two-dimensional marginal sea overflow study with mixing and entrainment and (iv) the DOME test case with a dense bottom current propagating down a broad linear slope. The method has a number of advantages over previously introduced estimates for numerical mixing.
Segregation parameters and pair-exchange mixing models for turbulent nonpremixed flames
NASA Technical Reports Server (NTRS)
Chen, J.-Y.; Kollman, W.
1991-01-01
The progress of chemical reactions in nonpremixed turbulent flows depends on the coexistence of reactants, which are brought together by mixing. The degree of mixing can strongly influence the chemical reactions and it can be quantified by segregation parameters. In this paper, the relevance of segregation parameters to turbulent mixing and chemical reactions is explored. An analysis of the pair-exchange mixing models is performed and an explanation is given for the peculiar behavior of such models in homogeneous turbulence. The nature of segregation parameters in a H2/Ar-air nonpremixed jet flame is investigated. The results show that Monte Carlo simulation with the modified Curl's mixing model predicts segregation parameters in close agreement with the experimental values, providing an indirect validation for the theoretical model.
Model analysis of influences of aerosol mixing state upon its optical properties in East Asia
NASA Astrophysics Data System (ADS)
Han, Xiao; Zhang, Meigen; Zhu, Lingyun; Xu, Liren
2013-07-01
The air quality model system RAMS (Regional Atmospheric Modeling System)-CMAQ (Models-3 Community Multi-scale Air Quality) coupled with an aerosol optical/radiative module was applied to investigate the impact of different aerosol mixing states (i.e., externally mixed, half externally and half internally mixed, and internally mixed) on radiative forcing in East Asia. The simulation results show that the aerosol optical depth (AOD) generally increased when the aerosol mixing state changed from externally mixed to internally mixed, while the single scattering albedo (SSA) decreased. Therefore, the scattering and absorption properties of aerosols can be significantly affected by the change of aerosol mixing states. Comparison of simulated and observed SSAs at five AERONET (Aerosol Robotic Network) sites suggests that SSA could be better estimated by considering aerosol particles to be internally mixed. Model analysis indicates that the impact of aerosol mixing state upon aerosol direct radiative forcing (DRF) is complex. Generally, the cooling effect of aerosols over East Asia are enhanced in the northern part of East Asia (Northern China, Korean peninsula, and the surrounding area of Japan) and are reduced in the southern part of East Asia (Sichuan Basin and Southeast China) by internal mixing process, and the variation range can reach ±5 W m-2. The analysis shows that the internal mixing between inorganic salt and dust is likely the main reason that the cooling effect strengthens. Conversely, the internal mixture of anthropogenic aerosols, including sulfate, nitrate, ammonium, black carbon, and organic carbon, could obviously weaken the cooling effect.
Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model
Rossi, R; Gallagher, B; Neville, J; Henderson, K
2011-11-11
Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied our model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.
Improving Mixed-phase Cloud Parameterization in Climate Model with the ACRF Measurements
Wang, Zhien
2016-12-13
Mixed-phase cloud microphysical and dynamical processes are still poorly understood, and their representation in GCMs is a major source of uncertainties in overall cloud feedback in GCMs. Thus improving mixed-phase cloud parameterizations in climate models is critical to reducing the climate forecast uncertainties. This study aims at providing improved knowledge of mixed-phase cloud properties from the long-term ACRF observations and improving mixed-phase clouds simulations in the NCAR Community Atmosphere Model version 5 (CAM5). The key accomplishments are: 1) An improved retrieval algorithm was developed to provide liquid droplet concentration for drizzling or mixed-phase stratiform clouds. 2) A new ice concentration retrieval algorithm for stratiform mixed-phase clouds was developed. 3) A strong seasonal aerosol impact on ice generation in Arctic mixed-phase clouds was identified, which is mainly attributed to the high dust occurrence during the spring season. 4) A suite of multi-senor algorithms was applied to long-term ARM observations at the Barrow site to provide a complete dataset (LWC and effective radius profile for liquid phase, and IWC, Dge profiles and ice concentration for ice phase) to characterize Arctic stratiform mixed-phase clouds. This multi-year stratiform mixed-phase cloud dataset provides necessary information to study related processes, evaluate model stratiform mixed-phase cloud simulations, and improve model stratiform mixed-phase cloud parameterization. 5). A new in situ data analysis method was developed to quantify liquid mass partition in convective mixed-phase clouds. For the first time, we reliably compared liquid mass partitions in stratiform and convective mixed-phase clouds. Due to the different dynamics in stratiform and convective mixed-phase clouds, the temperature dependencies of liquid mass partitions are significantly different due to much higher ice concentrations in convective mixed phase clouds. 6) Systematic evaluations
Graphical Language for Data Processing
NASA Technical Reports Server (NTRS)
Alphonso, Keith
2011-01-01
A graphical language for processing data allows processing elements to be connected with virtual wires that represent data flows between processing modules. The processing of complex data, such as lidar data, requires many different algorithms to be applied. The purpose of this innovation is to automate the processing of complex data, such as LIDAR, without the need for complex scripting and programming languages. The system consists of a set of user-interface components that allow the user to drag and drop various algorithmic and processing components onto a process graph. By working graphically, the user can completely visualize the process flow and create complex diagrams. This innovation supports the nesting of graphs, such that a graph can be included in another graph as a single step for processing. In addition to the user interface components, the system includes a set of .NET classes that represent the graph internally. These classes provide the internal system representation of the graphical user interface. The system includes a graph execution component that reads the internal representation of the graph (as described above) and executes that graph. The execution of the graph follows the interpreted model of execution in that each node is traversed and executed from the original internal representation. In addition, there are components that allow external code elements, such as algorithms, to be easily integrated into the system, thus making the system infinitely expandable.
NASA Astrophysics Data System (ADS)
Kaya, Ilhan; Santhanam, Anand P.; Lee, Kye-Sung; Meemon, Panomsak; Papp, Nicolene; Rolland, Jannick P.
Tissue engineering has broad applications from creating the much-needed engineered tissue and organ structures for regenerative medicine to providing in vitro testbeds for drug testing. In the latter, application domain, creating alveolar lung tissue, and simulating the diffusion process of oxygen and other possible agents from the air into the blood stream as well as modeling the removal of carbon dioxide and other possible entities from the blood stream are of critical importance to simulating lung functions in various environments. In this chapter, we propose a physics-based model to simulate the alveolar gas exchange and the alveolar
User's Guide for Mixed-Size Sediment Transport Model for Networks of One-Dimensional Open Channels
Bennett, James P.
2001-01-01
This user's guide describes a mathematical model for predicting the transport of mixed sizes of sediment by flow in networks of one-dimensional open channels. The simulation package is useful for general sediment routing problems, prediction of erosion and deposition following dam removal, and scour in channels at road embankment crossings or other artificial structures. The model treats input hydrographs as stepwise steady-state, and the flow computation algorithm automatically switches between sub- and supercritical flow as dictated by channel geometry and discharge. A variety of boundary conditions including weirs and rating curves may be applied both external and internal to the flow network. The model may be used to compute flow around islands and through multiple openings in embankments, but the network must be 'simple' in the sense that the flow directions in all channels can be specified before simulation commences. The location and shape of channel banks are user specified, and all bedelevation changes take place between these banks and above a user-specified bedrock elevation. Computation of sediment-transport emphasizes the sand-size range (0.0625-2.0 millimeter) but the user may select any desired range of particle diameters including silt and finer (<0.0625 millimeter). As part of data input, the user may set the original bed-sediment composition of any number of layers of known thickness. The model computes the time evolution of total transport and the size composition of bed- and suspended-load sand through any cross section of interest. It also tracks bed -surface elevation and size composition. The model is written in the FORTRAN programming language for implementation on personal computers using the WINDOWS operating system and, along with certain graphical output display capability, is accessed from a graphical user interface (GUI). The GUI provides a framework for selecting input files and parameters of a number of components of the sediment
Photonic states mixing beyond the plasmon hybridization model
NASA Astrophysics Data System (ADS)
Suryadharma, Radius N. S.; Iskandar, Alexander A.; Tjia, May-On
2016-07-01
A study is performed on a photonic-state mixing-pattern in an insulator-metal-insulator cylindrical silver nanoshell and its rich variations induced by changes in the geometry and dielectric media of the system, representing the combined influences of plasmon coupling strength and cavity effects. This study is performed in terms of the photonic local density of states (LDOS) calculated using the Green tensor method, in order to elucidate those combined effects. The energy profiles of LDOS inside the dielectric core are shown to exhibit consistently growing number of redshifted photonic states due to an enhanced plasmon coupling induced state mixing arising from decreased shell thickness, increased cavity size effect, and larger symmetry breaking effect induced by increased permittivity difference between the core and the background media. Further, an increase in cavity size leads to increased additional peaks that spread out toward the lower energy regime. A systematic analysis of those variations for a silver nanoshell with a fixed inner radius in vacuum background reveals a certain pattern of those growing number of redshifted states with an analytic expression for the corresponding energy downshifts, signifying a photonic state mixing scheme beyond the commonly adopted plasmon hybridization scheme. Finally, a remarkable correlation is demonstrated between the LDOS energy profiles outside the shell and the corresponding scattering efficiencies.
Experimental constraints on the neutrino oscillations and a simple model of three-flavor mixing
Raczka, P.A.; Szymacha, A. ); Tatur, S. )
1994-02-01
A simple model of neutrino mixing is considered which contains only one right-handed neutrino field coupled, via the mass term, to the three usual left-handed fields. This is the simplest model that allows for three-flavor neutrino oscillations. The existing experimental limits on the neutrino oscillations are used to obtain constraints on the two free-mixing parameters of the model. A specific sum rule relating the oscillation probabilities of different flavors is derived.
Mathematical, physical and numerical principles essential for models of turbulent mixing
Sharp, David Howland; Lim, Hyunkyung; Yu, Yan; Glimm, James G
2009-01-01
We propose mathematical, physical and numerical principles which are important for the modeling of turbulent mixing, especially the classical and well studied Rayleigh-Taylor and Richtmyer-Meshkov instabilities which involve acceleration driven mixing of a fluid discontinuity layer, by a steady accerleration or an impulsive force.
Pricing European option under the time-changed mixed Brownian-fractional Brownian model
NASA Astrophysics Data System (ADS)
Guo, Zhidong; Yuan, Hongjun
2014-07-01
This paper deals with the problem of discrete time option pricing by a mixed Brownian-fractional subdiffusive Black-Scholes model. Under the assumption that the price of the underlying stock follows a time-changed mixed Brownian-fractional Brownian motion, we derive a pricing formula for the European call option in a discrete time setting.
Software For Animated Graphics
NASA Technical Reports Server (NTRS)
Merritt, F.; Bancroft, G.; Kelaita, P.
1992-01-01
Graphics Animation System (GAS) software package serves as easy-to-use, menu-driven program providing fast, simple viewing capabilities as well as more-complex features for rendering and animation in computational fluid dynamics (CFD). Displays two- and three-dimensional objects along with computed data and records animation sequences on video digital disk, videotape, and 16-mm film. Written in C.
Computer Graphics Verification
NASA Technical Reports Server (NTRS)
1992-01-01
Video processing creates technical animation sequences using studio quality equipment to realistically represent fluid flow over space shuttle surfaces, helicopter rotors, and turbine blades.Computer systems Co-op, Tim Weatherford, performing computer graphics verification. Part of Co-op brochure.
ERIC Educational Resources Information Center
Schulze, Patricia
This is a prewriting activity for personal memoir or autobiographical writing. Grade 6-8 students brainstorm for important memories, create graphics or symbols for their most important memories, and construct a life map on tag board or construction paper, connecting drawings and captions of high and low points with a highway. During four 50-minute…
ERIC Educational Resources Information Center
Cleaver, Samantha
2008-01-01
Not so many years ago, comic books in school were considered the enemy. Students caught sneaking comics between the pages of bulky--and less engaging--textbooks were likely sent to the principal. Today, however, comics, including classics such as "Superman" but also their generally more complex, nuanced cousins, graphic novels, are not only…
Computing Graphical Confidence Bounds
NASA Technical Reports Server (NTRS)
Mezzacappa, M. A.
1983-01-01
Approximation for graphical confidence bounds is simple enough to run on programmable calculator. Approximation is used in lieu of numerical tables not always available, and exact calculations, which often require rather sizable computer resources. Approximation verified for collection of up to 50 data points. Method used to analyze tile-strength data on Space Shuttle thermal-protection system.
ERIC Educational Resources Information Center
Kan, Katherine L.
1994-01-01
Reviews graphic novels for young adults, including five titles from "The Adventures of Tintin," a French series that often uses ethnic and racial stereotypes which reflect the time in which they were published, and "Wolverine," a Marvel comic character adventure. (Contains six references.) (LRW)
NASA Astrophysics Data System (ADS)
Callies, Ulrich; Scharfe, Mirco
2015-07-01
We analyze inter-annual changes of marine observations at Helgoland Roads (nitrate, phosphate, salinity, Secchi depth) in relation to hydro-climatic conditions and Elbe River discharge as potential drivers. Focusing on mean spring conditions we explore graphical covariance selection modeling as a means to both identify and represent the structure of parameter interactions. While river discharge is able to modify spatial distributions and related gradients in the station's vicinity, atmospherically forced regional transport patterns govern the time dependent local conditions the station is actually exposed to. A model consistent with the data confirms the interplay of the two forcing factors for observations at station Helgoland Roads. Introducing water temperature as a third predictor of inter-annual variability does not much improve the model. Comparing a Helgoland Roads dependence graph with corresponding graphs for other stations or related model simulations, for instance, could help identify differences in underlying mechanisms without referring to specific realizations of external forcing. With regard to prediction, supplementary numerical experiments reveal that imposing constraints on parameter interactions can reduce the chance of fitting regression models to noise.
A Simple Scheme to Implement a Nonlocal Turbulent Convection Model for Convective Overshoot Mixing
NASA Astrophysics Data System (ADS)
Zhang, Q. S.
2016-02-01
Classical “ballistic” overshoot models show some contradictions and are not consistent with numerical simulations and asteroseismic studies. Asteroseismic studies imply that overshoot is a weak mixing process. A diffusion model is suitable to deal with it. The form of diffusion coefficient in a diffusion model is crucial. Because overshoot mixing is related to convective heat transport (i.e., entropy mixing), there should be some similarity between them. A recent overshoot mixing model shows consistency between composition mixing and entropy mixing in the overshoot region. A prerequisite to apply the model is to know the dissipation rate of turbulent kinetic energy. The dissipation rate can be worked out by solving turbulent convection models (TCMs). But it is difficult to apply TCMs because of some numerical problems and the enormous time cost. In order to find a convenient way, we have used the asymptotic solution and simplified the TCM to a single linear equation for turbulent kinetic energy. This linear model is easy to implement in calculations of stellar evolution with negligible extra time cost. We have tested the linear model in stellar evolution, and have found that it can well reproduce the turbulent kinetic energy profile of the full TCM, as well as the diffusion coefficient, abundance profile, and stellar evolutionary tracks. We have also studied the effects of different values of the model parameters and have found that the effect due to the modification of temperature gradient in the overshoot region is slight.
NASA Technical Reports Server (NTRS)
Archer, G. T.
1974-01-01
The model presents a systems analysis of a human circulatory regulation based almost entirely on experimental data and cumulative present knowledge of the many facets of the circulatory system. The model itself consists of eighteen different major systems that enter into circulatory control. These systems are grouped into sixteen distinct subprograms that are melded together to form the total model. The model develops circulatory and fluid regulation in a simultaneous manner. Thus, the effects of hormonal and autonomic control, electrolyte regulation, and excretory dynamics are all important and are all included in the model.
Bayes factor between Student t and Gaussian mixed models within an animal breeding context
Casellas, Joaquim; Ibáñez-Escriche, Noelia; García-Cortés, Luis Alberto; Varona, Luis
2008-01-01
The implementation of Student t mixed models in animal breeding has been suggested as a useful statistical tool to effectively mute the impact of preferential treatment or other sources of outliers in field data. Nevertheless, these additional sources of variation are undeclared and we do not know whether a Student t mixed model is required or if a standard, and less parameterized, Gaussian mixed model would be sufficient to serve the intended purpose. Within this context, our aim was to develop the Bayes factor between two nested models that only differed in a bounded variable in order to easily compare a Student t and a Gaussian mixed model. It is important to highlight that the Student t density converges to a Gaussian process when degrees of freedom tend to infinity. The twomodels can then be viewed as nested models that differ in terms of degrees of freedom. The Bayes factor can be easily calculated from the output of a Markov chain Monte Carlo sampling of the complex model (Student t mixed model). The performance of this Bayes factor was tested under simulation and on a real dataset, using the deviation information criterion (DIC) as the standard reference criterion. The two statistical tools showed similar trends along the parameter space, although the Bayes factor appeared to be the more conservative. There was considerable evidence favoring the Student t mixed model for data sets simulated under Student t processes with limited degrees of freedom, and moderate advantages associated with using the Gaussian mixed model when working with datasets simulated with 50 or more degrees of freedom. For the analysis of real data (weight of Pietrain pigs at six months), both the Bayes factor and DIC slightly favored the Student t mixed model, with there being a reduced incidence of outlier individuals in this population. PMID:18558073
Drikvandi, Reza
2017-02-13
Nonlinear mixed-effects models are frequently used for pharmacokinetic data analysis, and they account for inter-subject variability in pharmacokinetic parameters by incorporating subject-specific random effects into the model. The random effects are often assumed to follow a (multivariate) normal distribution. However, many articles have shown that misspecifying the random-effects distribution can introduce bias in the estimates of parameters and affect inferences about the random effects themselves, such as estimation of the inter-subject variability. Because random effects are unobservable latent variables, it is difficult to assess their distribution. In a recent paper we developed a diagnostic tool based on the so-called gradient function to assess the random-effects distribution in mixed models. There we evaluated the gradient function for generalized liner mixed models and in the presence of a single random effect. However, assessing the random-effects distribution in nonlinear mixed-effects models is more challenging, especially when multiple random effects are present, and therefore the results from linear and generalized linear mixed models may not be valid for such nonlinear models. In this paper, we further investigate the gradient function and evaluate its performance for such nonlinear mixed-effects models which are common in pharmacokinetics and pharmacodynamics. We use simulations as well as real data from an intensive pharmacokinetic study to illustrate the proposed diagnostic tool.
Representation and evaluation of aerosol mixing state in a climate model
NASA Astrophysics Data System (ADS)
Bauer, S. E.; Prather, K. A.; Ault, A. P.
2011-12-01
Aerosol particles in the atmosphere are composed out of multiple chemical species. The aerosol mixing state is an important aerosol property that will determine the interaction of aerosols with the climate system via radiative forcings and cloud activation. Through the introduction of aerosol microphysics into climate models, aerosol mixing state is by now taken into account to a certain extend in climate models, and evaluation of mixing state is the next challenge. Here we use data from the Aerosol Time of Flight Mass Spectrometer (ATOFMS) and compare the results to the GISS-modelE-MATRIX model, a global climate model including a detailed aerosol micro-physical scheme. We use data from various field campaigns probing, urban, rural and maritime air masses and compare those to climatological and nudged simulations for the years 2005 to 2009. ATOFMS provides information about the size distributions of several mixing state classes, including the chemical components of black and organic carbon, sulfates, dust and salts. MATRIX simulates 16 aerosol populations, which definitions are based on mixing state. We have grouped ATOFMS and MATRIX data into similar mixing state classes and compare the size resolved number concentrations against each other. As a first result we find that climatological simulations are rather difficult to evaluate with field data, and that nudged simulations give a much better agreement. However this is not just caused by the better fit of natural - meteorological driven - aerosol components, but also due to the interaction between meteorology and aerosol formation. The model seems to get the right amount of mixing state of black carbon material with sulfate and organic components, but seems to always overestimate the fraction of black carbon that is externally mixed. In order to understand this bias between model and the ATOFMS data, we will look into microphysical processes near emission sources and investigate the climate relevance of these sub
Akio, Suzuki; Shunji, Awazu
2010-04-01
In order to examine the importance of fully representing graphic information items in graphic aids to facilitate comprehension of explanatory texts, we established and randomly assigned fifty university students into the following four groups: (a) participants who study the text without the aid, (b) participants who study the text with the aid, whose literal (key words) and graphic (arrows, boxes, etc.) information items are fully displayed, (c) participants who study the text with the aid, whose graphic information items are fully displayed but whose literal information items are partially displayed, and (d) participants who study the text with the aid, whose literal and graphic information items are partially displayed. The results of two kinds of comprehension tests "textbase and situation model" revealed that groups (b) and (c) outperformed groups (a) and (d). These findings suggest that graphic aids can facilitate students' text comprehension when graphic information items are fully displayed and literal information items are displayed either fully or partially; however, the aid cannot facilitate comprehension when both literal and graphic elements are displayed partially.
Unit physics performance of a mix model in Eulerian fluid computations
Vold, Erik; Douglass, Rod
2011-01-25
In this report, we evaluate the performance of a K-L drag-buoyancy mix model, described in a reference study by Dimonte-Tipton [1] hereafter denoted as [D-T]. The model was implemented in an Eulerian multi-material AMR code, and the results are discussed here for a series of unit physics tests. The tests were chosen to calibrate the model coefficients against empirical data, principally from RT (Rayleigh-Taylor) and RM (Richtmyer-Meshkov) experiments, and the present results are compared to experiments and to results reported in [D-T]. Results show the Eulerian implementation of the mix model agrees well with expectations for test problems in which there is no convective flow of the mass averaged fluid, i.e., in RT mix or in the decay of homogeneous isotropic turbulence (HIT). In RM shock-driven mix, the mix layer moves through the Eulerian computational grid, and there are differences with the previous results computed in a Lagrange frame [D-T]. The differences are attributed to the mass averaged fluid motion and examined in detail. Shock and re-shock mix are not well matched simultaneously. Results are also presented and discussed regarding model sensitivity to coefficient values and to initial conditions (IC), grid convergence, and the generation of atomically mixed volume fractions.
The Brown Muck of $B^0$ and $B^0_s$ Mixing: Beyond the Standard Model
Bouchard, Christopher Michael
2011-01-01
Standard Model contributions to neutral $B$ meson mixing begin at the one loop level where they are further suppressed by a combination of the GIM mechanism and Cabibbo suppression. This combination makes $B$ meson mixing a promising probe of new physics, where as yet undiscovered particles and/or interactions can participate in the virtual loops. Relating underlying interactions of the mixing process to experimental observation requires a precise calculation of the non-perturbative process of hadronization, characterized by hadronic mixing matrix elements. This thesis describes a calculation of the hadronic mixing matrix elements relevant to a large class of new physics models. The calculation is performed via lattice QCD using the MILC collaboration's gauge configurations with $2+1$ dynamical sea quarks.
The Impact of Varied Discrimination Parameters on Mixed-Format Item Response Theory Model Selection
ERIC Educational Resources Information Center
Whittaker, Tiffany A.; Chang, Wanchen; Dodd, Barbara G.
2013-01-01
Whittaker, Chang, and Dodd compared the performance of model selection criteria when selecting among mixed-format IRT models and found that the criteria did not perform adequately when selecting the more parameterized models. It was suggested by M. S. Johnson that the problems when selecting the more parameterized models may be because of the low…
An R2 statistic for fixed effects in the linear mixed model.
Edwards, Lloyd J; Muller, Keith E; Wolfinger, Russell D; Qaqish, Bahjat F; Schabenberger, Oliver
2008-12-20
Statisticians most often use the linear mixed model to analyze Gaussian longitudinal data. The value and familiarity of the R(2) statistic in the linear univariate model naturally creates great interest in extending it to the linear mixed model. We define and describe how to compute a model R(2) statistic for the linear mixed model by using only a single model. The proposed R(2) statistic measures multivariate association between the repeated outcomes and the fixed effects in the linear mixed model. The R(2) statistic arises as a 1-1 function of an appropriate F statistic for testing all fixed effects (except typically the intercept) in a full model. The statistic compares the full model with a null model with all fixed effects deleted (except typically the intercept) while retaining exactly the same covariance structure. Furthermore, the R(2) statistic leads immediately to a natural definition of a partial R(2) statistic. A mixed model in which ethnicity gives a very small p-value as a longitudinal predictor of blood pressure (BP) compellingly illustrates the value of the statistic. In sharp contrast to the extreme p-value, a very small R(2) , a measure of statistical and scientific importance, indicates that ethnicity has an almost negligible association with the repeated BP outcomes for the study.
NASA Astrophysics Data System (ADS)
Belousov, V. I.; Ezhela, V. V.; Kuyanov, Yu. V.; Tkachenko, N. P.
2015-12-01
The experience of using the dynamic atlas of the experimental data and mathematical models of their description in the problems of adjusting parametric models of observable values depending on kinematic variables is presented. The functional possibilities of an image of a large number of experimental data and the models describing them are shown by examples of data and models of observable values determined by the amplitudes of elastic scattering of hadrons. The Internet implementation of an interactive tool DaMoScope and its interface with the experimental data and codes of adjusted parametric models with the parameters of the best description of data are schematically shown. The DaMoScope codes are freely available.
Belousov, V. I.; Ezhela, V. V.; Kuyanov, Yu. V. Tkachenko, N. P.
2015-12-15
The experience of using the dynamic atlas of the experimental data and mathematical models of their description in the problems of adjusting parametric models of observable values depending on kinematic variables is presented. The functional possibilities of an image of a large number of experimental data and the models describing them are shown by examples of data and models of observable values determined by the amplitudes of elastic scattering of hadrons. The Internet implementation of an interactive tool DaMoScope and its interface with the experimental data and codes of adjusted parametric models with the parameters of the best description of data are schematically shown. The DaMoScope codes are freely available.
Integrating Commercial Off-The-Shelf (COTS) graphics and extended memory packages with CLIPS
NASA Technical Reports Server (NTRS)
Callegari, Andres C.
1990-01-01
This paper addresses the question of how to mix CLIPS with graphics and how to overcome PC's memory limitations by using the extended memory available in the computer. By adding graphics and extended memory capabilities, CLIPS can be converted into a complete and powerful system development tool, on the other most economical and popular computer platform. New models of PCs have amazing processing capabilities and graphic resolutions that cannot be ignored and should be used to the fullest of their resources. CLIPS is a powerful expert system development tool, but it cannot be complete without the support of a graphics package needed to create user interfaces and general purpose graphics, or without enough memory to handle large knowledge bases. Now, a well known limitation on the PC's is the usage of real memory which limits CLIPS to use only 640 Kb of real memory, but now that problem can be solved by developing a version of CLIPS that uses extended memory. The user has access of up to 16 MB of memory on 80286 based computers and, practically, all the available memory (4 GB) on computers that use the 80386 processor. So if we give CLIPS a self-configuring graphics package that will automatically detect the graphics hardware and pointing device present in the computer, and we add the availability of the extended memory that exists in the computer (with no special hardware needed), the user will be able to create more powerful systems at a fraction of the cost and on the most popular, portable, and economic platform available such as the PC platform.
A quantitative approach to combine sources in stable isotope mixing models
Stable isotope mixing models, used to estimate source contributions to a mixture, typically yield highly uncertain estimates when there are many sources and relatively few isotope elements. Previously, ecologists have either accepted the uncertain contribution estimates for indiv...
Phillips & Koch (2002) outlined a new stable isotope mixing model which incorporates differences in elemental concentrations in the determinations of source proportions in a mixture. They illustrated their method with sensitivity analyses and two examples from the wildlife ecolog...
A physiologically-based pharmacokinetic (PBPK) model incorporating mixed enzyme inhibition was used to determine mechanism of the metabolic interactions occurring during simultaneous inhalation exposures to the organic solvents chloroform and trichloroethylene (TCE).
V...
Nguyen, Nam-Trung; Huang, Xiaoyang
2005-11-01
This paper theoretically and experimentally investigates a micromixer based on combined hydrodynamic focusing and time-interleaved segmentation. Both hydrodynamic focusing and time-interleaved segmentation are used in the present study to reduce mixing path, to shorten mixing time, and to enhance mixing quality. While hydrodynamic focusing reduces the transversal mixing path, time-interleaved sequential segmentation shortens the axial mixing path. With the same viscosity in the different streams, the focused width can be adjusted by the flow rate ratio. The axial mixing path or the segment length can be controlled by the switching frequency and the mean velocity of the flow. Mixing ratio can be controlled by both flow rate ratio and pulse width modulation of the switching signal. This paper first presents a time-dependent two-dimensional analytical model for the mixing concept. The model considers an arbitrary mixing ratio between solute and solvent as well as the axial Taylor-Aris dispersion. A micromixer was designed and fabricated based on lamination of four polymer layers. The layers were machined using a CO2 laser. Time-interleaved segmentation was realized by two piezoelectric valves. The sheath streams for hydrodynamic focusing are introduced through the other two inlets. A special measurement set-up was designed with synchronization of the mixer's switching signal and the camera's trigger signal. The set-up allows a relatively slow and low-resolution CCD camera to freeze and to capture a large transient concentration field. The concentration profile along the mixing channel agrees qualitatively well with the analytical model. The analytical model and the device promise to be suitable tools for studying Taylor-Aris dispersion near the entrance of a flat microchannel.
Experimental testing and modeling analysis of solute mixing at water distribution pipe junctions.
Shao, Yu; Jeffrey Yang, Y; Jiang, Lijie; Yu, Tingchao; Shen, Cheng
2014-06-01
Flow dynamics at a pipe junction controls particle trajectories, solute mixing and concentrations in downstream pipes. The effect can lead to different outcomes of water quality modeling and, hence, drinking water management in a distribution network. Here we have investigated solute mixing behavior in pipe junctions of five hydraulic types, for which flow distribution factors and analytical equations for network modeling are proposed. First, based on experiments, the degree of mixing at a cross is found to be a function of flow momentum ratio that defines a junction flow distribution pattern and the degree of departure from complete mixing. Corresponding analytical solutions are also validated using computational-fluid-dynamics (CFD) simulations. Second, the analytical mixing model is further extended to double-Tee junctions. Correspondingly the flow distribution factor is modified to account for hydraulic departure from a cross configuration. For a double-Tee(A) junction, CFD simulations show that the solute mixing depends on flow momentum ratio and connection pipe length, whereas the mixing at double-Tee(B) is well represented by two independent single-Tee junctions with a potential water stagnation zone in between. Notably, double-Tee junctions differ significantly from a cross in solute mixing and transport. However, it is noted that these pipe connections are widely, but incorrectly, simplified as cross junctions of assumed complete solute mixing in network skeletonization and water quality modeling. For the studied pipe junction types, analytical solutions are proposed to characterize the incomplete mixing and hence may allow better water quality simulation in a distribution network.
NASA Astrophysics Data System (ADS)
Herman, Jeffrey; Fry, David
1990-08-01
Because graphic files can be stored in a number ofdifferent file formats, it has traditionally been difficult to create a graphics database from which users can open, copy, and print graphic files, where each file in the database may be in one ofseverai different formats. HyperCard Graphics Database Toolkit has been designed and written by Apple Computer to enable software developers to facilitate the creation of customized graphics databases. Using a database developed with the toolkit, users can open, copy, or print a graphic transparently, without having to know or understand the complexities of file formats. In addition, the toolkit includes a graphic user interface, graphic design, on-line help, and search algorithms that enable users to locate specific graphics quickly. Currently, the toolkit handles graphics in the formats MPNT, PICT, and EPSF, and is open to supporting other formats as well. Developers can use the toolkit to alter the code, the interface, and the graphic design in order to customize their database for the needs oftheir users. This paper discusses the structure ofthe toolkit and one implementation, Apple Graphics Source (AGS). AGS contains over 2,000 graphics used in Apple's books and manuals. AGS enables users to find existing graphics of Apple products and use them for presentations, new publications, papers, and software projects.
NASA Technical Reports Server (NTRS)
Putnam, William M.
2011-01-01
Earth system models like the Goddard Earth Observing System model (GEOS-5) have been pushing the limits of large clusters of multi-core microprocessors, producing breath-taking fidelity in resolving cloud systems at a global scale. GPU computing presents an opportunity for improving the efficiency of these leading edge models. A GPU implementation of GEOS-5 will facilitate the use of cloud-system resolving resolutions in data assimilation and weather prediction, at resolutions near 3.5 km, improving our ability to extract detailed information from high-resolution satellite observations and ultimately produce better weather and climate predictions
Marwan, Wolfgang; Rohr, Christian; Heiner, Monika
2012-01-01
Using the example of phosphate regulation in enteric bacteria, we demonstrate the particular suitability of stochastic Petri nets to model biochemical phenomena and their simulative exploration by various features of the software tool Snoopy.
2014-09-30
Submesoscale Flows and Mixing in the Oceanic Surface Layer Using the Regional Oceanic Modeling System (ROMS) M. Jeroen Molemaker (PI) James C...long-term goals of this project are to further the insight into the dynamics of submesoscale flow in the oceanic surface layer. Using the Regional...Oceanic Modeling System (ROMS), we aim to understand the impact of submesoscale processes on tracer mixing at small scales and the transfer of energy
An explicit SU(12) family and flavor unification model with natural fermion masses and mixings
Albright, Carl H.; Feger, Robert P.; Kephart, Thomas W.
2012-07-01
We present an SU(12) unification model with three light chiral families, avoiding any external flavor symmetries. The hierarchy of quark and lepton masses and mixings is explained by higher dimensional Yukawa interactions involving Higgs bosons that contain SU(5) singlet fields with VEVs about 50 times smaller than the SU(12) unification scale. The presented model has been analyzed in detail and found to be in very good agreement with the observed quark and lepton masses and mixings.
Efficient multivariate linear mixed model algorithms for genome-wide association studies.
Zhou, Xiang; Stephens, Matthew
2014-04-01
Multivariate linear mixed models (mvLMMs) are powerful tools for testing associations between single-nucleotide polymorphisms and multiple correlated phenotypes while controlling for population stratification in genome-wide association studies. We present efficient algorithms in the genome-wide efficient mixed model association (GEMMA) software for fitting mvLMMs and computing likelihood ratio tests. These algorithms offer improved computation speed, power and P-value calibration over existing methods, and can deal with more than two phenotypes.