WorldWideScience

Sample records for interaction adaptive modelling

  1. Semantic models for adaptive interactive systems

    CERN Document Server

    Hussein, Tim; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle

    2013-01-01

    Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models.Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using

  2. Modelling interactions between mitigation, adaptation and sustainable development

    Science.gov (United States)

    Reusser, D. E.; Siabatto, F. A. P.; Garcia Cantu Ros, A.; Pape, C.; Lissner, T.; Kropp, J. P.

    2012-04-01

    Managing the interdependence of climate mitigation, adaptation and sustainable development requires a good understanding of the dominant socioecological processes that have determined the pathways in the past. Key variables include water and food availability which depend on climate and overall ecosystem services, as well as energy supply and social, political and economic conditions. We present our initial steps to build a system dynamic model of nations that represents a minimal set of relevant variables of the socio- ecological development. The ultimate goal of the modelling exercise is to derive possible future scenarios and test those for their compatibility with sustainability boundaries. Where dynamics go beyond sustainability boundaries intervention points in the dynamics can be searched.

  3. A new adaptive control scheme based on the interacting multiple model (IMM) estimation

    International Nuclear Information System (INIS)

    Afshari, Hamed H.; Al-Ani, Dhafar; Habibi, Saeid

    2016-01-01

    In this paper, an Interacting multiple model (IMM) adaptive estimation approach is incorporated to design an optimal adaptive control law for stabilizing an Unmanned vehicle. Due to variations of the forward velocity of the Unmanned vehicle, its aerodynamic derivatives are constantly changing. In order to stabilize the unmanned vehicle and achieve the control objectives for in-flight conditions, one seeks for an adaptive control strategy that can adjust itself to varying flight conditions. In this context, a bank of linear models is used to describe the vehicle dynamics in different operating modes. Each operating mode represents a particular dynamic with a different forward velocity. These models are then used within an IMM filter containing a bank of Kalman filters (KF) in a parallel operating mechanism. To regulate and stabilize the vehicle, a Linear quadratic regulator (LQR) law is designed and implemented for each mode. The IMM structure determines the particular mode based on the stored models and in-flight input-output measurements. The LQR controller also provides a set of controllers; each corresponds to a particular flight mode and minimizes the tracking error. Finally, the ultimate control law is obtained as a weighted summation of all individual controllers whereas weights are obtained using mode probabilities of each operating mode.

  4. Improved Discovery of Molecular Interactions in Genome-Scale Data with Adaptive Model-Based Normalization

    Science.gov (United States)

    Brown, Patrick O.

    2013-01-01

    Background High throughput molecular-interaction studies using immunoprecipitations (IP) or affinity purifications are powerful and widely used in biology research. One of many important applications of this method is to identify the set of RNAs that interact with a particular RNA-binding protein (RBP). Here, the unique statistical challenge presented is to delineate a specific set of RNAs that are enriched in one sample relative to another, typically a specific IP compared to a non-specific control to model background. The choice of normalization procedure critically impacts the number of RNAs that will be identified as interacting with an RBP at a given significance threshold – yet existing normalization methods make assumptions that are often fundamentally inaccurate when applied to IP enrichment data. Methods In this paper, we present a new normalization methodology that is specifically designed for identifying enriched RNA or DNA sequences in an IP. The normalization (called adaptive or AD normalization) uses a basic model of the IP experiment and is not a variant of mean, quantile, or other methodology previously proposed. The approach is evaluated statistically and tested with simulated and empirical data. Results and Conclusions The adaptive (AD) normalization method results in a greatly increased range in the number of enriched RNAs identified, fewer false positives, and overall better concordance with independent biological evidence, for the RBPs we analyzed, compared to median normalization. The approach is also applicable to the study of pairwise RNA, DNA and protein interactions such as the analysis of transcription factors via chromatin immunoprecipitation (ChIP) or any other experiments where samples from two conditions, one of which contains an enriched subset of the other, are studied. PMID:23349766

  5. An overview of adaptive model theory: solving the problems of redundancy, resources, and nonlinear interactions in human movement control.

    Science.gov (United States)

    Neilson, Peter D; Neilson, Megan D

    2005-09-01

    Adaptive model theory (AMT) is a computational theory that addresses the difficult control problem posed by the musculoskeletal system in interaction with the environment. It proposes that the nervous system creates motor maps and task-dependent synergies to solve the problems of redundancy and limited central resources. These lead to the adaptive formation of task-dependent feedback/feedforward controllers able to generate stable, noninteractive control and render nonlinear interactions unobservable in sensory-motor relationships. AMT offers a unified account of how the nervous system might achieve these solutions by forming internal models. This is presented as the design of a simulator consisting of neural adaptive filters based on cerebellar circuitry. It incorporates a new network module that adaptively models (in real time) nonlinear relationships between inputs with changing and uncertain spectral and amplitude probability density functions as is the case for sensory and motor signals.

  6. Adapting to a Changing Environment: Modeling the Interaction of Directional Selection and Plasticity.

    Science.gov (United States)

    Nunney, Leonard

    2016-01-01

    Human-induced habitat loss and fragmentation constrains the range of many species, making them unable to respond to climate change by moving. For such species to avoid extinction, they must respond with some combination of phenotypic plasticity and genetic adaptation. Haldane's "cost of natural selection" limits the rate of adaptation, but, although modeling has shown that in very large populations long-term adaptation can be maintained at rates substantially faster than Haldane's suggested limit, maintaining large populations is often an impossibility, so phenotypic plasticity may be crucial in enhancing the long-term survival of small populations. The potential importance of plasticity is in "buying time" for populations subject to directional environmental change: if genotypes can encompass a greater environmental range, then populations can maintain high fitness for a longer period of time. Alternatively, plasticity could be detrimental by lessening the effectiveness of natural selection in promoting genetic adaptation. Here, I modeled a directionally changing environment in which a genotype's adaptive phenotypic plasticity is centered around the environment where its fitness is highest. Plasticity broadens environmental tolerance and, provided it is not too costly, is favored by natural selection. However, a paradoxical result of the individually advantageous spread of plasticity is that, unless the adaptive trait is determined by very few loci, the long-term extinction risk of a population increases. This effect reflects a conflict between the short-term individual benefit of plasticity and a long-term detriment to population persistence, adding to the multiple threats facing small populations under conditions of climate change. © The American Genetic Association. 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  7. The Basic Immune Simulator: An agent-based model to study the interactions between innate and adaptive immunity

    Directory of Open Access Journals (Sweden)

    Orosz Charles G

    2007-09-01

    Full Text Available Abstract Background We introduce the Basic Immune Simulator (BIS, an agent-based model created to study the interactions between the cells of the innate and adaptive immune system. Innate immunity, the initial host response to a pathogen, generally precedes adaptive immunity, which generates immune memory for an antigen. The BIS simulates basic cell types, mediators and antibodies, and consists of three virtual spaces representing parenchymal tissue, secondary lymphoid tissue and the lymphatic/humoral circulation. The BIS includes a Graphical User Interface (GUI to facilitate its use as an educational and research tool. Results The BIS was used to qualitatively examine the innate and adaptive interactions of the immune response to a viral infection. Calibration was accomplished via a parameter sweep of initial agent population size, and comparison of simulation patterns to those reported in the basic science literature. The BIS demonstrated that the degree of the initial innate response was a crucial determinant for an appropriate adaptive response. Deficiency or excess in innate immunity resulted in excessive proliferation of adaptive immune cells. Deficiency in any of the immune system components increased the probability of failure to clear the simulated viral infection. Conclusion The behavior of the BIS matches both normal and pathological behavior patterns in a generic viral infection scenario. Thus, the BIS effectively translates mechanistic cellular and molecular knowledge regarding the innate and adaptive immune response and reproduces the immune system's complex behavioral patterns. The BIS can be used both as an educational tool to demonstrate the emergence of these patterns and as a research tool to systematically identify potential targets for more effective treatment strategies for diseases processes including hypersensitivity reactions (allergies, asthma, autoimmunity and cancer. We believe that the BIS can be a useful addition to

  8. ECClipids17: adapting atomistic lipid models to correct cation-membrane interactions

    Czech Academy of Sciences Publication Activity Database

    Melcr, Josef; Ollila, Samuli; Baxová, Katarína; Jungwirth, Pavel; Martinez-Seara, Hector

    2017-01-01

    Roč. 46, Suppl 1 (2017), S224 ISSN 0175-7571. [IUPAB congress /19./ and EBSA congress /11./. 16.07.2017-20.07.2017, Edinburgh] Institutional support: RVO:61388963 Keywords : ECC * membrane interactions Subject RIV: BO - Biophysics

  9. Perspectives on Adaptivity in Information Retrieval Interaction (PAIRI)

    DEFF Research Database (Denmark)

    Ingwersen, Peter; Larsen, Birger; Kelly, Diane

    2010-01-01

    Adaptivity in IR interactions requires the IR systems adapting to users’ situations and the users adapting to the systems. System adaption entails dynamic user modeling, effective information architecture and enhanced search features such as search integration and relevance feedback; user adaptat...

  10. Opinion: Interactions of innate and adaptive lymphocytes

    Science.gov (United States)

    Gasteiger, Georg; Rudensky, Alexander Y.

    2015-01-01

    Innate lymphocytes, including natural killer (NK) cells and the recently discovered innate lymphoid cells (ILCs) have crucial roles during infection, tissue injury and inflammation. Innate signals regulate the activation and homeostasis of innate lymphocytes. Less well understood is the contribution of the adaptive immune system to the orchestration of innate lymphocyte responses. We review our current understanding of the interactions between adaptive and innate lymphocytes, and propose a model in which adaptive T cells function as antigen-specific sensors for the activation of innate lymphocytes to amplify and instruct local immune responses. We highlight the potential role of regulatory and helper T cells in these processes and discuss major questions in the emerging area of crosstalk between adaptive and innate lymphocytes. PMID:25132095

  11. STSV2 as a Model Crenarchaeal Virus for Studying Virus-Host Interactions and CRISPR-Cas Adaptive Immunity

    DEFF Research Database (Denmark)

    León Sobrino, Carlos

    , the archaea harbour their own viruses, which constitute an extraordinarily diverse group with exotic morphologies and unique features. Prokaryotes possess a variety of defence mechanisms. The CRISPR-Cas adaptive immune system is of great importance for archaea –84% of them possess it, compared to 45...... generate immune memory by inserting in its own genome short invader-derived DNA fragments forming a database –the CRISPR locus. Little was known about this system until recent years, and the generation of immune memory has been the most elusive step. In this work, the interactions of the spindle......-shaped monocaudavirus STSV2 and its host Sulfolobus islandicus REY15A were studied. This interaction produced, after several days, de novo CRISPR adaptation – that is, without any previous memory that can act as a trigger. We employed transcriptome sequencing to characterise the long-term progression...

  12. Affective Interface Adaptations in the Musickiosk Interactive Entertainment Application

    Science.gov (United States)

    Malatesta, L.; Raouzaiou, A.; Pearce, L.; Karpouzis, K.

    The current work presents the affective interface adaptations in the Musickiosk application. Adaptive interaction poses several open questions since there is no unique way of mapping affective factors of user behaviour to the output of the system. Musickiosk uses a non-contact interface and implicit interaction through emotional affect rather than explicit interaction where a gesture, sound or other input directly maps to an output behaviour - as in traditional entertainment applications. PAD model is used for characterizing the different affective states and emotions.

  13. What Drives Business Model Adaptation?

    DEFF Research Database (Denmark)

    Saebi, Tina; Lien, Lasse B.; Foss, Nicolai Juul

    2017-01-01

    Business models change as managers not only innovate business models, but also engage in more mundane adaptation in response to external changes, such as changes in the level or composition of demand. However, little is known about what causes such business model adaptation. We employ threat......-rigidity as well as prospect theory to examine business model adaptation in response to external threats and opportunities. Additionally, drawing on the behavioural theory of the firm, we argue that the past strategic orientation of a firm creates path dependencies that influence the propensity of the firm...... to adapt its business model. We test our hypotheses on a sample of 1196 Norwegian companies, and find that firms are more likely to adapt their business model under conditions of perceived threats than opportunities, and that strategic orientation geared towards market development is more conducive...

  14. Identification of Molecular Fingerprints in Human Heat Pain Thresholds by Use of an Interactive Mixture Model R Toolbox (AdaptGauss).

    Science.gov (United States)

    Ultsch, Alfred; Thrun, Michael C; Hansen-Goos, Onno; Lötsch, Jörn

    2015-10-28

    Biomedical data obtained during cell experiments, laboratory animal research, or human studies often display a complex distribution. Statistical identification of subgroups in research data poses an analytical challenge. Here were introduce an interactive R-based bioinformatics tool, called "AdaptGauss". It enables a valid identification of a biologically-meaningful multimodal structure in the data by fitting a Gaussian mixture model (GMM) to the data. The interface allows a supervised selection of the number of subgroups. This enables the expectation maximization (EM) algorithm to adapt more complex GMM than usually observed with a noninteractive approach. Interactively fitting a GMM to heat pain threshold data acquired from human volunteers revealed a distribution pattern with four Gaussian modes located at temperatures of 32.3, 37.2, 41.4, and 45.4 °C. Noninteractive fitting was unable to identify a meaningful data structure. Obtained results are compatible with known activity temperatures of different TRP ion channels suggesting the mechanistic contribution of different heat sensors to the perception of thermal pain. Thus, sophisticated analysis of the modal structure of biomedical data provides a basis for the mechanistic interpretation of the observations. As it may reflect the involvement of different TRP thermosensory ion channels, the analysis provides a starting point for hypothesis-driven laboratory experiments.

  15. Transport and environmental sustainability: An adapted SPE approach for modelling interactions between transport, infrastructure, economy and environment

    Energy Technology Data Exchange (ETDEWEB)

    Verhoef, Erik; Van den Bergh, Jeroen [Department of Spatial Economics, Faculty of Economics and Econometrics, Free University Amsterdam, Amsterdam (Netherlands)

    1994-05-01

    The present paper aims at shedding some light on the concept of `sustainable transport`. Within the context of a sustainable development, the consequences of interdependencies between transport, infrastructure, economy and environment for the formulation of optimal regulatory policies are investigated. The Spatial Price Equilibrium approach is adapted for the analysis of sustainable spatio-economic development, and for the evaluation of first-best and second-best regulatory policies on the issues at hand. The analysis demonstrates the need for integration of elements concerning economic structure, infrastructure, transportation, environment and space in one single analytical framework when considering questions on sustainability in relation to transport. 2 figs., 1 appendix, 10 refs.

  16. Electronic excitation of molecules in solution calculated using the symmetry-adapted cluster–configuration interaction method in the polarizable continuum model

    International Nuclear Information System (INIS)

    Fukuda, Ryoichi; Ehara, Masahiro

    2015-01-01

    The effects from solvent environment are specific to the electronic states; therefore, a computational scheme for solvent effects consistent with the electronic states is necessary to discuss electronic excitation of molecules in solution. The PCM (polarizable continuum model) SAC (symmetry-adapted cluster) and SAC-CI (configuration interaction) methods are developed for such purposes. The PCM SAC-CI adopts the state-specific (SS) solvation scheme where solvent effects are self-consistently considered for every ground and excited states. For efficient computations of many excited states, we develop a perturbative approximation for the PCM SAC-CI method, which is called corrected linear response (cLR) scheme. Our test calculations show that the cLR PCM SAC-CI is a very good approximation of the SS PCM SAC-CI method for polar and nonpolar solvents

  17. Interactive Dimensioning of Parametric Models

    KAUST Repository

    Kelly, T.

    2015-06-22

    We propose a solution for the dimensioning of parametric and procedural models. Dimensioning has long been a staple of technical drawings, and we present the first solution for interactive dimensioning: A dimension line positioning system that adapts to the view direction, given behavioral properties. After proposing a set of design principles for interactive dimensioning, we describe our solution consisting of the following major components. First, we describe how an author can specify the desired interactive behavior of a dimension line. Second, we propose a novel algorithm to place dimension lines at interactive speeds. Third, we introduce multiple extensions, including chained dimension lines, controls for different parameter types (e.g. discrete choices, angles), and the use of dimension lines for interactive editing. Our results show the use of dimension lines in an interactive parametric modeling environment for architectural, botanical, and mechanical models.

  18. Mapping Haplotype-haplotype Interactions with Adaptive LASSO

    Directory of Open Access Journals (Sweden)

    Li Ming

    2010-08-01

    Full Text Available Abstract Background The genetic etiology of complex diseases in human has been commonly viewed as a complex process involving both genetic and environmental factors functioning in a complicated manner. Quite often the interactions among genetic variants play major roles in determining the susceptibility of an individual to a particular disease. Statistical methods for modeling interactions underlying complex diseases between single genetic variants (e.g. single nucleotide polymorphisms or SNPs have been extensively studied. Recently, haplotype-based analysis has gained its popularity among genetic association studies. When multiple sequence or haplotype interactions are involved in determining an individual's susceptibility to a disease, it presents daunting challenges in statistical modeling and testing of the interaction effects, largely due to the complicated higher order epistatic complexity. Results In this article, we propose a new strategy in modeling haplotype-haplotype interactions under the penalized logistic regression framework with adaptive L1-penalty. We consider interactions of sequence variants between haplotype blocks. The adaptive L1-penalty allows simultaneous effect estimation and variable selection in a single model. We propose a new parameter estimation method which estimates and selects parameters by the modified Gauss-Seidel method nested within the EM algorithm. Simulation studies show that it has low false positive rate and reasonable power in detecting haplotype interactions. The method is applied to test haplotype interactions involved in mother and offspring genome in a small for gestational age (SGA neonates data set, and significant interactions between different genomes are detected. Conclusions As demonstrated by the simulation studies and real data analysis, the approach developed provides an efficient tool for the modeling and testing of haplotype interactions. The implementation of the method in R codes can be

  19. Model of aircraft noise adaptation

    Science.gov (United States)

    Dempsey, T. K.; Coates, G. D.; Cawthorn, J. M.

    1977-01-01

    Development of an aircraft noise adaptation model, which would account for much of the variability in the responses of subjects participating in human response to noise experiments, was studied. A description of the model development is presented. The principal concept of the model, was the determination of an aircraft adaptation level which represents an annoyance calibration for each individual. Results showed a direct correlation between noise level of the stimuli and annoyance reactions. Attitude-personality variables were found to account for varying annoyance judgements.

  20. Hybrid Adaptive Flight Control with Model Inversion Adaptation

    Science.gov (United States)

    Nguyen, Nhan

    2011-01-01

    This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

  1. Adaptive-network models of collective dynamics

    Science.gov (United States)

    Zschaler, G.

    2012-09-01

    Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge

  2. Interactive indirect illumination using adaptive multiresolution splatting.

    Science.gov (United States)

    Nichols, Greg; Wyman, Chris

    2010-01-01

    Global illumination provides a visual richness not achievable with the direct illumination models used by most interactive applications. To generate global effects, numerous approximations attempt to reduce global illumination costs to levels feasible in interactive contexts. One such approximation, reflective shadow maps, samples a shadow map to identify secondary light sources whose contributions are splatted into eye space. This splatting introduces significant overdraw that is usually reduced by artificially shrinking each splat's radius of influence. This paper introduces a new multiresolution approach for interactively splatting indirect illumination. Instead of reducing GPU fill rate by reducing splat size, we reduce fill rate by rendering splats into a multiresolution buffer. This takes advantage of the low-frequency nature of diffuse and glossy indirect lighting, allowing rendering of indirect contributions at low resolution where lighting changes slowly and at high-resolution near discontinuities. Because this multiresolution rendering occurs on a per-splat basis, we can significantly reduce fill rate without arbitrarily clipping splat contributions below a given threshold-those regions simply are rendered at a coarse resolution.

  3. Modeling adaptive and non-adaptive responses to environmental change

    DEFF Research Database (Denmark)

    Coulson, Tim; Kendall, Bruce E; Barthold, Julia A.

    2017-01-01

    , with plastic responses being either adaptive or non-adaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we...... construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses, and that the rate of adaptive evolution to a new environment depends upon whether plastic responses are adaptive or non-adaptive....... Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full...

  4. Interactive Teaching of Adaptive Signal Processing

    OpenAIRE

    Stewart, R W; Harteneck, M; Weiss, S

    2000-01-01

    Over the last 30 years adaptive digital signal processing has progressed from being a strictly graduate level advanced class in signal processing theory to a topic that is part of the core curriculum for many undergraduate signal processing classes. The key reason is the continued advance of communications technology, with its need for echo control and equalisation, and the widespread use of adaptive filters in audio, biomedical, and control applications. In this paper we will review the basi...

  5. Model Checking Feature Interactions

    DEFF Research Database (Denmark)

    Le Guilly, Thibaut; Olsen, Petur; Pedersen, Thomas

    2015-01-01

    This paper presents an offline approach to analyzing feature interactions in embedded systems. The approach consists of a systematic process to gather the necessary information about system components and their models. The model is first specified in terms of predicates, before being refined to t...... to timed automata. The consistency of the model is verified at different development stages, and the correct linkage between the predicates and their semantic model is checked. The approach is illustrated on a use case from home automation....

  6. Predictor-Based Model Reference Adaptive Control

    Science.gov (United States)

    Lavretsky, Eugene; Gadient, Ross; Gregory, Irene M.

    2010-01-01

    This paper is devoted to the design and analysis of a predictor-based model reference adaptive control. Stable adaptive laws are derived using Lyapunov framework. The proposed architecture is compared with the now classical model reference adaptive control. A simulation example is presented in which numerical evidence indicates that the proposed controller yields improved transient characteristics.

  7. The joy of interactive modeling

    Science.gov (United States)

    Donchyts, Gennadii; Baart, Fedor; van Dam, Arthur; Jagers, Bert

    2013-04-01

    The conventional way of working with hydrodynamical models usually consists of the following steps: 1) define a schematization (e.g., in a graphical user interface, or by editing input files) 2) run model from start to end 3) visualize results 4) repeat any of the previous steps. This cycle commonly takes up from hours to several days. What if we can make this happen instantly? As most of the research done using numerical models is in fact qualitative and exploratory (Oreskes et al., 1994), why not use these models as such? How can we adapt models so that we can edit model input, run and visualize results at the same time? More and more, interactive models become available as online apps, mainly for demonstration and educational purposes. These models often simplify the physics behind flows and run on simplified model geometries, particularly when compared with state-of-the-art scientific simulation packages. Here we show how the aforementioned conventional standalone models ("static, run once") can be transformed into interactive models. The basic concepts behind turning existing (conventional) model engines into interactive engines are the following. The engine does not run the model from start to end, but is always available in memory, and can be fed by new boundary conditions, or state changes at any time. The model can be run continuously, per step, or up to a specified time. The Hollywood principle dictates how the model engine is instructed from 'outside', instead of the model engine taking all necessary actions on its own initiative. The underlying techniques that facilitate these concepts are introspection of the computation engine, which exposes its state variables, and control functions, e.g. for time stepping, via a standardized interface, such as BMI (Peckam et. al., 2012). In this work we have used a shallow water flow model engine D-Flow Flexible Mesh. The model was converted from executable to a library, and coupled to the graphical modelling

  8. User interaction with user-adaptive information filters

    NARCIS (Netherlands)

    Cramer, H.S.M.; Evers, V.; Someren, van M.W.; Wielinga, B.J.; Besselink, S.; Rutledge, L.W.; Stash, N.; Aroyo, L.M.; Aykin, N.M.

    2007-01-01

    User-adaptive information filters can be a tool to achieve timely delivery of the right information to the right person, a feat critical in crisis management. This paper explores interaction issues that need to be taken into account when designing a user-adaptive information filter. Two case studies

  9. User Interaction with User-Adaptive Information Filters

    NARCIS (Netherlands)

    H. Cramer; V. Evers; M. van Someren; B. Wielinga; S. Besselink; L. Rutledge (Lloyd); N. Stash; L. Aroyo (Lora)

    2007-01-01

    htmlabstractUser-adaptive information filters can be a tool to achieve timely delivery of the right information to the right person, a feat critical in crisis management. This paper explores interaction issues that need to be taken into account when designing a user-adaptive information filter. Two

  10. Immigrants' Adaptation and Interracial/Interethnic Interactions in Natural Environments

    NARCIS (Netherlands)

    Stodolska, Monika; Peters, K.B.M.; Horolets, Anna

    2017-01-01

    This study examined the role of leisure in natural environments in immigrants' adaptation, with a particular emphasis on facilitating interracial/interethnic interactions. Berry's adaptation framework was used as a theoretical framework. The project used in-depth individual interviews with 70

  11. The interacting boson model

    International Nuclear Information System (INIS)

    Iachello, F.; Arima, A.

    1987-01-01

    The book gives an account of some of the properties of the interacting boson model. The model was introduced in 1974 to describe in a unified way the collective properties of nuclei. The book presents the mathematical techniques used to analyse the structure of the model. The mathematical framework of the model is discussed in detail. The book also contains all the formulae that have been developed throughout the years to account for collective properties of nuclei. These formulae can be used by experimentalists to compare their data with the predictions of the model. (U.K.)

  12. A systematic approach for the accurate non-invasive estimation of blood glucose utilizing a novel light-tissue interaction adaptive modelling scheme

    Energy Technology Data Exchange (ETDEWEB)

    Rybynok, V O; Kyriacou, P A [City University, London (United Kingdom)

    2007-10-15

    Diabetes is one of the biggest health challenges of the 21st century. The obesity epidemic, sedentary lifestyles and an ageing population mean prevalence of the condition is currently doubling every generation. Diabetes is associated with serious chronic ill health, disability and premature mortality. Long-term complications including heart disease, stroke, blindness, kidney disease and amputations, make the greatest contribution to the costs of diabetes care. Many of these long-term effects could be avoided with earlier, more effective monitoring and treatment. Currently, blood glucose can only be monitored through the use of invasive techniques. To date there is no widely accepted and readily available non-invasive monitoring technique to measure blood glucose despite the many attempts. This paper challenges one of the most difficult non-invasive monitoring techniques, that of blood glucose, and proposes a new novel approach that will enable the accurate, and calibration free estimation of glucose concentration in blood. This approach is based on spectroscopic techniques and a new adaptive modelling scheme. The theoretical implementation and the effectiveness of the adaptive modelling scheme for this application has been described and a detailed mathematical evaluation has been employed to prove that such a scheme has the capability of extracting accurately the concentration of glucose from a complex biological media.

  13. A systematic approach for the accurate non-invasive estimation of blood glucose utilizing a novel light-tissue interaction adaptive modelling scheme

    Science.gov (United States)

    Rybynok, V. O.; Kyriacou, P. A.

    2007-10-01

    Diabetes is one of the biggest health challenges of the 21st century. The obesity epidemic, sedentary lifestyles and an ageing population mean prevalence of the condition is currently doubling every generation. Diabetes is associated with serious chronic ill health, disability and premature mortality. Long-term complications including heart disease, stroke, blindness, kidney disease and amputations, make the greatest contribution to the costs of diabetes care. Many of these long-term effects could be avoided with earlier, more effective monitoring and treatment. Currently, blood glucose can only be monitored through the use of invasive techniques. To date there is no widely accepted and readily available non-invasive monitoring technique to measure blood glucose despite the many attempts. This paper challenges one of the most difficult non-invasive monitoring techniques, that of blood glucose, and proposes a new novel approach that will enable the accurate, and calibration free estimation of glucose concentration in blood. This approach is based on spectroscopic techniques and a new adaptive modelling scheme. The theoretical implementation and the effectiveness of the adaptive modelling scheme for this application has been described and a detailed mathematical evaluation has been employed to prove that such a scheme has the capability of extracting accurately the concentration of glucose from a complex biological media.

  14. A systematic approach for the accurate non-invasive estimation of blood glucose utilizing a novel light-tissue interaction adaptive modelling scheme

    International Nuclear Information System (INIS)

    Rybynok, V O; Kyriacou, P A

    2007-01-01

    Diabetes is one of the biggest health challenges of the 21st century. The obesity epidemic, sedentary lifestyles and an ageing population mean prevalence of the condition is currently doubling every generation. Diabetes is associated with serious chronic ill health, disability and premature mortality. Long-term complications including heart disease, stroke, blindness, kidney disease and amputations, make the greatest contribution to the costs of diabetes care. Many of these long-term effects could be avoided with earlier, more effective monitoring and treatment. Currently, blood glucose can only be monitored through the use of invasive techniques. To date there is no widely accepted and readily available non-invasive monitoring technique to measure blood glucose despite the many attempts. This paper challenges one of the most difficult non-invasive monitoring techniques, that of blood glucose, and proposes a new novel approach that will enable the accurate, and calibration free estimation of glucose concentration in blood. This approach is based on spectroscopic techniques and a new adaptive modelling scheme. The theoretical implementation and the effectiveness of the adaptive modelling scheme for this application has been described and a detailed mathematical evaluation has been employed to prove that such a scheme has the capability of extracting accurately the concentration of glucose from a complex biological media

  15. Designing Networked Adaptive Interactive Hybrid Systems

    NARCIS (Netherlands)

    Kester, L.J.H.M.

    2008-01-01

    Advances in network technologies enable distributed systems, operating in complex physical environments, to coordinate their activities over larger areas within shorter time intervals. In these systems humans and intelligent machines will, in close interaction, be able to reach their goals under

  16. The Roy Adaptation Model and Content Analysis

    OpenAIRE

    Fawcett, Jacqueline

    2006-01-01

    The purpose of this paper is to explain how the Roy Adaptation Model can be used to guide a combined qualitative and quantitative content analysis of responses to open-ended interviews questions. Responses can be categorized as adaptive or ineffective within the physiological, self-concept, role function, and interdependence modes of adaptation and then tallied to yield an adaptation score. El objetivo del presente estudio consiste en explicar de qué manera se puede utilizar el Modelo de A...

  17. Defining adaptation in a generic multi layer model: CAM: The GRAPPLE Conceptual Adaptation Model

    NARCIS (Netherlands)

    Hendrix, M.; De Bra, P.M.E.; Pechenizkiy, M.; Smits, D.; Cristea, A.I.; Dillenbourg, P.; Specht, M.

    2008-01-01

    Authoring of Adaptive Hypermedia is a difficult and time consuming task. Reference models like LAOS and AHAM separate adaptation and content in different layers. Systems like AHA!, offer graphical tools based on these models to allow authors to define adaptation without knowing any adaptation

  18. Interactive Dimensioning of Parametric Models

    KAUST Repository

    Kelly, T.; Wonka, Peter; Mueller, P.

    2015-01-01

    that adapts to the view direction, given behavioral properties. After proposing a set of design principles for interactive dimensioning, we describe our solution consisting of the following major components. First, we describe how an author can specify

  19. Smart swarms of bacteria-inspired agents with performance adaptable interactions.

    Directory of Open Access Journals (Sweden)

    Adi Shklarsh

    2011-09-01

    Full Text Available Collective navigation and swarming have been studied in animal groups, such as fish schools, bird flocks, bacteria, and slime molds. Computer modeling has shown that collective behavior of simple agents can result from simple interactions between the agents, which include short range repulsion, intermediate range alignment, and long range attraction. Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment--by decreasing the peers' influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots.

  20. Smart swarms of bacteria-inspired agents with performance adaptable interactions.

    Science.gov (United States)

    Shklarsh, Adi; Ariel, Gil; Schneidman, Elad; Ben-Jacob, Eshel

    2011-09-01

    Collective navigation and swarming have been studied in animal groups, such as fish schools, bird flocks, bacteria, and slime molds. Computer modeling has shown that collective behavior of simple agents can result from simple interactions between the agents, which include short range repulsion, intermediate range alignment, and long range attraction. Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment--by decreasing the peers' influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots.

  1. An Adaptive Critic Approach to Reference Model Adaptation

    Science.gov (United States)

    Krishnakumar, K.; Limes, G.; Gundy-Burlet, K.; Bryant, D.

    2003-01-01

    Neural networks have been successfully used for implementing control architectures for different applications. In this work, we examine a neural network augmented adaptive critic as a Level 2 intelligent controller for a C- 17 aircraft. This intelligent control architecture utilizes an adaptive critic to tune the parameters of a reference model, which is then used to define the angular rate command for a Level 1 intelligent controller. The present architecture is implemented on a high-fidelity non-linear model of a C-17 aircraft. The goal of this research is to improve the performance of the C-17 under degraded conditions such as control failures and battle damage. Pilot ratings using a motion based simulation facility are included in this paper. The benefits of using an adaptive critic are documented using time response comparisons for severe damage situations.

  2. Improved Transient Performance of a Fuzzy Modified Model Reference Adaptive Controller for an Interacting Coupled Tank System Using Real-Coded Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Asan Mohideen Khansadurai

    2014-01-01

    Full Text Available The main objective of the paper is to design a model reference adaptive controller (MRAC with improved transient performance. A modification to the standard direct MRAC called fuzzy modified MRAC (FMRAC is used in the paper. The FMRAC uses a proportional control based Mamdani-type fuzzy logic controller (MFLC to improve the transient performance of a direct MRAC. The paper proposes the application of real-coded genetic algorithm (RGA to tune the membership function parameters of the proposed FMRAC offline so that the transient performance of the FMRAC is improved further. In this study, a GA based modified MRAC (GAMMRAC, an FMRAC, and a GA based FMRAC (GAFMRAC are designed for a coupled tank setup in a hybrid tank process and their transient performances are compared. The results show that the proposed GAFMRAC gives a better transient performance than the GAMMRAC or the FMRAC. It is concluded that the proposed controller can be used to obtain very good transient performance for the control of nonlinear processes.

  3. Qualitative Analysis of Integration Adapter Modeling

    OpenAIRE

    Ritter, Daniel; Holzleitner, Manuel

    2015-01-01

    Integration Adapters are a fundamental part of an integration system, since they provide (business) applications access to its messaging channel. However, their modeling and configuration remain under-represented. In previous work, the integration control and data flow syntax and semantics have been expressed in the Business Process Model and Notation (BPMN) as a semantic model for message-based integration, while adapter and the related quality of service modeling were left for further studi...

  4. A diversified portfolio model of adaptability.

    Science.gov (United States)

    Chandra, Siddharth; Leong, Frederick T L

    2016-12-01

    A new model of adaptability, the diversified portfolio model (DPM) of adaptability, is introduced. In the 1950s, Markowitz developed the financial portfolio model by demonstrating that investors could optimize the ratio of risk and return on their portfolios through risk diversification. The DPM integrates attractive features of a variety of models of adaptability, including Linville's self-complexity model, the risk and resilience model, and Bandura's social cognitive theory. The DPM draws on the concept of portfolio diversification, positing that diversified investment in multiple life experiences, life roles, and relationships promotes positive adaptation to life's challenges. The DPM provides a new integrative model of adaptability across the biopsychosocial levels of functioning. More importantly, the DPM addresses a gap in the literature by illuminating the antecedents of adaptive processes studied in a broad array of psychological models. The DPM is described in relation to the biopsychosocial model and propositions are offered regarding its utility in increasing adaptiveness. Recommendations for future research are also offered. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  5. Mathematical models for plant-herbivore interactions

    Science.gov (United States)

    Feng, Zhilan; DeAngelis, Donald L.

    2017-01-01

    Mathematical Models of Plant-Herbivore Interactions addresses mathematical models in the study of practical questions in ecology, particularly factors that affect herbivory, including plant defense, herbivore natural enemies, and adaptive herbivory, as well as the effects of these on plant community dynamics. The result of extensive research on the use of mathematical modeling to investigate the effects of plant defenses on plant-herbivore dynamics, this book describes a toxin-determined functional response model (TDFRM) that helps explains field observations of these interactions. This book is intended for graduate students and researchers interested in mathematical biology and ecology.

  6. Unobtrusive user modeling for adaptive hypermedia

    NARCIS (Netherlands)

    Holz, H.J.; Hofmann, K.; Reed, C.; Uchyigit, G.; Ma, M.Y.

    2008-01-01

    We propose a technique for user modeling in Adaptive Hypermedia (AH) that is unobtrusive at both the level of observable behavior and that of cognition. Unobtrusive user modeling is complementary to transparent user modeling. Unobtrusive user modeling induces user models appropriate for Educational

  7. Effect of vergence adaptation on convergence-accommodation: model simulations.

    Science.gov (United States)

    Sreenivasan, Vidhyapriya; Bobier, William R; Irving, Elizabeth L; Lakshminarayanan, Vasudevan

    2009-10-01

    Several theoretical control models depict the adaptation effects observed in the accommodation and vergence mechanisms of the human visual system. Two current quantitative models differ in their approach of defining adaptation and in identifying the effect of controller adaptation on their respective cross-links between the vergence and accommodative systems. Here, we compare the simulation results of these adaptation models with empirical data obtained from emmetropic adults when they performed sustained near task through + 2D lens addition. The results of our experimental study showed an initial increase in exophoria (a divergent open-loop vergence position) and convergence-accommodation (CA) when viewing through +2D lenses. Prolonged fixation through the near addition lenses initiated vergence adaptation, which reduced the lens-induced exophoria and resulted in a concurrent reduction of CA. Both models showed good agreement with empirical measures of vergence adaptation. However, only one model predicted the experimental time course of reduction in CA. The pattern of our empirical results seem to be best described by the adaptation model that indicates the total vergence response to be a sum of two controllers, phasic and tonic, with the output of phasic controller providing input to the cross-link interactions.

  8. Estimating the effect of the reorganization of interactions on the adaptability of species to changing environments.

    Science.gov (United States)

    Cenci, Simone; Montero-Castaño, Ana; Saavedra, Serguei

    2018-01-21

    A major challenge in community ecology is to understand how species respond to environmental changes. Previous studies have shown that the reorganization of interactions among co-occurring species can modulate their chances to adapt to novel environmental conditions. Moreover, empirical evidence has shown that these ecological dynamics typically facilitate the persistence of groups of species rather than entire communities. However, so far, we have no systematic methodology to identify those groups of species with the highest or lowest chances to adapt to new environments through a reorganization of their interactions. Yet, this could prove extremely valuable for developing new conservation strategies. Here, we introduce a theoretical framework to estimate the effect of the reorganization of interactions on the adaptability of a group of species, within a community, to novel environmental conditions. We introduce the concept of the adaptation space of a group of species based on a feasibility analysis of a population dynamics model. We define the adaptation space of a group as the set of environmental conditions that can be made compatible with its persistence thorough the reorganization of interactions among species within the group. The larger the adaptation space of a group, the larger its likelihood to adapt to a novel environment. We show that the interactions in the community outside a group can act as structural constraints and be used to quantitatively compare the size of the adaptation space among different groups of species within a community. To test our theoretical framework, we perform a data analysis on several pairs of natural and artificially perturbed ecological communities. Overall, we find that the groups of species present in both control and perturbed communities are among the ones with the largest adaptation space. We believe that the results derived from our framework point out towards new directions to understand and estimate the

  9. Automated adaptive inference of phenomenological dynamical models

    Science.gov (United States)

    Daniels, Bryan

    Understanding the dynamics of biochemical systems can seem impossibly complicated at the microscopic level: detailed properties of every molecular species, including those that have not yet been discovered, could be important for producing macroscopic behavior. The profusion of data in this area has raised the hope that microscopic dynamics might be recovered in an automated search over possible models, yet the combinatorial growth of this space has limited these techniques to systems that contain only a few interacting species. We take a different approach inspired by coarse-grained, phenomenological models in physics. Akin to a Taylor series producing Hooke's Law, forgoing microscopic accuracy allows us to constrain the search over dynamical models to a single dimension. This makes it feasible to infer dynamics with very limited data, including cases in which important dynamical variables are unobserved. We name our method Sir Isaac after its ability to infer the dynamical structure of the law of gravitation given simulated planetary motion data. Applying the method to output from a microscopically complicated but macroscopically simple biological signaling model, it is able to adapt the level of detail to the amount of available data. Finally, using nematode behavioral time series data, the method discovers an effective switch between behavioral attractors after the application of a painful stimulus.

  10. A New Mobile Learning Adaptation Model

    OpenAIRE

    Mohamd Hassan Hassan; Jehad Al-Sadi

    2009-01-01

    This paper introduces a new model for m- Learning context adaptation due to the need of utilizing mobile technology in education. Mobile learning; m-Learning for short; in considered to be one of the hottest topics in the educational community, many researches had been done to conceptualize this new form of learning. We are presenting a promising design for a model to adapt the learning content in mobile learning applications in order to match the learner context, preferences and the educatio...

  11. Adaptive Inference on General Graphical Models

    OpenAIRE

    Acar, Umut A.; Ihler, Alexander T.; Mettu, Ramgopal; Sumer, Ozgur

    2012-01-01

    Many algorithms and applications involve repeatedly solving variations of the same inference problem; for example we may want to introduce new evidence to the model or perform updates to conditional dependencies. The goal of adaptive inference is to take advantage of what is preserved in the model and perform inference more rapidly than from scratch. In this paper, we describe techniques for adaptive inference on general graphs that support marginal computation and updates to the conditional ...

  12. Organizational Adaptative Behavior: The Complex Perspective of Individuals-Tasks Interaction

    Science.gov (United States)

    Wu, Jiang; Sun, Duoyong; Hu, Bin; Zhang, Yu

    Organizations with different organizational structures have different organizational behaviors when responding environmental changes. In this paper, we use a computational model to examine organizational adaptation on four dimensions: Agility, Robustness, Resilience, and Survivability. We analyze the dynamics of organizational adaptation by a simulation study from a complex perspective of the interaction between tasks and individuals in a sales enterprise. The simulation studies in different scenarios show that more flexible communication between employees and less hierarchy level with the suitable centralization can improve organizational adaptation.

  13. Unstructured mesh adaptivity for urban flooding modelling

    Science.gov (United States)

    Hu, R.; Fang, F.; Salinas, P.; Pain, C. C.

    2018-05-01

    Over the past few decades, urban floods have been gaining more attention due to their increase in frequency. To provide reliable flooding predictions in urban areas, various numerical models have been developed to perform high-resolution flood simulations. However, the use of high-resolution meshes across the whole computational domain causes a high computational burden. In this paper, a 2D control-volume and finite-element flood model using adaptive unstructured mesh technology has been developed. This adaptive unstructured mesh technique enables meshes to be adapted optimally in time and space in response to the evolving flow features, thus providing sufficient mesh resolution where and when it is required. It has the advantage of capturing the details of local flows and wetting and drying front while reducing the computational cost. Complex topographic features are represented accurately during the flooding process. For example, the high-resolution meshes around the buildings and steep regions are placed when the flooding water reaches these regions. In this work a flooding event that happened in 2002 in Glasgow, Scotland, United Kingdom has been simulated to demonstrate the capability of the adaptive unstructured mesh flooding model. The simulations have been performed using both fixed and adaptive unstructured meshes, and then results have been compared with those published 2D and 3D results. The presented method shows that the 2D adaptive mesh model provides accurate results while having a low computational cost.

  14. Monitoring and evaluating citizen-agency interactions: a framework developed for adaptive management.

    Science.gov (United States)

    Bruce Shindler; Kristin Aldred Cheek; George H. Stankey

    1999-01-01

    As the Forest Service and the Bureau of Land Management turn toward ecosystem and adaptive models of forest stewardship, they are being called on to develop meaningful and lasting relations with citizens. These new management styles require not only improved strategies for public involvement but also methods to examine the interactions between citizens and agencies in...

  15. Theoretical model for ultracold molecule formation via adaptive feedback control

    OpenAIRE

    Poschinger, Ulrich; Salzmann, Wenzel; Wester, Roland; Weidemueller, Matthias; Koch, Christiane P.; Kosloff, Ronnie

    2006-01-01

    We investigate pump-dump photoassociation of ultracold molecules with amplitude- and phase-modulated femtosecond laser pulses. For this purpose a perturbative model for the light-matter interaction is developed and combined with a genetic algorithm for adaptive feedback control of the laser pulse shapes. The model is applied to the formation of 85Rb2 molecules in a magneto-optical trap. We find for optimized pulse shapes an improvement for the formation of ground state molecules by more than ...

  16. Adaptive Partially Hidden Markov Models

    DEFF Research Database (Denmark)

    Forchhammer, Søren Otto; Rasmussen, Tage

    1996-01-01

    Partially Hidden Markov Models (PHMM) have recently been introduced. The transition and emission probabilities are conditioned on the past. In this report, the PHMM is extended with a multiple token version. The different versions of the PHMM are applied to bi-level image coding....

  17. Model analysis of adaptive car driving behavior

    NARCIS (Netherlands)

    Wewerinke, P.H.

    1996-01-01

    This paper deals with two modeling approaches to car driving. The first one is a system theoretic approach to describe adaptive human driving behavior. The second approach utilizes neural networks. As an illustrative example the overtaking task is considered and modeled in system theoretic terms.

  18. An adaptive stochastic model for financial markets

    International Nuclear Information System (INIS)

    Hernández, Juan Antonio; Benito, Rosa Marı´a; Losada, Juan Carlos

    2012-01-01

    An adaptive stochastic model is introduced to simulate the behavior of real asset markets. The model adapts itself by changing its parameters automatically on the basis of the recent historical data. The basic idea underlying the model is that a random variable uniformly distributed within an interval with variable extremes can replicate the histograms of asset returns. These extremes are calculated according to the arrival of new market information. This adaptive model is applied to the daily returns of three well-known indices: Ibex35, Dow Jones and Nikkei, for three complete years. The model reproduces the histograms of the studied indices as well as their autocorrelation structures. It produces the same fat tails and the same power laws, with exactly the same exponents, as in the real indices. In addition, the model shows a great adaptation capability, anticipating the volatility evolution and showing the same volatility clusters observed in the assets. This approach provides a novel way to model asset markets with internal dynamics which changes quickly with time, making it impossible to define a fixed model to fit the empirical observations.

  19. Model reference adaptive control and adaptive stability augmentation

    DEFF Research Database (Denmark)

    Henningsen, Arne; Ravn, Ole

    1993-01-01

    A comparison of the standard concepts in MRAC design suggests that a combination of the implicit and the explicit design techniques may lead to an improvement of the overall system performance in the presence of unmodelled dynamics. Using the ideas of adaptive stability augmentation a combined...... stability augmented model reference design is proposed. By utilizing the closed-loop control error, a simple auxiliary controller is tuned, using a normalized MIT rule for the parameter adjustment. The MIT adjustment is protected against the effects of unmodelled dynamics by lowpass filtering...... of the gradient. The proposed method is verified through simulation results indicating that the method may lead to an improvement of the model reference controller in the presence of unmodelled dynamics...

  20. Switching Adaptability in Human-Inspired Sidesteps: A Minimal Model.

    Science.gov (United States)

    Fujii, Keisuke; Yoshihara, Yuki; Tanabe, Hiroko; Yamamoto, Yuji

    2017-01-01

    Humans can adapt to abruptly changing situations by coordinating redundant components, even in bipedality. Conventional adaptability has been reproduced by various computational approaches, such as optimal control, neural oscillator, and reinforcement learning; however, the adaptability in bipedal locomotion necessary for biological and social activities, such as unpredicted direction change in chase-and-escape, is unknown due to the dynamically unstable multi-link closed-loop system. Here we propose a switching adaptation model for performing bipedal locomotion by improving autonomous distributed control, where autonomous actuators interact without central control and switch the roles for propulsion, balancing, and leg swing. Our switching mobility model achieved direction change at any time using only three actuators, although it showed higher motor costs than comparable models without direction change. Our method of evaluating such adaptation at any time should be utilized as a prerequisite for understanding universal motor control. The proposed algorithm may simply explain and predict the adaptation mechanism in human bipedality to coordinate the actuator functions within and between limbs.

  1. Multiple model adaptive control with mixing

    Science.gov (United States)

    Kuipers, Matthew

    Despite the remarkable theoretical accomplishments and successful applications of adaptive control, the field is not sufficiently mature to solve challenging control problems requiring strict performance and safety guarantees. Towards addressing these issues, a novel deterministic multiple-model adaptive control approach called adaptive mixing control is proposed. In this approach, adaptation comes from a high-level system called the supervisor that mixes into feedback a number of candidate controllers, each finely-tuned to a subset of the parameter space. The mixing signal, the supervisor's output, is generated by estimating the unknown parameters and, at every instant of time, calculating the contribution level of each candidate controller based on certainty equivalence. The proposed architecture provides two characteristics relevant to solving stringent, performance-driven applications. First, the full-suite of linear time invariant control tools is available. A disadvantage of conventional adaptive control is its restriction to utilizing only those control laws whose solutions can be feasibly computed in real-time, such as model reference and pole-placement type controllers. Because its candidate controllers are computed off line, the proposed approach suffers no such restriction. Second, the supervisor's output is smooth and does not necessarily depend on explicit a priori knowledge of the disturbance model. These characteristics can lead to improved performance by avoiding the unnecessary switching and chattering behaviors associated with some other multiple adaptive control approaches. The stability and robustness properties of the adaptive scheme are analyzed. It is shown that the mean-square regulation error is of the order of the modeling error. And when the parameter estimate converges to its true value, which is guaranteed if a persistence of excitation condition is satisfied, the adaptive closed-loop system converges exponentially fast to a closed

  2. Intelligent adaptive systems an interaction-centered design perspective

    CERN Document Server

    Hou, Ming; Burns, Catherine

    2014-01-01

    A synthesis of recent research and developments on intelligent adaptive systems from the HF (human factors) and HCI (human-computer interaction) domains, this book provides integrated design guidance and recommendations for researchers and system developers. It addresses a recognized lack of integration between the HF and HCI research communities, which has led to inconsistencies between the research approaches adopted, and a lack of exploitation of research from one field by the other. The book establishes design guidance through the review of conceptual frameworks, analytical methodologies,

  3. Adaptive regression for modeling nonlinear relationships

    CERN Document Server

    Knafl, George J

    2016-01-01

    This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models for different types of outcome variables. Such nonlinear dependence is often not considered in applied research, yet nonlinear relationships are common and so need to be addressed. A standard linear analysis can produce misleading conclusions, while a nonlinear analysis can provide novel insights into data, not otherwise possible. A variety of examples of the benefits of modeling nonlinear relationships are presented throughout the book. Methods are covered using what are called fractional polynomials based on real-valued power transformations of primary predictor variables combined with model selection based on likelihood cross-validation. The book covers how to formulate and conduct such adaptive fractional polynomial modeling in the s...

  4. An explanatory model of underwater adaptation

    Directory of Open Access Journals (Sweden)

    Joaquín Colodro

    Full Text Available The underwater environment is an extreme environment that requires a process of human adaptation with specific psychophysiological demands to ensure survival and productive activity. From the standpoint of existing models of intelligence, personality and performance, in this explanatory study we have analyzed the contribution of individual differences in explaining the adaptation of military personnel in a stressful environment. Structural equation analysis was employed to verify a model representing the direct effects of psychological variables on individual adaptation to an adverse environment, and we have been able to confirm, during basic military diving courses, the structural relationships among these variables and their ability to predict a third of the variance of a criterion that has been studied very little to date. In this way, we have confirmed in a sample of professionals (N = 575 the direct relationship of emotional adjustment, conscientiousness and general mental ability with underwater adaptation, as well as the inverse relationship of emotional reactivity. These constructs are the psychological basis for working under water, contributing to an improved adaptation to this environment and promoting risk prevention and safety in diving activities.

  5. Inference in models with adaptive learning

    NARCIS (Netherlands)

    Chevillon, G.; Massmann, M.; Mavroeidis, S.

    2010-01-01

    Identification of structural parameters in models with adaptive learning can be weak, causing standard inference procedures to become unreliable. Learning also induces persistent dynamics, and this makes the distribution of estimators and test statistics non-standard. Valid inference can be

  6. Models of behavioral change and adaptation

    NARCIS (Netherlands)

    Rasouli, S.; Timmermans, H.J.P.; Zhang, J.

    2017-01-01

    This chapter explains and summarizes models of behavioral change and adaptation, which have received less application in the life choice analysis associated with urban policy. Related to various life choices, life trajectory events are major decisions with a relatively long-lasting impact, such as

  7. A model for optimal constrained adaptive testing

    NARCIS (Netherlands)

    van der Linden, Willem J.; Reese, Lynda M.

    2001-01-01

    A model for constrained computerized adaptive testing is proposed in which the information on the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum

  8. A model for optimal constrained adaptive testing

    NARCIS (Netherlands)

    van der Linden, Willem J.; Reese, Lynda M.

    1997-01-01

    A model for constrained computerized adaptive testing is proposed in which the information in the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum

  9. Modeling and (adaptive) control of greenhouse climates

    NARCIS (Netherlands)

    Udink ten Cate, A.J.

    1983-01-01

    The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.

    System concepts

    In Chapters 1 and 2 an overview of the problem formulation

  10. Strong interactions - quark models

    International Nuclear Information System (INIS)

    Goto, M.; Ferreira, P.L.

    1979-01-01

    The variational method is used for the PSI and upsilon family spectra reproduction from the quark model, through several phenomenological potentials, viz.: linear, linear plus coulomb term and logarithmic. (L.C.) [pt

  11. Adaptive numerical modeling of dynamic crack propagation

    International Nuclear Information System (INIS)

    Adouani, H.; Tie, B.; Berdin, C.; Aubry, D.

    2006-01-01

    We propose an adaptive numerical strategy that aims at developing reliable and efficient numerical tools to model dynamic crack propagation and crack arrest. We use the cohesive zone theory as behavior of interface-type elements to model crack. Since the crack path is generally unknown beforehand, adaptive meshing is proposed to model the dynamic crack propagation. The dynamic study requires the development of specific solvers for time integration. As both geometry and finite element mesh of the studied structure evolve in time during transient analysis, the stability behavior of dynamic solver becomes a major concern. For this purpose, we use the space-time discontinuous Galerkin finite element method, well-known to provide a natural framework to manage meshes that evolve in time. As an important result, we prove that the space-time discontinuous Galerkin solver is unconditionally stable, when the dynamic crack propagation is modeled by the cohesive zone theory, which is highly non-linear. (authors)

  12. Adaptive Behaviour Assessment System: Indigenous Australian Adaptation Model (ABAS: IAAM)

    Science.gov (United States)

    du Plessis, Santie

    2015-01-01

    The study objectives were to develop, trial and evaluate a cross-cultural adaptation of the Adaptive Behavior Assessment System-Second Edition Teacher Form (ABAS-II TF) ages 5-21 for use with Indigenous Australian students ages 5-14. This study introduced a multiphase mixed-method design with semi-structured and informal interviews, school…

  13. Core monitoring with analytical model adaption

    International Nuclear Information System (INIS)

    Linford, R.B.; Martin, C.L.; Parkos, G.R.; Rahnema, F.; Williams, R.D.

    1992-01-01

    The monitoring of BWR cores has evolved rapidly due to more capable computer systems, improved analytical models and new types of core instrumentation. Coupling of first principles diffusion theory models such as applied to design to the core instrumentation has been achieved by GE with an adaptive methodology in the 3D Minicore system. The adaptive methods allow definition of 'leakage parameters' which are incorporated directly into the diffusion models to enhance monitoring accuracy and predictions. These improved models for core monitoring allow for substitution of traversing in-core probe (TIP) and local power range monitor (LPRM) with calculations to continue monitoring with no loss of accuracy or reduction of thermal limits. Experience in small BWR cores has shown that with one out of three TIP machines failed there was no operating limitation or impact from the substitute calculations. Other capabilities exist in 3D Monicore to align TIPs more accurately and accommodate other types of system measurements or anomalies. 3D Monicore also includes an accurate predictive capability which uses the adaptive results from previous monitoring calculations and is used to plan and optimize reactor maneuvers/operations to improve operating efficiency and reduce support requirements

  14. Modeling Adaptive Behavior for Systems Design

    DEFF Research Database (Denmark)

    Rasmussen, Jens

    1994-01-01

    Field studies in modern work systems and analysis of recent major accidents have pointed to a need for better models of the adaptive behavior of individuals and organizations operating in a dynamic and highly competitive environment. The paper presents a discussion of some key characteristics.......) The basic difference between the models of system functions used in engineering and design and those evolving from basic research within the various academic disciplines and finally 3.) The models and methods required for closed-loop, feedback system design....

  15. Adaptive Numerical Algorithms in Space Weather Modeling

    Science.gov (United States)

    Toth, Gabor; vanderHolst, Bart; Sokolov, Igor V.; DeZeeuw, Darren; Gombosi, Tamas I.; Fang, Fang; Manchester, Ward B.; Meng, Xing; Nakib, Dalal; Powell, Kenneth G.; hide

    2010-01-01

    Space weather describes the various processes in the Sun-Earth system that present danger to human health and technology. The goal of space weather forecasting is to provide an opportunity to mitigate these negative effects. Physics-based space weather modeling is characterized by disparate temporal and spatial scales as well as by different physics in different domains. A multi-physics system can be modeled by a software framework comprising of several components. Each component corresponds to a physics domain, and each component is represented by one or more numerical models. The publicly available Space Weather Modeling Framework (SWMF) can execute and couple together several components distributed over a parallel machine in a flexible and efficient manner. The framework also allows resolving disparate spatial and temporal scales with independent spatial and temporal discretizations in the various models. Several of the computationally most expensive domains of the framework are modeled by the Block-Adaptive Tree Solar wind Roe Upwind Scheme (BATS-R-US) code that can solve various forms of the magnetohydrodynamics (MHD) equations, including Hall, semi-relativistic, multi-species and multi-fluid MHD, anisotropic pressure, radiative transport and heat conduction. Modeling disparate scales within BATS-R-US is achieved by a block-adaptive mesh both in Cartesian and generalized coordinates. Most recently we have created a new core for BATS-R-US: the Block-Adaptive Tree Library (BATL) that provides a general toolkit for creating, load balancing and message passing in a 1, 2 or 3 dimensional block-adaptive grid. We describe the algorithms of BATL and demonstrate its efficiency and scaling properties for various problems. BATS-R-US uses several time-integration schemes to address multiple time-scales: explicit time stepping with fixed or local time steps, partially steady-state evolution, point-implicit, semi-implicit, explicit/implicit, and fully implicit numerical

  16. Discordant tasks and motor adjustments affect interactions between adaptations to altered kinematics and dynamics

    Directory of Open Access Journals (Sweden)

    Fritzie Arce

    2010-01-01

    Full Text Available Motor control and adaptation are multi-determinate processes with complex interactions. This is reflected for example in the ambiguous nature of interactions during sequential adaptation of reaching under kinematics and dynamics perturbations. It has been suggested that perturbations based on the same kinematic parameter interfere. Others posited that opposing motor adjustments underlie interference. Here, we examined the influence of discordances in task and in motor adjustments on sequential adaptations to visuomotor rotation and viscous force field perturbations. These two factors – perturbation direction and task discordance – have been examined separately by previous studies, thus the inherent difficulty to identify the roots of interference. Forty-eight human subjects adapted sequentially to one or two types of perturbations, of matched or conflicting directions. We found a gradient of interaction effects based on perturbation direction and task discordance. Perturbations of matched directions showed facilitation while perturbations of opposite directions, which required opposing motor adjustments, interfered with each other. Further, interaction effects increased with greater task discordance. We also found that force field and visuomotor rotation had mutual anterograde and retrograde effects. However, we found independence between anterograde and retrograde interferences between similar tasks. The results suggest that the newly acquired internal models of kinematic and dynamic perturbations are not independent but they share common neuronal resources and interact between them. Such overlap does not necessarily imply competition of resources. Rather, our results point to an additional principle of sensorimotor adaptation allowing the system to tap or harness common features across diverse sensory inputs and task contexts whenever available.

  17. Adaptive Control with Reference Model Modification

    Science.gov (United States)

    Stepanyan, Vahram; Krishnakumar, Kalmanje

    2012-01-01

    This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example

  18. Adapting Parent-Child Interaction Therapy to Foster Care

    Science.gov (United States)

    Mersky, Joshua P.; Topitzes, James; Grant-Savela, Stacey D.; Brondino, Michael J.; McNeil, Cheryl B.

    2016-01-01

    Objective: This study presents outcomes from a randomized trial of a novel Parent-Child Interaction Therapy (PCIT) model for foster families. Differential effects of two intervention doses on child externalizing and internalizing symptoms are examined. Method: A sample of 102 foster children was assigned to one of three conditions--brief PCIT,…

  19. The interaction of parental alcoholism, adaptation role, and familial dysfunction.

    Science.gov (United States)

    Scharff, Judith L; Broida, John P; Conway, Kim; Yue, Alicia

    2004-05-01

    Many people believe that parental alcoholism has adverse consequences on children-some research fails to support this hypothesis. Familial dysfunction is often regarded as having a more important impact on adults, perhaps because of a failure to recognize that adult children of alcoholics (ACOAs) may have adopted more than one coping strategy. The present study investigated within-group differences in psychological symptomology as measured by the Millon Clinical Multiaxial Inventory (MCMI). ACOAs, were compared by roles (Hero, Mascot, Lost Child, and Scapegoat) to non-ACOAs as measured by familial dysfunction and roles. MANOVA indicated significant main effects of dysfunction, role, ACOA, and an interaction of role and ACOA. Failures to recognize the impact of parental alcoholism may be caused by multiple adaptation strategies.

  20. Adaptive cyber-attack modeling system

    Science.gov (United States)

    Gonsalves, Paul G.; Dougherty, Edward T.

    2006-05-01

    The pervasiveness of software and networked information systems is evident across a broad spectrum of business and government sectors. Such reliance provides an ample opportunity not only for the nefarious exploits of lone wolf computer hackers, but for more systematic software attacks from organized entities. Much effort and focus has been placed on preventing and ameliorating network and OS attacks, a concomitant emphasis is required to address protection of mission critical software. Typical software protection technique and methodology evaluation and verification and validation (V&V) involves the use of a team of subject matter experts (SMEs) to mimic potential attackers or hackers. This manpower intensive, time-consuming, and potentially cost-prohibitive approach is not amenable to performing the necessary multiple non-subjective analyses required to support quantifying software protection levels. To facilitate the evaluation and V&V of software protection solutions, we have designed and developed a prototype adaptive cyber attack modeling system. Our approach integrates an off-line mechanism for rapid construction of Bayesian belief network (BN) attack models with an on-line model instantiation, adaptation and knowledge acquisition scheme. Off-line model construction is supported via a knowledge elicitation approach for identifying key domain requirements and a process for translating these requirements into a library of BN-based cyber-attack models. On-line attack modeling and knowledge acquisition is supported via BN evidence propagation and model parameter learning.

  1. Adaptive emotional memory: the key hippocampal-amygdalar interaction.

    Science.gov (United States)

    Desmedt, Aline; Marighetto, Aline; Richter-Levin, Gal; Calandreau, Ludovic

    2015-01-01

    For centuries philosophical and clinical studies have emphasized a fundamental dichotomy between emotion and cognition, as, for instance, between behavioral/emotional memory and explicit/representative memory. However, the last few decades cognitive neuroscience have highlighted data indicating that emotion and cognition, as well as their underlying neural networks, are in fact in close interaction. First, it turns out that emotion can serve cognition, as exemplified by its critical contribution to decision-making or to the enhancement of episodic memory. Second, it is also observed that reciprocally cognitive processes as reasoning, conscious appraisal or explicit representation of events can modulate emotional responses, like promoting or reducing fear. Third, neurobiological data indicate that reciprocal amygdalar-hippocampal influences underlie such mutual regulation of emotion and cognition. While supporting this view, the present review discusses experimental data, obtained in rodents, indicating that the hippocampal and amygdalar systems not only regulate each other and their functional outcomes, but also qualify specific emotional memory representations through specific activations and interactions. Specifically, we review consistent behavioral, electrophysiological, pharmacological, biochemical and imaging data unveiling a direct contribution of both the amygdala and hippocampal-septal system to the identification of the predictor of a threat in different situations of fear conditioning. Our suggestion is that these two brain systems and their interplay determine the selection of relevant emotional stimuli, thereby contributing to the adaptive value of emotional memory. Hence, beyond the mutual quantitative regulation of these two brain systems described so far, we develop the idea that different activations of the hippocampus and amygdala, leading to specific configurations of neural activity, qualitatively impact the formation of emotional memory

  2. ADAPTATION MODEL FOR REDUCING THE MANAGERIAL STRESS

    Directory of Open Access Journals (Sweden)

    VIOLETA GLIGOROVSKI

    2017-12-01

    Full Text Available Changes are an inseparable component of the company's life cycle and they can contribute to its essential growth in the future. The purpose of this paper is to explain managerial stress caused by implementation of changes and creating an adaptation model to decrease managerial stress. How much the manager will successfully lead the project for implementation of a change and how much they will manage to amortize stress among employees, mostly depends on their expertise, knowledge and skills to accurately and comprehensively inform and integrate the employees in the overall process. The adaptation model is actually a new approach and recommendation for managers for dealing with stress when the changes are implemented. Methodology. For this purpose, the data presented, in fact, were collected through a questionnaire that was submitted to 61 respondents/ managers. The data were measured using the Likert scale from 1 to 7. Namely, with the help of the Likert scale, quantification of stress was made in relation to the various variables that were identified as the most important for the researched issues. An adaption model (new approach for amortizing changes was created using the DIA Diagram application, to show the relations between manager and the relevant amortization approaches.

  3. Uncovering transcriptional interactions via an adaptive fuzzy logic approach

    Directory of Open Access Journals (Sweden)

    Chen Chung-Ming

    2009-12-01

    Full Text Available Abstract Background To date, only a limited number of transcriptional regulatory interactions have been uncovered. In a pilot study integrating sequence data with microarray data, a position weight matrix (PWM performed poorly in inferring transcriptional interactions (TIs, which represent physical interactions between transcription factors (TF and upstream sequences of target genes. Inferring a TI means that the promoter sequence of a target is inferred to match the consensus sequence motifs of a potential TF, and their interaction type such as AT or RT is also predicted. Thus, a robust PWM (rPWM was developed to search for consensus sequence motifs. In addition to rPWM, one feature extracted from ChIP-chip data was incorporated to identify potential TIs under specific conditions. An interaction type classifier was assembled to predict activation/repression of potential TIs using microarray data. This approach, combining an adaptive (learning fuzzy inference system and an interaction type classifier to predict transcriptional regulatory networks, was named AdaFuzzy. Results AdaFuzzy was applied to predict TIs using real genomics data from Saccharomyces cerevisiae. Following one of the latest advances in predicting TIs, constrained probabilistic sparse matrix factorization (cPSMF, and using 19 transcription factors (TFs, we compared AdaFuzzy to four well-known approaches using over-representation analysis and gene set enrichment analysis. AdaFuzzy outperformed these four algorithms. Furthermore, AdaFuzzy was shown to perform comparably to 'ChIP-experimental method' in inferring TIs identified by two sets of large scale ChIP-chip data, respectively. AdaFuzzy was also able to classify all predicted TIs into one or more of the four promoter architectures. The results coincided with known promoter architectures in yeast and provided insights into transcriptional regulatory mechanisms. Conclusion AdaFuzzy successfully integrates multiple types of

  4. Modelling land surface - atmosphere interactions

    DEFF Research Database (Denmark)

    Rasmussen, Søren Højmark

    representation of groundwater in the hydrological model is found to important and this imply resolving the small river valleys. Because, the important shallow groundwater is found in the river valleys. If the model does not represent the shallow groundwater then the area mean surface flux calculation......The study is investigates modelling of land surface – atmosphere interactions in context of fully coupled climatehydrological model. With a special focus of under what condition a fully coupled model system is needed. Regional climate model inter-comparison projects as ENSEMBLES have shown bias...... by the hydrological model is found to be insensitive to model resolution. Furthermore, this study highlights the effect of bias precipitation by regional climate model and it implications for hydrological modelling....

  5. Adaptive Engine Torque Compensation with Driveline Model

    Directory of Open Access Journals (Sweden)

    Park Jinrak

    2018-01-01

    Full Text Available Engine net torque is the total torque generated by the engine side, and includes the fuel combustion torque, the friction torque, and additionally the starter motor torque in case of hybrid vehicles. The engine net torque is utilized to control powertrain items such as the engine itself, the transmission clutch, also the engine clutch, and it must be accurate for the precise powertrain control. However, this net torque can vary with the engine operating conditions like the engine wear, the changes of the atmospheric pressure and the friction torque. Thus, this paper proposes the adaptive engine net torque compensator using driveline model which can cope with the net torque change according to engine operating conditions. The adaptive compensator was applied on the parallel hybrid vehicle and investigated via MATLAB Simcape Driveline simulation.

  6. Interactive differential equations modeling program

    International Nuclear Information System (INIS)

    Rust, B.W.; Mankin, J.B.

    1976-01-01

    Due to the recent emphasis on mathematical modeling, many ecologists are using mathematics and computers more than ever, and engineers, mathematicians and physical scientists are now included in ecological projects. However, the individual ecologist, with intuitive knowledge of the system, still requires the means to critically examine and adjust system models. An interactive program was developed with the primary goal of allowing an ecologist with minimal experience in either mathematics or computers to develop a system model. It has also been used successfully by systems ecologists, engineers, and mathematicians. This program was written in FORTRAN for the DEC PDP-10, a remote terminal system at Oak Ridge National Laboratory. However, with relatively minor modifications, it can be implemented on any remote terminal system with a FORTRAN IV compiler, or equivalent. This program may be used to simulate any phenomenon which can be described as a system of ordinary differential equations. The program allows the user to interactively change system parameters and/or initial conditions, to interactively select a set of variables to be plotted, and to model discontinuities in the state variables and/or their derivatives. One of the most useful features to the non-computer specialist is the ability to interactively address the system parameters by name and to interactively adjust their values between simulations. These and other features are described in greater detail

  7. Visuo-proprioceptive interactions during adaptation of the human reach.

    Science.gov (United States)

    Judkins, Timothy; Scheidt, Robert A

    2014-02-01

    We examined whether visual and proprioceptive estimates of transient (midreach) target capture errors contribute to motor adaptation according to the probabilistic rules of information integration used for perception. Healthy adult humans grasped and moved a robotic handle between targets in the horizontal plane while the robot generated springlike loads that varied unpredictably from trial to trial. For some trials, a visual cursor faithfully tracked hand motion. In others, the handle's position was locked and subjects viewed motion of a point-mass cursor driven by hand forces. In yet other trials, cursor feedback was dissociated from hand motion or altogether eliminated. We used time- and frequency-domain analyses to characterize how sensorimotor memories influence performance on subsequent reaches. When the senses were used separately, subjects were better at rejecting physical disturbances applied to the hand than virtual disturbances applied to the cursor. In part, this observation reflected differences in how participants used sensorimotor memories to adapt to perturbations when performance feedback was limited to only proprioceptive or visual information channels. When both vision and proprioception were available to guide movement, subjects processed memories in a manner indistinguishable from the vision-only condition, regardless of whether the cursor tracked the hand faithfully or whether we experimentally dissociated motions of the hand and cursor. This was true even though, on average, perceptual uncertainty in the proprioceptive estimation of movement extent exceeded that of visual estimation by just 47%. In contrast to perceptual tasks wherein vision and proprioception both contribute to an optimal estimate of limb state, our findings support a switched-input, multisensory model of predictive load compensation wherein visual feedback of transient performance errors overwhelmingly dominates proprioception in determining adaptive reach performance.

  8. A universal model of giftedness - adaptation of the Munich Model

    NARCIS (Netherlands)

    Jessurun, J.H.; Shearer, C.B.; Weggeman, M.C.D.P.

    2016-01-01

    The Munich Model of Giftedness (MMG) by Heller and his colleagues, developed for the identification of gifted children, is adapted and expanded, with the aim of making it more universally usable as a model for the pathway from talents to performance. On the side of the talent-factors, the concept of

  9. Interacting boson model with surface delta interaction between nucleons

    International Nuclear Information System (INIS)

    Druce, C.; Moszkowski, S.A.

    1984-01-01

    The surface delta interaction is used as an effective nucleon-nucleon interaction to investigate the structure and interaction of the bosons in the interacting boson model. The authors have obtained analytical expressions for the coefficients of a multipole expansion of the neutron-boson proton-boson interaction for the case of degenerate orbits

  10. Learner Open Modeling in Adaptive Mobile Learning System for Supporting Student to Learn English

    Directory of Open Access Journals (Sweden)

    Van Cong Pham

    2011-10-01

    Full Text Available This paper represents a personalized context-aware mobile learning architecture for supporting student to learn English as foreign language in order to prepare for TOEFL test. We consider how to apply open learner modeling techniques to adapt contents for different learners based on context, which includes location, amount of time to learn, the manner as well as learner's knowledge in learning progress. Through negotiation with system, the editable learner model will be updated to support adaptive engine to select adaptive contents meeting learner's demands. Empirical testing results for students who used application prototype indicate that interaction user modeling is helpful in supporting learner to learn adaptive materials.

  11. Introduction to interacting boson model

    International Nuclear Information System (INIS)

    Goutte, D.

    1986-01-01

    A very simple presentation of the interacting boson model is first given. The two computerized models which are presented allow, with few parameters, to reproduce an impressive quantity of data characterizing the deformed nuclei. Their excitation spectra, the reduced transition probabilities, the quadrupolar moments, the two nucleon transfer experiment results, ... Then a specific application of the model is given: radial extension reproduction of nuclear functions. It is shown first how the electron inelastic scattering allows to measure observables related to these radial functions, the transition charge densities, then, on some examples, how the model allows to reproduce them [fr

  12. Simulation of Fuzzy Adaptive PI Controlled Grid Interactive Inverter

    Directory of Open Access Journals (Sweden)

    Necmi ALTIN

    2009-03-01

    Full Text Available In this study, a voltage source grid interactive inverter is modeled and simulated in MATLAB/Simulink. Inverter is designed as current controlled and a fuzzy-PI current controller used for the generation of switching pattern to shape the inverter output current. The grid interactive inverter consists of a line frequency transformer and a LC type filter. Galvanic isolation between the grid and renewable energy source is obtained by the line frequency transformer and LC filter is employed to filter the high frequency harmonic components in current waveform due to PWM switching and to reduce the output current THD. Results of the MATLAB/Simulink simulation show that inverter output current is in sinusoidal waveform and in phase with line voltage, and current harmonics are in the limits of international standards (

  13. Interactive effects of body-size structure and adaptive foraging on food-web stability.

    Science.gov (United States)

    Heckmann, Lotta; Drossel, Barbara; Brose, Ulrich; Guill, Christian

    2012-03-01

    Body-size structure of food webs and adaptive foraging of consumers are two of the dominant concepts of our understanding how natural ecosystems maintain their stability and diversity. The interplay of these two processes, however, is a critically important yet unresolved issue. To fill this gap in our knowledge of ecosystem stability, we investigate dynamic random and niche model food webs to evaluate the proportion of persistent species. We show that stronger body-size structures and faster adaptation stabilise these food webs. Body-size structures yield stabilising configurations of interaction strength distributions across food webs, and adaptive foraging emphasises links to resources closer to the base. Moreover, both mechanisms combined have a cumulative effect. Most importantly, unstructured random webs evolve via adaptive foraging into stable size-structured food webs. This offers a mechanistic explanation of how size structure adaptively emerges in complex food webs, thus building a novel bridge between these two important stabilising mechanisms. © 2012 Blackwell Publishing Ltd/CNRS.

  14. Adaptive interaction a utility maximization approach to understanding human interaction with technology

    CERN Document Server

    Payne, Stephen J

    2013-01-01

    This lecture describes a theoretical framework for the behavioural sciences that holds high promise for theory-driven research and design in Human-Computer Interaction. The framework is designed to tackle the adaptive, ecological, and bounded nature of human behaviour. It is designed to help scientists and practitioners reason about why people choose to behave as they do and to explain which strategies people choose in response to utility, ecology, and cognitive information processing mechanisms. A key idea is that people choose strategies so as to maximise utility given constraints. The frame

  15. Adaptability and stability of maize varieties using mixed model methodology

    Directory of Open Access Journals (Sweden)

    Walter Fernandes Meirelles

    2012-01-01

    Full Text Available The objective of this study was to evaluate the performance, adaptability and stability of corn cultivars simultaneously in unbalanced experiments, using the method of harmonic means of the relative performance of genetic values. The grain yield of 45 cultivars, including hybrids and varieties, was evaluated in 49 environments in two growing seasons. In the 2007/2008 growing season, 36 cultivars were evaluated and in 2008/2009 25 cultivars, of which 16 were used in both seasons. Statistical analyses were performed based on mixed models, considering genotypes as random and replications within environments as fixed factors. The experimental precision in the combined analyses was high (accuracy estimates > 92 %. Despite the existence of genotype x environment interaction, hybrids and varieties with high adaptability and stability were identified. Results showed that the method of harmonic means of the relative performance of genetic values is a suitable method for maize breeding programs.

  16. Stochastic hyperfine interactions modeling library

    Science.gov (United States)

    Zacate, Matthew O.; Evenson, William E.

    2011-04-01

    The stochastic hyperfine interactions modeling library (SHIML) provides a set of routines to assist in the development and application of stochastic models of hyperfine interactions. The library provides routines written in the C programming language that (1) read a text description of a model for fluctuating hyperfine fields, (2) set up the Blume matrix, upon which the evolution operator of the system depends, and (3) find the eigenvalues and eigenvectors of the Blume matrix so that theoretical spectra of experimental techniques that measure hyperfine interactions can be calculated. The optimized vector and matrix operations of the BLAS and LAPACK libraries are utilized; however, there was a need to develop supplementary code to find an orthonormal set of (left and right) eigenvectors of complex, non-Hermitian matrices. In addition, example code is provided to illustrate the use of SHIML to generate perturbed angular correlation spectra for the special case of polycrystalline samples when anisotropy terms of higher order than A can be neglected. Program summaryProgram title: SHIML Catalogue identifier: AEIF_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIF_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU GPL 3 No. of lines in distributed program, including test data, etc.: 8224 No. of bytes in distributed program, including test data, etc.: 312 348 Distribution format: tar.gz Programming language: C Computer: Any Operating system: LINUX, OS X RAM: Varies Classification: 7.4 External routines: TAPP [1], BLAS [2], a C-interface to BLAS [3], and LAPACK [4] Nature of problem: In condensed matter systems, hyperfine methods such as nuclear magnetic resonance (NMR), Mössbauer effect (ME), muon spin rotation (μSR), and perturbed angular correlation spectroscopy (PAC) measure electronic and magnetic structure within Angstroms of nuclear probes through the hyperfine interaction. When

  17. Drug-model membrane interactions

    International Nuclear Information System (INIS)

    Deniz, Usha K.

    1994-01-01

    In the present day world, drugs play a very important role in medicine and it is necessary to understand their mode of action at the molecular level, in order to optimise their use. Studies of drug-biomembrane interactions are essential for gaining such as understanding. However, it would be prohibitively difficult to carry out such studies, since biomembranes are highly complex systems. Hence, model membranes (made up of these lipids which are important components of biomembranes) of varying degrees of complexity are used to investigate drug-membrane interactions. Bio- as well as model-membranes undergo a chain melting transition when heated, the chains being in a disordered state above the transition point, T CM . This transition is of physiological importance since biomembranes select their components such that T CM is less than the ambient temperature but not very much so, so that membrane flexibility is ensured and porosity, avoided. The influence of drugs on the transition gives valuable clues about various parameters such as the location of the drug in the membrane. Deep insights into drug-membrane interactions are obtained by observing the effect of drugs on membrane structure and the mobilities of the various groups in lipids, near T CM . Investigation of such changes have been carried out with several drugs, using techniques such as DSC, XRD and NMR. The results indicate that the drug-membrane interaction not only depends on the nature of drug and lipids but also on the form of the model membrane - stacked bilayer or vesicles. The light that these results shed on the nature of drug-membrane interactions is discussed. (author). 13 refs., 13 figs., 1 tab

  18. Dynamic Adaptation in Child-Adult Language Interaction

    Science.gov (United States)

    van Dijk, Marijn; van Geert, Paul; Korecky-Kröll, Katharina; Maillochon, Isabelle; Laaha, Sabine; Dressler, Wolfgang U.; Bassano, Dominique

    2013-01-01

    When speaking to young children, adults adapt their language to that of the child. In this article, we suggest that this child-directed speech (CDS) is the result of a transactional process of dynamic adaptation between the child and the adult. The study compares developmental trajectories of three children to those of the CDS of their caregivers.…

  19. The role of social interaction in farmers' climate adaptation choice

    NARCIS (Netherlands)

    van Duinen, Rianne; Filatova, Tatiana; van der Veen, Anne; Seppelt, R.; Voinov, A.A.; Lange, S.; Bankamp, D.

    2012-01-01

    Adaptation to climate change might not always occur, with potentially catastrophic results. Success depends on coordinated actions at both governmental and individual levels (public and private adaptation). Even for a “wet” country like the Netherlands, climate change projections show that the

  20. Adaptation in integrated assessment modeling: where do we stand?

    OpenAIRE

    Patt, A.; van Vuuren, D.P.; Berkhout, F.G.H.; Aaheim, A.; Hof, A.F.; Isaac, M.; Mechler, R.

    2010-01-01

    Adaptation is an important element on the climate change policy agenda. Integrated assessment models, which are key tools to assess climate change policies, have begun to address adaptation, either by including it implicitly in damage cost estimates, or by making it an explicit control variable. We analyze how modelers have chosen to describe adaptation within an integrated framework, and suggest many ways they could improve the treatment of adaptation by considering more of its bottom-up cha...

  1. Theoretical model for ultracold molecule formation via adaptive feedback control

    International Nuclear Information System (INIS)

    Poschinger, Ulrich; Salzmann, Wenzel; Wester, Roland; Weidemueller, Matthias; Koch, Christiane P; Kosloff, Ronnie

    2006-01-01

    We theoretically investigate pump-dump photoassociation of ultracold molecules with amplitude- and phase-modulated femtosecond laser pulses. For this purpose, a perturbative model for light-matter interaction is developed and combined with a genetic algorithm for adaptive feedback control of the laser pulse shapes. The model is applied to the formation of 85 Rb 2 molecules in a magneto-optical trap. We find that optimized pulse shapes may maximize the formation of ground state molecules in a specific vibrational state at a pump-dump delay time for which unshaped pulses lead to a minimum of the formation rate. Compared to the maximum formation rate obtained for unshaped pulses at the optimum pump-dump delay, the optimized pulses lead to a significant improvement of about 40% for the target level population. Since our model yields the spectral amplitudes and phases of the optimized pulses, the results are directly applicable in pulse shaping experiments

  2. Adaptive solution of some steady-state fluid-structure interaction problems

    International Nuclear Information System (INIS)

    Etienne, S.; Pelletier, D.

    2003-01-01

    This paper presents a general integrated and coupled formulation for modeling the steady-state interaction of a viscous incompressible flow with an elastic structure undergoing large displacements (geometric non-linearities). This constitutes an initial step towards developing a sensitivity analysis formulation for this class of problems. The formulation uses velocity and pressures as unknowns in a flow domain and displacements in the structural components. An interface formulation is presented that leads to clear and simple finite element implementation of the equilibrium conditions at the fluid-solid interface. Issues of error estimation and mesh adaptation are discussed. The adaptive formulation is verified on a problem with a closed form solution. It is then applied to a sample case for which the structure undergoes large displacements induced by the flow. (author)

  3. An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

    Science.gov (United States)

    Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

    2008-01-01

    This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

  4. Interacting Brain Modules for Memory: An Adaptive Representations Architecture

    National Research Council Canada - National Science Library

    Gluck, Mark A

    2008-01-01

    ...) as a central system for creating optimal and adaptive stimulus representations, and then worked outwards from the hippocampal region to the brain systems that it modulates, including the cerebellum...

  5. A population dynamics analysis of the interaction between adaptive regulatory T cells and antigen presenting cells.

    Directory of Open Access Journals (Sweden)

    David Fouchet

    Full Text Available BACKGROUND: Regulatory T cells are central actors in the maintenance of tolerance of self-antigens or allergens and in the regulation of the intensity of the immune response during infections by pathogens. An understanding of the network of the interaction between regulatory T cells, antigen presenting cells and effector T cells is starting to emerge. Dynamical systems analysis can help to understand the dynamical properties of an interaction network and can shed light on the different tasks that can be accomplished by a network. METHODOLOGY AND PRINCIPAL FINDINGS: We used a mathematical model to describe a interaction network of adaptive regulatory T cells, in which mature precursor T cells may differentiate into either adaptive regulatory T cells or effector T cells, depending on the activation state of the cell by which the antigen was presented. Using an equilibrium analysis of the mathematical model we show that, for some parameters, the network has two stable equilibrium states: one in which effector T cells are strongly regulated by regulatory T cells and another in which effector T cells are not regulated because the regulatory T cell population is vanishingly small. We then simulate different types of perturbations, such as the introduction of an antigen into a virgin system, and look at the state into which the system falls. We find that whether or not the interaction network switches from the regulated (tolerant state to the unregulated state depends on the strength of the antigenic stimulus and the state from which the network has been perturbed. CONCLUSION/SIGNIFICANCE: Our findings suggest that the interaction network studied in this paper plays an essential part in generating and maintaining tolerance against allergens and self-antigens.

  6. Evolutionary adaptation in three-way interactions between plants, microbes and arthropods

    OpenAIRE

    Biere, A.; Tack, A.J.M.

    2013-01-01

    Evolutionary adaptations in interactions between plants, microbes and arthropods are generally studied in interactions that involve only two of these groups, that is, plants and microbes, plants and arthropods or arthropods and microbes. We review the accumulating evidence from a wide variety of systems, including plant- and arthropod-associated microbes, and symbionts as well as antagonists, that selection and adaptation in seemingly two-way interactions between plants and microbes, plants a...

  7. Adaptable Authentication Model: Exploring Security with Weaker Attacker Models

    DEFF Research Database (Denmark)

    Ahmed, Naveed; Jensen, Christian D.

    2011-01-01

    suffer because of the identified vulnerabilities. Therefore, we may need to analyze a protocol for weaker notions of security. In this paper, we present a security model that supports such weaker notions. In this model, the overall goals of an authentication protocol are broken into a finer granularity......; for each fine level authentication goal, we determine the “least strongest-attacker” for which the authentication goal can be satisfied. We demonstrate that this model can be used to reason about the security of supposedly insecure protocols. Such adaptability is particularly useful in those applications...

  8. Interactive Genetic Algorithm - An Adaptive and Interactive Decision Support Framework for Design of Optimal Groundwater Monitoring Plans

    Science.gov (United States)

    Babbar-Sebens, M.; Minsker, B. S.

    2006-12-01

    In the water resources management field, decision making encompasses many kinds of engineering, social, and economic constraints and objectives. Representing all of these problem dependant criteria through models (analytical or numerical) and various formulations (e.g., objectives, constraints, etc.) within an optimization- simulation system can be a very non-trivial issue. Most models and formulations utilized for discerning desirable traits in a solution can only approximate the decision maker's (DM) true preference criteria, and they often fail to consider important qualitative and incomputable phenomena related to the management problem. In our research, we have proposed novel decision support frameworks that allow DMs to actively participate in the optimization process. The DMs explicitly indicate their true preferences based on their subjective criteria and the results of various simulation models and formulations. The feedback from the DMs is then used to guide the search process towards solutions that are "all-rounders" from the perspective of the DM. The two main research questions explored in this work are: a) Does interaction between the optimization algorithm and a DM assist the system in searching for groundwater monitoring designs that are robust from the DM's perspective?, and b) How can an interactive search process be made more effective when human factors, such as human fatigue and cognitive learning processes, affect the performance of the algorithm? The application of these frameworks on a real-world groundwater long-term monitoring (LTM) case study in Michigan highlighted the following salient advantages: a) in contrast to the non-interactive optimization methodology, the proposed interactive frameworks were able to identify low cost monitoring designs whose interpolation maps respected the expected spatial distribution of the contaminants, b) for many same-cost designs, the interactive methodologies were able to propose multiple alternatives

  9. Optimal region of latching activity in an adaptive Potts model for networks of neurons

    International Nuclear Information System (INIS)

    Abdollah-nia, Mohammad-Farshad; Saeedghalati, Mohammadkarim; Abbassian, Abdolhossein

    2012-01-01

    In statistical mechanics, the Potts model is a model for interacting spins with more than two discrete states. Neural networks which exhibit features of learning and associative memory can also be modeled by a system of Potts spins. A spontaneous behavior of hopping from one discrete attractor state to another (referred to as latching) has been proposed to be associated with higher cognitive functions. Here we propose a model in which both the stochastic dynamics of Potts models and an adaptive potential function are present. A latching dynamics is observed in a limited region of the noise(temperature)–adaptation parameter space. We hence suggest noise as a fundamental factor in such alternations alongside adaptation. From a dynamical systems point of view, the noise–adaptation alternations may be the underlying mechanism for multi-stability in attractor-based models. An optimality criterion for realistic models is finally inferred

  10. Domain Adaptation of Translation Models for Multilingual Applications

    Science.gov (United States)

    2009-04-01

    employed. In the past two years, domain adaptation for NLP tasks has become an active research area [3, 38, 25, 23]. New domain adaptation tasks have...and unlabeled data in the target domain and learn a mixture model to adapt from the source domain. Other NLP tasks where domain adaptation has been...evaluation forum, http://www.clef-campaign.org. [13] K. Darwish and D. Oard, CLIR experiments at maryland for TREC-2002: Evidence combination for arabic

  11. A theoretical adaptive model of thermal comfort - Adaptive Predicted Mean Vote (aPMV)

    Energy Technology Data Exchange (ETDEWEB)

    Yao, Runming [School of Construction Management and Engineering, The University of Reading (United Kingdom); Faculty of Urban Construction and Environmental Engineering, Chongqing University (China); Li, Baizhan [Key Laboratory of the Three Gorges Reservoir Region' s Eco-Environment (Ministry of Education), Chongqing University (China); Faculty of Urban Construction and Environmental Engineering, Chongqing University (China); Liu, Jing [School of Construction Management and Engineering, The University of Reading (United Kingdom)

    2009-10-15

    This paper presents in detail a theoretical adaptive model of thermal comfort based on the ''Black Box'' theory, taking into account factors such as culture, climate, social, psychological and behavioural adaptations, which have an impact on the senses used to detect thermal comfort. The model is called the Adaptive Predicted Mean Vote (aPMV) model. The aPMV model explains, by applying the cybernetics concept, the phenomena that the Predicted Mean Vote (PMV) is greater than the Actual Mean Vote (AMV) in free-running buildings, which has been revealed by many researchers in field studies. An Adaptive coefficient ({lambda}) representing the adaptive factors that affect the sense of thermal comfort has been proposed. The empirical coefficients in warm and cool conditions for the Chongqing area in China have been derived by applying the least square method to the monitored onsite environmental data and the thermal comfort survey results. (author)

  12. A computational framework for modeling targets as complex adaptive systems

    Science.gov (United States)

    Santos, Eugene; Santos, Eunice E.; Korah, John; Murugappan, Vairavan; Subramanian, Suresh

    2017-05-01

    Modeling large military targets is a challenge as they can be complex systems encompassing myriad combinations of human, technological, and social elements that interact, leading to complex behaviors. Moreover, such targets have multiple components and structures, extending across multiple spatial and temporal scales, and are in a state of change, either in response to events in the environment or changes within the system. Complex adaptive system (CAS) theory can help in capturing the dynamism, interactions, and more importantly various emergent behaviors, displayed by the targets. However, a key stumbling block is incorporating information from various intelligence, surveillance and reconnaissance (ISR) sources, while dealing with the inherent uncertainty, incompleteness and time criticality of real world information. To overcome these challenges, we present a probabilistic reasoning network based framework called complex adaptive Bayesian Knowledge Base (caBKB). caBKB is a rigorous, overarching and axiomatic framework that models two key processes, namely information aggregation and information composition. While information aggregation deals with the union, merger and concatenation of information and takes into account issues such as source reliability and information inconsistencies, information composition focuses on combining information components where such components may have well defined operations. Since caBKBs can explicitly model the relationships between information pieces at various scales, it provides unique capabilities such as the ability to de-aggregate and de-compose information for detailed analysis. Using a scenario from the Network Centric Operations (NCO) domain, we will describe how our framework can be used for modeling targets with a focus on methodologies for quantifying NCO performance metrics.

  13. High rate of adaptation of mammalian proteins that interact with Plasmodium and related parasites

    Science.gov (United States)

    Telis, Natalie; Petrov, Dmitri A.

    2017-01-01

    Plasmodium parasites, along with their Piroplasm relatives, have caused malaria-like illnesses in terrestrial mammals for millions of years. Several Plasmodium-protective alleles have recently evolved in human populations, but little is known about host adaptation to blood parasites over deeper evolutionary timescales. In this work, we analyze mammalian adaptation in ~500 Plasmodium- or Piroplasm- interacting proteins (PPIPs) manually curated from the scientific literature. We show that (i) PPIPs are enriched for both immune functions and pleiotropy with other pathogens, and (ii) the rate of adaptation across mammals is significantly elevated in PPIPs, compared to carefully matched control proteins. PPIPs with high pathogen pleiotropy show the strongest signatures of adaptation, but this pattern is fully explained by their immune enrichment. Several pieces of evidence suggest that blood parasites specifically have imposed selection on PPIPs. First, even non-immune PPIPs that lack interactions with other pathogens have adapted at twice the rate of matched controls. Second, PPIP adaptation is linked to high expression in the liver, a critical organ in the parasite life cycle. Finally, our detailed investigation of alpha-spectrin, a major red blood cell membrane protein, shows that domains with particularly high rates of adaptation are those known to interact specifically with P. falciparum. Overall, we show that host proteins that interact with Plasmodium and Piroplasm parasites have experienced elevated rates of adaptation across mammals, and provide evidence that some of this adaptation has likely been driven by blood parasites. PMID:28957326

  14. Translation, Cultural Adaptation and Validation of the Questionnaire on Teacher Interaction in Danish High Schools

    DEFF Research Database (Denmark)

    Lund, Lea; Cozart, Stacey Marie; Lyneborg Lund, Rolf

    2018-01-01

    The model for Interpersonal Teacher Behaviour (MITB), mapping the various teachers’ interpersonal behaviours, has been applied for research in countries all over the world. The Questionnaire on Teacher Interaction (QTI) has been developed in order to measure the students’ perceptions regarding th...... to translation and cultural adaption showed the importance of the dialogical process with informants to make sure the questions are sound and understood in correlation to the MITB model....... the psychometric properties of the Danish translation of the QTI in its 64-item version. The article is descriptive and stress the importance of the awareness of the cultural differences when translating and incorporating a questionnaire from one country’s educational setting to another. Results on the approach...... the interaction with their teachers. The QTI has been shown to be a valid and reliable instrument in all the different language versions in which it was adapted. The QTI with the 64-item version has not yet received a validation in Denmark. The present study tested the translation process – after the translation...

  15. Adaptive multimodal interaction in mobile augmented reality: A conceptual framework

    Science.gov (United States)

    Abidin, Rimaniza Zainal; Arshad, Haslina; Shukri, Saidatul A'isyah Ahmad

    2017-10-01

    Recently, Augmented Reality (AR) is an emerging technology in many mobile applications. Mobile AR was defined as a medium for displaying information merged with the real world environment mapped with augmented reality surrounding in a single view. There are four main types of mobile augmented reality interfaces and one of them are multimodal interfaces. Multimodal interface processes two or more combined user input modes (such as speech, pen, touch, manual gesture, gaze, and head and body movements) in a coordinated manner with multimedia system output. In multimodal interface, many frameworks have been proposed to guide the designer to develop a multimodal applications including in augmented reality environment but there has been little work reviewing the framework of adaptive multimodal interface in mobile augmented reality. The main goal of this study is to propose a conceptual framework to illustrate the adaptive multimodal interface in mobile augmented reality. We reviewed several frameworks that have been proposed in the field of multimodal interfaces, adaptive interface and augmented reality. We analyzed the components in the previous frameworks and measure which can be applied in mobile devices. Our framework can be used as a guide for designers and developer to develop a mobile AR application with an adaptive multimodal interfaces.

  16. Awareness, training and trust in interaction with adaptive spam filters

    NARCIS (Netherlands)

    Cramer, H.S.M.; Evers, V.; van Someren, M.W.; Wielinga, B.J.; Greenberg, S.; Hudson, S.E.; Hinckley, K.; Morris, M.R.; Olsen Jr., D.R.

    2009-01-01

    Even though adaptive (trainable) spam filters are a common example of systems that make (semi-)autonomous decisions on behalf of the user, trust in these filters has been underexplored. This paper reports a study of usage of spam filters in the daily workplace and user behaviour in training these

  17. Contemporary Ecological Interactions Improve Models of Past Trait Evolution.

    Science.gov (United States)

    Hutchinson, Matthew C; Gaiarsa, Marília P; Stouffer, Daniel B

    2018-02-20

    Despite the fact that natural selection underlies both traits and interactions, evolutionary models often neglect that ecological interactions may, and in many cases do, influence the evolution of traits. Here, we explore the interdependence of ecological interactions and functional traits in the pollination associations of hawkmoths and flowering plants. Specifically, we develop an adaptation of the Ornstein-Uhlenbeck model of trait evolution that allows us to study the influence of plant corolla depth and observed hawkmoth-plant interactions on the evolution of hawkmoth proboscis length. Across diverse modelling scenarios, we find that the inclusion of contemporary interactions can provide a better description of trait evolution than the null expectation. Moreover, we show that the pollination interactions provide more-likely models of hawkmoth trait evolution when interactions are considered at increasingly finescale groups of hawkmoths. Finally, we demonstrate how the results of best-fit modelling approaches can implicitly support the association between interactions and trait evolution that our method explicitly examines. In showing that contemporary interactions can provide insight into the historical evolution of hawkmoth proboscis length, we demonstrate the clear utility of incorporating additional ecological information to models designed to study past trait evolution.

  18. Measurement error models with interactions

    Science.gov (United States)

    Midthune, Douglas; Carroll, Raymond J.; Freedman, Laurence S.; Kipnis, Victor

    2016-01-01

    An important use of measurement error models is to correct regression models for bias due to covariate measurement error. Most measurement error models assume that the observed error-prone covariate (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$W$\\end{document}) is a linear function of the unobserved true covariate (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$X$\\end{document}) plus other covariates (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$Z$\\end{document}) in the regression model. In this paper, we consider models for \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$W$\\end{document} that include interactions between \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$X$\\end{document} and \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$Z$\\end{document}. We derive the conditional distribution of

  19. Geographical patterns of adaptation within a species' range : Interactions between drift and gene flow

    NARCIS (Netherlands)

    Alleaume-Benharira, M; Pen, IR; Ronce, O

    We use individual-based stochastic simulations and analytical deterministic predictions to investigate the interaction between drift, natural selection and gene flow on the patterns of local adaptation across a fragmented species' range under clinally varying selection. Migration between populations

  20. Analyzing Katana referral hospital as a complex adaptive system: agents, interactions and adaptation to a changing environment.

    Science.gov (United States)

    Karemere, Hermès; Ribesse, Nathalie; Marchal, Bruno; Macq, Jean

    2015-01-01

    This study deals with the adaptation of Katana referral hospital in Eastern Democratic Republic of Congo in a changing environment that is affected for more than a decade by intermittent armed conflicts. His objective is to generate theoretical proposals for addressing differently the analysis of hospitals governance in the aims to assess their performance and how to improve that performance. The methodology applied approach uses a case study using mixed methods ( qualitative and quantitative) for data collection. It uses (1) hospital data to measure the output of hospitals, (2) literature review to identify among others, events and interventions recorded in the history of hospital during the study period and (3) information from individual interviews to validate the interpretation of the results of the previous two sources of data and understand the responsiveness of management team referral hospital during times of change. The study brings four theoretical propositions: (1) Interaction between key agents is a positive force driving adaptation if the actors share a same vision, (2) The strength of the interaction between agents is largely based on the nature of institutional arrangements, which in turn are shaped by the actors themselves, (3) The owner and the management team play a decisive role in the implementation of effective institutional arrangements and establishment of positive interactions between agents, (4) The analysis of recipient population's perception of health services provided allow to better tailor and adapt the health services offer to the population's needs and expectations. Research shows that it isn't enough just to provide support (financial and technical), to manage a hospital for operate and adapt to a changing environment but must still animate, considering that it is a complex adaptive system and that this animation is nothing other than the induction of a positive interaction between agents.

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

    Science.gov (United States)

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

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

    Science.gov (United States)

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

  3. Modeling Two Types of Adaptation to Climate Change

    Science.gov (United States)

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

  4. Adapt

    Science.gov (United States)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  5. Efficient ECG Signal Compression Using Adaptive Heart Model

    National Research Council Canada - National Science Library

    Szilagyi, S

    2001-01-01

    This paper presents an adaptive, heart-model-based electrocardiography (ECG) compression method. After conventional pre-filtering the waves from the signal are localized and the model's parameters are determined...

  6. The role of idiotypic interactions in the adaptive immune system: a belief-propagation approach

    Science.gov (United States)

    Bartolucci, Silvia; Mozeika, Alexander; Annibale, Alessia

    2016-08-01

    In this work we use belief-propagation techniques to study the equilibrium behaviour of a minimal model for the immune system comprising interacting T and B clones. We investigate the effect of the so-called idiotypic interactions among complementary B clones on the system’s activation. Our results show that B-B interactions increase the system’s resilience to noise, making clonal activation more stable, while increasing the cross-talk between different clones. We derive analytically the noise level at which a B clone gets activated, in the absence of cross-talk, and find that this increases with the strength of idiotypic interactions and with the number of T cells sending signals to the B clones. We also derive, analytically and numerically, via population dynamics, the critical line where clonal cross-talk arises. Our approach allows us to derive the B clone size distribution, which can be experimentally measured and gives important information about the adaptive immune system response to antigens and vaccination.

  7. Interacting boson model with surface delta interaction between nucleons: Structure and interaction of bosons

    International Nuclear Information System (INIS)

    Druce, C.H.; Moszkowski, S.A.

    1986-01-01

    The surface delta interaction is used as an effective nucleon-nucleon interaction to investigate the structure and interaction of the bosons in the interacting boson model. We have obtained analytical expressions for the coefficients of a multipole expansion of the neutron-boson-proton-boson interaction for the case of degenerate orbits. A connection is made between these coefficients and the parameters of the interaction boson model Hamiltonian. A link between the latter parameters and the single boson energies is suggested

  8. Interacting boson model with surface delta interaction between nucleons: Structure and interaction of bosons

    Energy Technology Data Exchange (ETDEWEB)

    Druce, C.H.; Moszkowski, S.A.

    1986-01-01

    The surface delta interaction is used as an effective nucleon-nucleon interaction to investigate the structure and interaction of the bosons in the interacting boson model. We have obtained analytical expressions for the coefficients of a multipole expansion of the neutron-boson-proton-boson interaction for the case of degenerate orbits. A connection is made between these coefficients and the parameters of the interaction boson model Hamiltonian. A link between the latter parameters and the single boson energies is suggested.

  9. Human-Automation Interaction Design for Adaptive Cruise Control Systems of Ground Vehicles

    Directory of Open Access Journals (Sweden)

    Hwisoo Eom

    2015-06-01

    Full Text Available A majority of recently developed advanced vehicles have been equipped with various automated driver assistance systems, such as adaptive cruise control (ACC and lane keeping assistance systems. ACC systems have several operational modes, and drivers can be unaware of the mode in which they are operating. Because mode confusion is a significant human error factor that contributes to traffic accidents, it is necessary to develop user interfaces for ACC systems that can reduce mode confusion. To meet this requirement, this paper presents a new human-automation interaction design methodology in which the compatibility of the machine and interface models is determined using the proposed criteria, and if the models are incompatible, one or both of the models is/are modified to make them compatible. To investigate the effectiveness of our methodology, we designed two new interfaces by separately modifying the machine model and the interface model and then performed driver-in-the-loop experiments. The results showed that modifying the machine model provides a more compact, acceptable, effective, and safe interface than modifying the interface model.

  10. Human-Automation Interaction Design for Adaptive Cruise Control Systems of Ground Vehicles.

    Science.gov (United States)

    Eom, Hwisoo; Lee, Sang Hun

    2015-06-12

    A majority of recently developed advanced vehicles have been equipped with various automated driver assistance systems, such as adaptive cruise control (ACC) and lane keeping assistance systems. ACC systems have several operational modes, and drivers can be unaware of the mode in which they are operating. Because mode confusion is a significant human error factor that contributes to traffic accidents, it is necessary to develop user interfaces for ACC systems that can reduce mode confusion. To meet this requirement, this paper presents a new human-automation interaction design methodology in which the compatibility of the machine and interface models is determined using the proposed criteria, and if the models are incompatible, one or both of the models is/are modified to make them compatible. To investigate the effectiveness of our methodology, we designed two new interfaces by separately modifying the machine model and the interface model and then performed driver-in-the-loop experiments. The results showed that modifying the machine model provides a more compact, acceptable, effective, and safe interface than modifying the interface model.

  11. Adaptation dynamics of the quasispecies model

    Indian Academy of Sciences (India)

    We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly ...

  12. Modeling Family Adaptation to Fragile X Syndrome

    Science.gov (United States)

    Raspa, Melissa; Bailey, Donald, Jr.; Bann, Carla; Bishop, Ellen

    2014-01-01

    Using data from a survey of 1,099 families who have a child with Fragile X syndrome, we examined adaptation across 7 dimensions of family life: parenting knowledge, social support, social life, financial impact, well-being, quality of life, and overall impact. Results illustrate that although families report a high quality of life, they struggle…

  13. Histogram Equalization to Model Adaptation for Robust Speech Recognition

    Directory of Open Access Journals (Sweden)

    Suh Youngjoo

    2010-01-01

    Full Text Available We propose a new model adaptation method based on the histogram equalization technique for providing robustness in noisy environments. The trained acoustic mean models of a speech recognizer are adapted into environmentally matched conditions by using the histogram equalization algorithm on a single utterance basis. For more robust speech recognition in the heavily noisy conditions, trained acoustic covariance models are efficiently adapted by the signal-to-noise ratio-dependent linear interpolation between trained covariance models and utterance-level sample covariance models. Speech recognition experiments on both the digit-based Aurora2 task and the large vocabulary-based task showed that the proposed model adaptation approach provides significant performance improvements compared to the baseline speech recognizer trained on the clean speech data.

  14. The adaptation process following acute onset disability: an interactive two-dimensional approach applied to acquired brain injury.

    Science.gov (United States)

    Brands, Ingrid M H; Wade, Derick T; Stapert, Sven Z; van Heugten, Caroline M

    2012-09-01

    To describe a new model of the adaptation process following acquired brain injury, based on the patient's goals, the patient's abilities and the emotional response to the changes and the possible discrepancy between goals and achievements. The process of adaptation after acquired brain injury is characterized by a continuous interaction of two processes: achieving maximal restoration of function and adjusting to the alterations and losses that occur in the various domains of functioning. Consequently, adaptation requires a balanced mix of restoration-oriented coping and loss-oriented coping. The commonly used framework to explain adaptation and coping, 'The Theory of Stress and Coping' of Lazarus and Folkman, does not capture this interactive duality. This model additionally considers theories concerned with self-regulation of behaviour, self-awareness and self-efficacy, and with the setting and achievement of goals. THE TWO-DIMENSIONAL MODEL: Our model proposes the simultaneous and continuous interaction of two pathways; goal pursuit (short term and long term) or revision as a result of success and failure in reducing distance between current state and expected future state and an affective response that is generated by the experienced goal-performance discrepancies. This affective response, in turn, influences the goals set. This two-dimensional representation covers the processes mentioned above: restoration of function and consideration of long-term limitations. We propose that adaptation centres on readjustment of long-term goals to new achievable but desired and important goals, and that this adjustment underlies re-establishing emotional stability. We discuss how the proposed model is related to actual rehabilitation practice.

  15. Evolutionary adaptation in three-way interactions between plants, microbes and arthropods

    NARCIS (Netherlands)

    Biere, A.; Tack, A.J.M.

    2013-01-01

    Evolutionary adaptations in interactions between plants, microbes and arthropods are generally studied in interactions that involve only two of these groups, that is, plants and microbes, plants and arthropods or arthropods and microbes. We review the accumulating evidence from a wide variety of

  16. An analytical model for interactive failures

    International Nuclear Information System (INIS)

    Sun Yong; Ma Lin; Mathew, Joseph; Zhang Sheng

    2006-01-01

    In some systems, failures of certain components can interact with each other, and accelerate the failure rates of these components. These failures are defined as interactive failure. Interactive failure is a prevalent cause of failure associated with complex systems, particularly in mechanical systems. The failure risk of an asset will be underestimated if the interactive effect is ignored. When failure risk is assessed, interactive failures of an asset need to be considered. However, the literature is silent on previous research work in this field. This paper introduces the concepts of interactive failure, develops an analytical model to analyse this type of failure quantitatively, and verifies the model using case studies and experiments

  17. Model Adaptation in Parametric Space for POD-Galerkin Models

    Science.gov (United States)

    Gao, Haotian; Wei, Mingjun

    2017-11-01

    The development of low-order POD-Galerkin models is largely motivated by the expectation to use the model developed with a set of parameters at their native values to predict the dynamic behaviors of the same system under different parametric values, in other words, a successful model adaptation in parametric space. However, most of time, even small deviation of parameters from their original value may lead to large deviation or unstable results. It has been shown that adding more information (e.g. a steady state, mean value of a different unsteady state, or an entire different set of POD modes) may improve the prediction of flow with other parametric states. For a simple case of the flow passing a fixed cylinder, an orthogonal mean mode at a different Reynolds number may stabilize the POD-Galerkin model when Reynolds number is changed. For a more complicated case of the flow passing an oscillatory cylinder, a global POD-Galerkin model is first applied to handle the moving boundaries, then more information (e.g. more POD modes) is required to predicate the flow under different oscillatory frequencies. Supported by ARL.

  18. Adaptation in integrated assessment modeling: where do we stand?

    NARCIS (Netherlands)

    Patt, A.; van Vuuren, D.P.; Berkhout, F.G.H.; Aaheim, A.; Hof, A.F.; Isaac, M.; Mechler, R.

    2010-01-01

    Adaptation is an important element on the climate change policy agenda. Integrated assessment models, which are key tools to assess climate change policies, have begun to address adaptation, either by including it implicitly in damage cost estimates, or by making it an explicit control variable. We

  19. Physical models of biological information and adaptation.

    Science.gov (United States)

    Stuart, C I

    1985-04-07

    The bio-informational equivalence asserts that biological processes reduce to processes of information transfer. In this paper, that equivalence is treated as a metaphor with deeply anthropomorphic content of a sort that resists constitutive-analytical definition, including formulation within mathematical theories of information. It is argued that continuance of the metaphor, as a quasi-theoretical perspective in biology, must entail a methodological dislocation between biological and physical science. It is proposed that a general class of functions, drawn from classical physics, can serve to eliminate the anthropomorphism. Further considerations indicate that the concept of biological adaptation is central to the general applicability of the informational idea in biology; a non-anthropomorphic treatment of adaptive phenomena is suggested in terms of variational principles.

  20. Context aware adaptive security service model

    Science.gov (United States)

    Tunia, Marcin A.

    2015-09-01

    Present systems and devices are usually protected against different threats concerning digital data processing. The protection mechanisms consume resources, which are either highly limited or intensively utilized by many entities. The optimization of these resources usage is advantageous. The resources that are saved performing optimization may be utilized by other mechanisms or may be sufficient for longer time. It is usually assumed that protection has to provide specific quality and attack resistance. By interpreting context situation of business services - users and services themselves, it is possible to adapt security services parameters to countermeasure threats associated with current situation. This approach leads to optimization of used resources and maintains sufficient security level. This paper presents architecture of adaptive security service, which is context-aware and exploits quality of context data issue.

  1. Nonlinear adaptive inverse control via the unified model neural network

    Science.gov (United States)

    Jeng, Jin-Tsong; Lee, Tsu-Tian

    1999-03-01

    In this paper, we propose a new nonlinear adaptive inverse control via a unified model neural network. In order to overcome nonsystematic design and long training time in nonlinear adaptive inverse control, we propose the approximate transformable technique to obtain a Chebyshev Polynomials Based Unified Model (CPBUM) neural network for the feedforward/recurrent neural networks. It turns out that the proposed method can use less training time to get an inverse model. Finally, we apply this proposed method to control magnetic bearing system. The experimental results show that the proposed nonlinear adaptive inverse control architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

  2. Discrete Model Reference Adaptive Control System for Automatic Profiling Machine

    Directory of Open Access Journals (Sweden)

    Peng Song

    2012-01-01

    Full Text Available Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. In this paper, the discrete model reference adaptive control system of automatic profiling machine is discussed. Firstly, the model of automatic profiling machine is presented according to the parameters of DC motor. Then the design of the discrete model reference adaptive control is proposed, and the control rules are proven. The results of simulation show that adaptive control system has favorable dynamic performances.

  3. Rodent models of adaptive decision making.

    Science.gov (United States)

    Izquierdo, Alicia; Belcher, Annabelle M

    2012-01-01

    Adaptive decision making affords the animal the ability to respond quickly to changes in a dynamic environment: one in which attentional demands, cost or effort to procure the reward, and reward contingencies change frequently. The more flexible the organism is in adapting choice behavior, the more command and success the organism has in navigating its environment. Maladaptive decision making is at the heart of much neuropsychiatric disease, including addiction. Thus, a better understanding of the mechanisms that underlie normal, adaptive decision making helps achieve a better understanding of certain diseases that incorporate maladaptive decision making as a core feature. This chapter presents three general domains of methods that the experimenter can manipulate in animal decision-making tasks: attention, effort, and reward contingency. Here, we present detailed methods of rodent tasks frequently employed within these domains: the Attentional Set-Shift Task, Effortful T-maze Task, and Visual Discrimination Reversal Learning. These tasks all recruit regions within the frontal cortex and the striatum, and performance is heavily modulated by the neurotransmitter dopamine, making these assays highly valid measures in the study of psychostimulant addiction.

  4. Adapted Lethality: What We Can Learn from Guinea Pig-Adapted Ebola Virus Infection Model.

    Science.gov (United States)

    Cheresiz, S V; Semenova, E A; Chepurnov, A A

    2016-01-01

    Establishment of small animal models of Ebola virus (EBOV) infection is important both for the study of genetic determinants involved in the complex pathology of EBOV disease and for the preliminary screening of antivirals, production of therapeutic heterologic immunoglobulins, and experimental vaccine development. Since the wild-type EBOV is avirulent in rodents, the adaptation series of passages in these animals are required for the virulence/lethality to emerge in these models. Here, we provide an overview of our several adaptation series in guinea pigs, which resulted in the establishment of guinea pig-adapted EBOV (GPA-EBOV) variants different in their characteristics, while uniformly lethal for the infected animals, and compare the virologic, genetic, pathomorphologic, and immunologic findings with those obtained in the adaptation experiments of the other research groups.

  5. Adapted Lethality: What We Can Learn from Guinea Pig-Adapted Ebola Virus Infection Model

    Directory of Open Access Journals (Sweden)

    S. V. Cheresiz

    2016-01-01

    Full Text Available Establishment of small animal models of Ebola virus (EBOV infection is important both for the study of genetic determinants involved in the complex pathology of EBOV disease and for the preliminary screening of antivirals, production of therapeutic heterologic immunoglobulins, and experimental vaccine development. Since the wild-type EBOV is avirulent in rodents, the adaptation series of passages in these animals are required for the virulence/lethality to emerge in these models. Here, we provide an overview of our several adaptation series in guinea pigs, which resulted in the establishment of guinea pig-adapted EBOV (GPA-EBOV variants different in their characteristics, while uniformly lethal for the infected animals, and compare the virologic, genetic, pathomorphologic, and immunologic findings with those obtained in the adaptation experiments of the other research groups.

  6. Interaction Modeling at PROS Research Center

    OpenAIRE

    Panach , José ,; Aquino , Nathalie; PASTOR , Oscar

    2011-01-01

    Part 1: Long and Short Papers; International audience; This paper describes how the PROS Research Center deals with interaction in the context of a model-driven approach for the development of information systems. Interaction is specified in a conceptual model together with the structure and behavior of the system. Major achievements and current research challenges of PROS in the field of interaction modeling are presented.

  7. [Polish adaptation of swing questionnaire (Survey Work-home Interaction - Nijmegen)].

    Science.gov (United States)

    Mościcka-Teske, Agnieszka; Merecz, Dorota

    2012-01-01

    The aim of the paper is to present the Polish adaptation of Survey Work-Home Interaction - Nijmegen (SWING). The analyses were based on the survey results from two groups of subjects, a sample of workers, representative in terms of sex and age, living in urban areas (N = 600) and a group of 59 employees examined twice with a help of SWING to assess the stability of the obtained results over a month time. The analyses performed proved that the Polish version of SWING is a reliable tool for studying work-home interactions. Correlation coefficients of items with total result of negative work-home interaction (WHI) subscale varied from 0.51 to 0.74, with positive WHI subscale from 0.26 to 0.60, negative home-work interaction (HWI) subscale, from 0.54 to 0.68 and positive HWI subscale from 0.31 to 0.59. Cronbach's alpha for the whole survey was 0.79, and for subscales varied from 0.73 to 0.89. The results of factorial analysis confirmed a our-factor structure of SWING. Factors I, items had loading from 0.58 to 0.81; II, from 0.29 to 0.78; III, from 0.60 to 0.80; and IV, from 0.28 to 0.74. The values of fit index for a four-factor model, were 0.91 (NNFI), 0.06 (RMSEA), and 0.92 (CFI), which means that this model is characterized by a good fit to empirical data. The correlation coefficient between two measurements at one month interval were also high and reached the range of 0.63 to 0.84. The results obtained are comparable to the psychometric characteristic of the English version of SWING.

  8. Workload Model Based Dynamic Adaptation of Social Internet of Vehicles

    Directory of Open Access Journals (Sweden)

    Kazi Masudul Alam

    2015-09-01

    Full Text Available Social Internet of Things (SIoT has gained much interest among different research groups in recent times. As a key member of a smart city, the vehicular domain of SIoT (SIoV is also undergoing steep development. In the SIoV, vehicles work as sensor-hub to capture surrounding information using the in-vehicle and Smartphone sensors and later publish them for the consumers. A cloud centric cyber-physical system better describes the SIoV model where physical sensing-actuation process affects the cloud based service sharing or computation in a feedback loop or vice versa. The cyber based social relationship abstraction enables distributed, easily navigable and scalable peer-to-peer communication among the SIoV subsystems. These cyber-physical interactions involve a huge amount of data and it is difficult to form a real instance of the system to test the feasibility of SIoV applications. In this paper, we propose an analytical model to measure the workloads of various subsystems involved in the SIoV process. We present the basic model which is further extended to incorporate complex scenarios. We provide extensive simulation results for different parameter settings of the SIoV system. The findings of the analyses are further used to design example adaptation strategies for the SIoV subsystems which would foster deployment of intelligent transport systems.

  9. Workload Model Based Dynamic Adaptation of Social Internet of Vehicles

    Science.gov (United States)

    Alam, Kazi Masudul; Saini, Mukesh; El Saddik, Abdulmotaleb

    2015-01-01

    Social Internet of Things (SIoT) has gained much interest among different research groups in recent times. As a key member of a smart city, the vehicular domain of SIoT (SIoV) is also undergoing steep development. In the SIoV, vehicles work as sensor-hub to capture surrounding information using the in-vehicle and Smartphone sensors and later publish them for the consumers. A cloud centric cyber-physical system better describes the SIoV model where physical sensing-actuation process affects the cloud based service sharing or computation in a feedback loop or vice versa. The cyber based social relationship abstraction enables distributed, easily navigable and scalable peer-to-peer communication among the SIoV subsystems. These cyber-physical interactions involve a huge amount of data and it is difficult to form a real instance of the system to test the feasibility of SIoV applications. In this paper, we propose an analytical model to measure the workloads of various subsystems involved in the SIoV process. We present the basic model which is further extended to incorporate complex scenarios. We provide extensive simulation results for different parameter settings of the SIoV system. The findings of the analyses are further used to design example adaptation strategies for the SIoV subsystems which would foster deployment of intelligent transport systems. PMID:26389905

  10. Roy's Adaptation Model-Guided Education and Promoting the Adaptation of Veterans With Lower Extremities Amputation.

    Science.gov (United States)

    Azarmi, Somayeh; Farsi, Zahra

    2015-10-01

    Any defect in extremities of the body can affect different life aspects. The purpose of this study was to investigate the effect of Roy's adaptation model-guided education on promoting the adaptation of veterans with lower extremities amputation. In a randomized clinical trial, 60 veterans with lower extremities amputation referring to Kowsar Orthotics and Prosthetics Center of veterans clinic in Tehran, Iran, were recruited with convenience method and were randomly assigned to intervention and control groups during 2013 - 2014. For data collection, Roy's adaptation model questionnaire was used. After completing the questionnaires in both groups, maladaptive behaviors were determined in the intervention group and an education program based on Roy's adaptation model was implemented. After two months, both groups completed the questionnaires again. Data was analyzed with SPSS software. Independent t-test showed statistically significant differences between the two groups in the post-test stage in terms of the total score of adaptation (P = 0.001) as well as physiologic (P = 0.0001) and role function modes (P = 0.004). The total score of adaptation (139.43 ± 5.45 to 127.54 ± 14.55, P = 0.006) as well as the scores of physiologic (60.26 ± 5.45 to 53.73 ± 7.79, P = 0.001) and role function (20.30 ± 2.42 to 18.13 ± 3.18, P = 0.01) modes in the intervention group significantly increased, whereas the scores of self-concept (42.10 ± 4.71 to 39.40 ± 5.67, P = 0.21) and interdependence (16.76 ± 2.22 to 16.30 ± 2.57, P = 0.44) modes in the two stages did not have a significant difference. Findings of this research indicated that the Roy's adaptation model-guided education promoted the adaptation level of physiologic and role function modes in veterans with lower extremities amputation. However, this intervention could not promote adaptation in self-concept and interdependence modes. More intervention is advised based on Roy's adaptation model for improving the

  11. Models, methods and software tools for building complex adaptive traffic systems

    International Nuclear Information System (INIS)

    Alyushin, S.A.

    2011-01-01

    The paper studies the modern methods and tools to simulate the behavior of complex adaptive systems (CAS), the existing systems of traffic modeling in simulators and their characteristics; proposes requirements for assessing the suitability of the system to simulate the CAS behavior in simulators. The author has developed a model of adaptive agent representation and its functioning environment to meet certain requirements set above, and has presented methods of agents' interactions and methods of conflict resolution in simulated traffic situations. A simulation system realizing computer modeling for simulating the behavior of CAS in traffic situations has been created [ru

  12. Analysis of adaptive walks on NK fitness landscapes with different interaction schemes

    International Nuclear Information System (INIS)

    Nowak, Stefan; Krug, Joachim

    2015-01-01

    Fitness landscapes are genotype to fitness mappings commonly used in evolutionary biology and computer science which are closely related to spin glass models. In this paper, we study the NK model for fitness landscapes where the interaction scheme between genes can be explicitly defined. The focus is on how this scheme influences the overall shape of the landscape. Our main tool for the analysis are adaptive walks, an idealized dynamics by which the population moves uphill in fitness and terminates at a local fitness maximum. We use three different types of walks and investigate how their length (the number of steps required to reach a local peak) and height (the fitness at the endpoint of the walk) depend on the dimensionality and structure of the landscape. We find that the distribution of local maxima over the landscape is particularly sensitive to the choice of interaction pattern. Most quantities that we measure are simply correlated to the rank of the scheme, which is equal to the number of nonzero coefficients in the expansion of the fitness landscape in terms of Walsh functions

  13. Model wavefront sensor for adaptive confocal microscopy

    Science.gov (United States)

    Booth, Martin J.; Neil, Mark A. A.; Wilson, Tony

    2000-05-01

    A confocal microscope permits 3D imaging of volume objects by the inclusion of a pinhole in the detector path which eliminates out of focus light. This configuration is however very sensitive to aberrations induced by the specimen or the optical system and would therefore benefit from an adaptive optics approach. We present a wavefront sensor capable of measuring directly the Zernike components of an aberrated wavefront and show that it is particularly applicable to the confocal microscope since only those wavefronts originating in the focal region contribute to the measured aberration.

  14. Large-Scale Topic Detection and Language Model Adaptation

    National Research Council Canada - National Science Library

    Seymore, Kristie

    1997-01-01

    .... We have developed a language model adaptation scheme that takes apiece of text, chooses the most similar topic clusters from a set of over 5000 elemental topics, and uses topic specific language...

  15. PI controller based model reference adaptive control for nonlinear

    African Journals Online (AJOL)

    user

    Keywords: Model Reference Adaptive Controller (MRAC), Artificial Neural ... attention, and many new approaches have been applied to practical process .... effectiveness of proposed method, it is compared with the simulation results of the ...

  16. Modeling adaptation of carbon use efficiency in microbial communities

    Directory of Open Access Journals (Sweden)

    Steven D Allison

    2014-10-01

    Full Text Available In new microbial-biogeochemical models, microbial carbon use efficiency (CUE is often assumed to decline with increasing temperature. Under this assumption, soil carbon losses under warming are small because microbial biomass declines. Yet there is also empirical evidence that CUE may adapt (i.e. become less sensitive to warming, thereby mitigating negative effects on microbial biomass. To analyze potential mechanisms of CUE adaptation, I used two theoretical models to implement a tradeoff between microbial uptake rate and CUE. This rate-yield tradeoff is based on thermodynamic principles and suggests that microbes with greater investment in resource acquisition should have lower CUE. Microbial communities or individuals could adapt to warming by reducing investment in enzymes and uptake machinery. Consistent with this idea, a simple analytical model predicted that adaptation can offset 50% of the warming-induced decline in CUE. To assess the ecosystem implications of the rate-yield tradeoff, I quantified CUE adaptation in a spatially-structured simulation model with 100 microbial taxa and 12 soil carbon substrates. This model predicted much lower CUE adaptation, likely due to additional physiological and ecological constraints on microbes. In particular, specific resource acquisition traits are needed to maintain stoichiometric balance, and taxa with high CUE and low enzyme investment rely on low-yield, high-enzyme neighbors to catalyze substrate degradation. In contrast to published microbial models, simulations with greater CUE adaptation also showed greater carbon storage under warming. This pattern occurred because microbial communities with stronger CUE adaptation produced fewer degradative enzymes, despite increases in biomass. Thus the rate-yield tradeoff prevents CUE adaptation from driving ecosystem carbon loss under climate warming.

  17. Coupling internal cerebellar models enhances online adaptation and supports offline consolidation in sensorimotor tasks

    OpenAIRE

    Passot , Jean-Baptiste; Luque , Niceto R.; Arleo , Angelo

    2013-01-01

    International audience; The cerebellum is thought to mediate sensorimotor adaptation through the acquisition of internal models of the body-environment interaction. These representations can be of two types, identified as forward and inverse models. The first predicts the sensory consequences of actions, while the second provides the correct commands to achieve desired state transitions. In this paper, we propose a composite architecture consisting of multiple cerebellar internal models to ac...

  18. Adaptive Modeling of the International Space Station Electrical Power System

    Science.gov (United States)

    Thomas, Justin Ray

    2007-01-01

    Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

  19. Adaptive Game Level Creation through Rank-based Interactive Evolution

    DEFF Research Database (Denmark)

    Liapis, Antonios; Martínez, Héctor Pérez; Togelius, Julian

    2013-01-01

    as fitness functions for the optimization of the generated content. The preference models are built via ranking-based preference learning, while the content is generated via evolutionary search. The proposed method is evaluated on the creation of strategy game maps, and its performance is tested using...

  20. Modeling of processes of an adaptive business management

    Directory of Open Access Journals (Sweden)

    Karev Dmitry Vladimirovich

    2011-04-01

    Full Text Available On the basis of the analysis of systems of adaptive management board business proposed the original version of the real system of adaptive management, the basis of which used dynamic recursive model cash flow forecast and real data. Proposed definitions and the simulation of scales and intervals of model time in the control system, as well as the thresholds observations and conditions of changing (correction of the administrative decisions. The process of adaptive management is illustrated on the basis proposed by the author of the script of development of business.

  1. Physician behavioral adaptability: A model to outstrip a "one size fits all" approach.

    Science.gov (United States)

    Carrard, Valérie; Schmid Mast, Marianne

    2015-10-01

    Based on a literature review, we propose a model of physician behavioral adaptability (PBA) with the goal of inspiring new research. PBA means that the physician adapts his or her behavior according to patients' different preferences. The PBA model shows how physicians infer patients' preferences and adapt their interaction behavior from one patient to the other. We claim that patients will benefit from better outcomes if their physicians show behavioral adaptability rather than a "one size fits all" approach. This literature review is based on a literature search of the PsycINFO(®) and MEDLINE(®) databases. The literature review and first results stemming from the authors' research support the validity and viability of parts of the PBA model. There is evidence suggesting that physicians are able to show behavioral flexibility when interacting with their different patients, that a match between patients' preferences and physician behavior is related to better consultation outcomes, and that physician behavioral adaptability is related to better consultation outcomes. Training of physicians' behavioral flexibility and their ability to infer patients' preferences can facilitate physician behavioral adaptability and positive patient outcomes. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  2. Genotype x Environmental Interactions and Adaptation Abilities of Chickpea (Cicer arietinum L.) in Cukurova Conditions

    OpenAIRE

    MART, Dürdane

    2015-01-01

    During the study, at which genotype x environmental interactions and adaptation capacity of 18 chickpea varieties that took place at yield trials conducted in years 2001, 2002 and 2003 at two different locations (Doğankent, Taşçı) in Çukurova region were studied, it has been observed that studied characteristics are significantly affected from trial locations. Chickpea varieties used in the yield trial, demonstrated different adaptation capacities to different environmental conditions in term...

  3. The method of adaptation under the parameters of the subject of the information interaction

    Directory of Open Access Journals (Sweden)

    Инесса Анатольевна Воробьёва

    2014-12-01

    Full Text Available To ensure the effectiveness of settings (adaptation created software and hardware on the particular subject of the method was developed for adaptation under the parameters of the subject of information interaction in the form of a set of operations to build a network dialog procedures on the basis of accounting for entry-level qualification of the subject, assessment of the current level of skills and operational restructuring of the network in accordance with the assessment of his level.

  4. An adaptation model for trabecular bone at different mechanical levels

    Directory of Open Access Journals (Sweden)

    Lv Linwei

    2010-07-01

    Full Text Available Abstract Background Bone has the ability to adapt to mechanical usage or other biophysical stimuli in terms of its mass and architecture, indicating that a certain mechanism exists for monitoring mechanical usage and controlling the bone's adaptation behaviors. There are four zones describing different bone adaptation behaviors: the disuse, adaptation, overload, and pathologic overload zones. In different zones, the changes of bone mass, as calculated by the difference between the amount of bone formed and what is resorbed, should be different. Methods An adaptation model for the trabecular bone at different mechanical levels was presented in this study based on a number of experimental observations and numerical algorithms in the literature. In the proposed model, the amount of bone formation and the probability of bone remodeling activation were proposed in accordance with the mechanical levels. Seven numerical simulation cases under different mechanical conditions were analyzed as examples by incorporating the adaptation model presented in this paper with the finite element method. Results The proposed bone adaptation model describes the well-known bone adaptation behaviors in different zones. The bone mass and architecture of the bone tissue within the adaptation zone almost remained unchanged. Although the probability of osteoclastic activation is enhanced in the overload zone, the potential of osteoblasts to form bones compensate for the osteoclastic resorption, eventually strengthening the bones. In the disuse zone, the disuse-mode remodeling removes bone tissue in disuse zone. Conclusions The study seeks to provide better understanding of the relationships between bone morphology and the mechanical, as well as biological environments. Furthermore, this paper provides a computational model and methodology for the numerical simulation of changes of bone structural morphology that are caused by changes of mechanical and biological

  5. Towards an adaptive model for greenhouse control

    NARCIS (Netherlands)

    Speetjens, S.L.; Stigter, J.D.; Straten, van G.

    2009-01-01

    Application of advanced controllers in horticultural practice requires detailed models. Even highly sophisticated models require regular attention from the user due to changing circumstances like plant growth, changing material properties and modifications in greenhouse design and layout. Moreover,

  6. Descending and Local Network Interactions Control Adaptive Locomotion

    Science.gov (United States)

    2014-12-04

    coupled CPGs also has the added benefit of making rhythms more robust. This improves both responses to perturbations to walking and the stability of...includes the sensory pathways identified in the insect and CPGs at each joint. We also developed a new robotic cockroach leg model that includes additional...controller. Campaniform sensilla (CS) are sensory neurons whose dendrites insert into a cuticular cap on the exoskeleton (Fig. 14). The elliptical

  7. Context-dependent planktivory: interacting effects of turbidity and predation risk on adaptive foraging

    Science.gov (United States)

    Pangle, Kevin L.; Malinich, Timothy D.; Bunnell, David B.; DeVries, Dennis R.; Ludsin, Stuart A.

    2012-01-01

    By shaping species interactions, adaptive phenotypic plasticity can profoundly influence ecosystems. Predicting such outcomes has proven difficult, however, owing in part to the dependence of plasticity on the environmental context. Of particular relevance are environmental factors that affect sensory performance in organisms in ways that alter the tradeoffs associated with adaptive phenotypic responses. We explored the influence of turbidity, which simultaneously and differentially affects the sensory performance of consumers at multiple trophic levels, on the indirect effect of a top predator (piscivorous fish) on a basal prey resource (zooplankton) that is mediated through changes in the plastic foraging behavior of an intermediate consumer (zooplanktivorous fish). We first generated theoretical predictions of the adaptive foraging response of a zooplanktivore across wide gradients of turbidity and predation risk by a piscivore. Our model predicted that predation risk can change the negative relationship between intermediate consumer foraging and turbidity into a humped-shaped (unimodal) one in which foraging is low in both clear and highly turbid conditions due to foraging-related risk and visual constraints, respectively. Consequently, the positive trait-mediated indirect effect (TMIE) of the top predator on the basal resource is predicted to peak at low turbidity and decline thereafter until it reaches an asymptote of zero at intermediate turbidity levels (when foraging equals that which is predicted when the top predator is absent). We used field observations and a laboratory experiment to test our model predictions. In support, we found humped-shaped relationships between planktivory and turbidity for several zooplanktivorous fishes from diverse freshwater ecosystems with predation risk. Further, our experiment demonstrated that predation risk reduced zooplanktivory by yellow perch (Perca flavescens) at a low turbidity, but had no effect on consumption at

  8. Adaptive streaming applications : analysis and implementation models

    NARCIS (Netherlands)

    Zhai, Jiali Teddy

    2015-01-01

    This thesis presents a highly automated design framework, called DaedalusRT, and several novel techniques. As the foundation of the DaedalusRT design framework, two types of dataflow Models-of-Computation (MoC) are used, one as timing analysis model and another one as the implementation model. The

  9. Using Interaction Scenarios to Model Information Systems

    DEFF Research Database (Denmark)

    Bækgaard, Lars; Bøgh Andersen, Peter

    The purpose of this paper is to define and discuss a set of interaction primitives that can be used to model the dynamics of socio-technical activity systems, including information systems, in a way that emphasizes structural aspects of the interaction that occurs in such systems. The primitives...... a number of case studies that indicate that interaction primitives can be useful modeling tools for supplementing conventional flow-oriented modeling of business processes....... are based on a unifying, conceptual definition of the disparate interaction types - a robust model of the types. The primitives can be combined and may thus represent mediated interaction. We present a set of visualizations that can be used to define multiple related interactions and we present and discuss...

  10. Ecological opportunity and predator-prey interactions: linking eco-evolutionary processes and diversification in adaptive radiations.

    Science.gov (United States)

    Pontarp, Mikael; Petchey, Owen L

    2018-03-14

    Much of life's diversity has arisen through ecological opportunity and adaptive radiations, but the mechanistic underpinning of such diversification is not fully understood. Competition and predation can affect adaptive radiations, but contrasting theoretical and empirical results show that they can both promote and interrupt diversification. A mechanistic understanding of the link between microevolutionary processes and macroevolutionary patterns is thus needed, especially in trophic communities. Here, we use a trait-based eco-evolutionary model to investigate the mechanisms linking competition, predation and adaptive radiations. By combining available micro-evolutionary theory and simulations of adaptive radiations we show that intraspecific competition is crucial for diversification as it induces disruptive selection, in particular in early phases of radiation. The diversification rate is however decreased in later phases owing to interspecific competition as niche availability, and population sizes are decreased. We provide new insight into how predation tends to have a negative effect on prey diversification through decreased population sizes, decreased disruptive selection and through the exclusion of prey from parts of niche space. The seemingly disparate effects of competition and predation on adaptive radiations, listed in the literature, may thus be acting and interacting in the same adaptive radiation at different relative strength as the radiation progresses. © 2018 The Authors.

  11. Adaptive Networks Theory, Models and Applications

    CERN Document Server

    Gross, Thilo

    2009-01-01

    With adaptive, complex networks, the evolution of the network topology and the dynamical processes on the network are equally important and often fundamentally entangled. Recent research has shown that such networks can exhibit a plethora of new phenomena which are ultimately required to describe many real-world networks. Some of those phenomena include robust self-organization towards dynamical criticality, formation of complex global topologies based on simple, local rules, and the spontaneous division of "labor" in which an initially homogenous population of network nodes self-organizes into functionally distinct classes. These are just a few. This book is a state-of-the-art survey of those unique networks. In it, leading researchers set out to define the future scope and direction of some of the most advanced developments in the vast field of complex network science and its applications.

  12. Adapting Dynamic Mathematical Models to a Pilot Anaerobic Digestion Reactor

    Directory of Open Access Journals (Sweden)

    F. Haugen, R. Bakke, and B. Lie

    2013-04-01

    Full Text Available A dynamic model has been adapted to a pilot anaerobic reactor fed diarymanure. Both steady-state data from online sensors and laboratory analysis anddynamic operational data from online sensors are used in the model adaptation.The model is based on material balances, and comprises four state variables,namely biodegradable volatile solids, volatile fatty acids, acid generatingmicrobes (acidogens, and methane generating microbes (methanogens. The modelcan predict the methane gas flow produced in the reactor. The model may beused for optimal reactor design and operation, state-estimation and control.Also, a dynamic model for the reactor temperature based on energy balance ofthe liquid in the reactor is adapted. This model may be used for optimizationand control when energy and economy are taken into account.

  13. Fragmentary model of exchange interactions

    CERN Document Server

    Kotov, V M

    2000-01-01

    This article makes attempt to refusal from using neutrino for explanation continuous distribution of beta particle energy by conversion to characteristic exchange interaction particles in nucleolus. It is taking formulation for nuclear position with many different fragments. It is computing half-value period of spontaneous fission of heavy nucleolus. (author)

  14. The modeling of predator-prey interactions

    OpenAIRE

    Muhammad Shakil; H. A. Wahab; Muhammad Naeem, et al.

    2015-01-01

    In this paper, we aim to study the interactions between the territorial animals like foxes and the rabbits. The territories for the foxes are considered to be the simple cells. The interactions between predator and its prey are represented by the chemical reactions which obey the mass action law. In this sense, we apply the mass action law for predator prey models and the quasi chemical approach is applied for the interactions between the predator and its prey to develop the modeled equations...

  15. Modeling multimodal human-computer interaction

    NARCIS (Netherlands)

    Obrenovic, Z.; Starcevic, D.

    2004-01-01

    Incorporating the well-known Unified Modeling Language into a generic modeling framework makes research on multimodal human-computer interaction accessible to a wide range off software engineers. Multimodal interaction is part of everyday human discourse: We speak, move, gesture, and shift our gaze

  16. Modeling Students' Memory for Application in Adaptive Educational Systems

    Science.gov (United States)

    Pelánek, Radek

    2015-01-01

    Human memory has been thoroughly studied and modeled in psychology, but mainly in laboratory setting under simplified conditions. For application in practical adaptive educational systems we need simple and robust models which can cope with aspects like varied prior knowledge or multiple-choice questions. We discuss and evaluate several models of…

  17. Gravitational interactions of integrable models

    International Nuclear Information System (INIS)

    Abdalla, E.; Abdalla, M.C.B.

    1995-10-01

    We couple non-linear σ-models to Liouville gravity, showing that integrability properties of symmetric space models still hold for the matter sector. Using similar arguments for the fermionic counterpart, namely Gross-Neveu-type models, we verify that such conclusions must also hold for them, as recently suggested. (author). 18 refs

  18. Adaptive LINE-P: An Adaptive Linear Energy Prediction Model for Wireless Sensor Network Nodes.

    Science.gov (United States)

    Ahmed, Faisal; Tamberg, Gert; Le Moullec, Yannick; Annus, Paul

    2018-04-05

    In the context of wireless sensor networks, energy prediction models are increasingly useful tools that can facilitate the power management of the wireless sensor network (WSN) nodes. However, most of the existing models suffer from the so-called fixed weighting parameter, which limits their applicability when it comes to, e.g., solar energy harvesters with varying characteristics. Thus, in this article we propose the Adaptive LINE-P (all cases) model that calculates adaptive weighting parameters based on the stored energy profiles. Furthermore, we also present a profile compression method to reduce the memory requirements. To determine the performance of our proposed model, we have used real data for the solar and wind energy profiles. The simulation results show that our model achieves 90-94% accuracy and that the compressed method reduces memory overheads by 50% as compared to state-of-the-art models.

  19. The Adaptation Fund: a model for the future?

    Energy Technology Data Exchange (ETDEWEB)

    Chandani, Achala; Harmeling, Sven; Kaloga, Alpha Oumar

    2009-08-15

    With millions of the poor already facing the impacts of a changing climate, adaptation is a globally urgent – and costly – issue. The Adaptation Fund, created under the Kyoto Protocol, has unique features that could herald a new era of international cooperation on adaptation. Its governance structure, for instance, offers a fresh approach to fund management under the UN climate convention. The Fund's Board has also developed a constructive working atmosphere, and further progress is expected before the 2009 climate summit in Copenhagen. But developing countries' demand for adaptation funding is huge: conservative estimates put it at US$50 billion a year. The Fund's current structure and funding base are clearly only a first step towards filling that gap. And despite its significant progress over the last 18 months, many countries, particularly in the developed world, remain sceptical about this approach. Looking in detail at the Fund's evolution offers insight into its future potential as a model for adaptation finance.

  20. Coupling internal cerebellar models enhances online adaptation and supports offline consolidation in sensorimotor tasks.

    Science.gov (United States)

    Passot, Jean-Baptiste; Luque, Niceto R; Arleo, Angelo

    2013-01-01

    The cerebellum is thought to mediate sensorimotor adaptation through the acquisition of internal models of the body-environment interaction. These representations can be of two types, identified as forward and inverse models. The first predicts the sensory consequences of actions, while the second provides the correct commands to achieve desired state transitions. In this paper, we propose a composite architecture consisting of multiple cerebellar internal models to account for the adaptation performance of humans during sensorimotor learning. The proposed model takes inspiration from the cerebellar microcomplex circuit, and employs spiking neurons to process information. We investigate the intrinsic properties of the cerebellar circuitry subserving efficient adaptation properties, and we assess the complementary contributions of internal representations by simulating our model in a procedural adaptation task. Our simulation results suggest that the coupling of internal models enhances learning performance significantly (compared with independent forward and inverse models), and it allows for the reproduction of human adaptation capabilities. Furthermore, we provide a computational explanation for the performance improvement observed after one night of sleep in a wide range of sensorimotor tasks. We predict that internal model coupling is a necessary condition for the offline consolidation of procedural memories.

  1. Coupling internal cerebellar models enhances online adaptation and supports offline consolidation in sensorimotor tasks

    Directory of Open Access Journals (Sweden)

    Jean-Baptiste ePassot

    2013-07-01

    Full Text Available The cerebellum is thought to mediate sensorimotor adaptation through the acquisition of internal models of the body–environment interaction. These representations can be of two types, identified as forward and inverse models. The first predicts the sensory consequences of actions, while the second provides the correct commands to achieve desired state transitions. In this paper, we propose a composite architecture consisting of multiple cerebellar internal models to account for the adaptation performance of humans during sensorimotor learning. The proposed model takes inspiration from the cerebellar microcomplex circuit, and employs spiking neurons to process information. We investigate the intrinsic properties of the cerebellar circuitry subserving efficient adaptation properties, and we assess the complementary contributions of internal representations by simulating our model in a procedural adaptation task. Our simulation results suggest that the coupling of internal models enhances learning performance significantly (compared with independent forward and inverse models, and it allows for the reproduction of human adaptation capabilities. Furthermore, we provide a computational explanation for the performance improvement observed after one night of sleep in a wide range of sensorimotor tasks. We predict that internal model coupling is a necessary condition for the offline consolidation of procedural memories.

  2. Basic Research on Adaptive Model Algorithmic Control

    Science.gov (United States)

    1985-12-01

    Control Conference. Richalet, J., A. Rault, J.L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial...pp.977-982. Richalet, J., A. Rault, J. L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial processes

  3. Adaptive MPC based on MIMO ARX-Laguerre model.

    Science.gov (United States)

    Ben Abdelwahed, Imen; Mbarek, Abdelkader; Bouzrara, Kais

    2017-03-01

    This paper proposes a method for synthesizing an adaptive predictive controller using a reduced complexity model. This latter is given by the projection of the ARX model on Laguerre bases. The resulting model is entitled MIMO ARX-Laguerre and it is characterized by an easy recursive representation. The adaptive predictive control law is computed based on multi-step-ahead finite-element predictors, identified directly from experimental input/output data. The model is tuned in each iteration by an online identification algorithms of both model parameters and Laguerre poles. The proposed approach avoids time consuming numerical optimization algorithms associated with most common linear predictive control strategies, which makes it suitable for real-time implementation. The method is used to synthesize and test in numerical simulations adaptive predictive controllers for the CSTR process benchmark. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  4. Functional Dual Adaptive Control with Recursive Gaussian Process Model

    International Nuclear Information System (INIS)

    Prüher, Jakub; Král, Ladislav

    2015-01-01

    The paper deals with dual adaptive control problem, where the functional uncertainties in the system description are modelled by a non-parametric Gaussian process regression model. Current approaches to adaptive control based on Gaussian process models are severely limited in their practical applicability, because the model is re-adjusted using all the currently available data, which keeps growing with every time step. We propose the use of recursive Gaussian process regression algorithm for significant reduction in computational requirements, thus bringing the Gaussian process-based adaptive controllers closer to their practical applicability. In this work, we design a bi-criterial dual controller based on recursive Gaussian process model for discrete-time stochastic dynamic systems given in an affine-in-control form. Using Monte Carlo simulations, we show that the proposed controller achieves comparable performance with the full Gaussian process-based controller in terms of control quality while keeping the computational demands bounded. (paper)

  5. Importance of adaptation and genotype × environment interactions in tropical beef breeding systems.

    Science.gov (United States)

    Burrow, H M

    2012-05-01

    This paper examines the relative importance of productive and adaptive traits in beef breeding systems based on Bos taurus and tropically adapted breeds across temperate and (sub)tropical environments. In the (sub)tropics, differences that exist between breeds in temperate environments are masked by the effects of environmental stressors. Hence in tropical environments, breeds are best categorised into breed types to compare their performance across environments. Because of the presence of environmental stressors, there are more sources of genetic variation in tropical breeding programmes. It is therefore necessary to examine the genetic basis of productive and adaptive traits for breeding programmes in those environments. This paper reviews the heritabilities and genetic relationships between economically important productive and adaptive traits relevant to (sub)tropical breeding programmes. It is concluded that it is possible to simultaneously genetically improve productive and adaptive traits in tropically adapted breeds of beef cattle grazed in tropical environments without serious detrimental consequences for either adaptation or production. However, breed-specific parameters are required for genetic evaluations. The paper also reviews the magnitude of genotype × environment (G × E) interactions impacting on production and adaptation of cattle, where 'genotype' is defined as breed (within a crossbreeding system), sire within breed (in a within-breed selection programme) or associations between economically important traits and single nucleotide polymorphisms (SNPs - within a marker-assisted selection programme). It is concluded that re-ranking of breeds across environments is best managed by the use of the breed type(s) best suited to the particular production environment. Re-ranking of sires across environments is apparent in poorly adapted breed types across extreme tropical and temperate environments or where breeding animals are selected in a temperate

  6. Modeling Power Systems as Complex Adaptive Systems

    Energy Technology Data Exchange (ETDEWEB)

    Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.

    2004-12-30

    Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

  7. Model-based design of adaptive embedded systems

    CERN Document Server

    Hamberg, Roelof; Reckers, Frans; Verriet, Jacques

    2013-01-01

    Today’s embedded systems have to operate in a wide variety of dynamically changing environmental circumstances. Adaptivity, the ability of a system to autonomously adapt itself, is a means to optimise a system’s behaviour to accommodate changes in its environment. It involves making in-product trade-offs between system qualities at system level. The main challenge in the development of adaptive systems is keeping control of the intrinsic complexity of such systems while working with multi-disciplinary teams to create different parts of the system. Model-Based Development of Adaptive Embedded Systems focuses on the development of adaptive embedded systems both from an architectural and methodological point of view. It describes architectural solution patterns for adaptive systems and state-of-the-art model-based methods and techniques to support adaptive system development. In particular, the book describes the outcome of the Octopus project, a cooperation of a multi-disciplinary team of academic and indus...

  8. Development of structural model of adaptive training complex in ergatic systems for professional use

    Science.gov (United States)

    Obukhov, A. D.; Dedov, D. L.; Arkhipov, A. E.

    2018-03-01

    The article considers the structural model of the adaptive training complex (ATC), which reflects the interrelations between the hardware, software and mathematical model of ATC and describes the processes in this subject area. The description of the main components of software and hardware complex, their interaction and functioning within the common system are given. Also the article scrutinizers a brief description of mathematical models of personnel activity, a technical system and influences, the interactions of which formalize the regularities of ATC functioning. The studies of main objects of training complexes and connections between them will make it possible to realize practical implementation of ATC in ergatic systems for professional use.

  9. Adaptive Modeling and Real-Time Simulation

    Science.gov (United States)

    1984-01-01

    34 Artificial Inteligence , Vol. 13, pp. 27-39 (1980). Describes circumscription which is just the assumption that everything that is known to have a particular... Artificial Intelligence Truth Maintenance Planning Resolution Modeling Wcrld Models ~ .. ~2.. ASSTR AT (Coninue n evrse sieIf necesaran Identfy by...represents a marriage of (1) the procedural-network st, planning technology developed in artificial intelligence with (2) the PERT/CPM technology developed in

  10. THE JAPANESE EXPATRIATES IN MALAYSIA: INTERACTION AND ADAPTATION IN THE CULTURAL DIVERSE ENVIRONMENT

    OpenAIRE

    Ismail, Md. Rosli bin

    2013-01-01

    This study on the Japanese expatriates in Malaysia attempts to answer two research questions, i.e. (i) what is the classification of the Japanese expatriates based on communication skills, interaction and adaptation of culture, and (ii) what are the factors that are hindrance to communication and interaction? This study uses the analytical framework which argues that the Japanese society becomes the dominant culture of that corporation, and of individuals who work for the corporation. The stu...

  11. Deep Predictive Models in Interactive Music

    OpenAIRE

    Martin, Charles P.; Ellefsen, Kai Olav; Torresen, Jim

    2018-01-01

    Automatic music generation is a compelling task where much recent progress has been made with deep learning models. In this paper, we ask how these models can be integrated into interactive music systems; how can they encourage or enhance the music making of human users? Musical performance requires prediction to operate instruments, and perform in groups. We argue that predictive models could help interactive systems to understand their temporal context, and ensemble behaviour. Deep learning...

  12. An Immune-inspired Adaptive Automated Intrusion Response System Model

    Directory of Open Access Journals (Sweden)

    Ling-xi Peng

    2012-09-01

    Full Text Available An immune-inspired adaptive automated intrusion response system model, named as , is proposed. The descriptions of self, non-self, immunocyte, memory detector, mature detector and immature detector of the network transactions, and the realtime network danger evaluation equations are given. Then, the automated response polices are adaptively performed or adjusted according to the realtime network danger. Thus, not only accurately evaluates the network attacks, but also greatly reduces the response times and response costs.

  13. Interactive ontology-based user modelling for personalized learning content management

    NARCIS (Netherlands)

    Denaux, R.O.; Dimitrova, V.; Aroyo, L.M.; Aroyo, L.; Tasso, C.

    2004-01-01

    This position paper discusses the need for using interactive ontology-based user modeling to empower on the fly adaptation in learning information systems. We outline several open issues related to adaptive learning content delivery and present an approach to deal with these issues based on the

  14. Adaptive PID and Model Reference Adaptive Control Switch Controller for Nonlinear Hydraulic Actuator

    Directory of Open Access Journals (Sweden)

    Xin Zuo

    2017-01-01

    Full Text Available Nonlinear systems are modeled as piecewise linear systems at multiple operating points, where the operating points are modeled as switches between constituent linearized systems. In this paper, adaptive piecewise linear switch controller is proposed for improving the response time and tracking performance of the hydraulic actuator control system, which is essentially piecewise linear. The controller composed of PID and Model Reference Adaptive Control (MRAC adaptively chooses the proportion of these two components and makes the designed system have faster response time at the transient phase and better tracking performance, simultaneously. Then, their stability and tracking performance are analyzed and evaluated by the hydraulic actuator control system, the hydraulic actuator is controlled by the electrohydraulic system, and its model is built, which has piecewise linear characteristic. Then the controller results are compared between PID and MRAC and the switch controller designed in this paper is applied to the hydraulic actuator; it is obvious that adaptive switch controller has better effects both on response time and on tracking performance.

  15. Water System Adaptation To Hydrological Changes: Module 12, Models and Tools for Stormwater and Wastewater System Adaptation

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  16. Diffusion coefficient adaptive correction in Lagrangian puff model

    International Nuclear Information System (INIS)

    Tan Wenji; Wang Dezhong; Ma Yuanwei; Ji Zhilong

    2014-01-01

    Lagrangian puff model is widely used in the decision support system for nuclear emergency management. The diffusion coefficient is one of the key parameters impacting puff model. An adaptive method was proposed in this paper, which could correct the diffusion coefficient in Lagrangian puff model, and it aimed to improve the accuracy of calculating the nuclide concentration distribution. This method used detected concentration data, meteorological data and source release data to estimate the actual diffusion coefficient with least square method. The diffusion coefficient adaptive correction method was evaluated by Kincaid data in MVK, and was compared with traditional Pasquill-Gifford (P-G) diffusion scheme method. The results indicate that this diffusion coefficient adaptive correction method can improve the accuracy of Lagrangian puff model. (authors)

  17. Statistical Models of Adaptive Immune populations

    Science.gov (United States)

    Sethna, Zachary; Callan, Curtis; Walczak, Aleksandra; Mora, Thierry

    The availability of large (104-106 sequences) datasets of B or T cell populations from a single individual allows reliable fitting of complex statistical models for naïve generation, somatic selection, and hypermutation. It is crucial to utilize a probabilistic/informational approach when modeling these populations. The inferred probability distributions allow for population characterization, calculation of probability distributions of various hidden variables (e.g. number of insertions), as well as statistical properties of the distribution itself (e.g. entropy). In particular, the differences between the T cell populations of embryonic and mature mice will be examined as a case study. Comparing these populations, as well as proposed mixed populations, provides a concrete exercise in model creation, comparison, choice, and validation.

  18. Efficiently adapting graphical models for selectivity estimation

    DEFF Research Database (Denmark)

    Tzoumas, Kostas; Deshpande, Amol; Jensen, Christian S.

    2013-01-01

    cardinality estimation without making the independence assumption. By carefully using concepts from the field of graphical models, we are able to factor the joint probability distribution over all the attributes in the database into small, usually two-dimensional distributions, without a significant loss...... in estimation accuracy. We show how to efficiently construct such a graphical model from the database using only two-way join queries, and we show how to perform selectivity estimation in a highly efficient manner. We integrate our algorithms into the PostgreSQL DBMS. Experimental results indicate...

  19. Adaptive plasticity model for bucket foundations

    DEFF Research Database (Denmark)

    Ibsen, Lars Bo; Barari, Amin; Larsen, Kim A.

    2014-01-01

    Based on experimental investigations, the literature proposes different methods for modeling the behavior and capacity of foundations subjected to combined loading. Generally, two methods are used to predict the behavior of foundations: traditional approaches and hardening plasticity solutions......, potential, and failure surfaces are found to be dependent on the embedment ratio (i.e., ratio of skirt length to the diameter) and load path. For the models tested, associated flow is observed to be plausible in the radial planes, whereas nonassociated flow is observed in the planes along the V-axis....

  20. An Exploratory Investigation into the Effects of Adaptation in Child-Robot Interaction

    Science.gov (United States)

    Salter, Tamie; Michaud, François; Létourneau, Dominic

    The work presented in this paper describes an exploratory investigation into the potential effects of a robot exhibiting an adaptive behaviour in reaction to a child’s interaction. In our laboratory we develop robotic devices for a diverse range of children that differ in age, gender and ability, which includes children that are diagnosed with cognitive difficulties. As all children vary in their personalities and styles of interaction, it would follow that adaptation could bring many benefits. In this abstract we give our initial examination of a series of trials which explore the effects of a fully autonomous rolling robot exhibiting adaptation (through changes in motion and sound) compared to it exhibiting pre-programmed behaviours. We investigate sensor readings on-board the robot that record the level of ‘interaction’ that the robot receives when a child plays with it and also we discuss the results from analysing video footage looking at the social aspect of the trial.

  1. Adapting AIC to conditional model selection

    NARCIS (Netherlands)

    T. van Ommen (Thijs)

    2012-01-01

    textabstractIn statistical settings such as regression and time series, we can condition on observed information when predicting the data of interest. For example, a regression model explains the dependent variables $y_1, \\ldots, y_n$ in terms of the independent variables $x_1, \\ldots, x_n$.

  2. In silico biology of bone modelling and remodelling: adaptation.

    Science.gov (United States)

    Gerhard, Friederike A; Webster, Duncan J; van Lenthe, G Harry; Müller, Ralph

    2009-05-28

    Modelling and remodelling are the processes by which bone adapts its shape and internal structure to external influences. However, the cellular mechanisms triggering osteoclastic resorption and osteoblastic formation are still unknown. In order to investigate current biological theories, in silico models can be applied. In the past, most of these models were based on the continuum assumption, but some questions related to bone adaptation can be addressed better by models incorporating the trabecular microstructure. In this paper, existing simulation models are reviewed and one of the microstructural models is extended to test the hypothesis that bone adaptation can be simulated without particular knowledge of the local strain distribution in the bone. Validation using an experimental murine loading model showed that this is possible. Furthermore, the experimental model revealed that bone formation cannot be attributed only to an increase in trabecular thickness but also to structural reorganization including the growth of new trabeculae. How these new trabeculae arise is still an unresolved issue and might be better addressed by incorporating other levels of hierarchy, especially the cellular level. The cellular level sheds light on the activity and interplay between the different cell types, leading to the effective change in the whole bone. For this reason, hierarchical multi-scale simulations might help in the future to better understand the biomathematical laws behind bone adaptation.

  3. Multiple Model Adaptive Control Using Dual Youla-Kucera Factorisation

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, Klaus

    2012-01-01

    We propose a multi-model adaptive control scheme for uncertain linear plants based on the concept of model unfalsification. The approach relies on examining the ability of a pre-computed set of plant-controller candidates and choosing the one that is best able to reproduce observed in- and output...

  4. The behavior of adaptive bone-remodeling simulation models

    NARCIS (Netherlands)

    H.H. Weinans (Harrie); R. Huiskes (Rik); H.J. Grootenboer

    1992-01-01

    textabstractThe process of adaptive bone remodeling can be described mathematically and simulated in a computer model, integrated with the finite element method. In the model discussed here, cortical and trabecular bone are described as continuous materials with variable density. The remodeling rule

  5. A Method for Model Checking Feature Interactions

    DEFF Research Database (Denmark)

    Pedersen, Thomas; Le Guilly, Thibaut; Ravn, Anders Peter

    2015-01-01

    This paper presents a method to check for feature interactions in a system assembled from independently developed concurrent processes as found in many reactive systems. The method combines and refines existing definitions and adds a set of activities. The activities describe how to populate the ...... the definitions with models to ensure that all interactions are captured. The method is illustrated on a home automation example with model checking as analysis tool. In particular, the modelling formalism is timed automata and the analysis uses UPPAAL to find interactions....

  6. Porous models for wave-seabed interactions

    Energy Technology Data Exchange (ETDEWEB)

    Jeng, Dong-Sheng [Shanghai Jiaotong Univ., SH (China)

    2013-02-01

    Detailed discussion about the phenomenon of wave-seabed interactions. Novel models for wave-induced seabed response. Intensive theoretical derivations for wave-seabed interactions. Practical examples for engineering applications. ''Porous Models for Wave-seabed Interactions'' discusses the Phenomenon of wave-seabed interactions, which is a vital issue for coastal and geotechnical engineers involved in the design of foundations for marine structures such as pipelines, breakwaters, platforms, etc. The most important sections of this book will be the fully detailed theoretical models of wave-seabed interaction problem, which are particularly useful for postgraduate students and junior researchers entering the discipline of marine geotechnics and offshore engineering. This book also converts the research outcomes of theoretical studies to engineering applications that will provide front-line engineers with practical and effective tools in the assessment of seabed instability in engineering design.

  7. The Monash University Interactive Simple Climate Model

    Science.gov (United States)

    Dommenget, D.

    2013-12-01

    The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

  8. The Color Mutation Model for soft interaction

    International Nuclear Information System (INIS)

    Hwa, R.C.

    1998-01-01

    A comprehensive model for soft interaction is presented. It overcomes all the shortcomings of the existing models - in particular, the failure of Fritiof and Venus models in predicting the correct multiplicity fluctuations as observed in the intermittency data. The Color Mutation Model incorporates all the main features of hadronic interaction: eikonal formalism, parton model, evolution in color space according to QCD, branching of color neutral clusters, contraction due to confinement forces, dynamical self-similarity, resonance production, and power-law behavior of factorial moments. (author)

  9. N-barN interaction theoretical models

    International Nuclear Information System (INIS)

    Loiseau, B.

    1991-12-01

    In the framework of antinucleon-nucleon interaction theoretical models, our present understanding on the N-barN interaction is discussed, either from quark- or/and meson- and baryon-degrees of freedom, by considering the N-barN annihilation into mesons and the N-barN elastic and charge-exchange scattering. (author) 52 refs., 11 figs., 2 tabs

  10. Numerical modeling of magma-repository interactions

    NARCIS (Netherlands)

    Bokhove, Onno

    2001-01-01

    This report explains the numerical programs behind a comprehensive modeling effort of magma-repository interactions. Magma-repository interactions occur when a magma dike with high-volatile content magma ascends through surrounding rock and encounters a tunnel or drift filled with either a magmatic

  11. Discrete choice models for commuting interactions

    DEFF Research Database (Denmark)

    Rouwendal, Jan; Mulalic, Ismir; Levkovich, Or

    An emerging quantitative spatial economics literature models commuting interactions by a gravity equation that is mathematically equivalent to a multinomial logit model. This model is widely viewed as restrictive because of the independence of irrelevant alternatives (IIA) property that links sub...

  12. Modeling of soil-water-structure interaction

    DEFF Research Database (Denmark)

    Tang, Tian

    as the developed nonlinear soil displacements and stresses under monotonic and cyclic loading. With the FVM nonlinear coupled soil models as a basis, multiphysics modeling of wave-seabed-structure interaction is carried out. The computations are done in an open source code environment, OpenFOAM, where FVM models...

  13. Pose Estimation and Adaptive Robot Behaviour for Human-Robot Interaction

    DEFF Research Database (Denmark)

    Svenstrup, Mikael; Hansen, Søren Tranberg; Andersen, Hans Jørgen

    2009-01-01

    Abstract—This paper introduces a new method to determine a person’s pose based on laser range measurements. Such estimates are typically a prerequisite for any human-aware robot navigation, which is the basis for effective and timeextended interaction between a mobile robot and a human. The robot......’s pose. The resulting pose estimates are used to identify humans who wish to be approached and interacted with. The interaction motion of the robot is based on adaptive potential functions centered around the person that respect the persons social spaces. The method is tested in experiments...

  14. Adapting Modeling & SImulation for Network Enabled Operations

    Science.gov (United States)

    2011-03-01

    Awareness in Aerospace Operations ( AGARD - CP -478; pp. 5/1-5/8), Neuilly Sur Seine, France: NATO- AGARD . 243 ChApter 8 ShAping uk defenCe poliCy...Chapter 3 73 Increasing the Maturity of Command to Deal with Complex, Information Age Environments • Players could concentrate on their own areas; they...The results are shown in figure 4.16, which shows the fit for the first four serials. The model still explains 73 % of the vari- ability, down from 82

  15. A User-Centered Approach to Adaptive Hypertext Based on an Information Relevance Model

    Science.gov (United States)

    Mathe, Nathalie; Chen, James

    1994-01-01

    Rapid and effective to information in large electronic documentation systems can be facilitated if information relevant in an individual user's content can be automatically supplied to this user. However most of this knowledge on contextual relevance is not found within the contents of documents, it is rather established incrementally by users during information access. We propose a new model for interactively learning contextual relevance during information retrieval, and incrementally adapting retrieved information to individual user profiles. The model, called a relevance network, records the relevance of references based on user feedback for specific queries and user profiles. It also generalizes such knowledge to later derive relevant references for similar queries and profiles. The relevance network lets users filter information by context of relevance. Compared to other approaches, it does not require any prior knowledge nor training. More importantly, our approach to adaptivity is user-centered. It facilitates acceptance and understanding by users by giving them shared control over the adaptation without disturbing their primary task. Users easily control when to adapt and when to use the adapted system. Lastly, the model is independent of the particular application used to access information, and supports sharing of adaptations among users.

  16. Syndetic model of fundamental interactions

    Directory of Open Access Journals (Sweden)

    Ernest Ma

    2015-02-01

    Full Text Available The standard model of quarks and leptons is extended to connect three outstanding issues in particle physics and astrophysics: (1 the absence of strong CP nonconservation, (2 the existence of dark matter, and (3 the mechanism of nonzero neutrino masses, and that of the first family of quarks and leptons, all in the context of having only one Higgs boson in a renormalizable theory. Some phenomenological implications are discussed.

  17. Electron scattering in the interacting boson model

    NARCIS (Netherlands)

    Dieperink, AEL; Iachello, F; Rinat, A; Creswell, C

    1978-01-01

    It is suggested that the interacting boson model be used in the analysis of electron scattering data. Qualitative features of the expected behavior of the inelastic excitation of some 2 ÷ states inthe transitional Sm-Nd region are discussed

  18. Functional Modeling of Neural-Glia Interaction

    DEFF Research Database (Denmark)

    Postnov, D.E.; Brazhe, N.A.; Sosnovtseva, Olga

    2012-01-01

    Functional modeling is an approach that focuses on the representation of the qualitative dynamics of the individual components (e.g. cells) of a system and on the structure of the interaction network.......Functional modeling is an approach that focuses on the representation of the qualitative dynamics of the individual components (e.g. cells) of a system and on the structure of the interaction network....

  19. Adaptive Estimation of Heteroscedastic Money Demand Model of Pakistan

    Directory of Open Access Journals (Sweden)

    Muhammad Aslam

    2007-07-01

    Full Text Available For the problem of estimation of Money demand model of Pakistan, money supply (M1 shows heteroscedasticity of the unknown form. For estimation of such model we compare two adaptive estimators with ordinary least squares estimator and show the attractive performance of the adaptive estimators, namely, nonparametric kernel estimator and nearest neighbour regression estimator. These comparisons are made on the basis standard errors of the estimated coefficients, standard error of regression, Akaike Information Criteria (AIC value, and the Durban-Watson statistic for autocorrelation. We further show that nearest neighbour regression estimator performs better when comparing with the other nonparametric kernel estimator.

  20. Adaptive supervision: a theoretical model for social workers.

    Science.gov (United States)

    Latting, J E

    1986-01-01

    Two models of leadership styles are prominent in the management field: Blake and Mouton's managerial Grid and Hersey and Blanchard's Situational Leadership Model. Much of the research on supervisory styles in social work has been based on the former. A recent public debate between the two sets of theorists suggests that both have strengths and limitations. Accordingly, an adaptive model of social work supervision that combines elements of both theories is proposed.

  1. The adaptive cruise control vehicles in the cellular automata model

    International Nuclear Information System (INIS)

    Jiang Rui; Wu Qingsong

    2006-01-01

    This Letter presented a cellular automata model where the adaptive cruise control vehicles are modelled. In this model, the constant time headway policy is adopted. The fundamental diagram is presented. The simulation results are in good agreement with the analytical ones. The mixture of ACC vehicles with manually driven vehicles is investigated. It is shown that with the introduction of ACC vehicles, the jam can be suppressed

  2. Adaptive Shape Functions and Internal Mesh Adaptation for Modelling Progressive Failure in Adhesively Bonded Joints

    Science.gov (United States)

    Stapleton, Scott; Gries, Thomas; Waas, Anthony M.; Pineda, Evan J.

    2014-01-01

    Enhanced finite elements are elements with an embedded analytical solution that can capture detailed local fields, enabling more efficient, mesh independent finite element analysis. The shape functions are determined based on the analytical model rather than prescribed. This method was applied to adhesively bonded joints to model joint behavior with one element through the thickness. This study demonstrates two methods of maintaining the fidelity of such elements during adhesive non-linearity and cracking without increasing the mesh needed for an accurate solution. The first method uses adaptive shape functions, where the shape functions are recalculated at each load step based on the softening of the adhesive. The second method is internal mesh adaption, where cracking of the adhesive within an element is captured by further discretizing the element internally to represent the partially cracked geometry. By keeping mesh adaptations within an element, a finer mesh can be used during the analysis without affecting the global finite element model mesh. Examples are shown which highlight when each method is most effective in reducing the number of elements needed to capture adhesive nonlinearity and cracking. These methods are validated against analogous finite element models utilizing cohesive zone elements.

  3. Interactive physically-based structural modeling of hydrocarbon systems

    International Nuclear Information System (INIS)

    Bosson, Mael; Grudinin, Sergei; Bouju, Xavier; Redon, Stephane

    2012-01-01

    Hydrocarbon systems have been intensively studied via numerical methods, including electronic structure computations, molecular dynamics and Monte Carlo simulations. Typically, these methods require an initial structural model (atomic positions and types, topology, etc.) that may be produced using scripts and/or modeling tools. For many systems, however, these building methods may be ineffective, as the user may have to specify the positions of numerous atoms while maintaining structural plausibility. In this paper, we present an interactive physically-based modeling tool to construct structural models of hydrocarbon systems. As the user edits the geometry of the system, atomic positions are also influenced by the Brenner potential, a well-known bond-order reactive potential. In order to be able to interactively edit systems containing numerous atoms, we introduce a new adaptive simulation algorithm, as well as a novel algorithm to incrementally update the forces and the total potential energy based on the list of updated relative atomic positions. The computational cost of the adaptive simulation algorithm depends on user-defined error thresholds, and our potential update algorithm depends linearly with the number of updated bonds. This allows us to enable efficient physically-based editing, since the computational cost is decoupled from the number of atoms in the system. We show that our approach may be used to effectively build realistic models of hydrocarbon structures that would be difficult or impossible to produce using other tools.

  4. Vector-Interaction-Enhanced Bag Model

    Science.gov (United States)

    Cierniak, Mateusz; Klähn, Thomas; Fischer, Tobias; Bastian, Niels-Uwe

    2018-02-01

    A commonly applied quark matter model in astrophysics is the thermodynamic bag model (tdBAG). The original MIT bag model approximates the effect of quark confinement, but does not explicitly account for the breaking of chiral symmetry, an important property of Quantum Chromodynamics (QCD). It further ignores vector repulsion. The vector-interaction-enhanced bag model (vBag) improves the tdBAG approach by accounting for both dynamical chiral symmetry breaking and repulsive vector interactions. The latter is of particular importance to studies of dense matter in beta-equilibriumto explain the two solar mass maximum mass constraint for neutron stars. The model is motivated by analyses of QCD based Dyson-Schwinger equations (DSE), assuming a simple quark-quark contact interaction. Here, we focus on the study of hybrid neutron star properties resulting from the application of vBag and will discuss possible extensions.

  5. Stock market modeling and forecasting a system adaptation approach

    CERN Document Server

    Zheng, Xiaolian

    2013-01-01

    Stock Market Modeling translates experience in system adaptation gained in an engineering context to the modeling of financial markets with a view to improving the capture and understanding of market dynamics. The modeling process is considered as identifying a dynamic system in which a real stock market is treated as an unknown plant and the identification model proposed is tuned by feedback of the matching error. Like a physical system, a stock market exhibits fast and slow dynamics corresponding to internal (such as company value and profitability) and external forces (such as investor sentiment and commodity prices) respectively. The framework presented here, consisting of an internal model and an adaptive filter, is successful at considering both fast and slow market dynamics. A double selection method is efficacious in identifying input factors influential in market movements, revealing them to be both frequency- and market-dependent.   The authors present work on both developed and developing markets ...

  6. Addressing potential local adaptation in species distribution models: implications for conservation under climate change

    Science.gov (United States)

    Hällfors, Maria Helena; Liao, Jishan; Dzurisin, Jason D. K.; Grundel, Ralph; Hyvärinen, Marko; Towle, Kevin; Wu, Grace C.; Hellmann, Jessica J.

    2016-01-01

    Species distribution models (SDMs) have been criticized for involving assumptions that ignore or categorize many ecologically relevant factors such as dispersal ability and biotic interactions. Another potential source of model error is the assumption that species are ecologically uniform in their climatic tolerances across their range. Typically, SDMs to treat a species as a single entity, although populations of many species differ due to local adaptation or other genetic differentiation. Not taking local adaptation into account, may lead to incorrect range prediction and therefore misplaced conservation efforts. A constraint is that we often do not know the degree to which populations are locally adapted, however. Lacking experimental evidence, we still can evaluate niche differentiation within a species' range to promote better conservation decisions. We explore possible conservation implications of making type I or type II errors in this context. For each of two species, we construct three separate MaxEnt models, one considering the species as a single population and two of disjunct populations. PCA analyses and response curves indicate different climate characteristics in the current environments of the populations. Model projections into future climates indicate minimal overlap between areas predicted to be climatically suitable by the whole species versus population-based models. We present a workflow for addressing uncertainty surrounding local adaptation in SDM application and illustrate the value of conducting population-based models to compare with whole-species models. These comparisons might result in more cautious management actions when alternative range outcomes are considered.

  7. Student Modelling in Adaptive E-Learning Systems

    Directory of Open Access Journals (Sweden)

    Clemens Bechter

    2011-09-01

    Full Text Available Most e-Learning systems provide web-based learning so that students can access the same online courses via the Internet without adaptation, based on each student's profile and behavior. In an e-Learning system, one size does not fit all. Therefore, it is a challenge to make e-Learning systems that are suitably “adaptive”. The aim of adaptive e-Learning is to provide the students the appropriate content at the right time, means that the system is able to determine the knowledge level, keep track of usage, and arrange content automatically for each student for the best learning result. This study presents a proposed system which includes major adaptive features based on a student model. The proposed system is able to initialize the student model for determining the knowledge level of a student when the student registers for the course. After a student starts learning the lessons and doing many activities, the system can track information of the student until he/she takes a test. The student’s knowledge level, based on the test scores, is updated into the system for use in the adaptation process, which combines the student model with the domain model in order to deliver suitable course contents to the students. In this study, the proposed adaptive e-Learning system is implemented on an “Introduction to Java Programming Language” course, using LearnSquare software. After the system was tested, the results showed positive feedback towards the proposed system, especially in its adaptive capability.

  8. Adaptation.

    Science.gov (United States)

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  9. A model of mechanical interactions between heart and lungs.

    Science.gov (United States)

    Fontecave Jallon, Julie; Abdulhay, Enas; Calabrese, Pascale; Baconnier, Pierre; Gumery, Pierre-Yves

    2009-12-13

    To study the mechanical interactions between heart, lungs and thorax, we propose a mathematical model combining a ventilatory neuromuscular model and a model of the cardiovascular system, as described by Smith et al. (Smith, Chase, Nokes, Shaw & Wake 2004 Med. Eng. Phys.26, 131-139. (doi:10.1016/j.medengphy.2003.10.001)). The respiratory model has been adapted from Thibault et al. (Thibault, Heyer, Benchetrit & Baconnier 2002 Acta Biotheor. 50, 269-279. (doi:10.1023/A:1022616701863)); using a Liénard oscillator, it allows the activity of the respiratory centres, the respiratory muscles and rib cage internal mechanics to be simulated. The minimal haemodynamic system model of Smith includes the heart, as well as the pulmonary and systemic circulation systems. These two modules interact mechanically by means of the pleural pressure, calculated in the mechanical respiratory system, and the intrathoracic blood volume, calculated in the cardiovascular model. The simulation by the proposed model provides results, first, close to experimental data, second, in agreement with the literature results and, finally, highlighting the presence of mechanical cardiorespiratory interactions.

  10. The ADaptation and Anticipation Model (ADAM) of sensorimotor synchronization

    Science.gov (United States)

    van der Steen, M. C. (Marieke); Keller, Peter E.

    2013-01-01

    A constantly changing environment requires precise yet flexible timing of movements. Sensorimotor synchronization (SMS)—the temporal coordination of an action with events in a predictable external rhythm—is a fundamental human skill that contributes to optimal sensory-motor control in daily life. A large body of research related to SMS has focused on adaptive error correction mechanisms that support the synchronization of periodic movements (e.g., finger taps) with events in regular pacing sequences. The results of recent studies additionally highlight the importance of anticipatory mechanisms that support temporal prediction in the context of SMS with sequences that contain tempo changes. To investigate the role of adaptation and anticipatory mechanisms in SMS we introduce ADAM: an ADaptation and Anticipation Model. ADAM combines reactive error correction processes (adaptation) with predictive temporal extrapolation processes (anticipation) inspired by the computational neuroscience concept of internal models. The combination of simulations and experimental manipulations based on ADAM creates a novel and promising approach for exploring adaptation and anticipation in SMS. The current paper describes the conceptual basis and architecture of ADAM. PMID:23772211

  11. Relativistic direct interaction and hadron models

    International Nuclear Information System (INIS)

    Biswas, T.

    1984-01-01

    Direct interaction theories at a nonrelativistic level have been used successfully in several areas earlier (e.g. nuclear physics). But for hadron spectroscopy relativistic effects are important and hence the need for a relativistic direct interaction theory arises. It is the goal of this thesis to suggest such a theory which has the simplicity and the flexibility required for phenomenological model building. In general the introduction of relativity in a direct interaction theory is shown to be non-trivial. A first attempt leads to only an approximate form for allowed interactions. Even this is far too complex for phenomenological applicability. To simplify the model an extra spacelike particle called the vertex is introduced in any set of physical (timelike) particles. The vertex model is successfully used to fit and to predict experimental data on hadron spectra, γ and psi states fit very well with an interaction function inspired by QCD. Light mesons also fit reasonably well. Better forms of hyperfine interaction functions would be needed to improve the fitting of light mesons. The unexpectedly low pi meson mass is partially explained. Baryon ground states are fitted with unprecedented accuracy with very few adjustable parameters. For baryon excited states it is shown that better QCD motivated interaction functions are needed for a fit. Predictions for bb states in e + e - experiments are made to assist current experiments

  12. Adjoint based model adaptation for a linear problem

    NARCIS (Netherlands)

    Cnossen, J.M.; Bijl, H.; Koren, B.; Brummelen, van E.H.

    2004-01-01

    In aerospace engineering CFD is often applied to obtain values for quantities of interest which are global functionals of the solution. To optimise the balance between accuracy of the computed functional and CPU time we focus on dual-weighted adaptive hierarchical modelling of fluid flow. In this

  13. Adaptive Counseling and Therapy: An Integrative, Eclectic Model.

    Science.gov (United States)

    Howard, George S.; And Others

    1986-01-01

    Presents an integrative model, Adaptive Counseling and Therapy (ACT), for selecting a progression of therapist styles as clients move through developmental stages during the course of counseling and psychotherapy. ACT is intended to be useful to practitioners in case conceptualization and in the application of effective treatment planning.…

  14. A Model of Internal Communication in Adaptive Communication Systems.

    Science.gov (United States)

    Williams, M. Lee

    A study identified and categorized different types of internal communication systems and developed an applied model of internal communication in adaptive organizational systems. Twenty-one large organizations were selected for their varied missions and diverse approaches to managing internal communication. Individual face-to-face or telephone…

  15. Student feedback on an adapted appraisal model in resource ...

    African Journals Online (AJOL)

    Background. An appraisal model, a type of formal mentorship programme for a cohort of student doctors, is used at the University of Leeds, UK. The University of the Witwatersrand, Johannesburg, South Africa implemented an adapted version of the appraisal process that uses fewer resources. Objective. To explore ...

  16. A Neural Network Approach to Intention Modeling for User-Adapted Conversational Agents

    Directory of Open Access Journals (Sweden)

    David Griol

    2016-01-01

    Full Text Available Spoken dialogue systems have been proposed to enable a more natural and intuitive interaction with the environment and human-computer interfaces. In this contribution, we present a framework based on neural networks that allows modeling of the user’s intention during the dialogue and uses this prediction to dynamically adapt the dialogue model of the system taking into consideration the user’s needs and preferences. We have evaluated our proposal to develop a user-adapted spoken dialogue system that facilitates tourist information and services and provide a detailed discussion of the positive influence of our proposal in the success of the interaction, the information and services provided, and the quality perceived by the users.

  17. A Neural Network Approach to Intention Modeling for User-Adapted Conversational Agents.

    Science.gov (United States)

    Griol, David; Callejas, Zoraida

    2016-01-01

    Spoken dialogue systems have been proposed to enable a more natural and intuitive interaction with the environment and human-computer interfaces. In this contribution, we present a framework based on neural networks that allows modeling of the user's intention during the dialogue and uses this prediction to dynamically adapt the dialogue model of the system taking into consideration the user's needs and preferences. We have evaluated our proposal to develop a user-adapted spoken dialogue system that facilitates tourist information and services and provide a detailed discussion of the positive influence of our proposal in the success of the interaction, the information and services provided, and the quality perceived by the users.

  18. Modeling of hydrogen interactions with beryllium

    Energy Technology Data Exchange (ETDEWEB)

    Longhurst, G.R. [Lockheed Martin Idaho Technologies Co., Idaho Falls, ID (United States)

    1998-01-01

    In this paper, improved mathematical models are developed for hydrogen interactions with beryllium. This includes the saturation effect observed for high-flux implantation of ions from plasmas and retention of tritium produced from neutronic transmutations in beryllium. Use of the models developed is justified by showing how they can replicated experimental data using the TMAP4 tritium transport code. (author)

  19. Interacting p- Boson model with isospin

    International Nuclear Information System (INIS)

    Chen, C.H.-T.

    A description of collective states in self-conjugate nuclei is proposed, both odd-odd and even-even, in terms of an interacting isoscalar p-boson model. Within this model, two limiting cases can be identified with the anharmonic vibrator and axial rotor limits of the classical geometrical description. (Author) [pt

  20. Learning models of activities involving interacting objects

    DEFF Research Database (Denmark)

    Manfredotti, Cristina; Pedersen, Kim Steenstrup; Hamilton, Howard J.

    2013-01-01

    We propose the LEMAIO multi-layer framework, which makes use of hierarchical abstraction to learn models for activities involving multiple interacting objects from time sequences of data concerning the individual objects. Experiments in the sea navigation domain yielded learned models that were t...

  1. The Spiral-Interactive Program Evaluation Model.

    Science.gov (United States)

    Khaleel, Ibrahim Adamu

    1988-01-01

    Describes the spiral interactive program evaluation model, which is designed to evaluate vocational-technical education programs in secondary schools in Nigeria. Program evaluation is defined; utility oriented and process oriented models for evaluation are described; and internal and external evaluative factors and variables that define each…

  2. An introduction to the interacting boson model

    International Nuclear Information System (INIS)

    Iachello, F.

    1981-01-01

    This chapter introduces an alternative, algebraic, description of the properties of nuclei with several particles outside the closed shells. Focuses on the group theory of the interacting boson model. Discusses the group structure of the boson Hamiltonian; subalgebras; the classification of states; dynamical symmetry; electromagnetic transition rates; transitional classes; and general cases. Omits a discussion of the latest developments (e.g., the introduction of proton and neutron degrees of freedom); the spectra of odd-A nuclei; and the bosonfermion model. Concludes that the major new feature of the interacting boson model is the introduction and systematic exploitation of algebraic techniques, which allows a simple and detailed description of many nuclear properties

  3. Adaptation

    International Development Research Centre (IDRC) Digital Library (Canada)

    building skills, knowledge or networks on adaptation, ... the African partners leading the AfricaAdapt network, together with the UK-based Institute of Development Studies; and ... UNCCD Secretariat, Regional Coordination Unit for Africa, Tunis, Tunisia .... 26 Rural–urban Cooperation on Water Management in the Context of.

  4. Adaptive Maneuvering Frequency Method of Current Statistical Model

    Institute of Scientific and Technical Information of China (English)

    Wei Sun; Yongjian Yang

    2017-01-01

    Current statistical model(CSM) has a good performance in maneuvering target tracking. However, the fixed maneuvering frequency will deteriorate the tracking results, such as a serious dynamic delay, a slowly converging speedy and a limited precision when using Kalman filter(KF) algorithm. In this study, a new current statistical model and a new Kalman filter are proposed to improve the performance of maneuvering target tracking. The new model which employs innovation dominated subjection function to adaptively adjust maneuvering frequency has a better performance in step maneuvering target tracking, while a fluctuant phenomenon appears. As far as this problem is concerned, a new adaptive fading Kalman filter is proposed as well. In the new Kalman filter, the prediction values are amended in time by setting judgment and amendment rules,so that tracking precision and fluctuant phenomenon of the new current statistical model are improved. The results of simulation indicate the effectiveness of the new algorithm and the practical guiding significance.

  5. Adapting APSIM to model the physiology and genetics of complex adaptive traits in field crops.

    Science.gov (United States)

    Hammer, Graeme L; van Oosterom, Erik; McLean, Greg; Chapman, Scott C; Broad, Ian; Harland, Peter; Muchow, Russell C

    2010-05-01

    Progress in molecular plant breeding is limited by the ability to predict plant phenotype based on its genotype, especially for complex adaptive traits. Suitably constructed crop growth and development models have the potential to bridge this predictability gap. A generic cereal crop growth and development model is outlined here. It is designed to exhibit reliable predictive skill at the crop level while also introducing sufficient physiological rigour for complex phenotypic responses to become emergent properties of the model dynamics. The approach quantifies capture and use of radiation, water, and nitrogen within a framework that predicts the realized growth of major organs based on their potential and whether the supply of carbohydrate and nitrogen can satisfy that potential. The model builds on existing approaches within the APSIM software platform. Experiments on diverse genotypes of sorghum that underpin the development and testing of the adapted crop model are detailed. Genotypes differing in height were found to differ in biomass partitioning among organs and a tall hybrid had significantly increased radiation use efficiency: a novel finding in sorghum. Introducing these genetic effects associated with plant height into the model generated emergent simulated phenotypic differences in green leaf area retention during grain filling via effects associated with nitrogen dynamics. The relevance to plant breeding of this capability in complex trait dissection and simulation is discussed.

  6. Complex Environmental Data Modelling Using Adaptive General Regression Neural Networks

    Science.gov (United States)

    Kanevski, Mikhail

    2015-04-01

    The research deals with an adaptation and application of Adaptive General Regression Neural Networks (GRNN) to high dimensional environmental data. GRNN [1,2,3] are efficient modelling tools both for spatial and temporal data and are based on nonparametric kernel methods closely related to classical Nadaraya-Watson estimator. Adaptive GRNN, using anisotropic kernels, can be also applied for features selection tasks when working with high dimensional data [1,3]. In the present research Adaptive GRNN are used to study geospatial data predictability and relevant feature selection using both simulated and real data case studies. The original raw data were either three dimensional monthly precipitation data or monthly wind speeds embedded into 13 dimensional space constructed by geographical coordinates and geo-features calculated from digital elevation model. GRNN were applied in two different ways: 1) adaptive GRNN with the resulting list of features ordered according to their relevancy; and 2) adaptive GRNN applied to evaluate all possible models N [in case of wind fields N=(2^13 -1)=8191] and rank them according to the cross-validation error. In both cases training were carried out applying leave-one-out procedure. An important result of the study is that the set of the most relevant features depends on the month (strong seasonal effect) and year. The predictabilities of precipitation and wind field patterns, estimated using the cross-validation and testing errors of raw and shuffled data, were studied in detail. The results of both approaches were qualitatively and quantitatively compared. In conclusion, Adaptive GRNN with their ability to select features and efficient modelling of complex high dimensional data can be widely used in automatic/on-line mapping and as an integrated part of environmental decision support systems. 1. Kanevski M., Pozdnoukhov A., Timonin V. Machine Learning for Spatial Environmental Data. Theory, applications and software. EPFL Press

  7. Multisite Interactions in Lattice-Gas Models

    Science.gov (United States)

    Einstein, T. L.; Sathiyanarayanan, R.

    For detailed applications of lattice-gas models to surface systems, multisite interactions often play at least as significant a role as interactions between pairs of adatoms that are separated by a few lattice spacings. We recall that trio (3-adatom, non-pairwise) interactions do not inevitably create phase boundary asymmetries about half coverage. We discuss a sophisticated application to an experimental system and describe refinements in extracting lattice-gas energies from calculations of total energies of several different ordered overlayers. We describe how lateral relaxations complicate matters when there is direct interaction between the adatoms, an issue that is important when examining the angular dependence of step line tensions. We discuss the connector model as an alternative viewpoint and close with a brief account of recent work on organic molecule overlayers.

  8. Cranking model and attenuation of Coriolis interaction

    International Nuclear Information System (INIS)

    Lyutorovich, N.A.

    1987-01-01

    Description of rotational bands of odd deformed nuclei in the self-consistent Cranking model (SCM) is given. Causes of attenuation of the Coriolis interaction in the nuclei investigated are studied, and account of bound of one-particle degrees of freedom with rotation of the Hartree-Fock-Bogolyubov (HFB) self-consistent method is introduced additionally to SCM for qualitative agreement with experimental data. Merits and shortages of SCM in comparison with the quadruparticle-rotor (QR) model are discussed. All know ways for constructing the Hamiltonian QR model (or analog of such Hamiltonian) on the basis of the microscopic theory are shown to include two more approximations besides others: quasi-particle-rotational interaction leading to pair break is taken into account in the second order of the perturbation theory; some exchange diagrams are neglected among diagrams of the second order according to this interaction. If one makes the same approximations in SCM instead of HFB method, then the dependence of level energies on spin obtained in this case is turned out to be close to the results of the QR model. Besides, the problem on renormalization of matrix elements of quasi-rotational interaction occurs in such nonself-consistent approach as in the QR model. In so far as the similar problem does not occur in SCM, one can make the conclusion that the problem of attenuation of Coriolis interaction involves the approximations given above

  9. Interactive wood combustion for botanical tree models

    KAUST Repository

    Pirk, Sören

    2017-11-22

    We present a novel method for the combustion of botanical tree models. Tree models are represented as connected particles for the branching structure and a polygonal surface mesh for the combustion. Each particle stores biological and physical attributes that drive the kinetic behavior of a plant and the exothermic reaction of the combustion. Coupled with realistic physics for rods, the particles enable dynamic branch motions. We model material properties, such as moisture and charring behavior, and associate them with individual particles. The combustion is efficiently processed in the surface domain of the tree model on a polygonal mesh. A user can dynamically interact with the model by initiating fires and by inducing stress on branches. The flames realistically propagate through the tree model by consuming the available resources. Our method runs at interactive rates and supports multiple tree instances in parallel. We demonstrate the effectiveness of our approach through numerous examples and evaluate its plausibility against the combustion of real wood samples.

  10. Symmetry-adapted perturbation theory interaction energy decomposition for some noble gas complexes

    Science.gov (United States)

    Cukras, Janusz; Sadlej, Joanna

    2008-06-01

    This Letter contains a study of the interaction energy in HArF⋯N 2 and HArF⋯P 2 complexes. Symmetry-adapted perturbation theory (SAPT) has been applied to analyze the electrostatic, induction, dispersion and exchange contributions to the total interaction energy. The interaction energy has also been obtained by supermolecular method at the MP2, MP4, CCSD, CCSD(T) levels. The interaction energy for the studied complexes results from a partial cancelation of large attractive electrostatic, induction, dispersion terms by a strong repulsive exchange contribution. The induction and dispersion effects proved to be crucial in establishing the preference for the colinear HArF⋯N 2 and HArF⋯P 2 structures and shift direction of νHAr stretching vibrations.

  11. An Adaptable Neuromorphic Model of Orientation Selectivity Based On Floating Gate Dynamics

    Directory of Open Access Journals (Sweden)

    Priti eGupta

    2014-04-01

    Full Text Available The biggest challenge that the neuromorphic community faces today is to build systems that can be considered truly cognitive. Adaptation and self-organization are the two basic principles that underlie any cognitive function that the brain performs. If we can replicate this behavior in hardware, we move a step closer to our goal of having cognitive neuromorphic systems. Adaptive feature selectivity is a mechanism by which nature optimizes resources so as to have greater acuity for more abundant features. Developing neuromorphic feature maps can help design generic machines that can emulate this adaptive behavior. Most neuromorphic models that have attempted to build self-organizing systems, follow the approach of modeling abstract theoretical frameworks in hardware. While this is good from a modeling and analysis perspective, it may not lead to the most efficient hardware. On the other hand, exploiting hardware dynamics to build adaptive systems rather than forcing the hardware to behave like mathematical equations, seems to be a more robust methodology when it comes to developing actual hardware for real world applications. In this paper we use a novel time-staggered Winner Take All circuit, that exploits the adaptation dynamics of floating gate transistors, to model an adaptive cortical cell that demonstrates Orientation Selectivity, a well-known biological phenomenon observed in the visual cortex. The cell performs competitive learning, refining its weights in response to input patterns resembling different oriented bars, becoming selective to a particular oriented pattern. Different analysis performed on the cell such as orientation tuning, application of abnormal inputs, response to spatial frequency and periodic patterns reveal close similarity between our cell and its biological counterpart. Embedded in a RC grid, these cells interact diffusively exhibiting cluster formation, making way for adaptively building orientation selective maps

  12. Adaptive training algorithm for robot-assisted upper-arm rehabilitation, applicable to individualised and therapeutic human-robot interaction.

    Science.gov (United States)

    Chemuturi, Radhika; Amirabdollahian, Farshid; Dautenhahn, Kerstin

    2013-09-28

    Rehabilitation robotics is progressing towards developing robots that can be used as advanced tools to augment the role of a therapist. These robots are capable of not only offering more frequent and more accessible therapies but also providing new insights into treatment effectiveness based on their ability to measure interaction parameters. A requirement for having more advanced therapies is to identify how robots can 'adapt' to each individual's needs at different stages of recovery. Hence, our research focused on developing an adaptive interface for the GENTLE/A rehabilitation system. The interface was based on a lead-lag performance model utilising the interaction between the human and the robot. The goal of the present study was to test the adaptability of the GENTLE/A system to the performance of the user. Point-to-point movements were executed using the HapticMaster (HM) robotic arm, the main component of the GENTLE/A rehabilitation system. The points were displayed as balls on the screen and some of the points also had a real object, providing a test-bed for the human-robot interaction (HRI) experiment. The HM was operated in various modes to test the adaptability of the GENTLE/A system based on the leading/lagging performance of the user. Thirty-two healthy participants took part in the experiment comprising of a training phase followed by the actual-performance phase. The leading or lagging role of the participant could be used successfully to adjust the duration required by that participant to execute point-to-point movements, in various modes of robot operation and under various conditions. The adaptability of the GENTLE/A system was clearly evident from the durations recorded. The regression results showed that the participants required lower execution times with the help from a real object when compared to just a virtual object. The 'reaching away' movements were longer to execute when compared to the 'returning towards' movements irrespective of the

  13. Interacting orientations and instrumentalities to adapt a learning tool for health professionals

    Directory of Open Access Journals (Sweden)

    Kathrine L. Nygård

    2015-09-01

    Full Text Available Web-based instructional software offers new opportunities for collaborative, task-oriented in-service training. Planning and negotiation of content to adapt a web-based learning resource for nursing is the topic of this paper. We draw from Cultural Historical Activity Theory to elaborate the dialectical relationship of changing and stabilizing organizational practice. Local adaptation to create a domain-specific resource plays out as interactions of orientations and instrumentalities. Our analysis traces how orientations, i.e., in situ selection of knowledge and mobilization of experiences, and instrumentality, i.e., interpreted affordances of available cultural tools, interact. The adaptation processes are mediated by a set of new and current tools that interact with multiple orientations to ensure stability and promote change. Practice and project are introduced as intermediate, analytic concepts to assess tensions in the observed activity. Our analysis shows three central tensions, how they are introduced, addressed and subsequently resolved. Considering the opportunities help understand how engagement with technology can lead to new representations for introduction to a local knowledge domain.

  14. Direct model reference adaptive control with application to flexible robots

    Science.gov (United States)

    Steinvorth, Rodrigo; Kaufman, Howard; Neat, Gregory W.

    1992-01-01

    A modification to a direct command generator tracker-based model reference adaptive control (MRAC) system is suggested in this paper. This modification incorporates a feedforward into the reference model's output as well as the plant's output. Its purpose is to eliminate the bounded model following error present in steady state when previous MRAC systems were used. The algorithm was evaluated using the dynamics for a single-link flexible-joint arm. The results of these simulations show a response with zero steady state model following error. These results encourage further use of MRAC for various types of nonlinear plants.

  15. Effect of interactions for one-dimensional asymmetric exclusion processes under periodic and bath-adapted coupling environment

    Science.gov (United States)

    Midha, Tripti; Kolomeisky, Anatoly B.; Gupta, Arvind Kumar

    2018-04-01

    Stimulated by the effect of the nearest neighbor interactions in vehicular traffic and motor proteins, we study a 1D driven lattice gas model, in which the nearest neighbor particle interactions are taken in accordance with the thermodynamic concepts. The non-equilibrium steady-state properties of the system are analyzed under both open and periodic boundary conditions using a combination of cluster mean-field analysis and Monte Carlo simulations. Interestingly, the fundamental diagram of current versus density shows a complex behavior with a unimodal dependence for attractions and weak repulsions that turns into the bimodal behavior for stronger repulsive interactions. Specific details of system-reservoir coupling for the open system have a strong effect on the stationary phases. We produce the steady-state phase diagrams for the bulk-adapted coupling to the reservoir using the minimum and maximum current principles. The strength and nature of interaction energy has a striking influence on the number of stationary phases. We observe that interactions lead to correlations having a strong impact on the system dynamical properties. The correlation between any two sites decays exponentially as the distance between the sites increases. Moreover, they are found to be short-range for repulsions and long-range for attractions. Our results also suggest that repulsions and attractions asymmetrically modify the dynamics of interacting particles in exclusion processes.

  16. Modeling of interaction effects in granular systems

    International Nuclear Information System (INIS)

    El-Hilo, M.; Shatnawy, M.; Al-Rsheed, A.

    2000-01-01

    Interaction effects on the magnetic behavior of granular solid systems are examined using a numerical model which is capable of predicting the field, temperature and time dependence of magnetization. In this work, interaction effects on the temperature dependence of time viscosity coefficient S(T) and formation of minor hysteresis loops have been studied. The results for the time- and temperature dependence of remanence ratio have showed that the distribution of energy barriers f(ΔE) obtained depend critically on the strength and nature of interactions. These interactions-based changes in f(ΔE) can easily give a temperature-independent behavior of S(T) when these changes give a 1/ΔE behavior to the distribution of energy barriers. Thus, conclusions about macroscopic quantum tunneling must be carefully drawn when the temperature dependence of S(T) is used to probe for MQT effects. For minor hysteresis effects, the result shows that for the non-interacting case, no minor hysteresis loops occur and the loops are only predicted when the interaction field is positive. From these predictions, minor loops will form when the interaction field is strong enough to magnetize some moments during the recoil process back to zero field. Thus, these minor loops are originated from interaction driving irreversible changes along the recoil curve and the irreversible component of magnetization has no direct influence on the formation of these minor loops

  17. Adaptive surrogate model based multiobjective optimization for coastal aquifer management

    Science.gov (United States)

    Song, Jian; Yang, Yun; Wu, Jianfeng; Wu, Jichun; Sun, Xiaomin; Lin, Jin

    2018-06-01

    In this study, a novel surrogate model assisted multiobjective memetic algorithm (SMOMA) is developed for optimal pumping strategies of large-scale coastal groundwater problems. The proposed SMOMA integrates an efficient data-driven surrogate model with an improved non-dominated sorted genetic algorithm-II (NSGAII) that employs a local search operator to accelerate its convergence in optimization. The surrogate model based on Kernel Extreme Learning Machine (KELM) is developed and evaluated as an approximate simulator to generate the patterns of regional groundwater flow and salinity levels in coastal aquifers for reducing huge computational burden. The KELM model is adaptively trained during evolutionary search to satisfy desired fidelity level of surrogate so that it inhibits error accumulation of forecasting and results in correctly converging to true Pareto-optimal front. The proposed methodology is then applied to a large-scale coastal aquifer management in Baldwin County, Alabama. Objectives of minimizing the saltwater mass increase and maximizing the total pumping rate in the coastal aquifers are considered. The optimal solutions achieved by the proposed adaptive surrogate model are compared against those solutions obtained from one-shot surrogate model and original simulation model. The adaptive surrogate model does not only improve the prediction accuracy of Pareto-optimal solutions compared with those by the one-shot surrogate model, but also maintains the equivalent quality of Pareto-optimal solutions compared with those by NSGAII coupled with original simulation model, while retaining the advantage of surrogate models in reducing computational burden up to 94% of time-saving. This study shows that the proposed methodology is a computationally efficient and promising tool for multiobjective optimizations of coastal aquifer managements.

  18. Quark interchange model of baryon interactions

    Energy Technology Data Exchange (ETDEWEB)

    Maslow, J.N.

    1983-01-01

    The strong interactions at low energy are traditionally described by meson field theories treating hadrons as point-like particles. Here a mesonic quark interchange model (QIM) is presented which takes into account the finite size of the baryons and the internal quark structure of hadrons. The model incorporates the basic quark-gluon coupling of quantum chromodynamics (QCD) and the MIT bag model for color confinement. Because the quark-gluon coupling constant is large and it is assumed that confinement excludes overlap of hadronic quark bags except at high momenta, a non-perturbative method of nuclear interactions is presented. The QIM allows for exchange of quark quantum numbers at the bag boundary between colliding hadrons mediated at short distances by a gluon exchange between two quarks within the hadronic interior. This generates, via a Fierz transformation, an effective space-like t channel exchange of color singlet (q anti-q) states that can be identified with the low lying meson multiplets. Thus, a one boson exchange (OBE) model is obtained that allows for comparison with traditional phenomenological models of nuclear scattering. Inclusion of strange quarks enables calculation of YN scattering. The NN and YN coupling constants and the nucleon form factors show good agreement with experimental values as do the deuteron low energy data and the NN low energy phase shifts. Thus, the QIM provides a simple model of strong interactions that is chirally invariant, includes confinement and allows for an OBE form of hadronic interaction at low energies and momentum transfers.

  19. Quark interchange model of baryon interactions

    International Nuclear Information System (INIS)

    Maslow, J.N.

    1983-01-01

    The strong interactions at low energy are traditionally described by meson field theories treating hadrons as point-like particles. Here a mesonic quark interchange model (QIM) is presented which takes into account the finite size of the baryons and the internal quark structure of hadrons. The model incorporates the basic quark-gluon coupling of quantum chromodynamics (QCD) and the MIT bag model for color confinement. Because the quark-gluon coupling constant is large and it is assumed that confinement excludes overlap of hadronic quark bags except at high momenta, a non-perturbative method of nuclear interactions is presented. The QIM allows for exchange of quark quantum numbers at the bag boundary between colliding hadrons mediated at short distances by a gluon exchange between two quarks within the hadronic interior. This generates, via a Fierz transformation, an effective space-like t channel exchange of color singlet (q anti-q) states that can be identified with the low lying meson multiplets. Thus, a one boson exchange (OBE) model is obtained that allows for comparison with traditional phenomenological models of nuclear scattering. Inclusion of strange quarks enables calculation of YN scattering. The NN and YN coupling constants and the nucleon form factors show good agreement with experimental values as do the deuteron low energy data and the NN low energy phase shifts. Thus, the QIM provides a simple model of strong interactions that is chirally invariant, includes confinement and allows for an OBE form of hadronic interaction at low energies and momentum transfers

  20. A metasystem of framework model organisms to study emergence of new host-microbe adaptations.

    Science.gov (United States)

    Gopalan, Suresh; Ausubel, Frederick M

    2008-01-01

    An unintended consequence of global industrialization and associated societal rearrangements is new interactions of microbes and potential hosts (especially mammals and plants), providing an opportunity for the rapid emergence of host-microbe adaptation and eventual establishment of new microbe-related diseases. We describe a new model system comprising the model plant Arabidopsis thaliana and several microbes, each representing different modes of interaction, to study such "maladaptations". The model microbes include human and agricultural pathogens and microbes that are commonly considered innocuous. The system has a large knowledge base corresponding to each component organism and is amenable to high-throughput automation assisted perturbation screens for identifying components that modulate host-pathogen interactions. This would aid in the study of emergence and progression of host-microbe maladaptations in a controlled environment.

  1. Modelling of molten fuel/concrete interactions

    International Nuclear Information System (INIS)

    Muir, J.F.; Benjamin, A.S.

    1980-01-01

    A computer program modelling the interaction between molten core materials and structural concrete (CORCON) is being developed to provide quantitative estimates of fuel-melt accident consequences suitable for risk assessment of light water reactors. The principal features of CORCON are reviewed. Models developed for the principal interaction phenomena, inter-component heat transfer, concrete erosion, and melt/gas chemical reactions, are described. Alternative models for the controlling phenomenon, heat transfer from the molten pool to the surrounding concrete, are presented. These models, formulated in conjunction with the development of CORCON, are characterized by the presence or absence of either a gas film or viscous layer of molten concrete at the melt/concrete interface. Predictions of heat transfer based on these models compare favorably with available experimental data

  2. Zealotry effects on opinion dynamics in the adaptive voter model

    Science.gov (United States)

    Klamser, Pascal P.; Wiedermann, Marc; Donges, Jonathan F.; Donner, Reik V.

    2017-11-01

    The adaptive voter model has been widely studied as a conceptual model for opinion formation processes on time-evolving social networks. Past studies on the effect of zealots, i.e., nodes aiming to spread their fixed opinion throughout the system, only considered the voter model on a static network. Here we extend the study of zealotry to the case of an adaptive network topology co-evolving with the state of the nodes and investigate opinion spreading induced by zealots depending on their initial density and connectedness. Numerical simulations reveal that below the fragmentation threshold a low density of zealots is sufficient to spread their opinion to the whole network. Beyond the transition point, zealots must exhibit an increased degree as compared to ordinary nodes for an efficient spreading of their opinion. We verify the numerical findings using a mean-field approximation of the model yielding a low-dimensional set of coupled ordinary differential equations. Our results imply that the spreading of the zealots' opinion in the adaptive voter model is strongly dependent on the link rewiring probability and the average degree of normal nodes in comparison with that of the zealots. In order to avoid a complete dominance of the zealots' opinion, there are two possible strategies for the remaining nodes: adjusting the probability of rewiring and/or the number of connections with other nodes, respectively.

  3. Interactive Visual Analysis within Dynamic Ocean Models

    Science.gov (United States)

    Butkiewicz, T.

    2012-12-01

    The many observation and simulation based ocean models available today can provide crucial insights for all fields of marine research and can serve as valuable references when planning data collection missions. However, the increasing size and complexity of these models makes leveraging their contents difficult for end users. Through a combination of data visualization techniques, interactive analysis tools, and new hardware technologies, the data within these models can be made more accessible to domain scientists. We present an interactive system that supports exploratory visual analysis within large-scale ocean flow models. The currents and eddies within the models are illustrated using effective, particle-based flow visualization techniques. Stereoscopic displays and rendering methods are employed to ensure that the user can correctly perceive the complex 3D structures of depth-dependent flow patterns. Interactive analysis tools are provided which allow the user to experiment through the introduction of their customizable virtual dye particles into the models to explore regions of interest. A multi-touch interface provides natural, efficient interaction, with custom multi-touch gestures simplifying the otherwise challenging tasks of navigating and positioning tools within a 3D environment. We demonstrate the potential applications of our visual analysis environment with two examples of real-world significance: Firstly, an example of using customized particles with physics-based behaviors to simulate pollutant release scenarios, including predicting the oil plume path for the 2010 Deepwater Horizon oil spill disaster. Secondly, an interactive tool for plotting and revising proposed autonomous underwater vehicle mission pathlines with respect to the surrounding flow patterns predicted by the model; as these survey vessels have extremely limited energy budgets, designing more efficient paths allows for greater survey areas.

  4. An Agent Model Integrating an Adaptive Model for Environmental Dynamics

    NARCIS (Netherlands)

    Treur, J.; Umair, M.

    2011-01-01

    The environments in which agents are used often may be described by dynamical models, e.g., in the form of a set of differential equations. In this paper, an agent model is proposed that can perform model-based reasoning about the environment, based on a numerical (dynamical system) model of the

  5. Adaptation of streeter model - Phelps for water quality modeling in a large semi-arid basin.

    OpenAIRE

    Wagner Josà da Silva Mendes

    2014-01-01

    This paper presents an adaptation of the classical model of Streeter-Phelps modeling of Dissolved Oxygen (DO) and Biochemical Oxygen Demand (BOD) in the basin of the Upper Jaguaribe (25,000 km2), State of Ceara, Brazil. The adaptation of the model consisted of the numerical solution of differential equations Streeter-Phelps, considering the effect of incremental flows and sewage releases over the sections, as well as the variability of the sections of rivers and tributaries. For model calibra...

  6. Mirid (Hemiptera: Heteroptera) specialists of sticky plants: adaptations, interactions, and ecological implications.

    Science.gov (United States)

    Wheeler, Alfred G; Krimmel, Billy A

    2015-01-07

    Sticky plants-those having glandular trichomes (hairs) that produce adhesive, viscous exudates-can impede the movement of, and entrap, generalist insects. Disparate arthropod groups have adapted to these widespread and taxonomically diverse plants, yet their interactions with glandular hosts rarely are incorporated into broad ecological theory. Ecologists and entomologists might be unaware of even well-documented examples of insects that are sticky-plant specialists. The hemipteran family Miridae (more specifically, the omnivorous Dicyphini: Dicyphina) is the best-known group of arthropods that specializes on sticky plants. In the first synthesis of relationships with glandular plants for any insect family, we review mirid interactions with sticky hosts, including their adaptations (behavioral, morphological, and physiological) and mutualisms with carnivorous plants, and the ecological and agricultural implications of mirid-sticky plant systems. We propose that mirid research applies generally to tritrophic interactions on trichome-defended plants, enhances an understanding of insect-plant interactions, and provides information useful in managing crop pests.

  7. Modelling Safe Interface Interactions in Web Applications

    Science.gov (United States)

    Brambilla, Marco; Cabot, Jordi; Grossniklaus, Michael

    Current Web applications embed sophisticated user interfaces and business logic. The original interaction paradigm of the Web based on static content pages that are browsed by hyperlinks is, therefore, not valid anymore. In this paper, we advocate a paradigm shift for browsers and Web applications, that improves the management of user interaction and browsing history. Pages are replaced by States as basic navigation nodes, and Back/Forward navigation along the browsing history is replaced by a full-fledged interactive application paradigm, supporting transactions at the interface level and featuring Undo/Redo capabilities. This new paradigm offers a safer and more precise interaction model, protecting the user from unexpected behaviours of the applications and the browser.

  8. Adaptive filters and internal models: multilevel description of cerebellar function.

    Science.gov (United States)

    Porrill, John; Dean, Paul; Anderson, Sean R

    2013-11-01

    Cerebellar function is increasingly discussed in terms of engineering schemes for motor control and signal processing that involve internal models. To address the relation between the cerebellum and internal models, we adopt the chip metaphor that has been used to represent the combination of a homogeneous cerebellar cortical microcircuit with individual microzones having unique external connections. This metaphor indicates that identifying the function of a particular cerebellar chip requires knowledge of both the general microcircuit algorithm and the chip's individual connections. Here we use a popular candidate algorithm as embodied in the adaptive filter, which learns to decorrelate its inputs from a reference ('teaching', 'error') signal. This algorithm is computationally powerful enough to be used in a very wide variety of engineering applications. However, the crucial issue is whether the external connectivity required by such applications can be implemented biologically. We argue that some applications appear to be in principle biologically implausible: these include the Smith predictor and Kalman filter (for state estimation), and the feedback-error-learning scheme for adaptive inverse control. However, even for plausible schemes, such as forward models for noise cancellation and novelty-detection, and the recurrent architecture for adaptive inverse control, there is unlikely to be a simple mapping between microzone function and internal model structure. This initial analysis suggests that cerebellar involvement in particular behaviours is therefore unlikely to have a neat classification into categories such as 'forward model'. It is more likely that cerebellar microzones learn a task-specific adaptive-filter operation which combines a number of signal-processing roles. Copyright © 2012 Elsevier Ltd. All rights reserved.

  9. A new adaptive hybrid electromagnetic damper: modelling, optimization, and experiment

    International Nuclear Information System (INIS)

    Asadi, Ehsan; Ribeiro, Roberto; Behrad Khamesee, Mir; Khajepour, Amir

    2015-01-01

    This paper presents the development of a new electromagnetic hybrid damper which provides regenerative adaptive damping force for various applications. Recently, the introduction of electromagnetic technologies to the damping systems has provided researchers with new opportunities for the realization of adaptive semi-active damping systems with the added benefit of energy recovery. In this research, a hybrid electromagnetic damper is proposed. The hybrid damper is configured to operate with viscous and electromagnetic subsystems. The viscous medium provides a bias and fail-safe damping force while the electromagnetic component adds adaptability and the capacity for regeneration to the hybrid design. The electromagnetic component is modeled and analyzed using analytical (lumped equivalent magnetic circuit) and electromagnetic finite element method (FEM) (COMSOL ® software package) approaches. By implementing both modeling approaches, an optimization for the geometric aspects of the electromagnetic subsystem is obtained. Based on the proposed electromagnetic hybrid damping concept and the preliminary optimization solution, a prototype is designed and fabricated. A good agreement is observed between the experimental and FEM results for the magnetic field distribution and electromagnetic damping forces. These results validate the accuracy of the modeling approach and the preliminary optimization solution. An analytical model is also presented for viscous damping force, and is compared with experimental results The results show that the damper is able to produce damping coefficients of 1300 and 0–238 N s m −1 through the viscous and electromagnetic components, respectively. (paper)

  10. Adapting interaction environments to diverse users through online action set selection

    CSIR Research Space (South Africa)

    Hassan Mahmud, MM

    2014-06-01

    Full Text Available their personal optimum. We introduce a new class of problem in interface personalization where the task of the adaptive interface is to choose the subset of actions of the full interface to present to the user. In formalizing this problem, we model the user as a...

  11. Co-adapting societal and ecological interactions following large disturbances in urban park woodlands

    Science.gov (United States)

    Margaret Carreiro; Wayne Zipperer

    2011-01-01

    The responses of urban park woodlands to large disturbances provide the opportunity to identify and examine linkages in social-ecological systems in urban landscapes.We propose that the Panarchy model consisting of hierarchically nested adaptive cycles provides a useful framework to evaluate those linkages.We use two case studies as examples – Cherokee Park in...

  12. Effect of a care plan based on Roy adaptation model biological dimension on stroke patients' physiologic adaptation level.

    Science.gov (United States)

    Alimohammadi, Nasrollah; Maleki, Bibi; Shahriari, Mohsen; Chitsaz, Ahmad

    2015-01-01

    Stroke is a stressful event with several functional, physical, psychological, social, and economic problems that affect individuals' different living balances. With coping strategies, patients try to control these problems and return to their natural life. The aim of this study is to investigate the effect of a care plan based on Roy adaptation model biological dimension on stroke patients' physiologic adaptation level. This study is a clinical trial in which 50 patients, affected by brain stroke and being admitted in the neurology ward of Kashani and Alzahra hospitals, were randomly assigned to control and study groups in Isfahan in 2013. Roy adaptation model care plan was administered in biological dimension in the form of four sessions and phone call follow-ups for 1 month. The forms related to Roy adaptation model were completed before and after intervention in the two groups. Chi-square test and t-test were used to analyze the data through SPSS 18. There was a significant difference in mean score of adaptation in physiological dimension in the study group after intervention (P adaptation in the patients affected by brain stroke in the study and control groups showed a significant increase in physiological dimension in the study group by 47.30 after intervention (P adaptation model biological dimension care plan can result in an increase in adaptation in patients with stroke in physiological dimension. Nurses can use this model for increasing patients' adaptation.

  13. Direct Model Reference Adaptive Control for a Magnetic Bearing

    Energy Technology Data Exchange (ETDEWEB)

    Durling, Mike [Rensselaer Polytechnic Inst., Troy, NY (United States)

    1999-11-01

    A Direct Model Reference Adaptive Controller (DMRAC) is applied to a magnetic bearing test stand. The bearing of interest is the MBC 500 Magnetic Bearing System manufactured by Magnetic Moments, LLC. The bearing model is presented in state space form and the system transfer function is measured directly using a closed-loop swept sine technique. Next, the bearing models are used to design a phase-lead controller, notch filter and then a DMRAC. The controllers are tuned in simulations and finally are implemented using a combination of MATLAB, SIMULINK and dSPACE. The results show a successful implementation of a DMRAC on the magnetic bearing hardware.

  14. Transcultural adaptation into Portuguese of an instrument for pain evaluation based on the biopsychosocial model

    Directory of Open Access Journals (Sweden)

    Monique Rocha Peixoto dos Santos

    Full Text Available Abstract Introduction: Pain is an individual experience influenced by multiple interacting factors. The “biopsychosocial” care model has gained popularity in response to growing research evidence indicating the influence of biological, psychological, and social factors on the pain experience. The implementation of this model is a challenge in the practice of the health professional. Objective: To perform the transcultural adaptation of the SCEBS method into Brazilian Portuguese. Methods: The instrument was translated and applied to 50 healthy subjects and 50 participants with non-specific chronic pain in the spine. The process of cross-cultural adaptation included the following steps: transcultural adaptation, content analysis of the scale, pre-test, revision, back-translation review, cross-cultural adaptation, revised text correction and final report. Results: The translated and adapted 51-item Portuguese version of the SCEBS method produced an instrument called SCEBS-BR. In the assessment by the target population, 50 adult users of the Brazilian Unified Health System answered the questionnaire and showed good understanding of the instrument on the verbal rating scale. Conclusion: The SCEBS-BR was proved to be easily understandable, showing good semantic validation regardless of schooling level or age, and can be considered adequate for clinical use.

  15. New aspects of the interacting boson model

    International Nuclear Information System (INIS)

    Nadzakov, E.G.; Mikhajlov, I.N.

    1987-01-01

    In the framework of the boson space extension called interacting multiboson model: conserving the model basic dynamic symmetries, the s p d f boson model is considered. It does not destruct the intermediate mass nuclei simple description, and at the same time includes the number of levels and transitions, inaccessible to the usual s d boson model. Its applicability, even in a brief version, to the recently observed asymmetric nuclear shape effect in the Ra-Th-U region (and in other regions) with possible octupole and dipole deformation is demonstrated. It is done by reproducing algebraically the yrast lines of nuclei with vibrational, transitional and rotational spectra

  16. ERM model analysis for adaptation to hydrological model errors

    Science.gov (United States)

    Baymani-Nezhad, M.; Han, D.

    2018-05-01

    Hydrological conditions are changed continuously and these phenomenons generate errors on flood forecasting models and will lead to get unrealistic results. Therefore, to overcome these difficulties, a concept called model updating is proposed in hydrological studies. Real-time model updating is one of the challenging processes in hydrological sciences and has not been entirely solved due to lack of knowledge about the future state of the catchment under study. Basically, in terms of flood forecasting process, errors propagated from the rainfall-runoff model are enumerated as the main source of uncertainty in the forecasting model. Hence, to dominate the exciting errors, several methods have been proposed by researchers to update the rainfall-runoff models such as parameter updating, model state updating, and correction on input data. The current study focuses on investigations about the ability of rainfall-runoff model parameters to cope with three types of existing errors, timing, shape and volume as the common errors in hydrological modelling. The new lumped model, the ERM model, has been selected for this study to evaluate its parameters for its use in model updating to cope with the stated errors. Investigation about ten events proves that the ERM model parameters can be updated to cope with the errors without the need to recalibrate the model.

  17. Modelling hadronic interactions in HEP MC generators

    CERN Document Server

    Skands, Peter

    2015-01-01

    HEP event generators aim to describe high-energy collisions in full exclusive detail. They combine perturbative matrix elements and parton showers with dynamical models of less well-understood phenomena such as hadronization, diffraction, and the so-called underlying event. We briefly summarise some of the main concepts relevant to the modelling of soft/inclusive hadron interactions in MC generators, in particular PYTHIA, with emphasis on questions recently highlighted by LHC data.

  18. Interacting dark energy model and thermal stability

    Energy Technology Data Exchange (ETDEWEB)

    Bhandari, Pritikana; Haldar, Sourav; Chakraborty, Subenoy [Jadavpur University, Department of Mathematics, Kolkata, West Bengal (India)

    2017-12-15

    In the background of the homogeneous and isotropic FLRW model, the thermodynamics of the interacting DE fluid is investigated in the present work. By studying the thermodynamical parameters, namely the heat capacities and the compressibilities, both thermal and mechanical stability are discussed and the restrictions on the equation of state parameter of the dark fluid are analyzed. (orig.)

  19. Intuitionistic preference modeling and interactive decision making

    CERN Document Server

    Xu, Zeshui

    2014-01-01

    This book offers an in-depth and comprehensive introduction to the priority methods of intuitionistic preference relations, the consistency and consensus improving procedures for intuitionistic preference relations, the approaches to group decision making based on intuitionistic preference relations, the approaches and models for interactive decision making with intuitionistic fuzzy information, and the extended results in interval-valued intuitionistic fuzzy environments.

  20. QSO evolution in the interaction model

    International Nuclear Information System (INIS)

    De Robertis, M.

    1985-01-01

    QSO evolution is investigated according to the interaction hypothesis described most recently by Stockton (1982), in which activity results from an interaction between two galaxies resulting in the transfer of gas onto a supermassive black hole (SBH) at the center of at least one participant. Explicit models presented here for interactions in cluster environments show that a peak QSO population can be formed in this way at zroughly-equal2--3, with little activity prior to this epoch. Calculated space densities match those inferred from observations for this epoch. Substantial density evolution is expected in such models, since, after virialization, conditions in the cores of rich clusters lead to the depletion of gas-rich systems through ram-pressure stripping. Density evolution parameters of 6--12 are easily accounted for. At smaller redshifts, however, QSOs should be found primarily in poor clusters or groups. Probability estimates provided by this model are consistent with local estimates for the observed number of QSOs per interaction. Significant luminosity-dependent evolution might also be expected in these models. It is suggested that the mean SBH mass increases with lookback time, leading to a statistical brightening with redshift. Undoubtedly, both forms of evolution contribute to the overall QSO luminosity function

  1. Sphericity in the interacting boson model

    International Nuclear Information System (INIS)

    Ogata, H.

    1977-01-01

    The interacting boson model (IBM) of Arima and Iachello is examined. The transition between the rotational and vibrational modes of even-even nuclei is presented as a function of a sphericity parameter, which is determined primarily from yrast band spectra. The backbending feature is reasonably reproduced. (author)

  2. Electron scattering in the interacting boson model

    International Nuclear Information System (INIS)

    Dieperink, A.E.L.; Iachello, F.; Creswell, C.

    1978-01-01

    It is suggested that the interacting boson model be used in the analysis of electron scattering data. Qualitative features of the expected behavior of the inelastic excitation of some 2 + states in the transitional Sm-Nd region are discussed. (Auth.)

  3. Interacting dark energy model and thermal stability

    International Nuclear Information System (INIS)

    Bhandari, Pritikana; Haldar, Sourav; Chakraborty, Subenoy

    2017-01-01

    In the background of the homogeneous and isotropic FLRW model, the thermodynamics of the interacting DE fluid is investigated in the present work. By studying the thermodynamical parameters, namely the heat capacities and the compressibilities, both thermal and mechanical stability are discussed and the restrictions on the equation of state parameter of the dark fluid are analyzed. (orig.)

  4. A fashion model with social interaction

    Science.gov (United States)

    Nakayama, Shoichiro; Nakamura, Yasuyuki

    2004-06-01

    In general, it is difficult to investigate social phenomena mathematically or quantitatively due to non-linear interactions. Statistical physics can provide powerful methods for studying social phenomena with interactions, and could be very useful for them. In this study, we take a focus on fashion as a social phenomenon with interaction. The social interaction considered here are “bandwagon effect” and “snob effect.” In the bandwagon effect, the correlation between one's behavior and others is positive. People feel fashion weary or boring when it is overly popular. This is the snob effect. It is assumed that the fashion phenomenon is formed by the aggregation of individual's binary choice, that is, the fashion is adopted or not. We formulate the fashion phenomenon as the logit model, which is based on the random utility theory in social science, especially economics. The model derived here basically has the similarity with the pioneering model by Weidlich (Phys. Rep. 204 (1991) 1), which was derived from the master equation, the Langevin equation, or the Fokker-Planck equation. This study seems to give the behavioral or behaviormetrical foundation to his model. As a result of dynamical analysis, it is found that in the case that both the bandwagon effect and the snob effect work, periodic or chaotic behavior of fashion occurs under certain conditions.

  5. Evaluation-Function-based Model-free Adaptive Fuzzy Control

    Directory of Open Access Journals (Sweden)

    Agus Naba

    2016-12-01

    Full Text Available Designs of adaptive fuzzy controllers (AFC are commonly based on the Lyapunov approach, which requires a known model of the controlled plant. They need to consider a Lyapunov function candidate as an evaluation function to be minimized. In this study these drawbacks were handled by designing a model-free adaptive fuzzy controller (MFAFC using an approximate evaluation function defined in terms of the current state, the next state, and the control action. MFAFC considers the approximate evaluation function as an evaluative control performance measure similar to the state-action value function in reinforcement learning. The simulation results of applying MFAFC to the inverted pendulum benchmark verified the proposed scheme’s efficacy.

  6. On valuing information in adaptive-management models.

    Science.gov (United States)

    Moore, Alana L; McCarthy, Michael A

    2010-08-01

    Active adaptive management looks at the benefit of using strategies that may be suboptimal in the near term but may provide additional information that will facilitate better management in the future. In many adaptive-management problems that have been studied, the optimal active and passive policies (accounting for learning when designing policies and designing policy on the basis of current best information, respectively) are very similar. This seems paradoxical; when faced with uncertainty about the best course of action, managers should spend very little effort on actively designing programs to learn about the system they are managing. We considered two possible reasons why active and passive adaptive solutions are often similar. First, the benefits of learning are often confined to the particular case study in the modeled scenario, whereas in reality information gained from local studies is often applied more broadly. Second, management objectives that incorporate the variance of an estimate may place greater emphasis on learning than more commonly used objectives that aim to maximize an expected value. We explored these issues in a case study of Merri Creek, Melbourne, Australia, in which the aim was to choose between two options for revegetation. We explicitly incorporated monitoring costs in the model. The value of the terminal rewards and the choice of objective both influenced the difference between active and passive adaptive solutions. Explicitly considering the cost of monitoring provided a different perspective on how the terminal reward and management objective affected learning. The states for which it was optimal to monitor did not always coincide with the states in which active and passive adaptive management differed. Our results emphasize that spending resources on monitoring is only optimal when the expected benefits of the options being considered are similar and when the pay-off for learning about their benefits is large.

  7. Statistical pairwise interaction model of stock market

    Science.gov (United States)

    Bury, Thomas

    2013-03-01

    Financial markets are a classical example of complex systems as they are compound by many interacting stocks. As such, we can obtain a surprisingly good description of their structure by making the rough simplification of binary daily returns. Spin glass models have been applied and gave some valuable results but at the price of restrictive assumptions on the market dynamics or they are agent-based models with rules designed in order to recover some empirical behaviors. Here we show that the pairwise model is actually a statistically consistent model with the observed first and second moments of the stocks orientation without making such restrictive assumptions. This is done with an approach only based on empirical data of price returns. Our data analysis of six major indices suggests that the actual interaction structure may be thought as an Ising model on a complex network with interaction strengths scaling as the inverse of the system size. This has potentially important implications since many properties of such a model are already known and some techniques of the spin glass theory can be straightforwardly applied. Typical behaviors, as multiple equilibria or metastable states, different characteristic time scales, spatial patterns, order-disorder, could find an explanation in this picture.

  8. Thermodynamic data bases and calculation code adapted to the modelling of molten core concrete interaction (M.C.C.I.) phenomena, developed jointly by Thermodata and the ''Institut de Protection et de Surete Nucleaire'' (France)

    International Nuclear Information System (INIS)

    Cenerino, G.

    1992-01-01

    An oxide data base containing the main five oxides Al 2 O 3 , CaO, SiO 2 , UO 2 and ZrO 2 of a corium obtained if the reactor core melts through the vessel and slumps into the concrete reactor cavity is developed using the GEMINI2 code. This oxide quinary system study takes into account physical realistic thermodynamical modeling of all the possible equilibrium species of the system. Two applications are presented: the determination of liquidus and solidus temperatures of some selected mixtures of the quinary system (core: UO 2 -ZrO 2 and concrete: Al 2 O 3 -CaO-SiO 2 ), a better modeling of the fission products release by vaporization from the corium. (A.B.). 5 refs., 2 figs

  9. Multivariable robust adaptive controller using reduced-order model

    Directory of Open Access Journals (Sweden)

    Wei Wang

    1990-04-01

    Full Text Available In this paper a multivariable robust adaptive controller is presented for a plant with bounded disturbances and unmodeled dynamics due to plant-model order mismatches. The robust stability of the closed-loop system is achieved by using the normalization technique and the least squares parameter estimation scheme with dead zones. The weighting polynomial matrices are incorporated into the control law, so that the open-loop unstable or/and nonminimum phase plants can be handled.

  10. Goal-oriented model adaptivity for viscous incompressible flows

    KAUST Repository

    van Opstal, T. M.

    2015-04-04

    © 2015, Springer-Verlag Berlin Heidelberg. In van Opstal et al. (Comput Mech 50:779–788, 2012) airbag inflation simulations were performed where the flow was approximated by Stokes flow. Inside the intricately folded initial geometry the Stokes assumption is argued to hold. This linearity assumption leads to a boundary-integral representation, the key to bypassing mesh generation and remeshing. It therefore enables very large displacements with near-contact. However, such a coarse assumption cannot hold throughout the domain, where it breaks down one needs to revert to the original model. The present work formalizes this idea. A model adaptive approach is proposed, in which the coarse model (a Stokes boundary-integral equation) is locally replaced by the original high-fidelity model (Navier–Stokes) based on a-posteriori estimates of the error in a quantity of interest. This adaptive modeling framework aims at taking away the burden and heuristics of manually partitioning the domain while providing new insight into the physics. We elucidate how challenges pertaining to model disparity can be addressed. Essentially, the solution in the interior of the coarse model domain is reconstructed as a post-processing step. We furthermore present a two-dimensional numerical experiments to show that the error estimator is reliable.

  11. Enhancing Perception with Tactile Object Recognition in Adaptive Grippers for Human–Robot Interaction

    Directory of Open Access Journals (Sweden)

    Juan M. Gandarias

    2018-02-01

    Full Text Available The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. Here, the integration of the tactile sensor in adaptive grippers is evaluated, measuring the performance of an object recognition task based on deep convolutional neural networks (DCNNs using a flexible sensor mounted in adaptive grippers. A total of 15 classes with 50 tactile images each were trained, including human body parts and common environment objects, in semi-rigid and flexible adaptive grippers based on the fin ray effect. The classifier was compared against the rigid configuration and a support vector machine classifier (SVM. Finally, a two-level output network has been proposed to provide both object-type recognition and human/non-human classification. Sensors in adaptive grippers have a higher number of non-null tactels (up to 37% more, with a lower mean of pressure values (up to 72% less than when using a rigid sensor, with a softer grip, which is needed in physical human–robot interaction (pHRI. A semi-rigid implementation with 95.13% object recognition rate was chosen, even though the human/non-human classification had better results (98.78% with a rigid sensor.

  12. Enhancing Perception with Tactile Object Recognition in Adaptive Grippers for Human-Robot Interaction.

    Science.gov (United States)

    Gandarias, Juan M; Gómez-de-Gabriel, Jesús M; García-Cerezo, Alfonso J

    2018-02-26

    The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. Here, the integration of the tactile sensor in adaptive grippers is evaluated, measuring the performance of an object recognition task based on deep convolutional neural networks (DCNNs) using a flexible sensor mounted in adaptive grippers. A total of 15 classes with 50 tactile images each were trained, including human body parts and common environment objects, in semi-rigid and flexible adaptive grippers based on the fin ray effect. The classifier was compared against the rigid configuration and a support vector machine classifier (SVM). Finally, a two-level output network has been proposed to provide both object-type recognition and human/non-human classification. Sensors in adaptive grippers have a higher number of non-null tactels (up to 37% more), with a lower mean of pressure values (up to 72% less) than when using a rigid sensor, with a softer grip, which is needed in physical human-robot interaction (pHRI). A semi-rigid implementation with 95.13% object recognition rate was chosen, even though the human/non-human classification had better results (98.78%) with a rigid sensor.

  13. Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

    Energy Technology Data Exchange (ETDEWEB)

    Park, Sang Hyun [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Gao, Yaozong, E-mail: yzgao@cs.unc.edu [Department of Computer Science, Department of Radiology, and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Shi, Yinghuan, E-mail: syh@nju.edu.cn [State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023 (China); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul 136-713 (Korea, Republic of)

    2014-11-01

    Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to

  14. Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

    International Nuclear Information System (INIS)

    Park, Sang Hyun; Gao, Yaozong; Shi, Yinghuan; Shen, Dinggang

    2014-01-01

    Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to

  15. Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection.

    Science.gov (United States)

    Park, Sang Hyun; Gao, Yaozong; Shi, Yinghuan; Shen, Dinggang

    2014-11-01

    Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to evaluate both the efficiency

  16. Language Model Combination and Adaptation Using Weighted Finite State Transducers

    Science.gov (United States)

    Liu, X.; Gales, M. J. F.; Hieronymus, J. L.; Woodland, P. C.

    2010-01-01

    In speech recognition systems language model (LMs) are often constructed by training and combining multiple n-gram models. They can be either used to represent different genres or tasks found in diverse text sources, or capture stochastic properties of different linguistic symbol sequences, for example, syllables and words. Unsupervised LM adaption may also be used to further improve robustness to varying styles or tasks. When using these techniques, extensive software changes are often required. In this paper an alternative and more general approach based on weighted finite state transducers (WFSTs) is investigated for LM combination and adaptation. As it is entirely based on well-defined WFST operations, minimum change to decoding tools is needed. A wide range of LM combination configurations can be flexibly supported. An efficient on-the-fly WFST decoding algorithm is also proposed. Significant error rate gains of 7.3% relative were obtained on a state-of-the-art broadcast audio recognition task using a history dependently adapted multi-level LM modelling both syllable and word sequences

  17. Covert rapid action-memory simulation (CRAMS): a hypothesis of hippocampal-prefrontal interactions for adaptive behavior.

    Science.gov (United States)

    Wang, Jane X; Cohen, Neal J; Voss, Joel L

    2015-01-01

    Effective choices generally require memory, yet little is known regarding the cognitive or neural mechanisms that allow memory to influence choices. We outline a new framework proposing that covert memory processing of hippocampus interacts with action-generation processing of prefrontal cortex in order to arrive at optimal, memory-guided choices. Covert, rapid action-memory simulation (CRAMS) is proposed here as a framework for understanding cognitive and/or behavioral choices, whereby prefrontal-hippocampal interactions quickly provide multiple simulations of potential outcomes used to evaluate the set of possible choices. We hypothesize that this CRAMS process is automatic, obligatory, and covert, meaning that many cycles of action-memory simulation occur in response to choice conflict without an individual's necessary intention and generally without awareness of the simulations, leading to adaptive behavior with little perceived effort. CRAMS is thus distinct from influential proposals that adaptive memory-based behavior in humans requires consciously experienced memory-based construction of possible future scenarios and deliberate decisions among possible future constructions. CRAMS provides an account of why hippocampus has been shown to make critical contributions to the short-term control of behavior, and it motivates several new experimental approaches and hypotheses that could be used to better understand the ubiquitous role of prefrontal-hippocampal interactions in situations that require adaptively using memory to guide choices. Importantly, this framework provides a perspective that allows for testing decision-making mechanisms in a manner that translates well across human and nonhuman animal model systems. Copyright © 2014 Elsevier Inc. All rights reserved.

  18. An adaptive distance measure for use with nonparametric models

    International Nuclear Information System (INIS)

    Garvey, D. R.; Hines, J. W.

    2006-01-01

    Distance measures perform a critical task in nonparametric, locally weighted regression. Locally weighted regression (LWR) models are a form of 'lazy learning' which construct a local model 'on the fly' by comparing a query vector to historical, exemplar vectors according to a three step process. First, the distance of the query vector to each of the exemplar vectors is calculated. Next, these distances are passed to a kernel function, which converts the distances to similarities or weights. Finally, the model output or response is calculated by performing locally weighted polynomial regression. To date, traditional distance measures, such as the Euclidean, weighted Euclidean, and L1-norm have been used as the first step in the prediction process. Since these measures do not take into consideration sensor failures and drift, they are inherently ill-suited for application to 'real world' systems. This paper describes one such LWR model, namely auto associative kernel regression (AAKR), and describes a new, Adaptive Euclidean distance measure that can be used to dynamically compensate for faulty sensor inputs. In this new distance measure, the query observations that lie outside of the training range (i.e. outside the minimum and maximum input exemplars) are dropped from the distance calculation. This allows for the distance calculation to be robust to sensor drifts and failures, in addition to providing a method for managing inputs that exceed the training range. In this paper, AAKR models using the standard and Adaptive Euclidean distance are developed and compared for the pressure system of an operating nuclear power plant. It is shown that using the standard Euclidean distance for data with failed inputs, significant errors in the AAKR predictions can result. By using the Adaptive Euclidean distance it is shown that high fidelity predictions are possible, in spite of the input failure. In fact, it is shown that with the Adaptive Euclidean distance prediction

  19. Anisotropic mesh adaptation for marine ice-sheet modelling

    Science.gov (United States)

    Gillet-Chaulet, Fabien; Tavard, Laure; Merino, Nacho; Peyaud, Vincent; Brondex, Julien; Durand, Gael; Gagliardini, Olivier

    2017-04-01

    Improving forecasts of ice-sheets contribution to sea-level rise requires, amongst others, to correctly model the dynamics of the grounding line (GL), i.e. the line where the ice detaches from its underlying bed and goes afloat on the ocean. Many numerical studies, including the intercomparison exercises MISMIP and MISMIP3D, have shown that grid refinement in the GL vicinity is a key component to obtain reliable results. Improving model accuracy while maintaining the computational cost affordable has then been an important target for the development of marine icesheet models. Adaptive mesh refinement (AMR) is a method where the accuracy of the solution is controlled by spatially adapting the mesh size. It has become popular in models using the finite element method as they naturally deal with unstructured meshes, but block-structured AMR has also been successfully applied to model GL dynamics. The main difficulty with AMR is to find efficient and reliable estimators of the numerical error to control the mesh size. Here, we use the estimator proposed by Frey and Alauzet (2015). Based on the interpolation error, it has been found effective in practice to control the numerical error, and has some flexibility, such as its ability to combine metrics for different variables, that makes it attractive. Routines to compute the anisotropic metric defining the mesh size have been implemented in the finite element ice flow model Elmer/Ice (Gagliardini et al., 2013). The mesh adaptation is performed using the freely available library MMG (Dapogny et al., 2014) called from Elmer/Ice. Using a setup based on the inter-comparison exercise MISMIP+ (Asay-Davis et al., 2016), we study the accuracy of the solution when the mesh is adapted using various variables (ice thickness, velocity, basal drag, …). We show that combining these variables allows to reduce the number of mesh nodes by more than one order of magnitude, for the same numerical accuracy, when compared to uniform mesh

  20. Nonlinear PI Control with Adaptive Interaction Algorithm for Multivariable Wastewater Treatment Process

    Directory of Open Access Journals (Sweden)

    S. I. Samsudin

    2014-01-01

    Full Text Available The wastewater treatment plant (WWTP is highly known with the nonlinearity of the control parameters, thus it is difficult to be controlled. In this paper, the enhancement of nonlinear PI controller (ENon-PI to compensate the nonlinearity of the activated sludge WWTP is proposed. The ENon-PI controller is designed by cascading a sector-bounded nonlinear gain to linear PI controller. The rate variation of the nonlinear gain kn is automatically updated based on adaptive interaction algorithm. Initiative to simplify the ENon-PI control structure by adapting kn has been proved by significant improvement under various dynamic influents. More than 30% of integral square error and 14% of integral absolute error are reduced compared to benchmark PI for DO control and nitrate in nitrogen removal control. Better average effluent qualities, less number of effluent violations, and lower aeration energy consumption resulted.

  1. Understanding and modelling Man-Machine Interaction

    International Nuclear Information System (INIS)

    Cacciabue, P.C.

    1991-01-01

    This paper gives an overview of the current state of the art in man machine systems interaction studies, focusing on the problems derived from highly automated working environments and the role of humans in the control loop. In particular, it is argued that there is a need for sound approaches to design and analysis of Man-Machine Interaction (MMI), which stem from the contribution of three expertises in interfacing domains, namely engineering, computer science and psychology: engineering for understanding and modelling plants and their material and energy conservation principles; psychology for understanding and modelling humans and their cognitive behaviours; computer science for converting models in sound simulations running in appropriate computer architectures. (author)

  2. Understanding and modelling man-machine interaction

    International Nuclear Information System (INIS)

    Cacciabue, P.C.

    1996-01-01

    This paper gives an overview of the current state of the art in man-machine system interaction studies, focusing on the problems derived from highly automated working environments and the role of humans in the control loop. In particular, it is argued that there is a need for sound approaches to the design and analysis of man-machine interaction (MMI), which stem from the contribution of three expertises in interfacing domains, namely engineering, computer science and psychology: engineering for understanding and modelling plants and their material and energy conservation principles; psychology for understanding and modelling humans an their cognitive behaviours; computer science for converting models in sound simulations running in appropriate computer architectures. (orig.)

  3. COGNITIVE DIALOG GAMES AS COGNITIVE ASSISTANTS: TRACKING AND ADAPTING KNOWLEDGE AND INTERACTIONS IN STUDENT’S DIALOGS

    Directory of Open Access Journals (Sweden)

    Adem Karahoca

    2018-04-01

    Full Text Available This study introduces a system design in a form of cognitive dialog game (DiaCog to support pedagogical factors and student learning model ideas. The purpose of the study is to describe how such a design achieves tracking and adapting students’ knowledge and mastery learning levels as a cognitive assistant. Also, this study shows alternative ways for supporting intelligent personal learning, tutoring systems, and MOOCS. This paper explains method called DiaCog that uses structure for students` thinking in an online dialog by tracking student`s level of learning/knowledge status. The methodology of computing is the semantic that match between students` interactions in a dialog. By this way it informs DiaCog’s learner model to inform the pedagogical model. Semantic fingerprint matching method of DiaCog allows making comparisons with expert knowledge to detect students` mastery levels in learning. The paper concludes with the DiaCog tool and methodologies that used for intelligent cognitive assistant design to implement pedagogical and learner model to track and adapt students’ learning. Finally, this paper discusses future improvements and planned experimental set up to advance the techniques introduced in DiaCog design.

  4. Model Adaptation for Prognostics in a Particle Filtering Framework

    Directory of Open Access Journals (Sweden)

    Bhaskar Saha

    2011-01-01

    Full Text Available One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the “curse of dimensionality”, i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for “well-designed” particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion and Li-Polymer batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  5. Model Adaptation for Prognostics in a Particle Filtering Framework

    Science.gov (United States)

    Saha, Bhaskar; Goebel, Kai Frank

    2011-01-01

    One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the "curse of dimensionality", i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for "well-designed" particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  6. Career success criteria and locus of control as indicators of adaptive readiness in the career adaptation model.

    OpenAIRE

    Zhou, W.; Guan, Y.; Xin, L.; Mak, M.C.K.; Deng, Y.

    2016-01-01

    The present research had two goals. The first goal was to identify additional individual characteristics that may contribute to adaptive readiness. The second goal was to test if these characteristics fit the career adaptation model of readiness to resources to responses. We examined whether career success criteria (measured at Time 1) and career locus of control (measured at Time 1) would contribute to adaptivity and predict university students’ career decision-making self-efficacy (measured...

  7. Adaptive thermal modeling of Li-ion batteries

    International Nuclear Information System (INIS)

    Shadman Rad, M.; Danilov, D.L.; Baghalha, M.; Kazemeini, M.; Notten, P.H.L.

    2013-01-01

    Highlights: • A simple, accurate and adaptive thermal model is proposed for Li-ion batteries. • Equilibrium voltages, overpotentials and entropy changes are quantified from experimental results. • Entropy changes are highly dependent on the battery State-of-Charge. • Good agreement between simulated and measured heat development is obtained under all conditions. • Radiation contributes to about 50% of heat dissipation at elevated temperatures. -- Abstract: An accurate thermal model to predict the heat generation in rechargeable batteries is an essential tool for advanced thermal management in high power applications, such as electric vehicles. For such applications, the battery materials’ details and cell design are normally not provided. In this work a simple, though accurate, thermal model for batteries has been developed, considering the temperature- and current-dependent overpotential heat generation and State-of-Charge dependent entropy contributions. High power rechargeable Li-ion (7.5 Ah) batteries have been experimentally investigated and the results are used for model verification. It is shown that the State-of-Charge dependent entropy is a significant heat source and is therefore essential to correctly predict the thermal behavior of Li-ion batteries under a wide variety of operating conditions. An adaptive model is introduced to obtain these entropy values. A temperature-dependent equation for heat transfer to the environment is also taken into account. Good agreement between the simulations and measurements is obtained in all cases. The parameters for both the heat generation and heat transfer processes can be applied to the thermal design of advanced battery packs. The proposed methodology is generic and independent on the cell chemistry and battery design. The parameters for the adaptive model can be determined by performing simple cell potential/current and temperature measurements for a limited number of charge/discharge cycles

  8. Geometrical analysis of the interacting boson model

    International Nuclear Information System (INIS)

    Dieperink, A.E.L.

    1983-01-01

    The Interacting Boson Model is considered, in relation with geometrical models and the application of mean field techniques to algebraic models, in three lectures. In the first, several methods are reviewed to establish a connection between the algebraic formulation of collective nuclear properties in terms of the group SU(6) and the geometric approach. In the second lecture the geometric interpretation of new degrees of freedom that arise in the neutron-proton IBA is discussed, and in the third one some further applications of algebraic techniques to the calculation of static and dynamic collective properties are presented. (U.K.)

  9. Localisation in a Growth Model with Interaction

    Science.gov (United States)

    Costa, M.; Menshikov, M.; Shcherbakov, V.; Vachkovskaia, M.

    2018-05-01

    This paper concerns the long term behaviour of a growth model describing a random sequential allocation of particles on a finite cycle graph. The model can be regarded as a reinforced urn model with graph-based interaction. It is motivated by cooperative sequential adsorption, where adsorption rates at a site depend on the configuration of existing particles in the neighbourhood of that site. Our main result is that, with probability one, the growth process will eventually localise either at a single site, or at a pair of neighbouring sites.

  10. Genes of the major histocompatibility complex highlight interactions of the innate and adaptive immune system

    Directory of Open Access Journals (Sweden)

    Barbara Lukasch

    2017-08-01

    Full Text Available Background A well-functioning immune defence is crucial for fitness, but our knowledge about the immune system and its complex interactions is still limited. Major histocompatibility complex (MHC molecules are involved in T-cell mediated adaptive immune responses, but MHC is also highly upregulated during the initial innate immune response. The aim of our study was therefore to determine to what extent the highly polymorphic MHC is involved in interactions of the innate and adaptive immune defence and if specific functional MHC alleles (FA or heterozygosity at the MHC are more important. Methods To do this we used captive house sparrows (Passer domesticus to survey MHC diversity and immune function controlling for several environmental factors. MHC class I alleles were identified using parallel amplicon sequencing and to mirror immune function, several immunological tests that correspond to the innate and adaptive immunity were conducted. Results Our results reveal that MHC was linked to all immune tests, highlighting its importance for the immune defence. While all innate responses were associated with one single FA, adaptive responses (cell-mediated and humoral were associated with several different alleles. Discussion We found that repeated injections of an antibody in nestlings and adults were linked to different FA and hence might affect different areas of the immune system. Also, individuals with a higher number of different FA produced a smaller secondary response, indicating a disadvantage of having numerous MHC alleles. These results demonstrate the complexity of the immune system in relation to the MHC and lay the foundation for other studies to further investigate this topic.

  11. Genes of the major histocompatibility complex highlight interactions of the innate and adaptive immune system.

    Science.gov (United States)

    Lukasch, Barbara; Westerdahl, Helena; Strandh, Maria; Winkler, Hans; Moodley, Yoshan; Knauer, Felix; Hoi, Herbert

    2017-01-01

    A well-functioning immune defence is crucial for fitness, but our knowledge about the immune system and its complex interactions is still limited. Major histocompatibility complex (MHC) molecules are involved in T-cell mediated adaptive immune responses, but MHC is also highly upregulated during the initial innate immune response. The aim of our study was therefore to determine to what extent the highly polymorphic MHC is involved in interactions of the innate and adaptive immune defence and if specific functional MHC alleles (FA) or heterozygosity at the MHC are more important. To do this we used captive house sparrows ( Passer domesticus ) to survey MHC diversity and immune function controlling for several environmental factors. MHC class I alleles were identified using parallel amplicon sequencing and to mirror immune function, several immunological tests that correspond to the innate and adaptive immunity were conducted. Our results reveal that MHC was linked to all immune tests, highlighting its importance for the immune defence. While all innate responses were associated with one single FA, adaptive responses (cell-mediated and humoral) were associated with several different alleles. We found that repeated injections of an antibody in nestlings and adults were linked to different FA and hence might affect different areas of the immune system. Also, individuals with a higher number of different FA produced a smaller secondary response, indicating a disadvantage of having numerous MHC alleles. These results demonstrate the complexity of the immune system in relation to the MHC and lay the foundation for other studies to further investigate this topic.

  12. Ab Initio Symmetry-Adapted No-Core Shell Model

    International Nuclear Information System (INIS)

    Draayer, J P; Dytrych, T; Launey, K D

    2011-01-01

    A multi-shell extension of the Elliott SU(3) model, the SU(3) symmetry-adapted version of the no-core shell model (SA-NCSM), is described. The significance of this SA-NCSM emerges from the physical relevance of its SU(3)-coupled basis, which – while it naturally manages center-of-mass spuriosity – provides a microscopic description of nuclei in terms of mixed shape configurations. Since typically configurations of maximum spatial deformation dominate, only a small part of the model space suffices to reproduce the low-energy nuclear dynamics and hence, offers an effective symmetry-guided framework for winnowing of model space. This is based on our recent findings of low-spin and high-deformation dominance in realistic NCSM results and, in turn, holds promise to significantly enhance the reach of ab initio shell models.

  13. Multi-Model Adaptive Fuzzy Controller for a CSTR Process

    Directory of Open Access Journals (Sweden)

    Shubham Gogoria

    2015-09-01

    Full Text Available Continuous Stirred Tank Reactors are intensively used to control exothermic reactions in chemical industries. It is a very complex multi-variable system with non-linear characteristics. This paper deals with linearization of the mathematical model of a CSTR Process. Multi model adaptive fuzzy controller has been designed to control the reactor concentration and temperature of CSTR process. This method combines the output of multiple Fuzzy controllers, which are operated at various operating points. The proposed solution is a straightforward implementation of Fuzzy controller with gain scheduler to control the linearly inseparable parameters of a highly non-linear process.

  14. Adaptive real-time models of vehicle dynamics; Adaptive Echtzeitmodelle fuer die Kraftfahrzeugdynamik

    Energy Technology Data Exchange (ETDEWEB)

    Halfmann, C.; Holzmann, H.; Isermann, R. [Technische Univ. Darmstadt (Germany). Inst. fuer Automatisierungstechnik; Hamann, C.D.; Simm, N. [Opel (A.) AG, Ruesselsheim (Germany). Gruppe Chassis und Fahrerassistenzsysteme

    1999-12-01

    The application of modern simulation tools offering additional support during the vehicle development process is accepted to a large extent by most car manufacturers. Just like new model-based control strategies, these simulation investigations require very accurate - and thus very complex - models of vehicle dynamics, which can be processed in real time. As an example of such a vehicle model, this article describes a real-time vehicle simulation model which was developed at the Institute of Automatic Control at Darmstadt University of Technology, in co-operation with the ITDC of the Adam OPEL AG. By applying modern adaptation techniques, this vehicle model is able to calculate onboard the important variables describing the actual driving state even if the environmental conditions change. (orig.) [German] Der Einsatz von Simulationswerkzeugen zur Unterstuetzung der Fahrzeugentwicklung hat sich bei den meisten Automobilherstellern weitgehend durchgesetzt. Ebenso wie neuartige modellbasierte Regelstrategien verlangen diese Simulationsuntersuchungen nach immer exakteren - und damit komplexeren - fahrdynamischen Modellen, die in Echtzeit ausgewertet werden. Als Beispiel fuer ein solches Gesamtfahrzeugmodell beschreibt dieser Beitrag ein echtzeitfaehiges Modell fuer die Bewegung des Fahrzeugs um alle drei Hauptachsen, das am Institut fuer Automatisierungstechnik der TU Darmstadt in Kooperation mit dem Internationalen Technischen Entwicklungszentrum (ITEZ) der Adam Opel AG entwickelt wurde. Es ist durch den Einsatz von Adaptionsmethoden in der Lage, wichtige fahrdynamische Zustandsgroessen im Fahrzeug auch unter veraenderlichen Umgebungsbedingungen zu ermitteln. (orig.)

  15. A Systems Biology Approach to the Coordination of Defensive and Offensive Molecular Mechanisms in the Innate and Adaptive Host-Pathogen Interaction Networks.

    Science.gov (United States)

    Wu, Chia-Chou; Chen, Bor-Sen

    2016-01-01

    Infected zebrafish coordinates defensive and offensive molecular mechanisms in response to Candida albicans infections, and invasive C. albicans coordinates corresponding molecular mechanisms to interact with the host. However, knowledge of the ensuing infection-activated signaling networks in both host and pathogen and their interspecific crosstalk during the innate and adaptive phases of the infection processes remains incomplete. In the present study, dynamic network modeling, protein interaction databases, and dual transcriptome data from zebrafish and C. albicans during infection were used to infer infection-activated host-pathogen dynamic interaction networks. The consideration of host-pathogen dynamic interaction systems as innate and adaptive loops and subsequent comparisons of inferred innate and adaptive networks indicated previously unrecognized crosstalk between known pathways and suggested roles of immunological memory in the coordination of host defensive and offensive molecular mechanisms to achieve specific and powerful defense against pathogens. Moreover, pathogens enhance intraspecific crosstalk and abrogate host apoptosis to accommodate enhanced host defense mechanisms during the adaptive phase. Accordingly, links between physiological phenomena and changes in the coordination of defensive and offensive molecular mechanisms highlight the importance of host-pathogen molecular interaction networks, and consequent inferences of the host-pathogen relationship could be translated into biomedical applications.

  16. CONSTRUCTIVE MODEL OF ADAPTATION OF DATA STRUCTURES IN RAM. PART II. CONSTRUCTORS OF SCENARIOS AND ADAPTATION PROCESSES

    Directory of Open Access Journals (Sweden)

    V. I. Shynkarenko

    2016-04-01

    Full Text Available Purpose.The second part of the paper completes presentation of constructive and the productive structures (CPS, modeling adaptation of data structures in memory (RAM. The purpose of the second part in the research is to develop a model of process of adaptation data in a RAM functioning in different hardware and software environments and scenarios of data processing. Methodology. The methodology of mathematical and algorithmic constructionism was applied. In this part of the paper, changes were developed the constructors of scenarios and adaptation processes based on a generalized CPS through its transformational conversions. Constructors are interpreted, specialized CPS. Were highlighted the terminal alphabets of the constructor scenarios in the form of data processing algorithms and the constructor of adaptation – in the form of algorithmic components of the adaptation process. The methodology involves the development of substitution rules that determine the output process of the relevant structures. Findings. In the second part of the paper, system is represented by CPS modeling adaptation data placement in the RAM, namely, constructors of scenarios and of adaptation processes. The result of the implementation of constructor of scenarios is a set of data processing operations in the form of text in the language of programming C#, constructor of the adaptation processes – a process of adaptation, and the result the process of adaptation – the adapted binary code of processing data structures. Originality. For the first time proposed the constructive model of data processing – the scenario that takes into account the order and number of calls to the various elements of data structures and adaptation of data structures to the different hardware and software environments. At the same the placement of data in RAM and processing algorithms are adapted. Constructionism application in modeling allows to link data models and algorithms for

  17. Communication: An adaptive configuration interaction approach for strongly correlated electrons with tunable accuracy

    Energy Technology Data Exchange (ETDEWEB)

    Schriber, Jeffrey B.; Evangelista, Francesco A. [Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322 (United States)

    2016-04-28

    We introduce a new procedure for iterative selection of determinant spaces capable of describing highly correlated systems. This adaptive configuration interaction (ACI) determines an optimal basis by an iterative procedure in which the determinant space is expanded and coarse grained until self-consistency. Two importance criteria control the selection process and tune the ACI to a user-defined level of accuracy. The ACI is shown to yield potential energy curves of N{sub 2} with nearly constant errors, and it predicts singlet-triplet splittings of acenes up to decacene that are in good agreement with the density matrix renormalization group.

  18. A predictive model to inform adaptive management of double-crested cormorants and fisheries in Michigan

    Science.gov (United States)

    Tsehaye, Iyob; Jones, Michael L.; Irwin, Brian J.; Fielder, David G.; Breck, James E.; Luukkonen, David R.

    2015-01-01

    The proliferation of double-crested cormorants (DCCOs; Phalacrocorax auritus) in North America has raised concerns over their potential negative impacts on game, cultured and forage fishes, island and terrestrial resources, and other colonial water birds, leading to increased public demands to reduce their abundance. By combining fish surplus production and bird functional feeding response models, we developed a deterministic predictive model representing bird–fish interactions to inform an adaptive management process for the control of DCCOs in multiple colonies in Michigan. Comparisons of model predictions with observations of changes in DCCO numbers under management measures implemented from 2004 to 2012 suggested that our relatively simple model was able to accurately reconstruct past DCCO population dynamics. These comparisons helped discriminate among alternative parameterizations of demographic processes that were poorly known, especially site fidelity. Using sensitivity analysis, we also identified remaining critical uncertainties (mainly in the spatial distributions of fish vs. DCCO feeding areas) that can be used to prioritize future research and monitoring needs. Model forecasts suggested that continuation of existing control efforts would be sufficient to achieve long-term DCCO control targets in Michigan and that DCCO control may be necessary to achieve management goals for some DCCO-impacted fisheries in the state. Finally, our model can be extended by accounting for parametric or ecological uncertainty and including more complex assumptions on DCCO–fish interactions as part of the adaptive management process.

  19. Adaptive scenarios: a training model for today's public health workforce.

    Science.gov (United States)

    Uden-Holman, Tanya; Bedet, Jennifer; Walkner, Laurie; Abd-Hamid, Nor Hashidah

    2014-01-01

    With the current economic climate, money for training is scarce. In addition, time is a major barrier to participation in trainings. To meet the public health workforce's rising demand for training, while struggling with less time and fewer resources, the Upper Midwest Preparedness and Emergency Response Learning Center has developed a model of online training that provides the public health workforce with individually customized, needs-based training experiences. Adaptive scenarios are rooted in case-based reasoning, a learning approach that focuses on the specific knowledge needed to solve a problem. Proponents of case-based reasoning argue that learners benefit from being able to remember previous similar situations and reusing information and knowledge from that situation. Adaptive scenarios based on true-to-life job performance provide an opportunity to assess skills by presenting the user with choices to make in a problem-solving context. A team approach was used to develop the adaptive scenarios. Storylines were developed that incorporated situations aligning with the knowledge, skills, and attitudes outlined in the Public Health Preparedness and Response Core Competency Model. This article examines 2 adaptive scenarios: "Ready or Not? A Family Preparedness Scenario" and "Responding to a Crisis: Managing Emotions and Stress Scenario." The scenarios are available on Upper Midwest Preparedness and Emergency Response Learning Center's Learning Management System, the Training Source (http://training-source.org). Evaluation data indicate that users' experiences have been positive. Integrating the assessment and training elements of the scenarios so that the training experience is uniquely adaptive to each user is one of the most efficient ways to provide training. The opportunity to provide individualized, needs-based training without having to administer separate assessments has the potential to save time and resources. These adaptive scenarios continue to be

  20. Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design

    NARCIS (Netherlands)

    Burgos, Daniel; Tattersall, Colin; Koper, Rob

    2006-01-01

    Burgos, D., Tattersall, C., & Koper, E. J. R. (2007). Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design. In B. Fernández Manjon, J. M. Sanchez Perez, J. A. Gómez Pulido, M. A. Vega Rodriguez & J. Bravo (Eds.), Computers and Education:

  1. Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design

    OpenAIRE

    Burgos, Daniel; Tattersall, Colin; Koper, Rob

    2006-01-01

    Burgos, D., Tattersall, C., & Koper, E. J. R. (2007). Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design. In B. Fernández Manjon, J. M. Sanchez Perez, J. A. Gómez Pulido, M. A. Vega Rodriguez & J. Bravo (Eds.), Computers and Education: E-learning - from theory to practice. Germany: Kluwer.

  2. Modeling of interaction effects in granular systems

    CERN Document Server

    El-Hilo, M; Al-Rsheed, A

    2000-01-01

    Interaction effects on the magnetic behavior of granular solid systems are examined using a numerical model which is capable of predicting the field, temperature and time dependence of magnetization. In this work, interaction effects on the temperature dependence of time viscosity coefficient S(T) and formation of minor hysteresis loops have been studied. The results for the time- and temperature dependence of remanence ratio have showed that the distribution of energy barriers f(DELTA E) obtained depend critically on the strength and nature of interactions. These interactions-based changes in f(DELTA E) can easily give a temperature-independent behavior of S(T) when these changes give a 1/DELTA E behavior to the distribution of energy barriers. Thus, conclusions about macroscopic quantum tunneling must be carefully drawn when the temperature dependence of S(T) is used to probe for MQT effects. For minor hysteresis effects, the result shows that for the non-interacting case, no minor hysteresis loops occur an...

  3. A two-particle exchange interaction model

    International Nuclear Information System (INIS)

    Lyubina, Julia; Mueller, Karl-Hartmut; Wolf, Manfred; Hannemann, Ullrich

    2010-01-01

    The magnetisation reversal of two interacting particles was investigated within a simple model describing exchange coupling of magnetically uniaxial single-domain particles. Depending on the interaction strength W, the reversal may be cooperative or non-cooperative. A non-collinear reversal mode is obtained even for two particles with parallel easy axes. The model yields different phenomena as observed in spring magnets such as recoil hysteresis in the second quadrant of the field-magnetisation-plane, caused by exchange bias, as well as the mentioned reversal-rotation mode. The Wohlfarth's remanence analysis performed on aggregations of such pairs of interacting particles shows that the deviation δM(H m ) usually being considered as a hallmark of magnetic interaction vanishes for all maximum applied fields H m not only at W=0, but also for sufficiently large values of W. Furthermore, this so-called δM-plot depends on whether the sample is ac-field or thermally demagnetised.

  4. A two-particle exchange interaction model

    Energy Technology Data Exchange (ETDEWEB)

    Lyubina, Julia, E-mail: j.lyubina@ifw-dresden.d [IFW Dresden, Institute for Metallic Materials, P.O. Box 270016, D-01171 Dresden (Germany); Mueller, Karl-Hartmut; Wolf, Manfred; Hannemann, Ullrich [IFW Dresden, Institute for Metallic Materials, P.O. Box 270016, D-01171 Dresden (Germany)

    2010-10-15

    The magnetisation reversal of two interacting particles was investigated within a simple model describing exchange coupling of magnetically uniaxial single-domain particles. Depending on the interaction strength W, the reversal may be cooperative or non-cooperative. A non-collinear reversal mode is obtained even for two particles with parallel easy axes. The model yields different phenomena as observed in spring magnets such as recoil hysteresis in the second quadrant of the field-magnetisation-plane, caused by exchange bias, as well as the mentioned reversal-rotation mode. The Wohlfarth's remanence analysis performed on aggregations of such pairs of interacting particles shows that the deviation {delta}M(H{sub m}) usually being considered as a hallmark of magnetic interaction vanishes for all maximum applied fields H{sub m} not only at W=0, but also for sufficiently large values of W. Furthermore, this so-called {delta}M-plot depends on whether the sample is ac-field or thermally demagnetised.

  5. [Analysis of the stability and adaptability of near infrared spectra qualitative analysis model].

    Science.gov (United States)

    Cao, Wu; Li, Wei-jun; Wang, Ping; Zhang, Li-ping

    2014-06-01

    The stability and adaptability of model of near infrared spectra qualitative analysis were studied. Method of separate modeling can significantly improve the stability and adaptability of model; but its ability of improving adaptability of model is limited. Method of joint modeling can not only improve the adaptability of the model, but also the stability of model, at the same time, compared to separate modeling, the method can shorten the modeling time, reduce the modeling workload; extend the term of validity of model, and improve the modeling efficiency. The experiment of model adaptability shows that, the correct recognition rate of separate modeling method is relatively low, which can not meet the requirements of application, and joint modeling method can reach the correct recognition rate of 90%, and significantly enhances the recognition effect. The experiment of model stability shows that, the identification results of model by joint modeling are better than the model by separate modeling, and has good application value.

  6. Motion Model Employment using interacting Motion Model Algorithm

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar

    2006-01-01

    The paper presents a simulation study to track a maneuvering target using a selective approach in choosing Interacting Multiple Models (IMM) algorithm to provide a wider coverage to track such targets.  Initially, there are two motion models in the system to track a target.  Probability of each m...

  7. Adaptive Multiscale Modeling of Geochemical Impacts on Fracture Evolution

    Science.gov (United States)

    Molins, S.; Trebotich, D.; Steefel, C. I.; Deng, H.

    2016-12-01

    Understanding fracture evolution is essential for many subsurface energy applications, including subsurface storage, shale gas production, fracking, CO2 sequestration, and geothermal energy extraction. Geochemical processes in particular play a significant role in the evolution of fractures through dissolution-driven widening, fines migration, and/or fracture sealing due to precipitation. One obstacle to understanding and exploiting geochemical fracture evolution is that it is a multiscale process. However, current geochemical modeling of fractures cannot capture this multi-scale nature of geochemical and mechanical impacts on fracture evolution, and is limited to either a continuum or pore-scale representation. Conventional continuum-scale models treat fractures as preferential flow paths, with their permeability evolving as a function (often, a cubic law) of the fracture aperture. This approach has the limitation that it oversimplifies flow within the fracture in its omission of pore scale effects while also assuming well-mixed conditions. More recently, pore-scale models along with advanced characterization techniques have allowed for accurate simulations of flow and reactive transport within the pore space (Molins et al., 2014, 2015). However, these models, even with high performance computing, are currently limited in their ability to treat tractable domain sizes (Steefel et al., 2013). Thus, there is a critical need to develop an adaptive modeling capability that can account for separate properties and processes, emergent and otherwise, in the fracture and the rock matrix at different spatial scales. Here we present an adaptive modeling capability that treats geochemical impacts on fracture evolution within a single multiscale framework. Model development makes use of the high performance simulation capability, Chombo-Crunch, leveraged by high resolution characterization and experiments. The modeling framework is based on the adaptive capability in Chombo

  8. Adaptive Active Noise Suppression Using Multiple Model Switching Strategy

    Directory of Open Access Journals (Sweden)

    Quanzhen Huang

    2017-01-01

    Full Text Available Active noise suppression for applications where the system response varies with time is a difficult problem. The computation burden for the existing control algorithms with online identification is heavy and easy to cause control system instability. A new active noise control algorithm is proposed in this paper by employing multiple model switching strategy for secondary path varying. The computation is significantly reduced. Firstly, a noise control system modeling method is proposed for duct-like applications. Then a multiple model adaptive control algorithm is proposed with a new multiple model switching strategy based on filter-u least mean square (FULMS algorithm. Finally, the proposed algorithm was implemented on Texas Instruments digital signal processor (DSP TMS320F28335 and real time experiments were done to test the proposed algorithm and FULMS algorithm with online identification. Experimental verification tests show that the proposed algorithm is effective with good noise suppression performance.

  9. Microscopic foundation of the interacting boson model

    International Nuclear Information System (INIS)

    Arima, Akito

    1994-01-01

    A microscopic foundation of the interacting boson model is described. The importance of monopole and quadrupole pairs of nucleons is emphasized. Those pairs are mapped onto the s and d bosons. It is shown that this mapping provides a good approximation in vibrational and transitional nuclei. In appendix, it is shown that the monopole pair of electrons plays possibly an important role in metal clusters. (orig.)

  10. Interactive Procedural Modelling of Coherent Waterfall Scenes

    OpenAIRE

    Emilien , Arnaud; Poulin , Pierre; Cani , Marie-Paule; Vimont , Ulysse

    2015-01-01

    International audience; Combining procedural generation and user control is a fundamental challenge for the interactive design of natural scenery. This is particularly true for modelling complex waterfall scenes where, in addition to taking charge of geometric details, an ideal tool should also provide a user with the freedom to shape the running streams and falls, while automatically maintaining physical plausibility in terms of flow network, embedding into the terrain, and visual aspects of...

  11. Interactions between Innate Lymphoid Cells and Cells of the Innate and Adaptive Immune System.

    Science.gov (United States)

    Symowski, Cornelia; Voehringer, David

    2017-01-01

    Type 2 innate lymphoid cells (ILC2s) are a major source of cytokines, which are also produced by Th2 cells and several cell types of the innate immune system. Work over the past few years indicates that ILC2s play a central role in regulating type 2 immune responses against allergens and helminths. ILC2s can interact with a variety of cells types of the innate and adaptive immune system by cell-cell contacts or by communication via soluble factors. In this review, we provide an overview about recent advances in our understanding how ILC2s orchestrate type 2 immune responses with focus on direct interactions between ILC2s and other cells of the immune system.

  12. Nonlinear interaction model of subsonic jet noise.

    Science.gov (United States)

    Sandham, Neil D; Salgado, Adriana M

    2008-08-13

    Noise generation in a subsonic round jet is studied by a simplified model, in which nonlinear interactions of spatially evolving instability modes lead to the radiation of sound. The spatial mode evolution is computed using linear parabolized stability equations. Nonlinear interactions are found on a mode-by-mode basis and the sound radiation characteristics are determined by solution of the Lilley-Goldstein equation. Since mode interactions are computed explicitly, it is possible to find their relative importance for sound radiation. The method is applied to a single stream jet for which experimental data are available. The model gives Strouhal numbers of 0.45 for the most amplified waves in the jet and 0.19 for the dominant sound radiation. While in near field axisymmetric and the first azimuthal modes are both important, far-field sound is predominantly axisymmetric. These results are in close correspondence with experiment, suggesting that the simplified model is capturing at least some of the important mechanisms of subsonic jet noise.

  13. Modeling Users' Experiences with Interactive Systems

    CERN Document Server

    Karapanos, Evangelos

    2013-01-01

    Over the past decade the field of Human-Computer Interaction has evolved from the study of the usability of interactive products towards a more holistic understanding of how they may mediate desired human experiences.  This book identifies the notion of diversity in usersʼ experiences with interactive products and proposes methods and tools for modeling this along two levels: (a) interpersonal diversity in usersʽ responses to early conceptual designs, and (b) the dynamics of usersʼ experiences over time. The Repertory Grid Technique is proposed as an alternative to standardized psychometric scales for modeling interpersonal diversity in usersʼ responses to early concepts in the design process, and new Multi-Dimensional Scaling procedures are introduced for modeling such complex quantitative data. iScale, a tool for the retrospective assessment of usersʼ experiences over time is proposed as an alternative to longitudinal field studies, and a semi-automated technique for the analysis of the elicited exper...

  14. Oil transformation sector modelling: price interactions

    International Nuclear Information System (INIS)

    Maurer, A.

    1992-01-01

    A global oil and oil product prices evolution model is proposed that covers the transformation sector incidence and the final user price establishment together with price interactions between gaseous and liquid hydrocarbons. High disparities among oil product prices in the various consumer zones (North America, Western Europe, Japan) are well described and compared with the low differences between oil supply prices in these zones. Final user price fluctuations are shown to be induced by transformation differences and competition; natural gas market is also modelled

  15. Some dynamical aspects of interacting quintessence model

    Science.gov (United States)

    Choudhury, Binayak S.; Mondal, Himadri Shekhar; Chatterjee, Devosmita

    2018-04-01

    In this paper, we consider a particular form of coupling, namely B=σ (\\dot{ρ _m}-\\dot{ρ _φ }) in spatially flat (k=0) Friedmann-Lemaitre-Robertson-Walker (FLRW) space-time. We perform phase-space analysis for this interacting quintessence (dark energy) and dark matter model for different numerical values of parameters. We also show the phase-space analysis for the `best-fit Universe' or concordance model. In our analysis, we observe the existence of late-time scaling attractors.

  16. Integrating adaptive behaviour in large-scale flood risk assessments: an Agent-Based Modelling approach

    Science.gov (United States)

    Haer, Toon; Aerts, Jeroen

    2015-04-01

    Between 1998 and 2009, Europe suffered over 213 major damaging floods, causing 1126 deaths, displacing around half a million people. In this period, floods caused at least 52 billion euro in insured economic losses making floods the most costly natural hazard faced in Europe. In many low-lying areas, the main strategy to cope with floods is to reduce the risk of the hazard through flood defence structures, like dikes and levees. However, it is suggested that part of the responsibility for flood protection needs to shift to households and businesses in areas at risk, and that governments and insurers can effectively stimulate the implementation of individual protective measures. However, adaptive behaviour towards flood risk reduction and the interaction between the government, insurers, and individuals has hardly been studied in large-scale flood risk assessments. In this study, an European Agent-Based Model is developed including agent representatives for the administrative stakeholders of European Member states, insurers and reinsurers markets, and individuals following complex behaviour models. The Agent-Based Modelling approach allows for an in-depth analysis of the interaction between heterogeneous autonomous agents and the resulting (non-)adaptive behaviour. Existing flood damage models are part of the European Agent-Based Model to allow for a dynamic response of both the agents and the environment to changing flood risk and protective efforts. By following an Agent-Based Modelling approach this study is a first contribution to overcome the limitations of traditional large-scale flood risk models in which the influence of individual adaptive behaviour towards flood risk reduction is often lacking.

  17. Building Adaptive Capacity with the Delphi Method and Mediated Modeling for Water Quality and Climate Change Adaptation in Lake Champlain Basin

    Science.gov (United States)

    Coleman, S.; Hurley, S.; Koliba, C.; Zia, A.; Exler, S.

    2014-12-01

    Eutrophication and nutrient pollution of surface waters occur within complex governance, social, hydrologic and biophysical basin contexts. The pervasive and perennial nutrient pollution in Lake Champlain Basin, despite decades of efforts, exemplifies problems found across the world's surface waters. Stakeholders with diverse values, interests, and forms of explicit and tacit knowledge determine water quality impacts through land use, agricultural and water resource decisions. Uncertainty, ambiguity and dynamic feedback further complicate the ability to promote the continual provision of water quality and ecosystem services. Adaptive management of water resources and land use requires mechanisms to allow for learning and integration of new information over time. The transdisciplinary Research on Adaptation to Climate Change (RACC) team is working to build regional adaptive capacity in Lake Champlain Basin while studying and integrating governance, land use, hydrological, and biophysical systems to evaluate implications for adaptive management. The RACC team has engaged stakeholders through mediated modeling workshops, online forums, surveys, focus groups and interviews. In March 2014, CSS2CC.org, an interactive online forum to source and identify adaptive interventions from a group of stakeholders across sectors was launched. The forum, based on the Delphi Method, brings forward the collective wisdom of stakeholders and experts to identify potential interventions and governance designs in response to scientific uncertainty and ambiguity surrounding the effectiveness of any strategy, climate change impacts, and the social and natural systems governing water quality and eutrophication. A Mediated Modeling Workshop followed the forum in May 2014, where participants refined and identified plausible interventions under different governance, policy and resource scenarios. Results from the online forum and workshop can identify emerging consensus across scales and sectors

  18. Model-based scenario planning to develop climate change adaptation strategies for rare plant populations in grassland reserves

    Science.gov (United States)

    Laura Phillips-Mao; Susan M. Galatowitsch; Stephanie A. Snyder; Robert G. Haight

    2016-01-01

    Incorporating climate change into conservation decision-making at site and population scales is challenging due to uncertainties associated with localized climate change impacts and population responses to multiple interacting impacts and adaptation strategies. We explore the use of spatially explicit population models to facilitate scenario analysis, a conservation...

  19. Patterns of coral bleaching: Modeling the adaptive bleaching hypothesis

    Science.gov (United States)

    Ware, J.R.; Fautin, D.G.; Buddemeier, R.W.

    1996-01-01

    Bleaching - the loss of symbiotic dinoflagellates (zooxanthellae) from animals normally possessing them - can be induced by a variety of stresses, of which temperature has received the most attention. Bleaching is generally considered detrimental, but Buddemeier and Fautin have proposed that bleaching is also adaptive, providing an opportunity for recombining hosts with alternative algal types to form symbioses that might be better adapted to altered circumstances. Our mathematical model of this "adaptive bleaching hypothesis" provides insight into how animal-algae symbioses might react under various circumstances. It emulates many aspects of the coral bleaching phenomenon including: corals bleaching in response to a temperature only slightly greater than their average local maximum temperature; background bleaching; bleaching events being followed by bleaching of lesser magnitude in the subsequent one to several years; higher thermal tolerance of corals subject to environmental variability compared with those living under more constant conditions; patchiness in bleaching; and bleaching at temperatures that had not previously resulted in bleaching. ?? 1996 Elsevier Science B.V. All rights reserved.

  20. Accessing Wireless Sensor Networks Via Dynamically Reconfigurable Interaction Models

    Directory of Open Access Journals (Sweden)

    Maria Cecília Gomes

    2012-12-01

    Full Text Available The Wireless Sensor Networks (WSNs technology is already perceived as fundamental for science across many domains, since it provides a low cost solution for environment monitoring. WSNs representation via the service concept and its inclusion in Web environments, e.g. through Web services, supports particularly their open/standard access and integration. Although such Web enabled WSNs simplify data access, network parameterization and aggregation, the existing interaction models and run-time adaptation mechanisms available to clients are still scarce. Nevertheless, applications increasingly demand richer and more flexible accesses besides the traditional client/server. For instance, applications may require a streaming model in order to avoid sequential data requests, or the asynchronous notification of subscribed data through the publish/subscriber. Moreover, the possibility to automatically switch between such models at runtime allows applications to define flexible context-based data acquisition. To this extent, this paper discusses the relevance of the session and pattern abstractions on the design of a middleware prototype providing richer and dynamically reconfigurable interaction models to Web enabled WSNs.

  1. Modeling adaptation of wetland plants under changing environments

    Science.gov (United States)

    Muneepeerakul, R.; Muneepeerakul, C. P.

    2010-12-01

    An evolutionary-game-theoretic approach is used to study the changes in traits of wetland plants in response to environmental changes, e.g., altered patterns of rainfall and nutrients. Here, a wetland is considered as a complex adaptive system where plants can adapt their strategies and influence one another. The system is subject to stochastic rainfall, which controls the dynamics of water level, soil moisture, and alternation between aerobic and anaerobic conditions in soil. Based on our previous work, a plant unit is characterized by three traits, namely biomass nitrogen content, specific leaf area, and allocation to rhizome. These traits control the basic functions of plants such as assimilation, respiration, and nutrient uptake, while affecting their environment through litter chemistry, root oxygenation, and thus soil microbial dynamics. The outcome of this evolutionary game, i.e., the best-performing plant traits against the backdrop of these interactions and feedbacks, is analyzed and its implications on important roles of wetlands in supporting our sustainability such as carbon sequestration in biosphere, nutrient cycling, and repository of biodiversity are discussed.

  2. dSPACE based adaptive neuro-fuzzy controller of grid interactive inverter

    International Nuclear Information System (INIS)

    Altin, Necmi; Sefa, İbrahim

    2012-01-01

    Highlights: ► We propose a dSPACE based neuro-fuzzy controlled grid interactive inverter. ► The membership functions and rule base of fuzzy logic controller by using ANFIS. ► A LCL output filter is designed. ► A high performance controller is designed. - Abstract: In this study, design, simulation and implementation of a dSPACE based grid interactive voltage source inverter are proposed. This inverter has adaptive neuro-fuzzy controller and capable of importing electrical energy, generated from renewable energy sources such as the wind, the solar and the fuel cells to the grid. A line frequency transformer and a LCL filter are used at the output of the grid interactive inverter which is designed as current controlled to decrease the susceptibility to phase errors. Membership functions and rule base of the fuzzy logic controller, which control the inverter output current, are determined by using artificial neural networks. Both simulation and experimental results show that, the grid interactive inverter operates synchronously with the grid. The inverter output current which is imported to the grid is in sinusoidal waveform and the harmonic level of it meets the international standards (4.3 < 5.0%). In addition, simulation and experimental results of the neuro-fuzzy and the PI controlled inverter are given together and compared in detail. Simulation and experimental results show that the proposed inverter has faster response to the reference variations and lower steady state error than PI controller.

  3. Efficient Spike-Coding with Multiplicative Adaptation in a Spike Response Model

    NARCIS (Netherlands)

    S.M. Bohte (Sander)

    2012-01-01

    htmlabstractNeural adaptation underlies the ability of neurons to maximize encoded informa- tion over a wide dynamic range of input stimuli. While adaptation is an intrinsic feature of neuronal models like the Hodgkin-Huxley model, the challenge is to in- tegrate adaptation in models of neural

  4. Adaptive Modeling, Engineering Analysis and Design of Advanced Aerospace Vehicles

    Science.gov (United States)

    Mukhopadhyay, Vivek; Hsu, Su-Yuen; Mason, Brian H.; Hicks, Mike D.; Jones, William T.; Sleight, David W.; Chun, Julio; Spangler, Jan L.; Kamhawi, Hilmi; Dahl, Jorgen L.

    2006-01-01

    This paper describes initial progress towards the development and enhancement of a set of software tools for rapid adaptive modeling, and conceptual design of advanced aerospace vehicle concepts. With demanding structural and aerodynamic performance requirements, these high fidelity geometry based modeling tools are essential for rapid and accurate engineering analysis at the early concept development stage. This adaptive modeling tool was used for generating vehicle parametric geometry, outer mold line and detailed internal structural layout of wing, fuselage, skin, spars, ribs, control surfaces, frames, bulkheads, floors, etc., that facilitated rapid finite element analysis, sizing study and weight optimization. The high quality outer mold line enabled rapid aerodynamic analysis in order to provide reliable design data at critical flight conditions. Example application for structural design of a conventional aircraft and a high altitude long endurance vehicle configuration are presented. This work was performed under the Conceptual Design Shop sub-project within the Efficient Aerodynamic Shape and Integration project, under the former Vehicle Systems Program. The project objective was to design and assess unconventional atmospheric vehicle concepts efficiently and confidently. The implementation may also dramatically facilitate physics-based systems analysis for the NASA Fundamental Aeronautics Mission. In addition to providing technology for design and development of unconventional aircraft, the techniques for generation of accurate geometry and internal sub-structure and the automated interface with the high fidelity analysis codes could also be applied towards the design of vehicles for the NASA Exploration and Space Science Mission projects.

  5. Scale Adaptive Simulation Model for the Darrieus Wind Turbine

    DEFF Research Database (Denmark)

    Rogowski, K.; Hansen, Martin Otto Laver; Maroński, R.

    2016-01-01

    Accurate prediction of aerodynamic loads for the Darrieus wind turbine using more or less complex aerodynamic models is still a challenge. One of the problems is the small amount of experimental data available to validate the numerical codes. The major objective of the present study is to examine...... the scale adaptive simulation (SAS) approach for performance analysis of a one-bladed Darrieus wind turbine working at a tip speed ratio of 5 and at a blade Reynolds number of 40 000. The three-dimensional incompressible unsteady Navier-Stokes equations are used. Numerical results of aerodynamic loads...

  6. Model-free adaptive control of advanced power plants

    Science.gov (United States)

    Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang

    2015-08-18

    A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

  7. Model-Free Adaptive Control Algorithm with Data Dropout Compensation

    Directory of Open Access Journals (Sweden)

    Xuhui Bu

    2012-01-01

    Full Text Available The convergence of model-free adaptive control (MFAC algorithm can be guaranteed when the system is subject to measurement data dropout. The system output convergent speed gets slower as dropout rate increases. This paper proposes a MFAC algorithm with data compensation. The missing data is first estimated using the dynamical linearization method, and then the estimated value is introduced to update control input. The convergence analysis of the proposed MFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that the proposed algorithm can compensate the effect of the data dropout, and the better output performance can be obtained.

  8. Preference learning with evolutionary Multivariate Adaptive Regression Spline model

    DEFF Research Database (Denmark)

    Abou-Zleikha, Mohamed; Shaker, Noor; Christensen, Mads Græsbøll

    2015-01-01

    This paper introduces a novel approach for pairwise preference learning through combining an evolutionary method with Multivariate Adaptive Regression Spline (MARS). Collecting users' feedback through pairwise preferences is recommended over other ranking approaches as this method is more appealing...... for function approximation as well as being relatively easy to interpret. MARS models are evolved based on their efficiency in learning pairwise data. The method is tested on two datasets that collectively provide pairwise preference data of five cognitive states expressed by users. The method is analysed...

  9. Single image interpolation via adaptive nonlocal sparsity-based modeling.

    Science.gov (United States)

    Romano, Yaniv; Protter, Matan; Elad, Michael

    2014-07-01

    Single image interpolation is a central and extensively studied problem in image processing. A common approach toward the treatment of this problem in recent years is to divide the given image into overlapping patches and process each of them based on a model for natural image patches. Adaptive sparse representation modeling is one such promising image prior, which has been shown to be powerful in filling-in missing pixels in an image. Another force that such algorithms may use is the self-similarity that exists within natural images. Processing groups of related patches together exploits their correspondence, leading often times to improved results. In this paper, we propose a novel image interpolation method, which combines these two forces-nonlocal self-similarities and sparse representation modeling. The proposed method is contrasted with competitive and related algorithms, and demonstrated to achieve state-of-the-art results.

  10. Interacting proteins on human spermatozoa: adaptive evolution of the binding of semenogelin I to EPPIN.

    Directory of Open Access Journals (Sweden)

    Erick J R Silva

    Full Text Available Semenogelin I (SEMG1 is found in human semen coagulum and on the surface of spermatozoa bound to EPPIN. The physiological significance of the SEMG1/EPPIN interaction on the surface of spermatozoa is its capacity to modulate sperm progressive motility. The present study investigates the hypothesis that the interacting surface of SEMG1 and EPPIN co-evolved within the Hominoidea time scale, as a result of adaptive pressures applied by their roles in sperm protection and reproductive fitness. Our results indicate that some amino acid residues of SEMG1 and EPPIN possess a remarkable deficiency of variation among hominoid primates. We observe a distinct residue change unique to humans within the EPPIN sequence containing a SEMG1 interacting surface, namely His92. In addition, Bayes Empirical Bayes analysis for positive selection indicates that the SEMG1 Cys239 residue underwent positive selection in humans, probably as a consequence of its role in increasing the binding affinity of these interacting proteins. We confirm the critical role of Cys239 residue for SEMG1 binding to EPPIN and inhibition of sperm motility by showing that recombinant SEMG1 mutants in which Cys239 residue was changed to glycine, aspartic acid, histidine, serine or arginine have reduced capacity to interact to EPPIN and to inhibit human sperm motility in vitro. In conclusion, our results indicate that EPPIN and SEMG1 rapidly co-evolved in primates due to their critical role in the modulation of sperm motility in the semen coagulum, providing unique insights into the molecular co-evolution of sperm surface interacting proteins.

  11. Quadratic adaptive algorithm for solving cardiac action potential models.

    Science.gov (United States)

    Chen, Min-Hung; Chen, Po-Yuan; Luo, Ching-Hsing

    2016-10-01

    An adaptive integration method is proposed for computing cardiac action potential models accurately and efficiently. Time steps are adaptively chosen by solving a quadratic formula involving the first and second derivatives of the membrane action potential. To improve the numerical accuracy, we devise an extremum-locator (el) function to predict the local extremum when approaching the peak amplitude of the action potential. In addition, the time step restriction (tsr) technique is designed to limit the increase in time steps, and thus prevent the membrane potential from changing abruptly. The performance of the proposed method is tested using the Luo-Rudy phase 1 (LR1), dynamic (LR2), and human O'Hara-Rudy dynamic (ORd) ventricular action potential models, and the Courtemanche atrial model incorporating a Markov sodium channel model. Numerical experiments demonstrate that the action potential generated using the proposed method is more accurate than that using the traditional Hybrid method, especially near the peak region. The traditional Hybrid method may choose large time steps near to the peak region, and sometimes causes the action potential to become distorted. In contrast, the proposed new method chooses very fine time steps in the peak region, but large time steps in the smooth region, and the profiles are smoother and closer to the reference solution. In the test on the stiff Markov ionic channel model, the Hybrid blows up if the allowable time step is set to be greater than 0.1ms. In contrast, our method can adjust the time step size automatically, and is stable. Overall, the proposed method is more accurate than and as efficient as the traditional Hybrid method, especially for the human ORd model. The proposed method shows improvement for action potentials with a non-smooth morphology, and it needs further investigation to determine whether the method is helpful during propagation of the action potential. Copyright © 2016 Elsevier Ltd. All rights

  12. Ferromagnetic Potts models with multisite interaction

    Science.gov (United States)

    Schreiber, Nir; Cohen, Reuven; Haber, Simi

    2018-03-01

    We study the q -state Potts model with four-site interaction on a square lattice. Based on the asymptotic behavior of lattice animals, it is argued that when q ≤4 the system exhibits a second-order phase transition and when q >4 the transition is first order. The q =4 model is borderline. We find 1 /lnq to be an upper bound on Tc, the exact critical temperature. Using a low-temperature expansion, we show that 1 /(θ lnq ) , where θ >1 is a q -dependent geometrical term, is an improved upper bound on Tc. In fact, our findings support Tc=1 /(θ lnq ) . This expression is used to estimate the finite correlation length in first-order transition systems. These results can be extended to other lattices. Our theoretical predictions are confirmed numerically by an extensive study of the four-site interaction model using the Wang-Landau entropic sampling method for q =3 ,4 ,5 . In particular, the q =4 model shows an ambiguous finite-size pseudocritical behavior.

  13. Pre-relaxation in weakly interacting models

    Science.gov (United States)

    Bertini, Bruno; Fagotti, Maurizio

    2015-07-01

    We consider time evolution in models close to integrable points with hidden symmetries that generate infinitely many local conservation laws that do not commute with one another. The system is expected to (locally) relax to a thermal ensemble if integrability is broken, or to a so-called generalised Gibbs ensemble if unbroken. In some circumstances expectation values exhibit quasi-stationary behaviour long before their typical relaxation time. For integrability-breaking perturbations, these are also called pre-thermalisation plateaux, and emerge e.g. in the strong coupling limit of the Bose-Hubbard model. As a result of the hidden symmetries, quasi-stationarity appears also in integrable models, for example in the Ising limit of the XXZ model. We investigate a weak coupling limit, identify a time window in which the effects of the perturbations become significant and solve the time evolution through a mean-field mapping. As an explicit example we study the XYZ spin-\\frac{1}{2} chain with additional perturbations that break integrability. One of the most intriguing results of the analysis is the appearance of persistent oscillatory behaviour. To unravel its origin, we study in detail a toy model: the transverse-field Ising chain with an additional nonlocal interaction proportional to the square of the transverse spin per unit length (2013 Phys. Rev. Lett. 111 197203). Despite being nonlocal, this belongs to a class of models that emerge as intermediate steps of the mean-field mapping and shares many dynamical properties with the weakly interacting models under consideration.

  14. Adaptive and non-adaptive models of depression: A comparison using register data on antidepressant medication during divorce.

    Science.gov (United States)

    Rosenström, Tom; Fawcett, Tim W; Higginson, Andrew D; Metsä-Simola, Niina; Hagen, Edward H; Houston, Alasdair I; Martikainen, Pekka

    2017-01-01

    Divorce is associated with an increased probability of a depressive episode, but the causation of events remains unclear. Adaptive models of depression propose that depression is a social strategy in part, whereas non-adaptive models tend to propose a diathesis-stress mechanism. We compare an adaptive evolutionary model of depression to three alternative non-adaptive models with respect to their ability to explain the temporal pattern of depression around the time of divorce. Register-based data (304,112 individuals drawn from a random sample of 11% of Finnish people) on antidepressant purchases is used as a proxy for depression. This proxy affords an unprecedented temporal resolution (a 3-monthly prevalence estimates over 10 years) without any bias from non-compliance, and it can be linked with underlying episodes via a statistical model. The evolutionary-adaptation model (all time periods with risk of divorce are depressogenic) was the best quantitative description of the data. The non-adaptive stress-relief model (period before divorce is depressogenic and period afterwards is not) provided the second best quantitative description of the data. The peak-stress model (periods before and after divorce can be depressogenic) fit the data less well, and the stress-induction model (period following divorce is depressogenic and the preceding period is not) did not fit the data at all. The evolutionary model was the most detailed mechanistic description of the divorce-depression link among the models, and the best fit in terms of predicted curvature; thus, it offers most rigorous hypotheses for further study. The stress-relief model also fit very well and was the best model in a sensitivity analysis, encouraging development of more mechanistic models for that hypothesis.

  15. Interactions between baryon octets by quark model

    Energy Technology Data Exchange (ETDEWEB)

    Nakamoto, S. [Suzuka National College of Technology, Suzuka, Mie (Japan); Fujiwara, Y. [Kyoto Univ., Faculty of Science, Kyoto (Japan); Suzuki, Y. [Niigata Univ., Faculty of Science, Niigata (Japan); Kohno, M. [Kyushu Dental College, Kita-kyushu, Fukuoka (Japan)

    2003-03-01

    Interactions between the baryon octets are studied by using the two spin flavor SU{sub 6} quark models, namely fss2 and FSS. In all channels, results that can be systematically understood along with the flavor symmetry are obtained. Effect of the channel coupling in the {sup 1}S{sub 0} state of the system of strangeness-2 shows a tendency to be weak in the system of isospin 0 while strong in the system of isospin 1. It is shown that this tendency is due to the competitive contributions of the color magnetic term and the effective meson exchange potential to the transition potential. Flavor symmetry breaking weakens both the repulsive force in the short range and the attractive force in the intermediate range. It is revealed that the overall qualitative behavior is determined as the result of the competitive effect of those interactions. (S. Funahashi)

  16. On dark degeneracy and interacting models

    International Nuclear Information System (INIS)

    Carneiro, S.; Borges, H.A.

    2014-01-01

    Cosmological background observations cannot fix the dark energy equation of state, which is related to a degeneracy in the definition of the dark sector components. Here we show that this degeneracy can be broken at perturbation level by imposing two observational properties on dark matter. First, dark matter is defined as the clustering component we observe in large scale structures. This definition is meaningful only if dark energy is unperturbed, which is achieved if we additionally assume, as a second condition, that dark matter is cold, i.e. non-relativistic. As a consequence, dark energy models with equation-of-state parameter −1 ≤ ω < 0 are reduced to two observationally distinguishable classes with ω = −1, equally competitive when tested against observations. The first comprises the ΛCDM model with constant dark energy density. The second consists of interacting models with an energy flux from dark energy to dark matter

  17. Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations.

    Directory of Open Access Journals (Sweden)

    Tatiana Shashkova

    Full Text Available Intestinal microbiota plays an important role in the human health. It is involved in the digestion and protects the host against external pathogens. Examination of the intestinal microbiome interactions is required for understanding of the community influence on host health. Studies of the microbiome can provide insight on methods of improving health, including specific clinical procedures for individual microbial community composition modification and microbiota correction by colonizing with new bacterial species or dietary changes.In this work we report an agent-based model of interactions between two bacterial species and between species and the gut. The model is based on reactions describing bacterial fermentation of polysaccharides to acetate and propionate and fermentation of acetate to butyrate. Antibiotic treatment was chosen as disturbance factor and used to investigate stability of the system. System recovery after antibiotic treatment was analyzed as dependence on quantity of feedback interactions inside the community, therapy duration and amount of antibiotics. Bacterial species are known to mutate and acquire resistance to the antibiotics. The ability to mutate was considered to be a stochastic process, under this suggestion ratio of sensitive to resistant bacteria was calculated during antibiotic therapy and recovery.The model confirms a hypothesis of feedbacks mechanisms necessity for providing functionality and stability of the system after disturbance. High fraction of bacterial community was shown to mutate during antibiotic treatment, though sensitive strains could become dominating after recovery. The recovery of sensitive strains is explained by fitness cost of the resistance. The model demonstrates not only quantitative dynamics of bacterial species, but also gives an ability to observe the emergent spatial structure and its alteration, depending on various feedback mechanisms. Visual version of the model shows that spatial

  18. Adaptive inferential sensors based on evolving fuzzy models.

    Science.gov (United States)

    Angelov, Plamen; Kordon, Arthur

    2010-04-01

    A new technique to the design and use of inferential sensors in the process industry is proposed in this paper, which is based on the recently introduced concept of evolving fuzzy models (EFMs). They address the challenge that the modern process industry faces today, namely, to develop such adaptive and self-calibrating online inferential sensors that reduce the maintenance costs while keeping the high precision and interpretability/transparency. The proposed new methodology makes possible inferential sensors to recalibrate automatically, which reduces significantly the life-cycle efforts for their maintenance. This is achieved by the adaptive and flexible open-structure EFM used. The novelty of this paper lies in the following: (1) the overall concept of inferential sensors with evolving and self-developing structure from the data streams; (2) the new methodology for online automatic selection of input variables that are most relevant for the prediction; (3) the technique to detect automatically a shift in the data pattern using the age of the clusters (and fuzzy rules); (4) the online standardization technique used by the learning procedure of the evolving model; and (5) the application of this innovative approach to several real-life industrial processes from the chemical industry (evolving inferential sensors, namely, eSensors, were used for predicting the chemical properties of different products in The Dow Chemical Company, Freeport, TX). It should be noted, however, that the methodology and conclusions of this paper are valid for the broader area of chemical and process industries in general. The results demonstrate that well-interpretable and with-simple-structure inferential sensors can automatically be designed from the data stream in real time, which predict various process variables of interest. The proposed approach can be used as a basis for the development of a new generation of adaptive and evolving inferential sensors that can address the

  19. An Adaptive Channel Model for VBLAST in Vehicular Networks

    Directory of Open Access Journals (Sweden)

    Ghassan M. T. Abdalla

    2009-01-01

    Full Text Available The wireless transmission environment in vehicular ad hoc systems varies from line of sight with few surroundings to rich Rayleigh fading. An efficient communication system must adapt itself to these diverse conditions. Multiple antenna systems are known to provide superior performance compared to single antenna systems in terms of capacity and reliability. The correlation between the antennas has a great effect on the performance of MIMO systems. In this paper we introduce a novel adaptive channel model for MIMO-VBLAST systems in vehicular ad hoc networks. Using the proposed model, the correlation between the antennas was investigated. Although the line of sight is ideal for single antenna systems, it severely degrades the performance of VBLAST systems since it increases the correlation between the antennas. A channel update algorithm using single tap Kalman filters for VBLAST in flat fading channels has also been derived and evaluated. At 12 dB Es/N0, the new algorithm showed 50% reduction in the mean square error (MSE between the actual channel and the corresponding updated estimate compared to the MSE without update. The computational requirement of the proposed algorithm for a p×q VBLAST is 6p×q real multiplications and 4p×q real additions.

  20. Collaborative Education in Climate Change Sciences and Adaptation through Interactive Learning

    Science.gov (United States)

    Ozbay, G.; Sriharan, S.; Fan, C.

    2014-12-01

    As a result of several funded climate change education grants, collaboration between VSU, DSU, and MSU, was established to provide the innovative and cohesive education and research opportunities to underrepresented groups in the climate related sciences. Prior to offering climate change and adaptation related topics to the students, faculty members of the three collaborating institutions participated at a number of faculty training and preparation workshops for teaching climate change sciences (i.e. AMS Diversity Project Workshop, NCAR Faculty-Student Team on Climate Change, NASA-NICE Program). In order to enhance the teaching and student learning on various issues in the Environmental Sciences Programs, Climatology, Climate Change Sciences and Adaptation or related courses were developed at Delaware State University and its partner institutions (Virginia State University and Morgan State University). These courses were prepared to deliver information on physical basis for the earth's climate system and current climate change instruction modules by AMS and historic climate information (NOAA Climate Services, U.S. and World Weather Data, NCAR and NASA Climate Models). By using Global Seminar as a Model, faculty members worked in teams to engage students in videoconferencing on climate change through Contemporary Global Studies and climate courses including Climate Change and Adaptation Science, Sustainable Agriculture, Introduction to Environmental Sciences, Climatology, and Ecology and Adaptation courses. All climate change courses have extensive hands-on practices and research integrated into the student learning experiences. Some of these students have presented their classroom projects during Earth Day, Student Climate Change Symposium, Undergraduate Summer Symposium, and other national conferences.

  1. The interacting boson-fermion model

    International Nuclear Information System (INIS)

    Iachello, F.; Van Isacker, P.

    1990-01-01

    The interacting boson-fermion model has become in recent years the standard model for the description of atomic nuclei with an odd number of protons and/or neutrons. This book describes the mathematical framework on which the interacting boson-fermion model is built and presents applications to a variety of situations encountered in nuclei. The book addresses both the analytical and the numerical aspects of the problem. The analytical aspect requires the introduction of rather complex group theoretic methods, including the use of graded (or super) Lie algebras. The first (and so far only) example of supersymmetry occurring in nature is also discussed. The book is the first comprehensive treatment of the subject and will appeal to both theoretical and experimental physicists. The large number of explicit formulas for level energies, electromagnetic transition rates and intensities of transfer reactions presented in the book provide a simple but detailed way to analyze experimental data. This book can also be used as a textbook for advanced graduate students

  2. A model-adaptivity method for the solution of Lennard-Jones based adhesive contact problems

    Science.gov (United States)

    Ben Dhia, Hachmi; Du, Shuimiao

    2018-05-01

    The surface micro-interaction model of Lennard-Jones (LJ) is used for adhesive contact problems (ACP). To address theoretical and numerical pitfalls of this model, a sequence of partitions of contact models is adaptively constructed to both extend and approximate the LJ model. It is formed by a combination of the LJ model with a sequence of shifted-Signorini (or, alternatively, -Linearized-LJ) models, indexed by a shift parameter field. For each model of this sequence, a weak formulation of the associated local ACP is developed. To track critical localized adhesive areas, a two-step strategy is developed: firstly, a macroscopic frictionless (as first approach) linear-elastic contact problem is solved once to detect contact separation zones. Secondly, at each shift-adaptive iteration, a micro-macro ACP is re-formulated and solved within the multiscale Arlequin framework, with significant reduction of computational costs. Comparison of our results with available analytical and numerical solutions shows the effectiveness of our global strategy.

  3. Development of model reference adaptive control theory for electric power plant control applications

    Energy Technology Data Exchange (ETDEWEB)

    Mabius, L.E.

    1982-09-15

    The scope of this effort includes the theoretical development of a multi-input, multi-output (MIMO) Model Reference Control (MRC) algorithm, (i.e., model following control law), Model Reference Adaptive Control (MRAC) algorithm and the formulation of a nonlinear model of a typical electric power plant. Previous single-input, single-output MRAC algorithm designs have been generalized to MIMO MRAC designs using the MIMO MRC algorithm. This MRC algorithm, which has been developed using Command Generator Tracker methodologies, represents the steady state behavior (in the adaptive sense) of the MRAC algorithm. The MRC algorithm is a fundamental component in the MRAC design and stability analysis. An enhanced MRC algorithm, which has been developed for systems with more controls than regulated outputs, alleviates the MRC stability constraint of stable plant transmission zeroes. The nonlinear power plant model is based on the Cromby model with the addition of a governor valve management algorithm, turbine dynamics and turbine interactions with extraction flows. An application of the MRC algorithm to a linearization of this model demonstrates its applicability to power plant systems. In particular, the generated power changes at 7% per minute while throttle pressure and temperature, reheat temperature and drum level are held constant with a reasonable level of control. The enhanced algorithm reduces significantly control fluctuations without modifying the output response.

  4. Assortative and dissortative priorities for game interaction and strategy adaptation significantly bolster network reciprocity in the prisoner’s dilemma

    International Nuclear Information System (INIS)

    Tanimoto, Jun

    2014-01-01

    In 2 × 2 prisoner’s dilemma games, network reciprocity is one mechanism for adding social viscosity, which leads to cooperative equilibrium. Here we show that combining the process for selecting a gaming partner with the process for selecting an adaptation partner significantly enhances cooperation, even though such selection processes require additional costs to collect further information concerning which neighbor should be chosen. Based on elaborate investigations of the dynamics generated by our model, we find that high levels of cooperation result from two kinds of behavior: cooperators tend to interact with cooperators to prevent being exploited by defectors and defectors tend to choose cooperators to exploit despite the possibility that some defectors convert to cooperators. (paper)

  5. Adaptive control using neural networks and approximate models.

    Science.gov (United States)

    Narendra, K S; Mukhopadhyay, S

    1997-01-01

    The NARMA model is an exact representation of the input-output behavior of finite-dimensional nonlinear discrete-time dynamical systems in a neighborhood of the equilibrium state. However, it is not convenient for purposes of adaptive control using neural networks due to its nonlinear dependence on the control input. Hence, quite often, approximate methods are used for realizing the neural controllers to overcome computational complexity. In this paper, we introduce two classes of models which are approximations to the NARMA model, and which are linear in the control input. The latter fact substantially simplifies both the theoretical analysis as well as the practical implementation of the controller. Extensive simulation studies have shown that the neural controllers designed using the proposed approximate models perform very well, and in many cases even better than an approximate controller designed using the exact NARMA model. In view of their mathematical tractability as well as their success in simulation studies, a case is made in this paper that such approximate input-output models warrant a detailed study in their own right.

  6. Human Adaptive Mechatronics and Human-System Modelling

    Directory of Open Access Journals (Sweden)

    Satoshi Suzuki

    2013-03-01

    Full Text Available Several topics in projects for mechatronics studies, which are 'Human Adaptive Mechatronics (HAM' and 'Human-System Modelling (HSM', are presented in this paper. The main research theme of the HAM project is a design strategy for a new intelligent mechatronics system, which enhances operators' skills during machine operation. Skill analyses and control system design have been addressed. In the HSM project, human modelling based on hierarchical classification of skills was studied, including the following five types of skills: social, planning, cognitive, motion and sensory-motor skills. This paper includes digests of these research topics and the outcomes concerning each type of skill. Relationships with other research activities, knowledge and information that will be helpful for readers who are trying to study assistive human-mechatronics systems are also mentioned.

  7. Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models.

    Science.gov (United States)

    Torres, F E; Teodoro, P E; Rodrigues, E V; Santos, A; Corrêa, A M; Ceccon, G

    2016-04-29

    The aim of this study was to select erect cowpea (Vigna unguiculata L.) genotypes simultaneously for high adaptability, stability, and yield grain in Mato Grosso do Sul, Brazil using mixed models. We conducted six trials of different cowpea genotypes in 2005 and 2006 in Aquidauana, Chapadão do Sul, Dourados, and Primavera do Leste. The experimental design was randomized complete blocks with four replications and 20 genotypes. Genetic parameters were estimated by restricted maximum likelihood/best linear unbiased prediction, and selection was based on the harmonic mean of the relative performance of genetic values method using three strategies: selection based on the predicted breeding value, having considered the performance mean of the genotypes in all environments (no interaction effect); the performance in each environment (with an interaction effect); and the simultaneous selection for grain yield, stability, and adaptability. The MNC99542F-5 and MNC99-537F-4 genotypes could be grown in various environments, as they exhibited high grain yield, adaptability, and stability. The average heritability of the genotypes was moderate to high and the selective accuracy was 82%, indicating an excellent potential for selection.

  8. ADAPTATION OF WOFOST MODEL FROM CGMS TO ROMANIAN CONDITIONS

    Directory of Open Access Journals (Sweden)

    LAZĂR CĂTĂLIN

    2009-12-01

    Full Text Available This preliminary study is an inventory of the main resources and difficulties in adaptation of the Crop Growth Monitoring System (CGMS used by Agri4cast unit of IPSC from Joint Research Centre (JRC - Ispra of European Commission to conditions of Romania.In contrast with the original model calibrated mainly with statistical average yields at national level, for local calibration of the model the statistical yields at lower administrative units (macroregion or county must be used. In addition, for winter crops, the start of simulation in the new system will be in the autumn of the previous year. The start of simulation (and emergence day in the genuine system is 1st of January of the current year and the existing calibration was meant to provide a compensation system for this technical physiological delay.Proposed approach provides a better initialisation of the water balance (emergence occurs after start of simulation, as well as a better account for impact of wintering conditions, but obviously a new calibration for all cultivar dependent parameters is necessary. For the preoperational run, the localized model will use the weather data available till the last day available and the missing data from the rest of the year will be replaced either by the daily values of the long term averages or by the values from a year considered similar with the current one.Proposed adaptations permit a better use of information available on local scale and the localized model may be the core of a regional system for crop monitoring and in the same degree as the original system it can be used as tool for specific researches, such as studying the impact of climate changes.

  9. MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method.

    Science.gov (United States)

    Tuta, Jure; Juric, Matjaz B

    2018-03-24

    This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method), a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah) and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.). Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

  10. MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method

    Directory of Open Access Journals (Sweden)

    Jure Tuta

    2018-03-01

    Full Text Available This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method, a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.. Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

  11. A Mathematical Model of the Olfactory Bulb for the Selective Adaptation Mechanism in the Rodent Olfactory System.

    Science.gov (United States)

    Soh, Zu; Nishikawa, Shinya; Kurita, Yuichi; Takiguchi, Noboru; Tsuji, Toshio

    2016-01-01

    To predict the odor quality of an odorant mixture, the interaction between odorants must be taken into account. Previously, an experiment in which mice discriminated between odorant mixtures identified a selective adaptation mechanism in the olfactory system. This paper proposes an olfactory model for odorant mixtures that can account for selective adaptation in terms of neural activity. The proposed model uses the spatial activity pattern of the mitral layer obtained from model simulations to predict the perceptual similarity between odors. Measured glomerular activity patterns are used as input to the model. The neural interaction between mitral cells and granular cells is then simulated, and a dissimilarity index between odors is defined using the activity patterns of the mitral layer. An odor set composed of three odorants is used to test the ability of the model. Simulations are performed based on the odor discrimination experiment on mice. As a result, we observe that part of the neural activity in the glomerular layer is enhanced in the mitral layer, whereas another part is suppressed. We find that the dissimilarity index strongly correlates with the odor discrimination rate of mice: r = 0.88 (p = 0.019). We conclude that our model has the ability to predict the perceptual similarity of odorant mixtures. In addition, the model also accounts for selective adaptation via the odor discrimination rate, and the enhancement and inhibition in the mitral layer may be related to this selective adaptation.

  12. Walking-adaptability assessments with the Interactive Walkway: Between-systems agreement and sensitivity to task and subject variations.

    Science.gov (United States)

    Geerse, Daphne J; Coolen, Bert H; Roerdink, Melvyn

    2017-05-01

    The ability to adapt walking to environmental circumstances is an important aspect of walking, yet difficult to assess. The Interactive Walkway was developed to assess walking adaptability by augmenting a multi-Kinect-v2 10-m walkway with gait-dependent visual context (stepping targets, obstacles) using real-time processed markerless full-body kinematics. In this study we determined Interactive Walkway's usability for walking-adaptability assessments in terms of between-systems agreement and sensitivity to task and subject variations. Under varying task constraints, 21 healthy subjects performed obstacle-avoidance, sudden-stops-and-starts and goal-directed-stepping tasks. Various continuous walking-adaptability outcome measures were concurrently determined with the Interactive Walkway and a gold-standard motion-registration system: available response time, obstacle-avoidance and sudden-stop margins, step length, stepping accuracy and walking speed. The same holds for dichotomous classifications of success and failure for obstacle-avoidance and sudden-stops tasks and performed short-stride versus long-stride obstacle-avoidance strategies. Continuous walking-adaptability outcome measures generally agreed well between systems (high intraclass correlation coefficients for absolute agreement, low biases and narrow limits of agreement) and were highly sensitive to task and subject variations. Success and failure ratings varied with available response times and obstacle types and agreed between systems for 85-96% of the trials while obstacle-avoidance strategies were always classified correctly. We conclude that Interactive Walkway walking-adaptability outcome measures are reliable and sensitive to task and subject variations, even in high-functioning subjects. We therefore deem Interactive Walkway walking-adaptability assessments usable for obtaining an objective and more task-specific examination of one's ability to walk, which may be feasible for both high

  13. System health monitoring using multiple-model adaptive estimation techniques

    Science.gov (United States)

    Sifford, Stanley Ryan

    Monitoring system health for fault detection and diagnosis by tracking system parameters concurrently with state estimates is approached using a new multiple-model adaptive estimation (MMAE) method. This novel method is called GRid-based Adaptive Parameter Estimation (GRAPE). GRAPE expands existing MMAE methods by using new techniques to sample the parameter space. GRAPE expands on MMAE with the hypothesis that sample models can be applied and resampled without relying on a predefined set of models. GRAPE is initially implemented in a linear framework using Kalman filter models. A more generalized GRAPE formulation is presented using extended Kalman filter (EKF) models to represent nonlinear systems. GRAPE can handle both time invariant and time varying systems as it is designed to track parameter changes. Two techniques are presented to generate parameter samples for the parallel filter models. The first approach is called selected grid-based stratification (SGBS). SGBS divides the parameter space into equally spaced strata. The second approach uses Latin Hypercube Sampling (LHS) to determine the parameter locations and minimize the total number of required models. LHS is particularly useful when the parameter dimensions grow. Adding more parameters does not require the model count to increase for LHS. Each resample is independent of the prior sample set other than the location of the parameter estimate. SGBS and LHS can be used for both the initial sample and subsequent resamples. Furthermore, resamples are not required to use the same technique. Both techniques are demonstrated for both linear and nonlinear frameworks. The GRAPE framework further formalizes the parameter tracking process through a general approach for nonlinear systems. These additional methods allow GRAPE to either narrow the focus to converged values within a parameter range or expand the range in the appropriate direction to track the parameters outside the current parameter range boundary

  14. A dutch adaptation of the child-rearing styles inventory and a validation of krohne's two-process model.

    Science.gov (United States)

    Depreeuw, E; Lens, W; Horebeek, W

    1995-01-01

    Abstract A Questionnaire for the Parent-Child Interaction (VOKI) has been developed by adapting Krohne's German ESI for the Flemish high school population. The psychometric characteristics of the adaptation are satisfying. The ESI factor structure has been replicated and the VOKI scales are perfectly comparable to the original German scales. Further research on the VOKI and two questionnaires assessing achievement related concepts such as test anxiety, procrastination and achievement motivation yielded correlational patterns partly predicted from Krohne's Two-Process Model. The relations between parental child-rearing styles and competence and consequence expectancies are in line with this model, whereas test anxiety and procrastination seem more complexly determined.

  15. Interaction of Mastoparan with Model Membranes

    Science.gov (United States)

    Haloot, Justin

    2010-10-01

    The use of antimicrobial agents began during the 20th century to reduce the effects of infectious diseases. Since the 1990s, antimicrobial resistance has become an ever-increasing global problem. Our laboratory recently found that small antimicrobial peptides (AMPs) have potent antimicrobial activity against a wide range of Gram-negative and Gram-positive organisms including antibiotic resistant organisms. These AMPs are potential therapeutic agents against the growing problem of antimicrobial resistance. AMPs are small peptides produced by plants, insects and animals. Several hypotheses concede that these peptides cause some type of structural perturbations and increased membrane permeability in bacteria however, how AMPs kill bacteria remains unclear. The goal of this study was to design an assay that would allow us to evaluate and monitor the pore forming ability of an AMP, Mastoparan, on model membrane structures called liposomes. Development of this model will facilitate the study of how mastoparan and related AMPs interact with the bacterial membrane.

  16. Laser interaction with biological material mathematical modeling

    CERN Document Server

    Kulikov, Kirill

    2014-01-01

    This book covers the principles of laser interaction with biological cells and tissues of varying degrees of organization. The problems of biomedical diagnostics are considered. Scattering of laser irradiation of blood cells is modeled for biological structures (dermis, epidermis, vascular plexus). An analytic theory is provided which is based on solving the wave equation for the electromagnetic field. It allows the accurate analysis of interference effects arising from the partial superposition of scattered waves. Treated topics of mathematical modeling are: optical characterization of biological tissue with large-scale and small-scale inhomogeneities in the layers, heating blood vessel under laser irradiation incident on the outer surface of the skin and thermo-chemical denaturation of biological structures at the example of human skin.

  17. Interaction of Defensins with Model Cell Membranes

    Science.gov (United States)

    Sanders, Lori K.; Schmidt, Nathan W.; Yang, Lihua; Mishra, Abhijit; Gordon, Vernita D.; Selsted, Michael E.; Wong, Gerard C. L.

    2009-03-01

    Antimicrobial peptides (AMPs) comprise a key component of innate immunity for a wide range of multicellular organisms. For many AMPs, activity comes from their ability to selectively disrupt and lyse bacterial cell membranes. There are a number of proposed models for this action, but the detailed molecular mechanism of selective membrane permeation remains unclear. Theta defensins are circularized peptides with a high degree of selectivity. We investigate the interaction of model bacterial and eukaryotic cell membranes with theta defensins RTD-1, BTD-7, and compare them to protegrin PG-1, a prototypical AMP, using synchrotron small angle x-ray scattering (SAXS). The relationship between membrane composition and peptide induced changes in membrane curvature and topology is examined. By comparing the membrane phase behavior induced by these different peptides we will discuss the importance of amino acid composition and placement on membrane rearrangement.

  18. An interactive program for pharmacokinetic modeling.

    Science.gov (United States)

    Lu, D R; Mao, F

    1993-05-01

    A computer program, PharmK, was developed for pharmacokinetic modeling of experimental data. The program was written in C computer language based on the high-level user-interface Macintosh operating system. The intention was to provide a user-friendly tool for users of Macintosh computers. An interactive algorithm based on the exponential stripping method is used for the initial parameter estimation. Nonlinear pharmacokinetic model fitting is based on the maximum likelihood estimation method and is performed by the Levenberg-Marquardt method based on chi 2 criterion. Several methods are available to aid the evaluation of the fitting results. Pharmacokinetic data sets have been examined with the PharmK program, and the results are comparable with those obtained with other programs that are currently available for IBM PC-compatible and other types of computers.

  19. Pneumatic Adaptive Absorber: Mathematical Modelling with Experimental Verification

    Directory of Open Access Journals (Sweden)

    Grzegorz Mikułowski

    2016-01-01

    Full Text Available Many of mechanical energy absorbers utilized in engineering structures are hydraulic dampers, since they are simple and highly efficient and have favourable volume to load capacity ratio. However, there exist fields of applications where a threat of toxic contamination with the hydraulic fluid contents must be avoided, for example, food or pharmacy industries. A solution here can be a Pneumatic Adaptive Absorber (PAA, which is characterized by a high dissipation efficiency and an inactive medium. In order to properly analyse the characteristics of a PAA, an adequate mathematical model is required. This paper proposes a concept for mathematical modelling of a PAA with experimental verification. The PAA is considered as a piston-cylinder device with a controllable valve incorporated inside the piston. The objective of this paper is to describe a thermodynamic model of a double chamber cylinder with gas migration between the inner volumes of the device. The specific situation considered here is that the process cannot be defined as polytropic, characterized by constant in time thermodynamic coefficients. Instead, the coefficients of the proposed model are updated during the analysis. The results of the experimental research reveal that the proposed mathematical model is able to accurately reflect the physical behaviour of the fabricated demonstrator of the shock absorber.

  20. From epidemics to information propagation : Striking differences in structurally similar adaptive network models

    NARCIS (Netherlands)

    Trajanovski, S.; Guo, D.; Van Mieghem, P.F.A.

    2015-01-01

    The continuous-time adaptive susceptible-infected-susceptible (ASIS) epidemic model and the adaptive information diffusion (AID) model are two adaptive spreading processes on networks, in which a link in the network changes depending on the infectious state of its end nodes, but in opposite ways:

  1. Method and system for rendering and interacting with an adaptable computing environment

    Science.gov (United States)

    Osbourn, Gordon Cecil [Albuquerque, NM; Bouchard, Ann Marie [Albuquerque, NM

    2012-06-12

    An adaptable computing environment is implemented with software entities termed "s-machines", which self-assemble into hierarchical data structures capable of rendering and interacting with the computing environment. A hierarchical data structure includes a first hierarchical s-machine bound to a second hierarchical s-machine. The first hierarchical s-machine is associated with a first layer of a rendering region on a display screen and the second hierarchical s-machine is associated with a second layer of the rendering region overlaying at least a portion of the first layer. A screen element s-machine is linked to the first hierarchical s-machine. The screen element s-machine manages data associated with a screen element rendered to the display screen within the rendering region at the first layer.

  2. Repetition-based Interactive Facade Modeling

    KAUST Repository

    AlHalawani, Sawsan

    2012-07-01

    Modeling and reconstruction of urban environments has gained researchers attention throughout the past few years. It spreads in a variety of directions across multiple disciplines such as image processing, computer graphics and computer vision as well as in architecture, geoscience and remote sensing. Having a virtual world of our real cities is very attractive in various directions such as entertainment, engineering, governments among many others. In this thesis, we address the problem of processing a single fa cade image to acquire useful information that can be utilized to manipulate the fa cade and generate variations of fa cade images which can be later used for buildings\\' texturing. Typical fa cade structures exhibit a rectilinear distribution where in windows and other elements are organized in a grid of horizontal and vertical repetitions of similar patterns. In the firt part of this thesis, we propose an efficient algorithm that exploits information obtained from a single image to identify the distribution grid of the dominant elements i.e. windows. This detection method is initially assisted with the user marking the dominant window followed by an automatic process for identifying its repeated instances which are used to define the structure grid. Given the distribution grid, we allow the user to interactively manipulate the fa cade by adding, deleting, resizing or repositioning the windows in order to generate new fa cade structures. Having the utility for the interactive fa cade is very valuable to create fa cade variations and generate new textures for building models. Ultimately, there is a wide range of interesting possibilities of interactions to be explored.

  3. Marginal and Interaction Effects in Ordered Response Models

    OpenAIRE

    Debdulal Mallick

    2009-01-01

    In discrete choice models the marginal effect of a variable of interest that is interacted with another variable differs from the marginal effect of a variable that is not interacted with any variable. The magnitude of the interaction effect is also not equal to the marginal effect of the interaction term. I present consistent estimators of both marginal and interaction effects in ordered response models. This procedure is general and can easily be extended to other discrete choice models. I ...

  4. Adaptive hierarchical grid model of water-borne pollutant dispersion

    Science.gov (United States)

    Borthwick, A. G. L.; Marchant, R. D.; Copeland, G. J. M.

    Water pollution by industrial and agricultural waste is an increasingly major public health issue. It is therefore important for water engineers and managers to be able to predict accurately the local behaviour of water-borne pollutants. This paper describes the novel and efficient coupling of dynamically adaptive hierarchical grids with standard solvers of the advection-diffusion equation. Adaptive quadtree grids are able to focus on regions of interest such as pollutant fronts, while retaining economy in the total number of grid elements through selective grid refinement. Advection is treated using Lagrangian particle tracking. Diffusion is solved separately using two grid-based methods; one is by explicit finite differences, the other a diffusion-velocity approach. Results are given in two dimensions for pure diffusion of an initially Gaussian plume, advection-diffusion of the Gaussian plume in the rotating flow field of a forced vortex, and the transport of species in a rectangular channel with side wall boundary layers. Close agreement is achieved with analytical solutions of the advection-diffusion equation and simulations from a Lagrangian random walk model. An application to Sepetiba Bay, Brazil is included to demonstrate the method with complex flows and topography.

  5. Scale-adaptive surface modeling of vascular structures

    Directory of Open Access Journals (Sweden)

    Ma Xin

    2010-11-01

    Full Text Available Abstract Background The effective geometric modeling of vascular structures is crucial for diagnosis, therapy planning and medical education. These applications require good balance with respect to surface smoothness, surface accuracy, triangle quality and surface size. Methods Our method first extracts the vascular boundary voxels from the segmentation result, and utilizes these voxels to build a three-dimensional (3D point cloud whose normal vectors are estimated via covariance analysis. Then a 3D implicit indicator function is computed from the oriented 3D point cloud by solving a Poisson equation. Finally the vessel surface is generated by a proposed adaptive polygonization algorithm for explicit 3D visualization. Results Experiments carried out on several typical vascular structures demonstrate that the presented method yields both a smooth morphologically correct and a topologically preserved two-manifold surface, which is scale-adaptive to the local curvature of the surface. Furthermore, the presented method produces fewer and better-shaped triangles with satisfactory surface quality and accuracy. Conclusions Compared to other state-of-the-art approaches, our method reaches good balance in terms of smoothness, accuracy, triangle quality and surface size. The vessel surfaces produced by our method are suitable for applications such as computational fluid dynamics simulations and real-time virtual interventional surgery.

  6. Neural network-based model reference adaptive control system.

    Science.gov (United States)

    Patino, H D; Liu, D

    2000-01-01

    In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.

  7. Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

    Science.gov (United States)

    Lin, Chien-Chuan; Wang, Ming-Shi

    2012-01-01

    A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

  8. Water System Adaptation To Hydrological Changes: Module 11, Methods and Tools: Computational Models

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  9. A Universal Model of Giftedness--An Adaptation of the Munich Model

    Science.gov (United States)

    Jessurun, J. H.; Shearer, C. B.; Weggeman, M. C. D. P.

    2016-01-01

    The Munich Model of Giftedness (MMG) by Heller and his colleagues, developed for the identification of gifted children, is adapted and expanded, with the aim of making it more universally usable as a model for the pathway from talents to performance. On the side of the talent-factors, the concept of multiple intelligences is introduced, and the…

  10. Modeling energy-economy interactions using integrated models

    International Nuclear Information System (INIS)

    Uyterlinde, M.A.

    1994-06-01

    Integrated models are defined as economic energy models that consist of several submodels, either coupled by an interface module, or embedded in one large model. These models can be used for energy policy analysis. Using integrated models yields the following benefits. They provide a framework in which energy-economy interactions can be better analyzed than in stand-alone models. Integrated models can represent both energy sector technological details, as well as the behaviour of the market and the role of prices. Furthermore, the combination of modeling methodologies in one model can compensate weaknesses of one approach with strengths of another. These advantages motivated this survey of the class of integrated models. The purpose of this literature survey therefore was to collect and to present information on integrated models. To carry out this task, several goals were identified. The first goal was to give an overview of what is reported on these models in general. The second one was to find and describe examples of such models. Other goals were to find out what kinds of models were used as component models, and to examine the linkage methodology. Solution methods and their convergence properties were also a subject of interest. The report has the following structure. In chapter 2, a 'conceptual framework' is given. In chapter 3 a number of integrated models is described. In a table, a complete overview is presented of all described models. Finally, in chapter 4, the report is summarized, and conclusions are drawn regarding the advantages and drawbacks of integrated models. 8 figs., 29 refs

  11. Modeling mechanical interactions between cancerous mammary acini

    Science.gov (United States)

    Wang, Jeffrey; Liphardt, Jan; Rycroft, Chris

    2015-03-01

    The rules and mechanical forces governing cell motility and interactions with the extracellular matrix of a tissue are often critical for understanding the mechanisms by which breast cancer is able to spread through the breast tissue and eventually metastasize. Ex vivo experimentation has demonstrated the the formation of long collagen fibers through collagen gels between the cancerous mammary acini responsible for milk production, providing a fiber scaffolding along which cancer cells can disorganize. We present a minimal mechanical model that serves as a potential explanation for the formation of these collagen fibers and the resultant motion. Our working hypothesis is that cancerous cells induce this fiber formation by pulling on the gel and taking advantage of the specific mechanical properties of collagen. To model this system, we employ a new Eulerian, fixed grid simulation method to model the collagen as a nonlinear viscoelastic material subject to various forces coupled with a multi-agent model to describe individual cancer cells. We find that these phenomena can be explained two simple ideas: cells pull collagen radially inwards and move towards the tension gradient of the collagen gel, while being exposed to standard adhesive and collision forces.

  12. Computer modeling describes gravity-related adaptation in cell cultures.

    Science.gov (United States)

    Alexandrov, Ludmil B; Alexandrova, Stoyana; Usheva, Anny

    2009-12-16

    Questions about the changes of biological systems in response to hostile environmental factors are important but not easy to answer. Often, the traditional description with differential equations is difficult due to the overwhelming complexity of the living systems. Another way to describe complex systems is by simulating them with phenomenological models such as the well-known evolutionary agent-based model (EABM). Here we developed an EABM to simulate cell colonies as a multi-agent system that adapts to hyper-gravity in starvation conditions. In the model, the cell's heritable characteristics are generated and transferred randomly to offspring cells. After a qualitative validation of the model at normal gravity, we simulate cellular growth in hyper-gravity conditions. The obtained data are consistent with previously confirmed theoretical and experimental findings for bacterial behavior in environmental changes, including the experimental data from the microgravity Atlantis and the Hypergravity 3000 experiments. Our results demonstrate that it is possible to utilize an EABM with realistic qualitative description to examine the effects of hypergravity and starvation on complex cellular entities.

  13. New realisation of Preisach model using adaptive polynomial approximation

    Science.gov (United States)

    Liu, Van-Tsai; Lin, Chun-Liang; Wing, Home-Young

    2012-09-01

    Modelling system with hysteresis has received considerable attention recently due to the increasing accurate requirement in engineering applications. The classical Preisach model (CPM) is the most popular model to demonstrate hysteresis which can be represented by infinite but countable first-order reversal curves (FORCs). The usage of look-up tables is one way to approach the CPM in actual practice. The data in those tables correspond with the samples of a finite number of FORCs. This approach, however, faces two major problems: firstly, it requires a large amount of memory space to obtain an accurate prediction of hysteresis; secondly, it is difficult to derive efficient ways to modify the data table to reflect the timing effect of elements with hysteresis. To overcome, this article proposes the idea of using a set of polynomials to emulate the CPM instead of table look-up. The polynomial approximation requires less memory space for data storage. Furthermore, the polynomial coefficients can be obtained accurately by using the least-square approximation or adaptive identification algorithm, such as the possibility of accurate tracking of hysteresis model parameters.

  14. Interactions of Model Cell Membranes with Nanoparticles

    Science.gov (United States)

    D'Angelo, S. M.; Camesano, T. A.; Nagarajan, R.

    2011-12-01

    The same properties that give nanoparticles their enhanced function, such as high surface area, small size, and better conductivity, can also alter the cytotoxicity of nanomaterials. Ultimately, many of these nanomaterials will be released into the environment, and can cause cytotoxic effects to environmental bacteria, aquatic organisms, and humans. Previous results from our laboratory suggest that nanoparticles can have a detrimental effect on cells, depending on nanoparticle size. It is our goal to characterize the properties of nanomaterials that can result in membrane destabilization. We tested the effects of nanoparticle size and chemical functionalization on nanoparticle-membrane interactions. Gold nanoparticles at 2, 5,10, and 80 nm were investigated, with a concentration of 1.1x1010 particles/mL. Model cell membranes were constructed of of L-α-phosphatidylcholine (egg PC), which has negatively charged lipid headgroups. A quartz crystal microbalance with dissipation (QCM-D) was used to measure frequency changes at different overtones, which were related to mass changes corresponding to nanoparticle interaction with the model membrane. In QCM-D, a lipid bilayer is constructed on a silicon dioxide crystal. The crystals, oscillate at different harmonic frequencies depending upon changes in mass or energy dissipation. When mass is added to the crystal surface, such as through addition of a lipid vesicle solution, the frequency change decreases. By monitoring the frequency and dissipation, we could verify that a supported lipid bilayer (SLB) formed on the silica surface. After formation of the SLB, the nanoparticles can be added to the system, and the changes in frequency and dissipation are monitored in order to build a mechanistic understanding of nanoparticle-cell membrane interactions. For all of the smaller nanoparticles (2, 5, and 10 nm), nanoparticle addition caused a loss of mass from the lipid bilayer, which appears to be due to the formation of holes

  15. Science Roles and Interactions in Adaptive Management of Large River Restoration Projects, Midwest United States

    Science.gov (United States)

    Jacobson, R. B.; Galat, D. L.; Smith, C. B.

    2010-12-01

    Most large-river restoration projects include formal or informal implementations of adaptive management strategies which acknowledge uncertainty and use scientific inquiry to learn and refine management options. Although the central role of science in reducing uncertainty is acknowledged in such projects, specific roles and interactions can vary widely, including how science relates to decision-making within the governance of these projects. Our objective is to present some structured generalizations about science roles and interactions as developed from the authors’ experiences in adaptive management of large river restoration in the Midwest United States. Scientific information may be introduced into decision making by scientists acting in any of the three roles common to adaptive management -- action agency representative, stakeholder, or science provider. We have observed that confusion and gridlock can arise when it is unclear if a scientist is acting as an advocate for a stakeholder or management position, or instead as an independent, “honest broker” of science. Although both advocacy and independence are proper and expected in public decision making, it is useful when scientists unambiguously identify their role. While complete scientific independence may be illusory, transparency and peer review can promote the ideal. Transparency comes from setting clear directions and objectives at the decision-making level and defining at the outset how learning will help assess progress and inform decisions. Independent peer reviews of proposals, study plans, and publications serve as a powerful tool to advance scientific independence, even if funding sources present a potential conflict of interest. Selection of experts for scientific advice and review often requires consideration of the balance between benefits of the “outside” expert (independent, knowledgeable but with little specific understanding of the river system), compared to those provided by the

  16. Agenda Setting for Health Promotion: Exploring an Adapted Model for the Social Media Era.

    Science.gov (United States)

    Albalawi, Yousef; Sixsmith, Jane

    2015-01-01

    The foundation of best practice in health promotion is a robust theoretical base that informs design, implementation, and evaluation of interventions that promote the public's health. This study provides a novel contribution to health promotion through the adaptation of the agenda-setting approach in response to the contribution of social media. This exploration and proposed adaptation is derived from a study that examined the effectiveness of Twitter in influencing agenda setting among users in relation to road traffic accidents in Saudi Arabia. The proposed adaptations to the agenda-setting model to be explored reflect two levels of engagement: agenda setting within the social media sphere and the position of social media within classic agenda setting. This exploratory research aims to assess the veracity of the proposed adaptations on the basis of the hypotheses developed to test these two levels of engagement. To validate the hypotheses, we collected and analyzed data from two primary sources: Twitter activities and Saudi national newspapers. Keyword mentions served as indicators of agenda promotion; for Twitter, interactions were used to measure the process of agenda setting within the platform. The Twitter final dataset comprised 59,046 tweets and 38,066 users who contributed by tweeting, replying, or retweeting. Variables were collected for each tweet and user. In addition, 518 keyword mentions were recorded from six popular Saudi national newspapers. The results showed significant ratification of the study hypotheses at both levels of engagement that framed the proposed adaptions. The results indicate that social media facilitates the contribution of individuals in influencing agendas (individual users accounted for 76.29%, 67.79%, and 96.16% of retweet impressions, total impressions, and amplification multipliers, respectively), a component missing from traditional constructions of agenda-setting models. The influence of organizations on agenda setting is

  17. Agenda Setting for Health Promotion: Exploring an Adapted Model for the Social Media Era

    Science.gov (United States)

    2015-01-01

    Background The foundation of best practice in health promotion is a robust theoretical base that informs design, implementation, and evaluation of interventions that promote the public’s health. This study provides a novel contribution to health promotion through the adaptation of the agenda-setting approach in response to the contribution of social media. This exploration and proposed adaptation is derived from a study that examined the effectiveness of Twitter in influencing agenda setting among users in relation to road traffic accidents in Saudi Arabia. Objective The proposed adaptations to the agenda-setting model to be explored reflect two levels of engagement: agenda setting within the social media sphere and the position of social media within classic agenda setting. This exploratory research aims to assess the veracity of the proposed adaptations on the basis of the hypotheses developed to test these two levels of engagement. Methods To validate the hypotheses, we collected and analyzed data from two primary sources: Twitter activities and Saudi national newspapers. Keyword mentions served as indicators of agenda promotion; for Twitter, interactions were used to measure the process of agenda setting within the platform. The Twitter final dataset comprised 59,046 tweets and 38,066 users who contributed by tweeting, replying, or retweeting. Variables were collected for each tweet and user. In addition, 518 keyword mentions were recorded from six popular Saudi national newspapers. Results The results showed significant ratification of the study hypotheses at both levels of engagement that framed the proposed adaptions. The results indicate that social media facilitates the contribution of individuals in influencing agendas (individual users accounted for 76.29%, 67.79%, and 96.16% of retweet impressions, total impressions, and amplification multipliers, respectively), a component missing from traditional constructions of agenda-setting models. The influence

  18. Integrating interactive computational modeling in biology curricula.

    Directory of Open Access Journals (Sweden)

    Tomáš Helikar

    2015-03-01

    Full Text Available While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

  19. Integrating interactive computational modeling in biology curricula.

    Science.gov (United States)

    Helikar, Tomáš; Cutucache, Christine E; Dahlquist, Lauren M; Herek, Tyler A; Larson, Joshua J; Rogers, Jim A

    2015-03-01

    While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

  20. Modeling the behavioral substrates of associate learning and memory - Adaptive neural models

    Science.gov (United States)

    Lee, Chuen-Chien

    1991-01-01

    Three adaptive single-neuron models based on neural analogies of behavior modification episodes are proposed, which attempt to bridge the gap between psychology and neurophysiology. The proposed models capture the predictive nature of Pavlovian conditioning, which is essential to the theory of adaptive/learning systems. The models learn to anticipate the occurrence of a conditioned response before the presence of a reinforcing stimulus when training is complete. Furthermore, each model can find the most nonredundant and earliest predictor of reinforcement. The behavior of the models accounts for several aspects of basic animal learning phenomena in Pavlovian conditioning beyond previous related models. Computer simulations show how well the models fit empirical data from various animal learning paradigms.

  1. Scale Adaptive Simulation Model for the Darrieus Wind Turbine

    Science.gov (United States)

    Rogowski, K.; Hansen, M. O. L.; Maroński, R.; Lichota, P.

    2016-09-01

    Accurate prediction of aerodynamic loads for the Darrieus wind turbine using more or less complex aerodynamic models is still a challenge. One of the problems is the small amount of experimental data available to validate the numerical codes. The major objective of the present study is to examine the scale adaptive simulation (SAS) approach for performance analysis of a one-bladed Darrieus wind turbine working at a tip speed ratio of 5 and at a blade Reynolds number of 40 000. The three-dimensional incompressible unsteady Navier-Stokes equations are used. Numerical results of aerodynamic loads and wake velocity profiles behind the rotor are compared with experimental data taken from literature. The level of agreement between CFD and experimental results is reasonable.

  2. Adaptive model predictive process control using neural networks

    Science.gov (United States)

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  3. Adapting models of visual aesthetics for personalized content creation

    DEFF Research Database (Denmark)

    Liapis, Antonios; Yannakakis, Georgios N.; Togelius, Julian

    2012-01-01

    This paper introduces a search-based approach to personalized content generation with respect to visual aesthetics. The approach is based on a two-step adaptation procedure where (1) the evaluation function that characterizes the content is adjusted to match the visual aesthetics of users and (2......) the content itself is optimized based on the personalized evaluation function. To test the efficacy of the approach we design fitness functions based on universal properties of visual perception, inspired by psychological and neurobiological research. Using these visual properties we generate aesthetically...... spaceships according to their visual taste: the impact of the various visual properties is adjusted based on player preferences and new content is generated online based on the updated computational model of visual aesthetics of the player. Results are presented which show the potential of the approach...

  4. From dysfunction to adaptation: an interactionist model of dependency.

    Science.gov (United States)

    Bornstein, Robert F

    2012-01-01

    Contrary to clinical lore, a dependent personality style is associated with active as well as passive behavior and may be adaptive in certain contexts (e.g., in fostering compliance with medical and psychotherapeutic treatment regimens). The cognitive/interactionist model conceptualizes dependency-related responding in terms of four components: (a) motivational (a marked need for guidance, support, and approval from others); (b) cognitive (a perception of oneself as powerless and ineffectual); (c) affective (a tendency to become anxious when required to function autonomously); and (d) behavioral (use of diverse self-presentation strategies to strengthen ties to potential caregivers). Clinicians' understanding of the etiology and dynamics of dependency has improved substantially in recent years; current challenges include delineating useful subtypes of dependency, developing valid symptom criteria for Dependent Personality Disorder in DSM-5 and beyond, and working effectively with dependent patients in the age of managed care.

  5. Rao-Blackwellization for Adaptive Gaussian Sum Nonlinear Model Propagation

    Science.gov (United States)

    Semper, Sean R.; Crassidis, John L.; George, Jemin; Mukherjee, Siddharth; Singla, Puneet

    2015-01-01

    When dealing with imperfect data and general models of dynamic systems, the best estimate is always sought in the presence of uncertainty or unknown parameters. In many cases, as the first attempt, the Extended Kalman filter (EKF) provides sufficient solutions to handling issues arising from nonlinear and non-Gaussian estimation problems. But these issues may lead unacceptable performance and even divergence. In order to accurately capture the nonlinearities of most real-world dynamic systems, advanced filtering methods have been created to reduce filter divergence while enhancing performance. Approaches, such as Gaussian sum filtering, grid based Bayesian methods and particle filters are well-known examples of advanced methods used to represent and recursively reproduce an approximation to the state probability density function (pdf). Some of these filtering methods were conceptually developed years before their widespread uses were realized. Advanced nonlinear filtering methods currently benefit from the computing advancements in computational speeds, memory, and parallel processing. Grid based methods, multiple-model approaches and Gaussian sum filtering are numerical solutions that take advantage of different state coordinates or multiple-model methods that reduced the amount of approximations used. Choosing an efficient grid is very difficult for multi-dimensional state spaces, and oftentimes expensive computations must be done at each point. For the original Gaussian sum filter, a weighted sum of Gaussian density functions approximates the pdf but suffers at the update step for the individual component weight selections. In order to improve upon the original Gaussian sum filter, Ref. [2] introduces a weight update approach at the filter propagation stage instead of the measurement update stage. This weight update is performed by minimizing the integral square difference between the true forecast pdf and its Gaussian sum approximation. By adaptively updating

  6. A model of adaptive decision-making from representation of information environment by quantum fields

    Science.gov (United States)

    Bagarello, F.; Haven, E.; Khrennikov, A.

    2017-10-01

    We present the mathematical model of decision-making (DM) of agents acting in a complex and uncertain environment (combining huge variety of economical, financial, behavioural and geopolitical factors). To describe interaction of agents with it, we apply the formalism of quantum field theory (QTF). Quantum fields are a purely informational nature. The QFT model can be treated as a far relative of the expected utility theory, where the role of utility is played by adaptivity to an environment (bath). However, this sort of utility-adaptivity cannot be represented simply as a numerical function. The operator representation in Hilbert space is used and adaptivity is described as in quantum dynamics. We are especially interested in stabilization of solutions for sufficiently large time. The outputs of this stabilization process, probabilities for possible choices, are treated in the framework of classical DM. To connect classical and quantum DM, we appeal to Quantum Bayesianism. We demonstrate the quantum-like interference effect in DM, which is exhibited as a violation of the formula of total probability, and hence the classical Bayesian inference scheme. This article is part of the themed issue `Second quantum revolution: foundational questions'.

  7. A model of adaptive decision-making from representation of information environment by quantum fields.

    Science.gov (United States)

    Bagarello, F; Haven, E; Khrennikov, A

    2017-11-13

    We present the mathematical model of decision-making (DM) of agents acting in a complex and uncertain environment (combining huge variety of economical, financial, behavioural and geopolitical factors). To describe interaction of agents with it, we apply the formalism of quantum field theory (QTF). Quantum fields are a purely informational nature. The QFT model can be treated as a far relative of the expected utility theory, where the role of utility is played by adaptivity to an environment (bath). However, this sort of utility-adaptivity cannot be represented simply as a numerical function. The operator representation in Hilbert space is used and adaptivity is described as in quantum dynamics. We are especially interested in stabilization of solutions for sufficiently large time. The outputs of this stabilization process, probabilities for possible choices, are treated in the framework of classical DM. To connect classical and quantum DM, we appeal to Quantum Bayesianism. We demonstrate the quantum-like interference effect in DM, which is exhibited as a violation of the formula of total probability, and hence the classical Bayesian inference scheme.This article is part of the themed issue 'Second quantum revolution: foundational questions'. © 2017 The Author(s).

  8. Smooth Adaptive Internal Model Control Based on U Model for Nonlinear Systems with Dynamic Uncertainties

    Directory of Open Access Journals (Sweden)

    Li Zhao

    2016-01-01

    Full Text Available An improved smooth adaptive internal model control based on U model control method is presented to simplify modeling structure and parameter identification for a class of uncertain dynamic systems with unknown model parameters and bounded external disturbances. Differing from traditional adaptive methods, the proposed controller can simplify the identification of time-varying parameters in presence of bounded external disturbances. Combining the small gain theorem and the virtual equivalent system theory, learning rate of smooth adaptive internal model controller has been analyzed and the closed-loop virtual equivalent system based on discrete U model has been constructed as well. The convergence of this virtual equivalent system is proved, which further shows the convergence of the complex closed-loop discrete U model system. Finally, simulation and experimental results on a typical nonlinear dynamic system verified the feasibility of the proposed algorithm. The proposed method is shown to have lighter identification burden and higher control accuracy than the traditional adaptive controller.

  9. Adaptive Surface Modeling of Soil Properties in Complex Landforms

    Directory of Open Access Journals (Sweden)

    Wei Liu

    2017-06-01

    Full Text Available Abstract: Spatial discontinuity often causes poor accuracy when a single model is used for the surface modeling of soil properties in complex geomorphic areas. Here we present a method for adaptive surface modeling of combined secondary variables to improve prediction accuracy during the interpolation of soil properties (ASM-SP. Using various secondary variables and multiple base interpolation models, ASM-SP was used to interpolate soil K+ in a typical complex geomorphic area (Qinghai Lake Basin, China. Five methods, including inverse distance weighting (IDW, ordinary kriging (OK, and OK combined with different secondary variables (e.g., OK-Landuse, OK-Geology, and OK-Soil, were used to validate the proposed method. The mean error (ME, mean absolute error (MAE, root mean square error (RMSE, mean relative error (MRE, and accuracy (AC were used as evaluation indicators. Results showed that: (1 The OK interpolation result is spatially smooth and has a weak bull's-eye effect, and the IDW has a stronger ‘bull’s-eye’ effect, relatively. They both have obvious deficiencies in depicting spatial variability of soil K+. (2 The methods incorporating combinations of different secondary variables (e.g., ASM-SP, OK-Landuse, OK-Geology, and OK-Soil were associated with lower estimation bias. Compared with IDW, OK, OK-Landuse, OK-Geology, and OK-Soil, the accuracy of ASM-SP increased by 13.63%, 10.85%, 9.98%, 8.32%, and 7.66%, respectively. Furthermore, ASM-SP was more stable, with lower MEs, MAEs, RMSEs, and MREs. (3 ASM-SP presents more details than others in the abrupt boundary, which can render the result consistent with the true secondary variables. In conclusion, ASM-SP can not only consider the nonlinear relationship between secondary variables and soil properties, but can also adaptively combine the advantages of multiple models, which contributes to making the spatial interpolation of soil K+ more reasonable.

  10. A user-specific human-machine interaction strategy for a prosthetic shank adapter

    Directory of Open Access Journals (Sweden)

    Stuhlenmiller Florian

    2017-09-01

    Full Text Available For people with lower limb amputation, a user-specific human-machine interaction with their prostheses is required to ensure safe and comfortable assistance. Especially during dynamic turning manoeuvres, users experience high loads at the stump, which decreases comfort and may lead to long-term tissue damage. Preliminary experiments with users wearing a configurable, passive torsional adaptor indicate increased comfort and safety achieved by adaptation of torsional stiffness and foot alignment. Moreover, the results show that the individual preference regarding both parameters depend on gait situation and individual preference. Hence, measured loads in the structure of the prosthesis and subjective feedback regarding comfort and safety during different turning motions are considered in a user-specific human-machine interaction strategy for a prosthetic shank adaptor. Therefore, the interrelations of gait parameters with optimal configuration are stored in an individual preference-setting matrix. Stiffness and foot alignment are actively adjusted to the optimal parameters by a parallel elastic actuator. Two subjects reported that they experienced appropriate variation of stiffness and foot alignment, a noticeable reduction of load at the stump and that they could turn with less effort.

  11. ABISM: an interactive image quality assessment tool for adaptive optics instruments

    Science.gov (United States)

    Girard, Julien H.; Tourneboeuf, Martin

    2016-07-01

    ABISM (Automatic Background Interactive Strehl Meter) is a interactive tool to evaluate the image quality of astronomical images. It works on seeing-limited point spread functions (PSF) but was developed in particular for diffraction-limited PSF produced by adaptive optics (AO) systems. In the VLT service mode (SM) operations framework, ABISM is designed to help support astronomers or telescope and instruments operators (TIOs) to quickly measure the Strehl ratio (SR) during or right after an observing block (OB) to evaluate whether it meets the requirements/predictions or whether is has to be repeated and will remain in the SM queue. It's a Python-based tool with a graphical user interface (GUI) that can be used with little AO knowledge. The night astronomer (NA) or Telescope and Instrument Operator (TIO) can launch ABISM in one click and the program is able to read keywords from the FITS header to avoid mistakes. A significant effort was also put to make ABISM as robust (and forgiven) with a high rate of repeatability. As a matter of fact, ABISM is able to automatically correct for bad pixels, eliminate stellar neighbours and estimate/fit properly the background, etc.

  12. AN INDUCTIVE, INTERACTIVE AND ADAPTIVE HYBRID PROBLEM-BASED LEARNING METHODOLOGY: APPLICATION TO STATISTICS

    Directory of Open Access Journals (Sweden)

    ADA ZHENG

    2011-10-01

    Full Text Available We have developed an innovative hybrid problem-based learning (PBL methodology. The methodology has the following distinctive features: i Each complex question was decomposed into a set of coherent finer subquestions by following the carefully designed criteria to maintain a delicate balance between guiding the students and inspiring them to think independently. This learning methodology enabled the students to solve the complex questions progressively in an inductive context. ii Facilitated by the utilization of our web-based learning systems, the teacher was able to interact with the students intensively and could allocate more teaching time to provide tailor-made feedback for individual student. The students were actively engaged in the learning activities, stimulated by the intensive interaction. iii The answers submitted by the students could be automatically consolidated in the report of the Moodle system in real-time. The teacher could adjust the teaching schedule and focus of the class to adapt to the learning progress of the students by analysing the automatically generated report and log files of the web-based learning system. As a result, the attendance rate of the students increased from about 50% to more than 90%, and the students’ learning motivation have been significantly enhanced.

  13. Identifying Opportunities for Exploiting Cross-Layer Interactions in Adaptive Wireless Systems

    Directory of Open Access Journals (Sweden)

    Troy Weingart

    2007-01-01

    Full Text Available The flexibility of cognitive and software-defined radio heralds an opportunity for researchers to reexamine how network protocol layers operate with respect to providing quality of service aware transmission among wireless nodes. This opportunity is enhanced by the continued development of spectrally responsive devices—ones that can detect and respond to changes in the radio frequency environment. Present wireless network protocols define reliability and other performance-related tasks narrowly within layers. For example, the frame size employed on 802.11 can substantially influence the throughput, delay, and jitter experienced by an application, but there is no simple way to adapt this parameter. Furthermore, while the data link layer of 802.11 provides error detection capabilities across a link, it does not specify additional features, such as forward error correction schemes, nor does it provide a means for throttling retransmissions at the transport layer (currently, the data link and transport layer can function counterproductively with respect to reliability. This paper presents an analysis of the interaction of physical, data link, and network layer parameters with respect to throughput, bit error rate, delay, and jitter. The goal of this analysis is to identify opportunities where system designers might exploit cross-layer interactions to improve the performance of Voice over IP (VoIP, instant messaging (IM, and file transfer applications.

  14. Adaptive unified continuum FEM modeling of a 3D FSI benchmark problem.

    Science.gov (United States)

    Jansson, Johan; Degirmenci, Niyazi Cem; Hoffman, Johan

    2017-09-01

    In this paper, we address a 3D fluid-structure interaction benchmark problem that represents important characteristics of biomedical modeling. We present a goal-oriented adaptive finite element methodology for incompressible fluid-structure interaction based on a streamline diffusion-type stabilization of the balance equations for mass and momentum for the entire continuum in the domain, which is implemented in the Unicorn/FEniCS software framework. A phase marker function and its corresponding transport equation are introduced to select the constitutive law, where the mesh tracks the discontinuous fluid-structure interface. This results in a unified simulation method for fluids and structures. We present detailed results for the benchmark problem compared with experiments, together with a mesh convergence study. Copyright © 2016 John Wiley & Sons, Ltd.

  15. Geodynamo Modeling of Core-Mantle Interactions

    Science.gov (United States)

    Kuang, Wei-Jia; Chao, Benjamin F.; Smith, David E. (Technical Monitor)

    2001-01-01

    Angular momentum exchange between the Earth's mantle and core influences the Earth's rotation on time scales of decades and longer, in particular in the length of day (LOD) which have been measured with progressively increasing accuracy for the last two centuries. There are four possible coupling mechanisms for transferring the axial angular momentum across the core-mantle boundary (CMB): viscous, magnetic, topography, and gravitational torques. Here we use our scalable, modularized, fully dynamic geodynamo model for the core to assess the importance of these torques. This numerical model, as an extension of the Kuang-Bloxham model that has successfully simulated the generation of the Earth's magnetic field, is used to obtain numerical results in various physical conditions in terms of specific parameterization consistent with the dynamical processes in the fluid outer core. The results show that depending on the electrical conductivity of the lower mantle and the amplitude of the boundary topography at CMB, both magnetic and topographic couplings can contribute significantly to the angular momentum exchange. This implies that the core-mantle interactions are far more complex than has been assumed and that there is unlikely a single dominant coupling mechanism for the observed decadal LOD variation.

  16. Using plural modeling for predicting decisions made by adaptive adversaries

    International Nuclear Information System (INIS)

    Buede, Dennis M.; Mahoney, Suzanne; Ezell, Barry; Lathrop, John

    2012-01-01

    Incorporating an appropriate representation of the likelihood of terrorist decision outcomes into risk assessments associated with weapons of mass destruction attacks has been a significant problem for countries around the world. Developing these likelihoods gets at the heart of the most difficult predictive problems: human decision making, adaptive adversaries, and adversaries about which very little is known. A plural modeling approach is proposed that incorporates estimates of all critical uncertainties: who is the adversary and what skills and resources are available to him, what information is known to the adversary and what perceptions of the important facts are held by this group or individual, what does the adversary know about the countermeasure actions taken by the government in question, what are the adversary's objectives and the priorities of those objectives, what would trigger the adversary to start an attack and what kind of success does the adversary desire, how realistic is the adversary in estimating the success of an attack, how does the adversary make a decision and what type of model best predicts this decision-making process. A computational framework is defined to aggregate the predictions from a suite of models, based on this broad array of uncertainties. A validation approach is described that deals with a significant scarcity of data.

  17. Interaction of elaiophylin with model bilayer membrane

    Science.gov (United States)

    Genova, J.; Dencheva-Zarkova, M.

    2017-01-01

    Elaiophylin is a new macrodiolide antibiotic, which is produced by the Streptomyces strains [1]. It displays biological activities against Gram-positive bacteria and fungi. The mode of action of this antibiotic has been attributed to an alteration of the membrane permeability. When this antibiotic is inserted into the bilayer membranes destabilization of the membrane and formation of ion-penetrable channels is observed. The macrodiolide antibiotic forms stable cation selective ion channels in synthetic lipid bilayer membranes. The aim of this work was to study the interactions of Elaiophylin with model bilayer membranes and to get information on the mechanical properties of lipid bilayers in presence of this antibiotic. Patch-clamp technique [2] were used in the study

  18. Neutron matter with a model interaction

    International Nuclear Information System (INIS)

    Amusia, M.Ya.; Shaginyan, V.R.

    2000-01-01

    An infinite system of neutrons interacting by a model pair potential is considered. We investigate a case when this potential is sufficiently strong attractive, so that its scattering length a tends to infinity, a →-∞. It appeared, that if the structure of the potential is simple enough, including no finite parameters, reliable evidences can be presented that such a system is completely unstable at any finite density. The incompressibility as a function of the density is negative, reaching zero value when the density tends to zero. If the potential contains a sufficiently strong repulsive core then the system possesses an equilibrium density. The main features of a theory describing such systems are considered. (orig.)

  19. Neutron matter with a model interaction

    Energy Technology Data Exchange (ETDEWEB)

    Amusia, M.Ya. [Hebrew Univ., Jerusalem (Israel). Racah Inst. of Physics; A.F. Ioffe Physical-Technical Institute, 194021 St. Petersburg (Russian Federation); Shaginyan, V.R. [Petersburg Institute of Nuclear Physics, 188350 Gatchina (Russian Federation); Department of Physics, University of Washington, Seattle, WA 98195 (United States)

    2000-05-01

    An infinite system of neutrons interacting by a model pair potential is considered. We investigate a case when this potential is sufficiently strong attractive, so that its scattering length a tends to infinity, a {yields}-{infinity}. It appeared, that if the structure of the potential is simple enough, including no finite parameters, reliable evidences can be presented that such a system is completely unstable at any finite density. The incompressibility as a function of the density is negative, reaching zero value when the density tends to zero. If the potential contains a sufficiently strong repulsive core then the system possesses an equilibrium density. The main features of a theory describing such systems are considered. (orig.)

  20. sdg Interacting boson model: two nucleon transfer

    International Nuclear Information System (INIS)

    Devi, Y.D.; Kota, V.K.B.

    1996-01-01

    A brief overview of the sdg interacting boson model (sdg IBM) is given. The two examples: (i) spectroscopic properties (spectra, B(E2)s, B(E4)s etc) of the rotor-γ unstable transitional Os-Pt isotopes and (ii) the analytical formulation of two nucleon transfer spectroscopic factors and sum-rule quantities are described in detail. They demonstrate that sdg IBM can be employed for systematic description of spectroscopic properties of nuclei and that large number of analytical formulas, which facilitate rapid analysis of data and provide a clear insight into the underlying structures, can be derived using sdg IBM dynamical symmetries respectively. (author). 24 refs., 5 figs., 3 tabs

  1. A Nonlinear Dynamic Inversion Predictor-Based Model Reference Adaptive Controller for a Generic Transport Model

    Science.gov (United States)

    Campbell, Stefan F.; Kaneshige, John T.

    2010-01-01

    Presented here is a Predictor-Based Model Reference Adaptive Control (PMRAC) architecture for a generic transport aircraft. At its core, this architecture features a three-axis, non-linear, dynamic-inversion controller. Command inputs for this baseline controller are provided by pilot roll-rate, pitch-rate, and sideslip commands. This paper will first thoroughly present the baseline controller followed by a description of the PMRAC adaptive augmentation to this control system. Results are presented via a full-scale, nonlinear simulation of NASA s Generic Transport Model (GTM).

  2. Spatially adaptive mixture modeling for analysis of FMRI time series.

    Science.gov (United States)

    Vincent, Thomas; Risser, Laurent; Ciuciu, Philippe

    2010-04-01

    Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In Makni et aL, 2005 and Makni et aL, 2008, a detection-estimation framework has been proposed to tackle these problems jointly, since they are connected to one another. In the Bayesian formalism, detection is achieved by modeling activating and nonactivating voxels through independent mixture models (IMM) within each region while hemodynamic response estimation is performed at a regional scale in a nonparametric way. Instead of IMMs, in this paper we take advantage of spatial mixture models (SMM) for their nonlinear spatial regularizing properties. The proposed method is unsupervised and spatially adaptive in the sense that the amount of spatial correlation is automatically tuned from the data and this setting automatically varies across brain regions. In addition, the level of regularization is specific to each experimental condition since both the signal-to-noise ratio and the activation pattern may vary across stimulus types in a given brain region. These aspects require the precise estimation of multiple partition functions of underlying Ising fields. This is addressed efficiently using first path sampling for a small subset of fields and then using a recently developed fast extrapolation technique for the large remaining set. Simulation results emphasize that detection relying on supervised SMM outperforms its IMM counterpart and that unsupervised spatial mixture models achieve similar results without any hand-tuning of the correlation parameter. On real datasets, the gain is illustrated in a localizer fMRI experiment: brain activations appear more spatially resolved using SMM in comparison with classical general linear model (GLM)-based approaches, while estimating a specific parcel-based HRF shape. Our approach therefore validates the treatment of unsmoothed fMRI data without fixed GLM

  3. Thermal-chemical Mantle Convection Models With Adaptive Mesh Refinement

    Science.gov (United States)

    Leng, W.; Zhong, S.

    2008-12-01

    In numerical modeling of mantle convection, resolution is often crucial for resolving small-scale features. New techniques, adaptive mesh refinement (AMR), allow local mesh refinement wherever high resolution is needed, while leaving other regions with relatively low resolution. Both computational efficiency for large- scale simulation and accuracy for small-scale features can thus be achieved with AMR. Based on the octree data structure [Tu et al. 2005], we implement the AMR techniques into the 2-D mantle convection models. For pure thermal convection models, benchmark tests show that our code can achieve high accuracy with relatively small number of elements both for isoviscous cases (i.e. 7492 AMR elements v.s. 65536 uniform elements) and for temperature-dependent viscosity cases (i.e. 14620 AMR elements v.s. 65536 uniform elements). We further implement tracer-method into the models for simulating thermal-chemical convection. By appropriately adding and removing tracers according to the refinement of the meshes, our code successfully reproduces the benchmark results in van Keken et al. [1997] with much fewer elements and tracers compared with uniform-mesh models (i.e. 7552 AMR elements v.s. 16384 uniform elements, and ~83000 tracers v.s. ~410000 tracers). The boundaries of the chemical piles in our AMR code can be easily refined to the scales of a few kilometers for the Earth's mantle and the tracers are concentrated near the chemical boundaries to precisely trace the evolvement of the boundaries. It is thus very suitable for our AMR code to study the thermal-chemical convection problems which need high resolution to resolve the evolvement of chemical boundaries, such as the entrainment problems [Sleep, 1988].

  4. Overcoming scepticism: Interacting influences of geographical location on perceived climate change adaptation measures to water resources in Spain

    Science.gov (United States)

    Iglesias, Ana; Garrote, Luis; Bardaji, Isabel; Iglesias, Pedro; Granados, Alfredo

    2016-04-01

    Though many climate adaptation efforts attempt to be defined with the participation of local communities, these strategies may be ineffective because among citizens affected equally, a local risk perception rather than scientific understanding largely drives adaptation choices. Further, the geographical location may polarize climate risk perceptions, making some adaptation efforts ineffective among sceptics. This study examines how the local degradation of the environment and water resources relates to adaption choices and in turn, climate change risk perception among a range of citizens in the Tagus basin, Spain (n = 300). We find respondents of less degraded areas have individualistic responses, and are significantly less likely to accept adaptation strategies than respondents in water stressed communities. The interaction between climate knowledge and adaptation choices is positively related to acceptance of adaptation choices in both groups, and had a stronger positive relationship among individualists. There is no statistical difference in acceptance of adaptation between individualists and communitarians at high levels of knowledge (top decile). Thus, education efforts specific to climate change may counteract divisions based geographical location and environmental stress.

  5. Basic emotions and adaptation. A computational and evolutionary model.

    Science.gov (United States)

    Pacella, Daniela; Ponticorvo, Michela; Gigliotta, Onofrio; Miglino, Orazio

    2017-01-01

    The core principles of the evolutionary theories of emotions declare that affective states represent crucial drives for action selection in the environment and regulated the behavior and adaptation of natural agents in ancestrally recurrent situations. While many different studies used autonomous artificial agents to simulate emotional responses and the way these patterns can affect decision-making, few are the approaches that tried to analyze the evolutionary emergence of affective behaviors directly from the specific adaptive problems posed by the ancestral environment. A model of the evolution of affective behaviors is presented using simulated artificial agents equipped with neural networks and physically inspired on the architecture of the iCub humanoid robot. We use genetic algorithms to train populations of virtual robots across generations, and investigate the spontaneous emergence of basic emotional behaviors in different experimental conditions. In particular, we focus on studying the emotion of fear, therefore the environment explored by the artificial agents can contain stimuli that are safe or dangerous to pick. The simulated task is based on classical conditioning and the agents are asked to learn a strategy to recognize whether the environment is safe or represents a threat to their lives and select the correct action to perform in absence of any visual cues. The simulated agents have special input units in their neural structure whose activation keep track of their actual "sensations" based on the outcome of past behavior. We train five different neural network architectures and then test the best ranked individuals comparing their performances and analyzing the unit activations in each individual's life cycle. We show that the agents, regardless of the presence of recurrent connections, spontaneously evolved the ability to cope with potentially dangerous environment by collecting information about the environment and then switching their behavior

  6. Demography-based adaptive network model reproduces the spatial organization of human linguistic groups

    Science.gov (United States)

    Capitán, José A.; Manrubia, Susanna

    2015-12-01

    The distribution of human linguistic groups presents a number of interesting and nontrivial patterns. The distributions of the number of speakers per language and the area each group covers follow log-normal distributions, while population and area fulfill an allometric relationship. The topology of networks of spatial contacts between different linguistic groups has been recently characterized, showing atypical properties of the degree distribution and clustering, among others. Human demography, spatial conflicts, and the construction of networks of contacts between linguistic groups are mutually dependent processes. Here we introduce an adaptive network model that takes all of them into account and successfully reproduces, using only four model parameters, not only those features of linguistic groups already described in the literature, but also correlations between demographic and topological properties uncovered in this work. Besides their relevance when modeling and understanding processes related to human biogeography, our adaptive network model admits a number of generalizations that broaden its scope and make it suitable to represent interactions between agents based on population dynamics and competition for space.

  7. Evaluate the interactive and reusable service in adaptive on demand applications

    OpenAIRE

    Hwang , Chyi-Wen

    2007-01-01

    In this paper, the researcher based on the open platforms and tools for personalized learning idea, with the “ Interactive & reusable” function in UI design model, directly dealing with Knowledge on demand (KOD) service from the aspect-oriented and object-oriented issue. Moreover, to propose the KOD combine with VOD (Video on Demand); AOD (Audio on Demand); COD (Course on Demand) and IOD (Information on Demand in Global index searching) in diversity of hypermedia metadata.

  8. Institute for Multiscale Modeling of Biological Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Paulaitis, Michael E; Garcia-Moreno, Bertrand; Lenhoff, Abraham

    2009-12-26

    The Institute for Multiscale Modeling of Biological Interactions (IMMBI) has two primary goals: Foster interdisciplinary collaborations among faculty and their research laboratories that will lead to novel applications of multiscale simulation and modeling methods in the biological sciences and engineering; and Building on the unique biophysical/biology-based engineering foundations of the participating faculty, train scientists and engineers to apply computational methods that collectively span multiple time and length scales of biological organization. The success of IMMBI will be defined by the following: Size and quality of the applicant pool for pre-doctoral and post-doctoral fellows; Academic performance; Quality of the pre-doctoral and post-doctoral research; Impact of the research broadly and to the DOE (ASCR program) mission; Distinction of the next career step for pre-doctoral and post-doctoral fellows; and Faculty collaborations that result from IMMBI activities. Specific details about accomplishments during the three years of DOE support for IMMBI have been documented in Annual Progress Reports (April 2005, June 2006, and March 2007) and a Report for a National Academy of Sciences Review (October 2005) that were submitted to DOE on the dates indicated. An overview of these accomplishments is provided.

  9. A model-based exploration of the role of pattern generating circuits during locomotor adaptation.

    Science.gov (United States)

    Marjaninejad, Ali; Finley, James M

    2016-08-01

    In this study, we used a model-based approach to explore the potential contributions of central pattern generating circuits (CPGs) during adaptation to external perturbations during locomotion. We constructed a neuromechanical modeled of locomotion using a reduced-phase CPG controller and an inverted pendulum mechanical model. Two different forms of locomotor adaptation were examined in this study: split-belt treadmill adaptation and adaptation to a unilateral, elastic force field. For each simulation, we first examined the effects of phase resetting and varying the model's initial conditions on the resulting adaptation. After evaluating the effect of phase resetting on the adaptation of step length symmetry, we examined the extent to which the results from these simple models could explain previous experimental observations. We found that adaptation of step length symmetry during split-belt treadmill walking could be reproduced using our model, but this model failed to replicate patterns of adaptation observed in response to force field perturbations. Given that spinal animal models can adapt to both of these types of perturbations, our findings suggest that there may be distinct features of pattern generating circuits that mediate each form of adaptation.

  10. ADAPTIVE TEXTURE SYNTHESIS FOR LARGE SCALE CITY MODELING

    Directory of Open Access Journals (Sweden)

    G. Despine

    2015-02-01

    Full Text Available Large scale city models textured with aerial images are well suited for bird-eye navigation but generally the image resolution does not allow pedestrian navigation. One solution to face this problem is to use high resolution terrestrial photos but it requires huge amount of manual work to remove occlusions. Another solution is to synthesize generic textures with a set of procedural rules and elementary patterns like bricks, roof tiles, doors and windows. This solution may give realistic textures but with no correlation to the ground truth. Instead of using pure procedural modelling we present a method to extract information from aerial images and adapt the texture synthesis to each building. We describe a workflow allowing the user to drive the information extraction and to select the appropriate texture patterns. We also emphasize the importance to organize the knowledge about elementary pattern in a texture catalogue allowing attaching physical information, semantic attributes and to execute selection requests. Roofs are processed according to the detected building material. Façades are first described in terms of principal colours, then opening positions are detected and some window features are computed. These features allow selecting the most appropriate patterns from the texture catalogue. We experimented this workflow on two samples with 20 cm and 5 cm resolution images. The roof texture synthesis and opening detection were successfully conducted on hundreds of buildings. The window characterization is still sensitive to the distortions inherent to the projection of aerial images onto the facades.

  11. Adaptive Texture Synthesis for Large Scale City Modeling

    Science.gov (United States)

    Despine, G.; Colleu, T.

    2015-02-01

    Large scale city models textured with aerial images are well suited for bird-eye navigation but generally the image resolution does not allow pedestrian navigation. One solution to face this problem is to use high resolution terrestrial photos but it requires huge amount of manual work to remove occlusions. Another solution is to synthesize generic textures with a set of procedural rules and elementary patterns like bricks, roof tiles, doors and windows. This solution may give realistic textures but with no correlation to the ground truth. Instead of using pure procedural modelling we present a method to extract information from aerial images and adapt the texture synthesis to each building. We describe a workflow allowing the user to drive the information extraction and to select the appropriate texture patterns. We also emphasize the importance to organize the knowledge about elementary pattern in a texture catalogue allowing attaching physical information, semantic attributes and to execute selection requests. Roofs are processed according to the detected building material. Façades are first described in terms of principal colours, then opening positions are detected and some window features are computed. These features allow selecting the most appropriate patterns from the texture catalogue. We experimented this workflow on two samples with 20 cm and 5 cm resolution images. The roof texture synthesis and opening detection were successfully conducted on hundreds of buildings. The window characterization is still sensitive to the distortions inherent to the projection of aerial images onto the facades.

  12. Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

    Energy Technology Data Exchange (ETDEWEB)

    Jablonowski, Christiane [Univ. of Michigan, Ann Arbor, MI (United States)

    2015-07-14

    The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively with advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project

  13. ADAPT: building conceptual models of the physical and biological processes across permafrost landscapes

    Science.gov (United States)

    Allard, M.; Vincent, W. F.; Lemay, M.

    2012-12-01

    Fundamental and applied permafrost research is called upon in Canada in support of environmental protection, economic development and for contributing to the international efforts in understanding climatic and ecological feedbacks of permafrost thawing under a warming climate. The five year "Arctic Development and Adaptation to Permafrost in Transition" program (ADAPT) funded by NSERC brings together 14 scientists from 10 Canadian universities and involves numerous collaborators from academia, territorial and provincial governments, Inuit communities and industry. The geographical coverage of the program encompasses all of the permafrost regions of Canada. Field research at a series of sites across the country is being coordinated. A common protocol for measuring ground thermal and moisture regime, characterizing terrain conditions (vegetation, topography, surface water regime and soil organic matter contents) is being applied in order to provide inputs for designing a general model to provide an understanding of transfers of energy and matter in permafrost terrain, and the implications for biological and human systems. The ADAPT mission is to produce an 'Integrated Permafrost Systems Science' framework that will be used to help generate sustainable development and adaptation strategies for the North in the context of rapid socio-economic and climate change. ADAPT has three major objectives: to examine how changing precipitation and warming temperatures affect permafrost geosystems and ecosystems, specifically by testing hypotheses concerning the influence of the snowpack, the effects of water as a conveyor of heat, sediments, and carbon in warming permafrost terrain and the processes of permafrost decay; to interact directly with Inuit communities, the public sector and the private sector for development and adaptation to changes in permafrost environments; and to train the new generation of experts and scientists in this critical domain of research in Canada

  14. Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model

    Science.gov (United States)

    Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.

    2010-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.

  15. Modeling Stochastic Complexity in Complex Adaptive Systems: Non-Kolmogorov Probability and the Process Algebra Approach.

    Science.gov (United States)

    Sulis, William H

    2017-10-01

    Walter Freeman III pioneered the application of nonlinear dynamical systems theories and methodologies in his work on mesoscopic brain dynamics.Sadly, mainstream psychology and psychiatry still cling to linear correlation based data analysis techniques, which threaten to subvert the process of experimentation and theory building. In order to progress, it is necessary to develop tools capable of managing the stochastic complexity of complex biopsychosocial systems, which includes multilevel feedback relationships, nonlinear interactions, chaotic dynamics and adaptability. In addition, however, these systems exhibit intrinsic randomness, non-Gaussian probability distributions, non-stationarity, contextuality, and non-Kolmogorov probabilities, as well as the absence of mean and/or variance and conditional probabilities. These properties and their implications for statistical analysis are discussed. An alternative approach, the Process Algebra approach, is described. It is a generative model, capable of generating non-Kolmogorov probabilities. It has proven useful in addressing fundamental problems in quantum mechanics and in the modeling of developing psychosocial systems.

  16. Methodology to explore interactions between the water system and society in order to identify adaptation strategies

    Science.gov (United States)

    Offermans, A. G. E.; Haasnoot, M.

    2009-04-01

    Development of sustainable water management strategies involves analysing current and future vulnerability, identification of adaptation possibilities, effect analysis and evaluation of the strategies under different possible futures. Recent studies on water management often followed the pressure-effect chain and compared the state of social, economic and ecological functions of the water systems in one or two future situations with the current situation. The future is, however, more complex and dynamic. Water management faces major challenges to cope with future uncertainties in both the water system as well as the social system. Uncertainties in our water system relate to (changes in) drivers and pressures and their effects on the state, like the effects of climate change on discharges. Uncertainties in the social world relate to changing of perceptions, objectives and demands concerning water (management), which are often related with the aforementioned changes in the physical environment. The methodology presented here comprises the 'Perspectives method', derived from the Cultural Theory, a method on analyzing and classifying social response to social and natural states and pressures. The method will be used for scenario analysis and to identify social responses including changes in perspectives and management strategies. The scenarios and responses will be integrated within a rapid assessment tool. The purpose of the tool is to provide users with insight about the interaction of the social and physical system and to identify robust water management strategies by analysing the effectiveness under different possible futures on the physical, social and socio-economic system. This method allows for a mutual interaction between the physical and social system. We will present the theoretical background of the perspectives method as well as a historical overview of perspective changes in the Dutch Meuse area to show how social and physical systems interrelate. We

  17. Modeling the Interaction of Europa with the Jovian Magnetosphere

    Science.gov (United States)

    Rubin, M.; Combi, M. R.; Daldorff, L.; Gombosi, T. I.; Hansen, K. C.; Jia, X.; Kivelson, M. G.; Tenishev, V.

    2011-12-01

    The interaction of Jupiter's corotating magnetosphere with Europa's subsurface water ocean is responsible for the observed induced dipolar magnetic field. Furthermore the pick-up process of newly ionized particles from Europa's neutral atmosphere alters the magnetic and electric field topology around the moon. We use the Block-Adaptive-Tree-Solarwind-Roe-Upwind-Scheme (BATS-R-US) of the Space Weather Modeling Framework (SWMF) to model the interaction of Europa with the Jovian magnetosphere. The BATS-R-US code solves the governing equations of magnetohydrodynamics (MHD) in a fully 3D adaptive mesh. In our approach we solve the equations for one single ion species, starting from the work by Kabin et al. (J. Geophys. Res., 104, A9, 19983-19992, 1999) accounting for the exospheric mass loading, ion-neutral charge exchange, and ion-electron recombination. We continue by separately solving the electron pressure equation and furthermore extend the magnetic induction equation by the resistive and Hall terms. The resistive term accounts for the finite electron diffusivity and thus allows a more adequate description of the effect of magnetic diffusion due to collisions [Ledvina et al., Sp. Sci. Rev., 139:143-189, 2008]. For this purpose we use ion-electron and electron-neutral collision rates presented by Schunk and Nagy (Ionospheres, Cambridge University Press, 2000). The Hall term allows ions and electrons to move at different velocities while the magnetic field remains frozen to the electrons. The assumed charge neutrality of the ion-electron plasma is maintained everywhere at all times. The model is run at different phases of Jupiter's rotation reflecting the different locations of Europa with respect to the center of the plasma sheet and is compared to measurements obtained by the Galileo magnetometer [Kivelson et al., J. Geophys. Res., 104:4609-4626, 1999]. The resulting influence on the induced magnetic dipolar field is studied and compared to the results from the

  18. Launch Vehicle Manual Steering with Adaptive Augmenting Control In-flight Evaluations of Adverse Interactions Using a Piloted Aircraft

    Science.gov (United States)

    Hanson, Curt; Miller, Chris; Wall, John H.; Vanzwieten, Tannen S.; Gilligan, Eric; Orr, Jeb S.

    2015-01-01

    An adaptive augmenting control algorithm for the Space Launch System has been developed at the Marshall Space Flight Center as part of the launch vehicles baseline flight control system. A prototype version of the SLS flight control software was hosted on a piloted aircraft at the Armstrong Flight Research Center to demonstrate the adaptive controller on a full-scale realistic application in a relevant flight environment. Concerns regarding adverse interactions between the adaptive controller and a proposed manual steering mode were investigated by giving the pilot trajectory deviation cues and pitch rate command authority. Two NASA research pilots flew a total of twenty five constant pitch-rate trajectories using a prototype manual steering mode with and without adaptive control.

  19. Revision of FMM-Yukawa: An adaptive fast multipole method for screened Coulomb interactions

    Science.gov (United States)

    Zhang, Bo; Huang, Jingfang; Pitsianis, Nikos P.; Sun, Xiaobai

    2010-12-01

    FMM-YUKAWA is a mathematical software package primarily for rapid evaluation of the screened Coulomb interactions of N particles in three dimensional space. Since its release, we have revised and re-organized the data structure, software architecture, and user interface, for the purpose of enabling more flexible, broader and easier use of the package. The package and its documentation are available at http://www.fastmultipole.org/, along with a few other closely related mathematical software packages. New version program summaryProgram title: FMM-Yukawa Catalogue identifier: AEEQ_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEQ_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU GPL 2.0 No. of lines in distributed program, including test data, etc.: 78 704 No. of bytes in distributed program, including test data, etc.: 854 265 Distribution format: tar.gz Programming language: FORTRAN 77, FORTRAN 90, and C. Requires gcc and gfortran version 4.4.3 or later Computer: All Operating system: Any Classification: 4.8, 4.12 Catalogue identifier of previous version: AEEQ_v1_0 Journal reference of previous version: Comput. Phys. Comm. 180 (2009) 2331 Does the new version supersede the previous version?: Yes Nature of problem: To evaluate the screened Coulomb potential and force field of N charged particles, and to evaluate a convolution type integral where the Green's function is the fundamental solution of the modified Helmholtz equation. Solution method: The new version of fast multipole method (FMM) that diagonalizes the multipole-to-local translation operator is applied with the tree structure adaptive to sample particle locations. Reasons for new version: To handle much larger particle ensembles, to enable the iterative use of the subroutines in a solver, and to remove potential contention in assignments for parallelization. Summary of revisions: The software package FMM-Yukawa has been

  20. Matrix models with Penner interaction inspired by interacting ...

    Indian Academy of Sciences (India)

    distribution of structure with temperature calculated from the NL model .... where φi are the random Hermitian matrices of size (N × N) placed at each base position ..... PB thanks UGC for research fellowships and ND thanks CSIR Project No.

  1. Model-Based Design of Adaptive Embedded Systems

    NARCIS (Netherlands)

    Basten, T.; Hamberg, R.; Reckers, F.; Verriet, J.

    2013-01-01

    Today’s embedded systems have to operate in a wide variety of dynamically changing environmental circumstances. Adaptivity, the ability of a system to autonomously adapt itself, is a means to optimise a system’s behaviour to accommodate changes in its environment. It involves making in-product

  2. Predicting mesh density for adaptive modelling of the global atmosphere.

    Science.gov (United States)

    Weller, Hilary

    2009-11-28

    The shallow water equations are solved using a mesh of polygons on the sphere, which adapts infrequently to the predicted future solution. Infrequent mesh adaptation reduces the cost of adaptation and load-balancing and will thus allow for more accurate mapping on adaptation. We simulate the growth of a barotropically unstable jet adapting the mesh every 12 h. Using an adaptation criterion based largely on the gradient of the vorticity leads to a mesh with around 20 per cent of the cells of a uniform mesh that gives equivalent results. This is a similar proportion to previous studies of the same test case with mesh adaptation every 1-20 min. The prediction of the mesh density involves solving the shallow water equations on a coarse mesh in advance of the locally refined mesh in order to estimate where features requiring higher resolution will grow, decay or move to. The adaptation criterion consists of two parts: that resolved on the coarse mesh, and that which is not resolved and so is passively advected on the coarse mesh. This combination leads to a balance between resolving features controlled by the large-scale dynamics and maintaining fine-scale features.

  3. Socio-hydrological modelling of floods: investigating community resilience, adaptation capacity and risk

    Science.gov (United States)

    Ciullo, Alessio; Viglione, Alberto; Castellarin, Attilio

    2016-04-01

    Changes in flood risk occur because of changes in climate and hydrology, and in societal exposure and vulnerability. Research on change in flood risk has demonstrated that the mutual interactions and continuous feedbacks between floods and societies has to be taken into account in flood risk management. The present work builds on an existing conceptual model of an hypothetical city located in the proximity of a river, along whose floodplains the community evolves over time. The model reproduces the dynamic co-evolution of four variables: flooding, population density of the flooplain, amount of structural protection measures and memory of floods. These variables are then combined in a way to mimic the temporal change of community resilience, defined as the (inverse of the) amount of time for the community to recover from a shock, and adaptation capacity, defined as ratio between damages due to subsequent events. Also, temporal changing exposure, vulnerability and probability of flooding are also modelled, which results in a dynamically varying flood-risk. Examples are provided that show how factors such as collective memory and risk taking attitude influence the dynamics of community resilience, adaptation capacity and risk.

  4. Evolution of cooperation through adaptive interaction in a spatial prisoner's dilemma game

    Science.gov (United States)

    Pan, Qiuhui; Liu, Xuesong; Bao, Honglin; Su, Yu; He, Mingfeng

    2018-02-01

    In this paper, we study the effect of adaptive interaction on the evolution of cooperation in a spatial prisoner's dilemma game. The connections of players are co-evolutionary with cooperation; whether adjacent players can play the prisoner's dilemma game is associated with the strategies they took in the preceding round. If a player defected in the preceding round, his neighbors will refuse to play the prisoner's dilemma game with him in accordance with a certain probability distribution. We use the disconnecting strength to represent this probability. We discuss the evolution of cooperation with different values of temptation to defect, sucker's payoff and disconnecting strength. The simulation results show that cooperation can be significantly enhanced through increasing the value of the disconnecting strength. In addition, the increase in disconnecting strength can improve the cooperators' ability to resist the increase in temptation and the decrease in reward. We study the parameter ranges for three different evolutionary results: cooperators extinction, defectors extinction, cooperator and defector co-existence. Meanwhile, we recruited volunteers and designed a human behavioral experiment to verify the theoretical simulation results. The punishment of disconnection has a positive effect on cooperation. A higher disconnecting strength will enhance cooperation more significantly. Our research findings reveal some significant insights into efficient mechanisms of the evolution of cooperation.

  5. Correlations in state space can cause sub-optimal adaptation of optimal feedback control models

    OpenAIRE

    Aprasoff, Jonathan; Donchin, Opher

    2011-01-01

    Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedb...

  6. Adapting the transtheoretical model of change to the bereavement process.

    Science.gov (United States)

    Calderwood, Kimberly A

    2011-04-01

    Theorists currently believe that bereaved people undergo some transformation of self rather than returning to their original state. To advance our understanding of this process, this article presents an adaptation of Prochaska and DiClemente's transtheoretical model of change as it could be applied to the journey that bereaved individuals experience. This theory is unique because it addresses attitudes, intentions, and behavioral processes at each stage; it allows for a focus on a broader range of emotions than just anger and depression; it allows for the recognition of two periods of regression during the bereavement process; and it adds a maintenance stage, which other theories lack. This theory can benefit bereaved individuals directly and through the increased awareness among counselors, family, friends, employers, and society at large. This theory may also be used as a tool for bereavement programs to consider whether they are meeting clients' needs throughout the transformation change bereavement process rather than only focusing on the initial stages characterized by intense emotion.

  7. Adaptive subdomain modeling: A multi-analysis technique for ocean circulation models

    Science.gov (United States)

    Altuntas, Alper; Baugh, John

    2017-07-01

    Many coastal and ocean processes of interest operate over large temporal and geographical scales and require a substantial amount of computational resources, particularly when engineering design and failure scenarios are also considered. This study presents an adaptive multi-analysis technique that improves the efficiency of these computations when multiple alternatives are being simulated. The technique, called adaptive subdomain modeling, concurrently analyzes any number of child domains, with each instance corresponding to a unique design or failure scenario, in addition to a full-scale parent domain providing the boundary conditions for its children. To contain the altered hydrodynamics originating from the modifications, the spatial extent of each child domain is adaptively adjusted during runtime depending on the response of the model. The technique is incorporated in ADCIRC++, a re-implementation of the popular ADCIRC ocean circulation model with an updated software architecture designed to facilitate this adaptive behavior and to utilize concurrent executions of multiple domains. The results of our case studies confirm that the method substantially reduces computational effort while maintaining accuracy.

  8. Basic emotions and adaptation. A computational and evolutionary model.

    Directory of Open Access Journals (Sweden)

    Daniela Pacella

    Full Text Available The core principles of the evolutionary theories of emotions declare that affective states represent crucial drives for action selection in the environment and regulated the behavior and adaptation of natural agents in ancestrally recurrent situations. While many different studies used autonomous artificial agents to simulate emotional responses and the way these patterns can affect decision-making, few are the approaches that tried to analyze the evolutionary emergence of affective behaviors directly from the specific adaptive problems posed by the ancestral environment. A model of the evolution of affective behaviors is presented using simulated artificial agents equipped with neural networks and physically inspired on the architecture of the iCub humanoid robot. We use genetic algorithms to train populations of virtual robots across generations, and investigate the spontaneous emergence of basic emotional behaviors in different experimental conditions. In particular, we focus on studying the emotion of fear, therefore the environment explored by the artificial agents can contain stimuli that are safe or dangerous to pick. The simulated task is based on classical conditioning and the agents are asked to learn a strategy to recognize whether the environment is safe or represents a threat to their lives and select the correct action to perform in absence of any visual cues. The simulated agents have special input units in their neural structure whose activation keep track of their actual "sensations" based on the outcome of past behavior. We train five different neural network architectures and then test the best ranked individuals comparing their performances and analyzing the unit activations in each individual's life cycle. We show that the agents, regardless of the presence of recurrent connections, spontaneously evolved the ability to cope with potentially dangerous environment by collecting information about the environment and then

  9. Design and Modeling of an Adaptively Controlled Rainwater Harvesting System

    Directory of Open Access Journals (Sweden)

    David Roman

    2017-12-01

    Full Text Available Management of urban stormwater to mitigate Combined Sewer Overflows (CSOs is a priority for many cities; yet, few truly innovative approaches have been proposed to address the problem. Recent advances in information technology are now, however, providing cost-effective opportunities to achieve better performance of conventional stormwater infrastructure through a Continuous Monitoring and Adaptive Control (CMAC approach. The primary objective of this study was to demonstrate that a CMAC approach can be applied to a conventional rainwater harvesting system in New York City to improve performance by minimizing discharge to the combined sewer during rainfall events, reducing water use for irrigation of local vegetation, and optimizing vegetation health. To achieve this objective, a hydrologic and hydraulic model was developed for a planned and designed rainwater harvesting system to explore multiple potential scenarios prior to the system’s actual construction. Model results indicate that the CMAC rainwater harvesting system is expected to provide significant performance improvements over conventional rainwater harvesting systems. The CMAC system is expected to capture and retain 76.6% of roof runoff per year on average, as compared to just 14.8% and 41.3% for conventional moisture and timer based systems, respectively. Similarly, the CMAC system is expected to use 81.4% and 18.0% less harvested rainwater than conventional moisture and timer based irrigation approaches, respectively. The flexibility of the CMAC approach to meet competing objectives is promising for widespread implementation in New York City and other heavily urbanized areas challenged by stormwater management issues.

  10. Nutrient-dependent/pheromone-controlled adaptive evolution: a model

    Directory of Open Access Journals (Sweden)

    James Vaughn Kohl

    2013-06-01

    Full Text Available Background: The prenatal migration of gonadotropin-releasing hormone (GnRH neurosecretory neurons allows nutrients and human pheromones to alter GnRH pulsatility, which modulates the concurrent maturation of the neuroendocrine, reproductive, and central nervous systems, thus influencing the development of ingestive behavior, reproductive sexual behavior, and other behaviors. Methods: This model details how chemical ecology drives adaptive evolution via: (1 ecological niche construction, (2 social niche construction, (3 neurogenic niche construction, and (4 socio-cognitive niche construction. This model exemplifies the epigenetic effects of olfactory/pheromonal conditioning, which alters genetically predisposed, nutrient-dependent, hormone-driven mammalian behavior and choices for pheromones that control reproduction via their effects on luteinizing hormone (LH and systems biology. Results: Nutrients are metabolized to pheromones that condition behavior in the same way that food odors condition behavior associated with food preferences. The epigenetic effects of olfactory/pheromonal input calibrate and standardize molecular mechanisms for genetically predisposed receptor-mediated changes in intracellular signaling and stochastic gene expression in GnRH neurosecretory neurons of brain tissue. For example, glucose and pheromones alter the hypothalamic secretion of GnRH and LH. A form of GnRH associated with sexual orientation in yeasts links control of the feedback loops and developmental processes required for nutrient acquisition, movement, reproduction, and the diversification of species from microbes to man. Conclusion: An environmental drive evolved from that of nutrient ingestion in unicellular organisms to that of pheromone-controlled socialization in insects. In mammals, food odors and pheromones cause changes in hormones such as LH, which has developmental affects on pheromone-controlled sexual behavior in nutrient-dependent reproductively

  11. Background-Modeling-Based Adaptive Prediction for Surveillance Video Coding.

    Science.gov (United States)

    Zhang, Xianguo; Huang, Tiejun; Tian, Yonghong; Gao, Wen

    2014-02-01

    The exponential growth of surveillance videos presents an unprecedented challenge for high-efficiency surveillance video coding technology. Compared with the existing coding standards that were basically developed for generic videos, surveillance video coding should be designed to make the best use of the special characteristics of surveillance videos (e.g., relative static background). To do so, this paper first conducts two analyses on how to improve the background and foreground prediction efficiencies in surveillance video coding. Following the analysis results, we propose a background-modeling-based adaptive prediction (BMAP) method. In this method, all blocks to be encoded are firstly classified into three categories. Then, according to the category of each block, two novel inter predictions are selectively utilized, namely, the background reference prediction (BRP) that uses the background modeled from the original input frames as the long-term reference and the background difference prediction (BDP) that predicts the current data in the background difference domain. For background blocks, the BRP can effectively improve the prediction efficiency using the higher quality background as the reference; whereas for foreground-background-hybrid blocks, the BDP can provide a better reference after subtracting its background pixels. Experimental results show that the BMAP can achieve at least twice the compression ratio on surveillance videos as AVC (MPEG-4 Advanced Video Coding) high profile, yet with a slightly additional encoding complexity. Moreover, for the foreground coding performance, which is crucial to the subjective quality of moving objects in surveillance videos, BMAP also obtains remarkable gains over several state-of-the-art methods.

  12. A Nonlinear Ship Manoeuvering Model: Identification and adaptive control with experiments for a model ship

    Directory of Open Access Journals (Sweden)

    Roger Skjetne

    2004-01-01

    Full Text Available Complete nonlinear dynamic manoeuvering models of ships, with numerical values, are hard to find in the literature. This paper presents a modeling, identification, and control design where the objective is to manoeuver a ship along desired paths at different velocities. Material from a variety of references have been used to describe the ship model, its difficulties, limitations, and possible simplifications for the purpose of automatic control design. The numerical values of the parameters in the model is identified in towing tests and adaptive manoeuvering experiments for a small ship in a marine control laboratory.

  13. Fantastic animals as an experimental model to teach animal adaptation

    Directory of Open Access Journals (Sweden)

    Veronesi Paola

    2007-08-01

    Full Text Available Abstract Background Science curricula and teachers should emphasize evolution in a manner commensurate with its importance as a unifying concept in science. The concept of adaptation represents a first step to understand the results of natural selection. We settled an experimental project of alternative didactic to improve knowledge of organism adaptation. Students were involved and stimulated in learning processes by creative activities. To set adaptation in a historic frame, fossil records as evidence of past life and evolution were considered. Results The experimental project is schematized in nine phases: review of previous knowledge; lesson on fossils; lesson on fantastic animals; planning an imaginary world; creation of an imaginary animal; revision of the imaginary animals; adaptations of real animals; adaptations of fossil animals; and public exposition. A rubric to evaluate the student's performances is reported. The project involved professors and students of the University of Modena and Reggio Emilia and of the "G. Marconi" Secondary School of First Degree (Modena, Italy. Conclusion The educational objectives of the project are in line with the National Indications of the Italian Ministry of Public Instruction: knowledge of the characteristics of living beings, the meanings of the term "adaptation", the meaning of fossils, the definition of ecosystem, and the particularity of the different biomes. At the end of the project, students will be able to grasp particular adaptations of real organisms and to deduce information about the environment in which the organism evolved. This project allows students to review previous knowledge and to form their personalities.

  14. Fantastic animals as an experimental model to teach animal adaptation

    Science.gov (United States)

    Guidetti, Roberto; Baraldi, Laura; Calzolai, Caterina; Pini, Lorenza; Veronesi, Paola; Pederzoli, Aurora

    2007-01-01

    Background Science curricula and teachers should emphasize evolution in a manner commensurate with its importance as a unifying concept in science. The concept of adaptation represents a first step to understand the results of natural selection. We settled an experimental project of alternative didactic to improve knowledge of organism adaptation. Students were involved and stimulated in learning processes by creative activities. To set adaptation in a historic frame, fossil records as evidence of past life and evolution were considered. Results The experimental project is schematized in nine phases: review of previous knowledge; lesson on fossils; lesson on fantastic animals; planning an imaginary world; creation of an imaginary animal; revision of the imaginary animals; adaptations of real animals; adaptations of fossil animals; and public exposition. A rubric to evaluate the student's performances is reported. The project involved professors and students of the University of Modena and Reggio Emilia and of the "G. Marconi" Secondary School of First Degree (Modena, Italy). Conclusion The educational objectives of the project are in line with the National Indications of the Italian Ministry of Public Instruction: knowledge of the characteristics of living beings, the meanings of the term "adaptation", the meaning of fossils, the definition of ecosystem, and the particularity of the different biomes. At the end of the project, students will be able to grasp particular adaptations of real organisms and to deduce information about the environment in which the organism evolved. This project allows students to review previous knowledge and to form their personalities. PMID:17767729

  15. Strategic Adaptation

    DEFF Research Database (Denmark)

    Andersen, Torben Juul

    2015-01-01

    This article provides an overview of theoretical contributions that have influenced the discourse around strategic adaptation including contingency perspectives, strategic fit reasoning, decision structure, information processing, corporate entrepreneurship, and strategy process. The related...... concepts of strategic renewal, dynamic managerial capabilities, dynamic capabilities, and strategic response capabilities are discussed and contextualized against strategic responsiveness. The insights derived from this article are used to outline the contours of a dynamic process of strategic adaptation....... This model incorporates elements of central strategizing, autonomous entrepreneurial behavior, interactive information processing, and open communication systems that enhance the organization's ability to observe exogenous changes and respond effectively to them....

  16. Functionalized anatomical models for EM-neuron Interaction modeling

    Science.gov (United States)

    Neufeld, Esra; Cassará, Antonino Mario; Montanaro, Hazael; Kuster, Niels; Kainz, Wolfgang

    2016-06-01

    The understanding of interactions between electromagnetic (EM) fields and nerves are crucial in contexts ranging from therapeutic neurostimulation to low frequency EM exposure safety. To properly consider the impact of in vivo induced field inhomogeneity on non-linear neuronal dynamics, coupled EM-neuronal dynamics modeling is required. For that purpose, novel functionalized computable human phantoms have been developed. Their implementation and the systematic verification of the integrated anisotropic quasi-static EM solver and neuronal dynamics modeling functionality, based on the method of manufactured solutions and numerical reference data, is described. Electric and magnetic stimulation of the ulnar and sciatic nerve were modeled to help understanding a range of controversial issues related to the magnitude and optimal determination of strength-duration (SD) time constants. The results indicate the importance of considering the stimulation-specific inhomogeneous field distributions (especially at tissue interfaces), realistic models of non-linear neuronal dynamics, very short pulses, and suitable SD extrapolation models. These results and the functionalized computable phantom will influence and support the development of safe and effective neuroprosthetic devices and novel electroceuticals. Furthermore they will assist the evaluation of existing low frequency exposure standards for the entire population under all exposure conditions.

  17. Aircraft Abnormal Conditions Detection, Identification, and Evaluation Using Innate and Adaptive Immune Systems Interaction

    Science.gov (United States)

    Al Azzawi, Dia

    Abnormal flight conditions play a major role in aircraft accidents frequently causing loss of control. To ensure aircraft operation safety in all situations, intelligent system monitoring and adaptation must rely on accurately detecting the presence of abnormal conditions as soon as they take place, identifying their root cause(s), estimating their nature and severity, and predicting their impact on the flight envelope. Due to the complexity and multidimensionality of the aircraft system under abnormal conditions, these requirements are extremely difficult to satisfy using existing analytical and/or statistical approaches. Moreover, current methodologies have addressed only isolated classes of abnormal conditions and a reduced number of aircraft dynamic parameters within a limited region of the flight envelope. This research effort aims at developing an integrated and comprehensive framework for the aircraft abnormal conditions detection, identification, and evaluation based on the artificial immune systems paradigm, which has the capability to address the complexity and multidimensionality issues related to aircraft systems. Within the proposed framework, a novel algorithm was developed for the abnormal conditions detection problem and extended to the abnormal conditions identification and evaluation. The algorithm and its extensions were inspired from the functionality of the biological dendritic cells (an important part of the innate immune system) and their interaction with the different components of the adaptive immune system. Immunity-based methodologies for re-assessing the flight envelope at post-failure and predicting the impact of the abnormal conditions on the performance and handling qualities are also proposed and investigated in this study. The generality of the approach makes it applicable to any system. Data for artificial immune system development were collected from flight tests of a supersonic research aircraft within a motion-based flight

  18. Calibration model maintenance in melamine resin production: Integrating drift detection, smart sample selection and model adaptation.

    Science.gov (United States)

    Nikzad-Langerodi, Ramin; Lughofer, Edwin; Cernuda, Carlos; Reischer, Thomas; Kantner, Wolfgang; Pawliczek, Marcin; Brandstetter, Markus

    2018-07-12

    The physico-chemical properties of Melamine Formaldehyde (MF) based thermosets are largely influenced by the degree of polymerization (DP) in the underlying resin. On-line supervision of the turbidity point by means of vibrational spectroscopy has recently emerged as a promising technique to monitor the DP of MF resins. However, spectroscopic determination of the DP relies on chemometric models, which are usually sensitive to drifts caused by instrumental and/or sample-associated changes occurring over time. In order to detect the time point when drifts start causing prediction bias, we here explore a universal drift detector based on a faded version of the Page-Hinkley (PH) statistic, which we test in three data streams from an industrial MF resin production process. We employ committee disagreement (CD), computed as the variance of model predictions from an ensemble of partial least squares (PLS) models, as a measure for sample-wise prediction uncertainty and use the PH statistic to detect changes in this quantity. We further explore supervised and unsupervised strategies for (semi-)automatic model adaptation upon detection of a drift. For the former, manual reference measurements are requested whenever statistical thresholds on Hotelling's T 2 and/or Q-Residuals are violated. Models are subsequently re-calibrated using weighted partial least squares in order to increase the influence of newer samples, which increases the flexibility when adapting to new (drifted) states. Unsupervised model adaptation is carried out exploiting the dual antecedent-consequent structure of a recently developed fuzzy systems variant of PLS termed FLEXFIS-PLS. In particular, antecedent parts are updated while maintaining the internal structure of the local linear predictors (i.e. the consequents). We found improved drift detection capability of the CD compared to Hotelling's T 2 and Q-Residuals when used in combination with the proposed PH test. Furthermore, we found that active

  19. Adapted Boolean network models for extracellular matrix formation

    Directory of Open Access Journals (Sweden)

    Wollbold Johannes

    2009-07-01

    Full Text Available Abstract Background Due to the rapid data accumulation on pathogenesis and progression of chronic inflammation, there is an increasing demand for approaches to analyse the underlying regulatory networks. For example, rheumatoid arthritis (RA is a chronic inflammatory disease, characterised by joint destruction and perpetuated by activated synovial fibroblasts (SFB. These abnormally express and/or secrete pro-inflammatory cytokines, collagens causing joint fibrosis, or tissue-degrading enzymes resulting in destruction of the extra-cellular matrix (ECM. We applied three methods to analyse ECM regulation: data discretisation to filter out noise and to reduce complexity, Boolean network construction to implement logic relationships, and formal concept analysis (FCA for the formation of minimal, but complete rule sets from the data. Results First, we extracted literature information to develop an interaction network containing 18 genes representing ECM formation and destruction. Subsequently, we constructed an asynchronous Boolean network with biologically plausible time intervals for mRNA and protein production, secretion, and inactivation. Experimental gene expression data was obtained from SFB stimulated by TGFβ1 or by TNFα and discretised thereafter. The Boolean functions of the initial network were improved iteratively by the comparison of the simulation runs to the experimental data and by exploitation of expert knowledge. This resulted in adapted networks for both cytokine stimulation conditions. The simulations were further analysed by the attribute exploration algorithm of FCA, integrating the observed time series in a fine-tuned and automated manner. The resulting temporal rules yielded new contributions to controversially discussed aspects of fibroblast biology (e.g., considerable expression of TNF and MMP9 by fibroblasts stimulation and corroborated previously known facts (e.g., co-expression of collagens and MMPs after TNF

  20. A Formal Framework for Adaptive Access Control Models.

    NARCIS (Netherlands)

    Spaccapietra, S.; Rinderle, S.B.; Reichert, M.U.

    For several reasons enterprises are frequently subject to organizational change. Respective adaptations may concern business processes, but also other components of an enterprise architecture. In particular, changes of organizational structures often become necessary. The information about

  1. Neural Control and Adaptive Neural Forward Models for Insect-like, Energy-Efficient, and Adaptable Locomotion of Walking Machines

    Directory of Open Access Journals (Sweden)

    Poramate eManoonpong

    2013-02-01

    Full Text Available Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs and sensory feedback (afferent-based control but also on internal forward models (efference copies. They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines.

  2. A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition

    Science.gov (United States)

    Oh, Yoo Rhee; Kim, Hong Kook

    In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.

  3. Statistical behaviour of adaptive multilevel splitting algorithms in simple models

    International Nuclear Information System (INIS)

    Rolland, Joran; Simonnet, Eric

    2015-01-01

    Adaptive multilevel splitting algorithms have been introduced rather recently for estimating tail distributions in a fast and efficient way. In particular, they can be used for computing the so-called reactive trajectories corresponding to direct transitions from one metastable state to another. The algorithm is based on successive selection–mutation steps performed on the system in a controlled way. It has two intrinsic parameters, the number of particles/trajectories and the reaction coordinate used for discriminating good or bad trajectories. We investigate first the convergence in law of the algorithm as a function of the timestep for several simple stochastic models. Second, we consider the average duration of reactive trajectories for which no theoretical predictions exist. The most important aspect of this work concerns some systems with two degrees of freedom. They are studied in detail as a function of the reaction coordinate in the asymptotic regime where the number of trajectories goes to infinity. We show that during phase transitions, the statistics of the algorithm deviate significatively from known theoretical results when using non-optimal reaction coordinates. In this case, the variance of the algorithm is peaking at the transition and the convergence of the algorithm can be much slower than the usual expected central limit behaviour. The duration of trajectories is affected as well. Moreover, reactive trajectories do not correspond to the most probable ones. Such behaviour disappears when using the optimal reaction coordinate called committor as predicted by the theory. We finally investigate a three-state Markov chain which reproduces this phenomenon and show logarithmic convergence of the trajectory durations

  4. Entrepreneural adaptation processes. An industry-geographic working model, illustrated by the example of Saarbergwerke AG

    International Nuclear Information System (INIS)

    Doerrenbaecher, P.

    1992-01-01

    The study has two goals: Solutions based in industrial geography and chronogeography are to be synthesized in order to develop a model of entrepreneurial adaptation processes. On the basis of this model, the development of Saarbergwerke AG in the first phase of the coal crisis (1957-1962) is reconstructed as an entrepreneurial adaptation process. (orig.) [de

  5. Computerized Adaptive Test (CAT) Applications and Item Response Theory Models for Polytomous Items

    Science.gov (United States)

    Aybek, Eren Can; Demirtasli, R. Nukhet

    2017-01-01

    This article aims to provide a theoretical framework for computerized adaptive tests (CAT) and item response theory models for polytomous items. Besides that, it aims to introduce the simulation and live CAT software to the related researchers. Computerized adaptive test algorithm, assumptions of item response theory models, nominal response…

  6. Cardiorespiratory adaptation to breath-holding in air: Analysis via a cardiopulmonary simulation model.

    Science.gov (United States)

    Albanese, Antonio; Limei Cheng; Ursino, Mauro; Chbat, Nicolas W

    2015-01-01

    Apnea via breath-holding (BH) in air induces cardiorespiratory adaptation that involves the activation of several reflex mechanisms and their complex interactions. Hence, the effects of BH in air on cardiorespiratory function can become hardly predictable and difficult to be interpreted. Particularly, the effect on heart rate is not yet completely understood because of the contradicting results of different physiological studies. In this paper we apply our previously developed cardiopulmonary model (CP Model) to a scenario of BH with a twofold intent: (1) further validating the CP Model via comparison against experimental data; (2) gaining insights into the physiological reasoning for such contradicting experimental results. Model predictions agreed with published experimental animal and human data and indicated that heart rate increases during BH in air. Changes in the balance between sympathetic and vagal effects on heart rate within the model proved to be effective in inverting directions of the heart rate changes during BH. Hence, the model suggests that intra-subject differences in such sympatho-vagal balance may be one of the reasons for the contradicting experimental results.

  7. Stresses in faulted tunnel models by photoelasticity and adaptive finite element

    International Nuclear Information System (INIS)

    Ladkany, S.G.; Huang, Y.

    1995-01-01

    Research efforts in this area continue to investigate the development of a proper technique to analyze the stresses in the Ghost Dance fault and the effect of the fault on the stability of drifts in the proposed repository. Results from two parallel techniques are being compared to each other - Photoelastic models and Finite Element (FE) models. The Photoelastic plexiglass model (88.89 mm thick ampersand 256.1 mm long and wide) has two adjacent spare openings (57.95 mm long and wide) and a central round opening (57.95 mm diameter) placed at a clear distance approximately equal to its diameter from the square openings. The vertical loading on top of the model is 2269 N (500 lb.). Saw cuts (0.5388 mm wide), representing a fault, are being propagated from the tunnels outward with stress measurements taken at predefined locations, as the saw cuts increase in length. The FE model duplicates exactly the Photoelastic models. The adaptive mesh generation method is used to refine the FE grid at every step of the analysis. This nonlinear interactive computational techniques uses various uses various percent tolerance errors in the convergence of stress values as a measure in ending the iterative process

  8. Adaptive Admittance Control for an Ankle Exoskeleton Using an EMG-Driven Musculoskeletal Model

    Directory of Open Access Journals (Sweden)

    Shaowei Yao

    2018-04-01

    Full Text Available Various rehabilitation robots have been employed to recover the motor function of stroke patients. To improve the effect of rehabilitation, robots should promote patient participation and provide compliant assistance. This paper proposes an adaptive admittance control scheme (AACS consisting of an admittance filter, inner position controller, and electromyography (EMG-driven musculoskeletal model (EDMM. The admittance filter generates the subject's intended motion according to the joint torque estimated by the EDMM. The inner position controller tracks the intended motion, and its parameters are adjusted according to the estimated joint stiffness. Eight healthy subjects were instructed to wear the ankle exoskeleton robot, and they completed a series of sinusoidal tracking tasks involving ankle dorsiflexion and plantarflexion. The robot was controlled by the AACS and a non-adaptive admittance control scheme (NAACS at four fixed parameter levels. The tracking performance was evaluated using the jerk value, position error, interaction torque, and EMG levels of the tibialis anterior (TA and gastrocnemius (GAS. For the NAACS, the jerk value and position error increased with the parameter levels, and the interaction torque and EMG levels of the TA tended to decrease. In contrast, the AACS could maintain a moderate jerk value, position error, interaction torque, and TA EMG level. These results demonstrate that the AACS achieves a good tradeoff between accurate tracking and compliant assistance because it can produce a real-time response to stiffness changes in the ankle joint. The AACS can alleviate the conflict between accurate tracking and compliant assistance and has potential for application in robot-assisted rehabilitation.

  9. Soft sensor modelling by time difference, recursive partial least squares and adaptive model updating

    International Nuclear Information System (INIS)

    Fu, Y; Xu, O; Yang, W; Zhou, L; Wang, J

    2017-01-01

    To investigate time-variant and nonlinear characteristics in industrial processes, a soft sensor modelling method based on time difference, moving-window recursive partial least square (PLS) and adaptive model updating is proposed. In this method, time difference values of input and output variables are used as training samples to construct the model, which can reduce the effects of the nonlinear characteristic on modelling accuracy and retain the advantages of recursive PLS algorithm. To solve the high updating frequency of the model, a confidence value is introduced, which can be updated adaptively according to the results of the model performance assessment. Once the confidence value is updated, the model can be updated. The proposed method has been used to predict the 4-carboxy-benz-aldehyde (CBA) content in the purified terephthalic acid (PTA) oxidation reaction process. The results show that the proposed soft sensor modelling method can reduce computation effectively, improve prediction accuracy by making use of process information and reflect the process characteristics accurately. (paper)

  10. Quantum dynamics modeled by interacting trajectories

    Science.gov (United States)

    Cruz-Rodríguez, L.; Uranga-Piña, L.; Martínez-Mesa, A.; Meier, C.

    2018-03-01

    We present quantum dynamical simulations based on the propagation of interacting trajectories where the effect of the quantum potential is mimicked by effective pseudo-particle interactions. The method is applied to several quantum systems, both for bound and scattering problems. For the bound systems, the quantum ground state density and zero point energy are shown to be perfectly obtained by the interacting trajectories. In the case of time-dependent quantum scattering, the Eckart barrier and uphill ramp are considered, with transmission coefficients in very good agreement with standard quantum calculations. Finally, we show that via wave function synthesis along the trajectories, correlation functions and energy spectra can be obtained based on the dynamics of interacting trajectories.

  11. Distributed Recurrent Neural Forward Models with Synaptic Adaptation and CPG-based control for Complex Behaviors of Walking Robots

    Directory of Open Access Journals (Sweden)

    Sakyasingha eDasgupta

    2015-09-01

    Full Text Available Walking animals, like stick insects, cockroaches or ants, demonstrate a fascinating range of locomotive abilities and complex behaviors. The locomotive behaviors can consist of a variety of walking patterns along with adaptation that allow the animals to deal with changes in environmental conditions, like uneven terrains, gaps, obstacles etc. Biological study has revealed that such complex behaviors are a result of a combination of biomechanics and neural mechanism thus representing the true nature of embodied interactions. While the biomechanics helps maintain flexibility and sustain a variety of movements, the neural mechanisms generate movements while making appropriate predictions crucial for achieving adaptation. Such predictions or planning ahead can be achieved by way of internal models that are grounded in the overall behavior of the animal. Inspired by these findings, we present here, an artificial bio-inspired walking system which effectively combines biomechanics (in terms of the body and leg structures with the underlying neural mechanisms. The neural mechanisms consist of 1 central pattern generator based control for generating basic rhythmic patterns and coordinated movements, 2 distributed (at each leg recurrent neural network based adaptive forward models with efference copies as internal models for sensory predictions and instantaneous state estimations, and 3 searching and elevation control for adapting the movement of an individual leg to deal with different environmental conditions. Using simulations we show that this bio-inspired approach with adaptive internal models allows the walking robot to perform complex locomotive behaviors as observed in insects, including walking on undulated terrains, crossing large gaps as well as climbing over high obstacles. Furthermore we demonstrate that the newly developed recurrent network based approach to sensorimotor prediction outperforms the previous state of the art adaptive neuron

  12. Aperiodic dynamics in a deterministic adaptive network model of attitude formation in social groups

    Science.gov (United States)

    Ward, Jonathan A.; Grindrod, Peter

    2014-07-01

    Adaptive network models, in which node states and network topology coevolve, arise naturally in models of social dynamics that incorporate homophily and social influence. Homophily relates the similarity between pairs of nodes' states to their network coupling strength, whilst social influence causes coupled nodes' states to convergence. In this paper we propose a deterministic adaptive network model of attitude formation in social groups that includes these effects, and in which the attitudinal dynamics are represented by an activato-inhibitor process. We illustrate that consensus, corresponding to all nodes adopting the same attitudinal state and being fully connected, may destabilise via Turing instability, giving rise to aperiodic dynamics with sensitive dependence on initial conditions. These aperiodic dynamics correspond to the formation and dissolution of sub-groups that adopt contrasting attitudes. We discuss our findings in the context of cultural polarisation phenomena. Social influence. This reflects the fact that people tend to modify their behaviour and attitudes in response to the opinions of others [22-26]. We model social influence via diffusion: agents adjust their state according to a weighted sum (dictated by the evolving network) of the differences between their state and the states of their neighbours. Homophily. This relates the similarity of individuals' states to their frequency and strength of interaction [27]. Thus in our model, homophily drives the evolution of the weighted ‘social' network. A precise formulation of our model is given in Section 2. Social influence and homophily underpin models of social dynamics [21], which cover a wide range of sociological phenomena, including the diffusion of innovations [28-32], complex contagions [33-36], collective action [37-39], opinion dynamics [19,20,40,10,11,13,15,41,16], the emergence of social norms [42-44], group stability [45], social differentiation [46] and, of particular relevance

  13. Adapting a strategic management model to hospital operating strategies. A model development and justification.

    Science.gov (United States)

    Swinehart, K; Zimmerer, T W; Oswald, S

    1995-01-01

    Industrial organizations have employed the process of strategic management in their attempts to cope effectively with global competitive pressures, while attempting to build and maintain competitive advantage. With health-care organizations presently trying to cope with an increasingly turbulent environment created by the uncertainty as to pending legislation and anticipated reform, the need for such organizational strategic planning is apparent. Presents and discusses a methodology for adapting a business-oriented model of strategic planning to health care.

  14. Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality.

    Science.gov (United States)

    Gosling, Simon N; Hondula, David M; Bunker, Aditi; Ibarreta, Dolores; Liu, Junguo; Zhang, Xinxin; Sauerborn, Rainer

    2017-08-16

    Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to "adaptation uncertainty" (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. This study had three aims: a ) Compare the range in projected impacts that arises from using different adaptation modeling methods; b ) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c ) recommend modeling method(s) to use in future impact assessments. We estimated impacts for 2070-2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634.

  15. Tensor Product Model Transformation Based Adaptive Integral-Sliding Mode Controller: Equivalent Control Method

    Directory of Open Access Journals (Sweden)

    Guoliang Zhao

    2013-01-01

    Full Text Available This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model.

  16. When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems.

    Science.gov (United States)

    Sauterey, Boris; Ward, Ben A; Follows, Michael J; Bowler, Chris; Claessen, David

    2015-01-01

    The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that "Everything is everywhere, but the environment selects", we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean.

  17. Adaptive resolution simulation of polarizable supramolecular coarse-grained water models

    International Nuclear Information System (INIS)

    Zavadlav, Julija; Praprotnik, Matej; Melo, Manuel N.; Marrink, Siewert J.

    2015-01-01

    Multiscale simulations methods, such as adaptive resolution scheme, are becoming increasingly popular due to their significant computational advantages with respect to conventional atomistic simulations. For these kind of simulations, it is essential to develop accurate multiscale water models that can be used to solvate biophysical systems of interest. Recently, a 4-to-1 mapping was used to couple the bundled-simple point charge water with the MARTINI model. Here, we extend the supramolecular mapping to coarse-grained models with explicit charges. In particular, the two tested models are the polarizable water and big multiple water models associated with the MARTINI force field. As corresponding coarse-grained representations consist of several interaction sites, we couple orientational degrees of freedom of the atomistic and coarse-grained representations via a harmonic energy penalty term. This additional energy term aligns the dipole moments of both representations. We test this coupling by studying the system under applied static external electric field. We show that our approach leads to the correct reproduction of the relevant structural and dynamical properties

  18. Neural Control and Adaptive Neural Forward Models for Insect-like, Energy-Efficient, and Adaptable Locomotion of Walking Machines

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Parlitz, Ulrich; Wörgötter, Florentin

    2013-01-01

    such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast...... on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models...... allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show...

  19. Estimation of Model's Marginal likelihood Using Adaptive Sparse Grid Surrogates in Bayesian Model Averaging

    Science.gov (United States)

    Zeng, X.

    2015-12-01

    A large number of model executions are required to obtain alternative conceptual models' predictions and their posterior probabilities in Bayesian model averaging (BMA). The posterior model probability is estimated through models' marginal likelihood and prior probability. The heavy computation burden hinders the implementation of BMA prediction, especially for the elaborated marginal likelihood estimator. For overcoming the computation burden of BMA, an adaptive sparse grid (SG) stochastic collocation method is used to build surrogates for alternative conceptual models through the numerical experiment of a synthetical groundwater model. BMA predictions depend on model posterior weights (or marginal likelihoods), and this study also evaluated four marginal likelihood estimators, including arithmetic mean estimator (AME), harmonic mean estimator (HME), stabilized harmonic mean estimator (SHME), and thermodynamic integration estimator (TIE). The results demonstrate that TIE is accurate in estimating conceptual models' marginal likelihoods. The BMA-TIE has better predictive performance than other BMA predictions. TIE has high stability for estimating conceptual model's marginal likelihood. The repeated estimated conceptual model's marginal likelihoods by TIE have significant less variability than that estimated by other estimators. In addition, the SG surrogates are efficient to facilitate BMA predictions, especially for BMA-TIE. The number of model executions needed for building surrogates is 4.13%, 6.89%, 3.44%, and 0.43% of the required model executions of BMA-AME, BMA-HME, BMA-SHME, and BMA-TIE, respectively.

  20. Scheme of adaptive polarization filtering based on Kalman model

    Institute of Scientific and Technical Information of China (English)

    Song Lizhong; Qi Haiming; Qiao Xiaolin; Meng Xiande

    2006-01-01

    A new kind of adaptive polarization filtering algorithm in order to suppress the angle cheating interference for the active guidance radar is presented. The polarization characteristic of the interference is dynamically tracked by using Kalman estimator under variable environments with time. The polarization filter parameters are designed according to the polarization characteristic of the interference, and the polarization filtering is finished in the target cell. The system scheme of adaptive polarization filter is studied and the tracking performance of polarization filter and improvement of angle measurement precision are simulated. The research results demonstrate this technology can effectively suppress the angle cheating interference in guidance radar and is feasible in engineering.

  1. Effect of Treatment Education Based on the Roy Adaptation Model on Adjustment of Hemodialysis Patients.

    Science.gov (United States)

    Kacaroglu Vicdan, Ayse; Gulseven Karabacak, Bilgi

    2016-01-01

    The Roy Adaptation Model examines the individual in 4 fields: physiological mode, self-concept mode, role function mode, and interdependence mode. Hemodialysis treatment is associated with the Roy Adaptation Model as it involves fields that might be needed by the individual with chronic renal disease. This research was conducted as randomized controlled experiment with the aim of determining the effect of the education given in accordance with the Roy Adaptation Model on physiological, psychological, and social adaptation of individuals undergoing hemodialysis treatment. This was a random controlled experimental study. The study was conducted at a dialysis center in Konya-Aksehir in Turkey between July 1 and December 31, 2012. The sample was composed of 82 individuals-41 experimental and 41 control. In the second interview, there was a decrease in the systolic blood pressures and body weights of the experimental group, an increase in the scores of functional performance and self-respect, and a decrease in the scores of psychosocial adaptation. In the control group, on the other hand, there was a decrease in the scores of self-respect and an increase in the scores of psychosocial adaptation. The 2 groups were compared in terms of adaptation variables and a difference was determined on behalf of the experimental group. The training that was provided and evaluated for individuals receiving hemodialysis according to 4 modes of the Roy Adaptation Model increased physical, psychological, and social adaptation.

  2. Adaptation Method for Overall and Local Performances of Gas Turbine Engine Model

    Science.gov (United States)

    Kim, Sangjo; Kim, Kuisoon; Son, Changmin

    2018-04-01

    An adaptation method was proposed to improve the modeling accuracy of overall and local performances of gas turbine engine. The adaptation method was divided into two steps. First, the overall performance parameters such as engine thrust, thermal efficiency, and pressure ratio were adapted by calibrating compressor maps, and second, the local performance parameters such as temperature of component intersection and shaft speed were adjusted by additional adaptation factors. An optimization technique was used to find the correlation equation of adaptation factors for compressor performance maps. The multi-island genetic algorithm (MIGA) was employed in the present optimization. The correlations of local adaptation factors were generated based on the difference between the first adapted engine model and performance test data. The proposed adaptation method applied to a low-bypass ratio turbofan engine of 12,000 lb thrust. The gas turbine engine model was generated and validated based on the performance test data in the sea-level static condition. In flight condition at 20,000 ft and 0.9 Mach number, the result of adapted engine model showed improved prediction in engine thrust (overall performance parameter) by reducing the difference from 14.5 to 3.3%. Moreover, there was further improvement in the comparison of low-pressure turbine exit temperature (local performance parameter) as the difference is reduced from 3.2 to 0.4%.

  3. Modelling microbial interactions and food structure in predictive microbiology

    NARCIS (Netherlands)

    Malakar, P.K.

    2002-01-01

    Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology.

    Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of

  4. Model and experiments to optimize co-adaptation in a simplified myoelectric control system.

    Science.gov (United States)

    Couraud, M; Cattaert, D; Paclet, F; Oudeyer, P Y; de Rugy, A

    2018-04-01

    To compensate for a limb lost in an amputation, myoelectric prostheses use surface electromyography (EMG) from the remaining muscles to control the prosthesis. Despite considerable progress, myoelectric controls remain markedly different from the way we normally control movements, and require intense user adaptation. To overcome this, our goal is to explore concurrent machine co-adaptation techniques that are developed in the field of brain-machine interface, and that are beginning to be used in myoelectric controls. We combined a simplified myoelectric control with a perturbation for which human adaptation is well characterized and modeled, in order to explore co-adaptation settings in a principled manner. First, we reproduced results obtained in a classical visuomotor rotation paradigm in our simplified myoelectric context, where we rotate the muscle pulling vectors used to reconstruct wrist force from EMG. Then, a model of human adaptation in response to directional error was used to simulate various co-adaptation settings, where perturbations and machine co-adaptation are both applied on muscle pulling vectors. These simulations established that a relatively low gain of machine co-adaptation that minimizes final errors generates slow and incomplete adaptation, while higher gains increase adaptation rate but also errors by amplifying noise. After experimental verification on real subjects, we tested a variable gain that cumulates the advantages of both, and implemented it with directionally tuned neurons similar to those used to model human adaptation. This enables machine co-adaptation to locally improve myoelectric control, and to absorb more challenging perturbations. The simplified context used here enabled to explore co-adaptation settings in both simulations and experiments, and to raise important considerations such as the need for a variable gain encoded locally. The benefits and limits of extending this approach to more complex and functional

  5. Model and experiments to optimize co-adaptation in a simplified myoelectric control system

    Science.gov (United States)

    Couraud, M.; Cattaert, D.; Paclet, F.; Oudeyer, P. Y.; de Rugy, A.

    2018-04-01

    Objective. To compensate for a limb lost in an amputation, myoelectric prostheses use surface electromyography (EMG) from the remaining muscles to control the prosthesis. Despite considerable progress, myoelectric controls remain markedly different from the way we normally control movements, and require intense user adaptation. To overcome this, our goal is to explore concurrent machine co-adaptation techniques that are developed in the field of brain-machine interface, and that are beginning to be used in myoelectric controls. Approach. We combined a simplified myoelectric control with a perturbation for which human adaptation is well characterized and modeled, in order to explore co-adaptation settings in a principled manner. Results. First, we reproduced results obtained in a classical visuomotor rotation paradigm in our simplified myoelectric context, where we rotate the muscle pulling vectors used to reconstruct wrist force from EMG. Then, a model of human adaptation in response to directional error was used to simulate various co-adaptation settings, where perturbations and machine co-adaptation are both applied on muscle pulling vectors. These simulations established that a relatively low gain of machine co-adaptation that minimizes final errors generates slow and incomplete adaptation, while higher gains increase adaptation rate but also errors by amplifying noise. After experimental verification on real subjects, we tested a variable gain that cumulates the advantages of both, and implemented it with directionally tuned neurons similar to those used to model human adaptation. This enables machine co-adaptation to locally improve myoelectric control, and to absorb more challenging perturbations. Significance. The simplified context used here enabled to explore co-adaptation settings in both simulations and experiments, and to raise important considerations such as the need for a variable gain encoded locally. The benefits and limits of extending this

  6. Large-scale symmetry-adapted perturbation theory computations via density fitting and Laplace transformation techniques: investigating the fundamental forces of DNA-intercalator interactions.

    Science.gov (United States)

    Hohenstein, Edward G; Parrish, Robert M; Sherrill, C David; Turney, Justin M; Schaefer, Henry F

    2011-11-07

    Symmetry-adapted perturbation theory (SAPT) provides a means of probing the fundamental nature of intermolecular interactions. Low-orders of SAPT (here, SAPT0) are especially attractive since they provide qualitative (sometimes quantitative) results while remaining tractable for large systems. The application of density fitting and Laplace transformation techniques to SAPT0 can significantly reduce the expense associated with these computations and make even larger systems accessible. We present new factorizations of the SAPT0 equations with density-fitted two-electron integrals and the first application of Laplace transformations of energy denominators to SAPT. The improved scalability of the DF-SAPT0 implementation allows it to be applied to systems with more than 200 atoms and 2800 basis functions. The Laplace-transformed energy denominators are compared to analogous partial Cholesky decompositions of the energy denominator tensor. Application of our new DF-SAPT0 program to the intercalation of DNA by proflavine has allowed us to determine the nature of the proflavine-DNA interaction. Overall, the proflavine-DNA interaction contains important contributions from both electrostatics and dispersion. The energetics of the intercalator interaction are are dominated by the stacking interactions (two-thirds of the total), but contain important contributions from the intercalator-backbone interactions. It is hypothesized that the geometry of the complex will be determined by the interactions of the intercalator with the backbone, because by shifting toward one side of the backbone, the intercalator can form two long hydrogen-bonding type interactions. The long-range interactions between the intercalator and the next-nearest base pairs appear to be negligible, justifying the use of truncated DNA models in computational studies of intercalation interaction energies.

  7. Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.

    Science.gov (United States)

    Aprasoff, Jonathan; Donchin, Opher

    2012-04-01

    Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.

  8. Measuring the Impact of a Moving Target: Towards a Dynamic Framework for Evaluating Collaborative Adaptive Interactive Technologies

    OpenAIRE

    O?Grady, Laura; Witteman, Holly; Bender, Jacqueline L; Urowitz, Sara; Wiljer, David; Jadad, Alejandro R

    2009-01-01

    Background Website evaluation is a key issue for researchers, organizations, and others responsible for designing, maintaining, endorsing, approving, and/or assessing the use and impact of interventions designed to influence health and health services. Traditionally, these evaluations have included elements such as content credibility, interface usability, and overall design aesthetics. With the emergence of collaborative, adaptive, and interactive ("Web 2.0") technologies such as wikis and o...

  9. Open Interactivity: A Model for Audience Agency

    Directory of Open Access Journals (Sweden)

    Charlotte Gould

    2018-04-01

    Full Text Available Artists have increasingly acknowledged the role of the audience as collaborators both in the construction of meaning (Bathes, 1977, through subjective experience (Dewey, 1934 and in contributing to the creative act by externalising the work. (Duchamp Lucy Lippard identifies 1966-72 as a period where artists turned increasingly towards the audience, representing a "dematerialization of the art object" (Lippard, 1997 through "Happenings" and "Fluxus" movements. Digital media has facilitated this trajectory, implicit in the interactive computer interface (Manovich, 2005, but interactivity per se may offer no more than a series of choices put forward by the artist (Daniels, 2011. Interactivity represents interplay between artist and audience (Dinka, 1996 and is potentially a process of audience empowerment to offer agency, defined as real and creative choice (Browning, 1964. Public screen installation "Peoples Screen" Guangzhou, linking China to Perth Australia (Sermon & Gould, 2015 offered a partnership between artist and audience to co-create content though playful narratives and active engagement in a drama that unfolds using improvisation and play. Initially visitors enjoy observing the self on the screen but audiences quickly start to interact with the environment and other participants. Immersed in play they lose a sense of the self (Callois, 2011 and enter a virtual third space where possibilities for creativity and direction of play are limitless. The self becomes an avatar where the audience can inhabit "the other" thereby exploring alternative realities through ludic play, promoting tolerance and empathy and developing collective memory.

  10. Modelling interactions in grass-clover mixtures

    NARCIS (Netherlands)

    Nassiri Mahallati, M.

    1998-01-01

    The study described in this thesis focuses on a quantitative understanding of the complex interactions in binary mixtures of perennial ryegrass (Lolium perenne L.) and white clover (Trifolium repens L.) under cutting. The first part of the study describes the dynamics of growth, production

  11. Yeast Colonies: A Model for Studies of Aging, Environmental Adaptation, and Longevity

    Directory of Open Access Journals (Sweden)

    Libuše Váchová

    2012-01-01

    Full Text Available When growing on solid surfaces, yeast, like other microorganisms, develops organized multicellular populations (colonies and biofilms that are composed of differentiated cells with specialized functions. Life within these populations is a prevalent form of microbial existence in natural settings that provides the cells with capabilities to effectively defend against environmental attacks as well as efficiently adapt and survive long periods of starvation and other stresses. Under such circumstances, the fate of an individual yeast cell is subordinated to the profit of the whole population. In the past decade, yeast colonies, with their complicated structure and high complexity that are also developed under laboratory conditions, have become an excellent model for studies of various basic cellular processes such as cell interaction, signaling, and differentiation. In this paper, we summarize current knowledge on the processes related to chronological aging, adaptation, and longevity of a colony cell population and of its differentiated cell constituents. These processes contribute to the colony ability to survive long periods of starvation and mostly differ from the survival strategies of individual yeast cells.

  12. Mixed models identify physic nut genotypes adapted to environments with different phosphorus availability.

    Science.gov (United States)

    Teodoro, P E; Laviola, B G; Martins, L D; Amaral, J F T; Rodrigues, W N

    2016-08-19

    The aim of this study was to screen physic nut (Jatropha curcas) genotypes that differ in their phosphorous (P) use, using mixed models. The experiment was conducted in a greenhouse located in the experimental area of the Centro de Ciências Agrárias of the Universidade Federal do Espírito Santo, in Alegre, ES, Brazil. The experiment was arranged in a randomized block design, using a 10 x 3-factorial scheme, including ten physic nut genotypes and two environments that differed in their levels of soil P availability (10 and 60 mg/dm 3 ), each with four replications. After 100 days of cultivation, we evaluated the plant height, stem diameter, root volume, root dry matter, aerial part dry matter, total dry matter, as well as the efficiency of absorption, and use. The parameters were estimated for combined selection while considering the studied parameters: stability and adaptability for both environments were obtained using the harmonic mean of the relative performance of the predicted genotypic values. High genotype by environment interactions were observed for most physic nut traits, indicating considerable influences of P availability on the phenotypic value. The genotype Paraíso simultaneously presented high adaptability and stability for aerial part dry matter, total dry matter, and P translocation efficiency. The genotype CNPAE-C2 showed a positive response to P fertilization by increasing both the total and aerial part dry matter.

  13. Separating the role of biotic interactions and climate in determining adaptive response of plants to climate change.

    Science.gov (United States)

    Tomiolo, Sara; Van der Putten, Wim H; Tielbörger, Katja

    2015-05-01

    Altered rainfall regimes will greatly affect the response of plant species to climate change. However, little is known about how direct effects of changing precipitation on plant performance may depend on other abiotic factors and biotic interactions. We used reciprocal transplants between climatically very different sites with simultaneous manipulation of soil, plant population origin, and neighbor conditions to evaluate local adaptation and possible adaptive response of four Eastern Mediterranean annual plant species to climate change. The effect of site on plant performance was negligible, but soil origin had a strong effect on fecundity, most likely due to differential water retaining ability. Competition by neighbors strongly reduced fitness. We separated the effects of the abiotic and biotic soil properties on plant performance by repeating the field experiment in a greenhouse under homogenous environmental conditions and including a soil biota manipulation treatment. As in the field, plant performance differed among soil origins and neighbor treatments. Moreover, we found plant species-specific responses to soil biota that may be best explained by the differential sensitivity to negative and positive soil biota effects. Overall, under the conditions of our experiment with two contrasting sites, biotic interactions had a strong effect on plant fitness that interacted with and eventually overrode climate. Because climate and biotic interactions covary, reciprocal transplants and climate gradient studies should consider soil biotic interactions and abiotic conditions when evaluating climate change effects on plant performance.

  14. Guided interaction exploration in artifact-centric process models

    NARCIS (Netherlands)

    van Eck, M.L.; Sidorova, N.; van der Aalst, W.M.P.

    2017-01-01

    Artifact-centric process models aim to describe complex processes as a collection of interacting artifacts. Recent development in process mining allow for the discovery of such models. However, the focus is often on the representation of the individual artifacts rather than their interactions. Based

  15. Sandgrouse as models of avian adaptations to deserts

    African Journals Online (AJOL)

    ploitation of wider areas around watering pOints, and saving water and energy on drinking flights; (e) Reduced metabolic rate and selec- tion of energy- and .... size, there are great advantages in looking for adaptive dif-. R eprod u ced.

  16. Energetic Metabolism and Biochemical Adaptation: A Bird Flight Muscle Model

    Science.gov (United States)

    Rioux, Pierre; Blier, Pierre U.

    2006-01-01

    The main objective of this class experiment is to measure the activity of two metabolic enzymes in crude extract from bird pectoral muscle and to relate the differences to their mode of locomotion and ecology. The laboratory is adapted to stimulate the interest of wildlife management students to biochemistry. The enzymatic activities of cytochrome…

  17. Adaptive Nonsingular Terminal Sliding Model Control and Its Application to Permanent Magnet Synchronous Motor Drive System

    OpenAIRE

    Liu Yue; Zhou Shuo

    2016-01-01

    To improve the dynamic performance of permanent magnet synchronous motor(PMSM) drive system, a adaptive nonsingular terminal sliding model control((NTSMC) strategy was proposed. The proposed control strategy presents an adaptive variable-rated exponential reaching law which the L1 norm of state variables is introduced. Exponential and constant approach speed can adaptively adjust according to the state variables’ distance to the equilibrium position.The proposed scheme can shorten the reachin...

  18. Interactive wood combustion for botanical tree models

    KAUST Repository

    Pirk, Sö ren; Jarząbek, Michał; Hadrich, Torsten; Michels, Dominik L.; Palubicki, Wojciech

    2017-01-01

    We present a novel method for the combustion of botanical tree models. Tree models are represented as connected particles for the branching structure and a polygonal surface mesh for the combustion. Each particle stores biological and physical

  19. Interactions between concentric form-from-structure and face perception revealed by visual masking but not adaptation

    Science.gov (United States)

    Feczko, Eric; Shulman, Gordon L.; Petersen, Steven E.; Pruett, John R.

    2014-01-01

    Findings from diverse subfields of vision research suggest a potential link between high-level aspects of face perception and concentric form-from-structure perception. To explore this relationship, typical adults performed two adaptation experiments and two masking experiments to test whether concentric, but not nonconcentric, Glass patterns (a type of form-from-structure stimulus) utilize a processing mechanism shared by face perception. For the adaptation experiments, subjects were presented with an adaptor for 5 or 20 s, prior to discriminating a target. In the masking experiments, subjects saw a mask, then a target, and then a second mask. Measures of discriminability and bias were derived and repeated measures analysis of variance tested for pattern-specific masking and adaptation effects. Results from Experiment 1 show no Glass pattern-specific effect of adaptation to faces; results from Experiment 2 show concentric Glass pattern masking, but not adaptation, may impair upright/inverted face discrimination; results from Experiment 3 show concentric and radial Glass pattern masking impaired subsequent upright/inverted face discrimination more than translational Glass pattern masking; and results from Experiment 4 show concentric and radial Glass pattern masking impaired subsequent face gender discrimination more than translational Glass pattern masking. Taken together, these findings demonstrate interactions between concentric form-from-structure and face processing, suggesting a possible common processing pathway. PMID:24563526

  20. Adaptive and interactive climate futures: systematic review of ‘serious games’ for engagement and decision-making

    Science.gov (United States)

    Flood, Stephen; Cradock-Henry, Nicholas A.; Blackett, Paula; Edwards, Peter

    2018-06-01

    Climate change is already having adverse impacts on ecosystems, communities and economic activities through higher temperatures, prolonged droughts, and more frequent extremes. However, a gap remains between public understanding, scientific knowledge about climate change, and changes in behaviour to effect adaptation. ‘Serious games’—games used for purposes other than entertainment—are one way to reduce this adaptation deficit by enhancing opportunities for social learning and enabling positive action. Games can provide communities with the opportunity to interactively explore different climate futures, build capability and capacity for dealing with complex challenges, and socialise adaptation priorities with diverse publics. Using systematic review methods, this paper identifies, reviews, synthesises and assesses the literature on serious games for climate change adaptation. To determine where and how impact is achieved, we draw on an evaluation framework grounded in social learning, to assess which combinations of cognitive (knowledge and thinking), normative (norms and approaches) and relational (how people connect and network building) learning are achieved. Results show that factors influencing the overall success in influencing behaviour and catalysing learning for adaptation include generating high levels of inter- and intra- level trust between researchers, practitioners and community participants; strong debriefing and evaluation practices; and the use of experienced and knowledgeable facilitators. These results can help inform future game design, and research methodologies to develop robust ways for engaging with stakeholders and end users, and enhance learning effects for resilient climate futures.