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Sample records for adaptive multiple model

  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. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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...

  7. Multiple Model Adaptive Attitude Control of LEO Satellite with Angular Velocity Constraints

    Science.gov (United States)

    Shahrooei, Abolfazl; Kazemi, Mohammad Hosein

    2018-04-01

    In this paper, the multiple model adaptive control is utilized to improve the transient response of attitude control system for a rigid spacecraft. An adaptive output feedback control law is proposed for attitude control under angular velocity constraints and its almost global asymptotic stability is proved. The multiple model adaptive control approach is employed to counteract large uncertainty in parameter space of the inertia matrix. The nonlinear dynamics of a low earth orbit satellite is simulated and the proposed control algorithm is implemented. The reported results show the effectiveness of the suggested scheme.

  8. Adapting and applying a multiple domain model of condom use to Chinese college students.

    Science.gov (United States)

    Xiao, Zhiwen; Palmgreen, Philip; Zimmerman, Rick; Noar, Seth

    2010-03-01

    This study adapts a multiple domain model (MDM) to explain condom use among a sample of sexually active Chinese college students. A cross-sectional survey was conducted and structural equation modeling was used to test the proposed model. Preparatory behaviors, theory of reasoned action (TRA)/theory of planned behavior variables, impulsivity, length of relationship, and alcohol use were significant direct predictors of condom use. The results suggest that MDM can provide a better understanding of heterosexual condom use among Chinese youth, and help in the design of HIV-preventive and safer sex interventions in China.

  9. 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.

  10. 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

  11. An Adaptive Model for Calculating the Correlation Degree of Multiple Adjacent Signalized Intersections

    Directory of Open Access Journals (Sweden)

    Linhong Wang

    2013-01-01

    Full Text Available As an important component of the urban adaptive traffic control system, subarea partition algorithm divides the road network into some small subareas and then determines the optimal signal control mode for each signalized intersection. Correlation model is the core of subarea partition algorithm because it can quantify the correlation degree of adjacent signalized intersections and decides whether these intersections can be grouped into one subarea. In most cases, there are more than two intersections in one subarea. However, current researches only focus on the correlation model for two adjacent intersections. The objective of this study is to develop a model which can calculate the correlation degree of multiple intersections adaptively. The cycle lengths, link lengths, number of intersections, and path flow between upstream and downstream coordinated phases were selected as the contributing factors of the correlation model. Their jointly impacts on the performance of the coordinated control mode relative to the isolated control mode were further studied using numerical experiments. The paper then proposed a correlation index (CI as an alternative to relative performance. The relationship between CI and the four contributing factors was established in order to predict the correlation, which determined whether adjacent intersections could be partitioned into one subarea. A value of 0 was set as the threshold of CI. If CI was larger than 0, multiple intersections could be partitioned into one subarea; otherwise, they should be separated. Finally, case studies were conducted in a real-life signalized network to evaluate the performance of the model. The results show that the CI simulates the relative performance well and could be a reliable index for subarea partition.

  12. Adaptive behaviour and multiple equilibrium states in a predator-prey model.

    Science.gov (United States)

    Pimenov, Alexander; Kelly, Thomas C; Korobeinikov, Andrei; O'Callaghan, Michael J A; Rachinskii, Dmitrii

    2015-05-01

    There is evidence that multiple stable equilibrium states are possible in real-life ecological systems. Phenomenological mathematical models which exhibit such properties can be constructed rather straightforwardly. For instance, for a predator-prey system this result can be achieved through the use of non-monotonic functional response for the predator. However, while formal formulation of such a model is not a problem, the biological justification for such functional responses and models is usually inconclusive. In this note, we explore a conjecture that a multitude of equilibrium states can be caused by an adaptation of animal behaviour to changes of environmental conditions. In order to verify this hypothesis, we consider a simple predator-prey model, which is a straightforward extension of the classic Lotka-Volterra predator-prey model. In this model, we made an intuitively transparent assumption that the prey can change a mode of behaviour in response to the pressure of predation, choosing either "safe" of "risky" (or "business as usual") behaviour. In order to avoid a situation where one of the modes gives an absolute advantage, we introduce the concept of the "cost of a policy" into the model. A simple conceptual two-dimensional predator-prey model, which is minimal with this property, and is not relying on odd functional responses, higher dimensionality or behaviour change for the predator, exhibits two stable co-existing equilibrium states with basins of attraction separated by a separatrix of a saddle point. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. Multiple Concurrent Visual-Motor Mappings: Implications for Models of Adaptation

    Science.gov (United States)

    Cunningham, H. A.; Welch, Robert B.

    1994-01-01

    Previous research on adaptation to visual-motor rearrangement suggests that the central nervous system represents accurately only 1 visual-motor mapping at a time. This idea was examined in 3 experiments where subjects tracked a moving target under repeated alternations between 2 initially interfering mappings (the 'normal' mapping characteristic of computer input devices and a 108' rotation of the normal mapping). Alternation between the 2 mappings led to significant reduction in error under the rotated mapping and significant reduction in the adaptation aftereffect ordinarily caused by switching between mappings. Color as a discriminative cue, interference versus decay in adaptation aftereffect, and intermanual transfer were also examined. The results reveal a capacity for multiple concurrent visual-motor mappings, possibly controlled by a parametric process near the motor output stage of processing.

  14. Adapting playware to multiple players

    DEFF Research Database (Denmark)

    Þorsteinsson, Arnar Tumi; Lund, Henrik Hautop; Mastorakis, Nikos

    2011-01-01

    With the creation of playware as intelligent hardware and software that creates play, it is possible to adapt the play tool to the individual user, and even to multiple users playing at the same time with the play tool. In this paper, we show how it is possible to implement adaptivity in modular...... to such differences, and argues that adaptivity is needed to make games fit to the individual users in both single-player games and multi-player games. As a case study, we implemented such adaptivity on modular interactive tiles for the single-user game ColorTimer, and for the multiple-user games PingPong, in which...

  15. An adaptive spatial model for precipitation data from multiple satellites over large regions

    KAUST Repository

    Chakraborty, Avishek

    2015-03-01

    Satellite measurements have of late become an important source of information for climate features such as precipitation due to their near-global coverage. In this article, we look at a precipitation dataset during a 3-hour window over tropical South America that has information from two satellites. We develop a flexible hierarchical model to combine instantaneous rainrate measurements from those satellites while accounting for their potential heterogeneity. Conceptually, we envision an underlying precipitation surface that influences the observed rain as well as absence of it. The surface is specified using a mean function centered at a set of knot locations, to capture the local patterns in the rainrate, combined with a residual Gaussian process to account for global correlation across sites. To improve over the commonly used pre-fixed knot choices, an efficient reversible jump scheme is used to allow the number of such knots as well as the order and support of associated polynomial terms to be chosen adaptively. To facilitate computation over a large region, a reduced rank approximation for the parent Gaussian process is employed.

  16. An adaptive spatial model for precipitation data from multiple satellites over large regions

    KAUST Repository

    Chakraborty, Avishek; De, Swarup; Bowman, Kenneth P.; Sang, Huiyan; Genton, Marc G.; Mallick, Bani K.

    2015-01-01

    South America that has information from two satellites. We develop a flexible hierarchical model to combine instantaneous rainrate measurements from those satellites while accounting for their potential heterogeneity. Conceptually, we envision

  17. Flight Control Failure Detection and Control Redistribution Using Multiple Model Adaptive Estimation with Filter Spawning

    National Research Council Canada - National Science Library

    Torres, Michael

    2002-01-01

    ...) are used together to identify failures and apply appropriate corrections. This effort explores the performance of the MMAE/FS/CR in different regions of the flight envelope using model and gain scheduling...

  18. Stochastic order in dichotomous item response models for fixed tests, research adaptive tests, or multiple abilities

    NARCIS (Netherlands)

    van der Linden, Willem J.

    1995-01-01

    Dichotomous item response theory (IRT) models can be viewed as families of stochastically ordered distributions of responses to test items. This paper explores several properties of such distributiom. The focus is on the conditions under which stochastic order in families of conditional

  19. On-line Multiple-model Based Adaptive Control Reconfiguration for a Class of Non-linear Control Systems

    DEFF Research Database (Denmark)

    Yang, Z.; Izadi-Zamanabadi, R.; Blanke, Mogens

    2000-01-01

    of LTI models are employed to approximate the faulty, reconfigured and nominal nonlinear systems respectively with respect to the on-line information of the operating system, and a set of compensating modules are proposed and designed so as to make the local LTI model approximating to the reconfigured...... nonlinear system match the corresponding LTI model approximating to the nominal nonlinear system in some optimal sense. The compensating modules are designed by the Pseudo-Inverse Method based on the local LTI models for the nominal and faulty nonlinear systems. Moreover, these modules should update...... corresponding to the updating of local LTI models, which validations are determined by the model approximation errors and the optimal index of local design. The test on a nonlinear ship propulsion system shows the promising potential of this method for system reconfiguration...

  20. Multiple time scales of adaptation in auditory cortex neurons.

    Science.gov (United States)

    Ulanovsky, Nachum; Las, Liora; Farkas, Dina; Nelken, Israel

    2004-11-17

    Neurons in primary auditory cortex (A1) of cats show strong stimulus-specific adaptation (SSA). In probabilistic settings, in which one stimulus is common and another is rare, responses to common sounds adapt more strongly than responses to rare sounds. This SSA could be a correlate of auditory sensory memory at the level of single A1 neurons. Here we studied adaptation in A1 neurons, using three different probabilistic designs. We showed that SSA has several time scales concurrently, spanning many orders of magnitude, from hundreds of milliseconds to tens of seconds. Similar time scales are known for the auditory memory span of humans, as measured both psychophysically and using evoked potentials. A simple model, with linear dependence on both short-term and long-term stimulus history, provided a good fit to A1 responses. Auditory thalamus neurons did not show SSA, and their responses were poorly fitted by the same model. In addition, SSA increased the proportion of failures in the responses of A1 neurons to the adapting stimulus. Finally, SSA caused a bias in the neuronal responses to unbiased stimuli, enhancing the responses to eccentric stimuli. Therefore, we propose that a major function of SSA in A1 neurons is to encode auditory sensory memory on multiple time scales. This SSA might play a role in stream segregation and in binding of auditory objects over many time scales, a property that is crucial for processing of natural auditory scenes in cats and of speech and music in humans.

  1. 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).

  2. Adaptation of flower and fruit colours to multiple, distinct mutualists.

    Science.gov (United States)

    Renoult, Julien P; Valido, Alfredo; Jordano, Pedro; Schaefer, H Martin

    2014-01-01

    Communication in plant-animal mutualisms frequently involves multiple perceivers. A fundamental uncertainty is whether and how species adapt to communicate with groups of mutualists having distinct sensory abilities. We quantified the colour conspicuousness of flowers and fruits originating from one European and two South American plant communities, using visual models of pollinators (bee and fly) and seed dispersers (bird, primate and marten). We show that flowers are more conspicuous than fruits to pollinators, and the reverse to seed dispersers. In addition, flowers are more conspicuous to pollinators than to seed dispersers and the reverse for fruits. Thus, despite marked differences in the visual systems of mutualists, flower and fruit colours have evolved to attract multiple, distinct mutualists but not unintended perceivers. We show that this adaptation is facilitated by a limited correlation between flower and fruit colours, and by the fact that colour signals as coded at the photoreceptor level are more similar within than between functional groups (pollinators and seed dispersers). Overall, these results provide the first quantitative demonstration that flower and fruit colours are adaptations allowing plants to communicate simultaneously with distinct groups of mutualists. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

  3. Multiple centroid method to evaluate the adaptability of alfalfa genotypes

    Directory of Open Access Journals (Sweden)

    Moysés Nascimento

    2015-02-01

    Full Text Available This study aimed to evaluate the efficiency of multiple centroids to study the adaptability of alfalfa genotypes (Medicago sativa L.. In this method, the genotypes are compared with ideotypes defined by the bissegmented regression model, according to the researcher's interest. Thus, genotype classification is carried out as determined by the objective of the researcher and the proposed recommendation strategy. Despite the great potential of the method, it needs to be evaluated under the biological context (with real data. In this context, we used data on the evaluation of dry matter production of 92 alfalfa cultivars, with 20 cuttings, from an experiment in randomized blocks with two repetitions carried out from November 2004 to June 2006. The multiple centroid method proved efficient for classifying alfalfa genotypes. Moreover, it showed no unambiguous indications and provided that ideotypes were defined according to the researcher's interest, facilitating data interpretation.

  4. 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...

  5. Adaptive Horizontal Gene Transfers between Multiple Cheese-Associated Fungi.

    Science.gov (United States)

    Ropars, Jeanne; Rodríguez de la Vega, Ricardo C; López-Villavicencio, Manuela; Gouzy, Jérôme; Sallet, Erika; Dumas, Émilie; Lacoste, Sandrine; Debuchy, Robert; Dupont, Joëlle; Branca, Antoine; Giraud, Tatiana

    2015-10-05

    Domestication is an excellent model for studies of adaptation because it involves recent and strong selection on a few, identified traits [1-5]. Few studies have focused on the domestication of fungi, with notable exceptions [6-11], despite their importance to bioindustry [12] and to a general understanding of adaptation in eukaryotes [5]. Penicillium fungi are ubiquitous molds among which two distantly related species have been independently selected for cheese making-P. roqueforti for blue cheeses like Roquefort and P. camemberti for soft cheeses like Camembert. The selected traits include morphology, aromatic profile, lipolytic and proteolytic activities, and ability to grow at low temperatures, in a matrix containing bacterial and fungal competitors [13-15]. By comparing the genomes of ten Penicillium species, we show that adaptation to cheese was associated with multiple recent horizontal transfers of large genomic regions carrying crucial metabolic genes. We identified seven horizontally transferred regions (HTRs) spanning more than 10 kb each, flanked by specific transposable elements, and displaying nearly 100% identity between distant Penicillium species. Two HTRs carried genes with functions involved in the utilization of cheese nutrients or competition and were found nearly identical in multiple strains and species of cheese-associated Penicillium fungi, indicating recent selective sweeps; they were experimentally associated with faster growth and greater competitiveness on cheese and contained genes highly expressed in the early stage of cheese maturation. These findings have industrial and food safety implications and improve our understanding of the processes of adaptation to rapid environmental changes. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  6. Adaptive multiple importance sampling for Gaussian processes

    Czech Academy of Sciences Publication Activity Database

    Xiong, X.; Šmídl, Václav; Filippone, M.

    2017-01-01

    Roč. 87, č. 8 (2017), s. 1644-1665 ISSN 0094-9655 R&D Projects: GA MŠk(CZ) 7F14287 Institutional support: RVO:67985556 Keywords : Gaussian Process * Bayesian estimation * Adaptive importance sampling Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 0.757, year: 2016 http://library.utia.cas.cz/separaty/2017/AS/smidl-0469804.pdf

  7. Adaptive Kalman filtering for diagnosis of multiple component degradations

    International Nuclear Information System (INIS)

    Aumeier, S. E.; Alpay, B.; Lee, J. C.

    2005-01-01

    We have developed an adaptive Kalman filtering algorithm for the diagnosis of faults or degradations of multiple components in nuclear power plants. We propose to detect the presence and magnitude of the fault(s) through noisy system observations when the measurements indicate significant deviations from predictions. Our diagnostic algorithm uses the measurement residuals, i.e., the difference between the measurements and predictions, to generate a noise input to the uncertain component state in an adaptive Kalman filtering algorithm so that various postulated component transitions or degradations may be statistically represented. The diagnostic algorithm has been tested with a balance of plant (BOP) model of a boiling water reactor (BWR). We have presented a set of algorithms for the detection and diagnosis of component faults of arbitrary magnitude and type within a multi-component system. By analyzing a number of transients including the one example illustrated in the paper, we find that these algorithms are not only capable of determining the correct component fault and magnitude for single components but also they can be used to determine binary faults satisfactorily. Additional study is under way to evaluate the performance of the proposed algorithm including the sensitivity of the diagnostic time to adaptive noise matrix introduced (see equations 7 and 8 illustrated in the paper)

  8. Classification of multiple sclerosis lesions using adaptive dictionary learning.

    Science.gov (United States)

    Deshpande, Hrishikesh; Maurel, Pierre; Barillot, Christian

    2015-12-01

    This paper presents a sparse representation and an adaptive dictionary learning based method for automated classification of multiple sclerosis (MS) lesions in magnetic resonance (MR) images. Manual delineation of MS lesions is a time-consuming task, requiring neuroradiology experts to analyze huge volume of MR data. This, in addition to the high intra- and inter-observer variability necessitates the requirement of automated MS lesion classification methods. Among many image representation models and classification methods that can be used for such purpose, we investigate the use of sparse modeling. In the recent years, sparse representation has evolved as a tool in modeling data using a few basis elements of an over-complete dictionary and has found applications in many image processing tasks including classification. We propose a supervised classification approach by learning dictionaries specific to the lesions and individual healthy brain tissues, which include white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). The size of the dictionaries learned for each class plays a major role in data representation but it is an even more crucial element in the case of competitive classification. Our approach adapts the size of the dictionary for each class, depending on the complexity of the underlying data. The algorithm is validated using 52 multi-sequence MR images acquired from 13 MS patients. The results demonstrate the effectiveness of our approach in MS lesion classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. 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.

  10. Behavioral training promotes multiple adaptive processes following acute hearing loss.

    Science.gov (United States)

    Keating, Peter; Rosenior-Patten, Onayomi; Dahmen, Johannes C; Bell, Olivia; King, Andrew J

    2016-03-23

    The brain possesses a remarkable capacity to compensate for changes in inputs resulting from a range of sensory impairments. Developmental studies of sound localization have shown that adaptation to asymmetric hearing loss can be achieved either by reinterpreting altered spatial cues or by relying more on those cues that remain intact. Adaptation to monaural deprivation in adulthood is also possible, but appears to lack such flexibility. Here we show, however, that appropriate behavioral training enables monaurally-deprived adult humans to exploit both of these adaptive processes. Moreover, cortical recordings in ferrets reared with asymmetric hearing loss suggest that these forms of plasticity have distinct neural substrates. An ability to adapt to asymmetric hearing loss using multiple adaptive processes is therefore shared by different species and may persist throughout the lifespan. This highlights the fundamental flexibility of neural systems, and may also point toward novel therapeutic strategies for treating sensory disorders.

  11. 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.

  12. Adaptation of the Electra Radio to Support Multiple Receive Channels

    Science.gov (United States)

    Satorius, Edgar H.; Shah, Biren N.; Bruvold, Kristoffer N.; Bell, David J.

    2011-01-01

    Proposed future Mars missions plan communication between multiple assets (rovers). This paper presents the results of a study carried out to assess the potential adaptation of the Electra radio to a multi-channel transceiver. The basic concept is a Frequency Division multiplexing (FDM) communications scheme wherein different receiver architectures are examined. Options considered include: (1) multiple IF slices, A/D and FPGAs each programmed with an Electra baseband modem; (2) common IF but multiple A/Ds and FPGAs and (3) common IF, single A/D and single or multiple FPGAs programmed to accommodate the FDM signals. These options represent the usual tradeoff between analog and digital complexity. Given the space application, a common IF is preferable; however, multiple users present dynamic range challenges (e.g., near-far constraints) that would favor multiple IF slices (Option 1). Vice versa, with a common IF and multiple A/Ds (Option 2), individual AGC control of the A/Ds would be an important consideration. Option 3 would require a common AGC control strategy and would entail multiple digital down conversion paths within the FPGA. In this paper, both FDM parameters as well as the different Electra design options will be examined. In particular, signal channel spacing as a function of user data rates and transmit powers will be evaluated. In addition, tradeoffs between the different Electra design options will be presented with the ultimate goal of defining an augmented Electra radio architecture for potential future missions.

  13. Geometrical model of multiple production

    International Nuclear Information System (INIS)

    Chikovani, Z.E.; Jenkovszky, L.L.; Kvaratshelia, T.M.; Struminskij, B.V.

    1988-01-01

    The relation between geometrical and KNO-scaling and their violation is studied in a geometrical model of multiple production of hadrons. Predictions concerning the behaviour of correlation coefficients at future accelerators are given

  14. Intelligent fault recognition strategy based on adaptive optimized multiple centers

    Science.gov (United States)

    Zheng, Bo; Li, Yan-Feng; Huang, Hong-Zhong

    2018-06-01

    For the recognition principle based optimized single center, one important issue is that the data with nonlinear separatrix cannot be recognized accurately. In order to solve this problem, a novel recognition strategy based on adaptive optimized multiple centers is proposed in this paper. This strategy recognizes the data sets with nonlinear separatrix by the multiple centers. Meanwhile, the priority levels are introduced into the multi-objective optimization, including recognition accuracy, the quantity of optimized centers, and distance relationship. According to the characteristics of various data, the priority levels are adjusted to ensure the quantity of optimized centers adaptively and to keep the original accuracy. The proposed method is compared with other methods, including support vector machine (SVM), neural network, and Bayesian classifier. The results demonstrate that the proposed strategy has the same or even better recognition ability on different distribution characteristics of data.

  15. Constructing an adaptive care model for the management of disease-related symptoms throughout the course of multiple sclerosis--performance improvement CME.

    Science.gov (United States)

    Miller, Aaron E; Cohen, Bruce A; Krieger, Stephen C; Markowitz, Clyde E; Mattson, David H; Tselentis, Helen N

    2014-01-01

    Symptom management remains a challenging clinical aspect of MS. To design a performance improvement continuing medical education (PI CME) activity for better clinical management of multiple sclerosis (MS)-related depression, fatigue, mobility impairment/falls, and spasticity. Ten volunteer MS centers participated in a three-stage PI CME model: A) baseline assessment; B) practice improvement CME intervention; C) reassessment. Expert faculty developed performance measures and activity intervention tools. Designated MS center champions reviewed patient charts and entered data into an online database. Stage C data were collected eight weeks after implementation of the intervention and compared with Stage A baseline data to measure change in performance. Aggregate data from the 10 participating MS centers (405 patient charts) revealed performance improvements in the assessment of all four MS-related symptoms. Statistically significant improvements were found in the documented assessment of mobility impairment/falls (p=0.003) and spasticity (pmodel (available at www.achlpicme.org/ms/toolkit) offers a new perspective on enhancing symptom management in patients with MS.

  16. 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...

  17. 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....

  18. 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.

  19. 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…

  20. 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

  1. 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.

  2. 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...

  3. 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

  4. Multiple Estimation Architecture in Discrete-Time Adaptive Mixing Control

    Directory of Open Access Journals (Sweden)

    Simone Baldi

    2013-05-01

    Full Text Available Adaptive mixing control (AMC is a recently developed control scheme for uncertain plants, where the control action coming from a bank of precomputed controller is mixed based on the parameter estimates generated by an on-line parameter estimator. Even if the stability of the control scheme, also in the presence of modeling errors and disturbances, has been shown analytically, its transient performance might be sensitive to the initial conditions of the parameter estimator. In particular, for some initial conditions, transient oscillations may not be acceptable in practical applications. In order to account for such a possible phenomenon and to improve the learning capability of the adaptive scheme, in this paper a new mixing architecture is developed, involving the use of parallel parameter estimators, or multi-estimators, each one working on a small subset of the uncertainty set. A supervisory logic, using performance signals based on the past and present estimation error, selects the parameter estimate to determine the mixing of the controllers. The stability and robustness properties of the resulting approach, referred to as multi-estimator adaptive mixing control (Multi-AMC, are analytically established. Besides, extensive simulations demonstrate that the scheme improves the transient performance of the original AMC with a single estimator. The control scheme and the analysis are carried out in a discrete-time framework, for easier implementation of the method in digital control.

  5. Retinal dopamine mediates multiple dimensions of light-adapted vision.

    Science.gov (United States)

    Jackson, Chad R; Ruan, Guo-Xiang; Aseem, Fazila; Abey, Jane; Gamble, Karen; Stanwood, Greg; Palmiter, Richard D; Iuvone, P Michael; McMahon, Douglas G

    2012-07-04

    Dopamine is a key neuromodulator in the retina and brain that supports motor, cognitive, and visual function. Here, we developed a mouse model on a C57 background in which expression of the rate-limiting enzyme for dopamine synthesis, tyrosine hydroxylase, is specifically disrupted in the retina. This model enabled assessment of the overall role of retinal dopamine in vision using electrophysiological (electroretinogram), psychophysical (optokinetic tracking), and pharmacological techniques. Significant disruptions were observed in high-resolution, light-adapted vision caused by specific deficits in light responses, contrast sensitivity, acuity, and circadian rhythms in this retinal dopamine-depleted mouse model. These global effects of retinal dopamine on vision are driven by the differential actions of dopamine D1 and D4 receptors on specific retinal functions and appear to be due to the ongoing bioavailability of dopamine rather than developmental effects. Together, our data indicate that dopamine is necessary for the circadian nature of light-adapted vision as well as optimal contrast detection and acuity.

  6. 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.

  7. Adaptive multi-node multiple input and multiple output (MIMO) transmission for mobile wireless multimedia sensor networks.

    Science.gov (United States)

    Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo

    2013-10-02

    Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase.

  8. 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...

  9. 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

  10. Sinusoidal error perturbation reveals multiple coordinate systems for sensorymotor adaptation.

    Science.gov (United States)

    Hudson, Todd E; Landy, Michael S

    2016-02-01

    A coordinate system is composed of an encoding, defining the dimensions of the space, and an origin. We examine the coordinate encoding used to update motor plans during sensory-motor adaptation to center-out reaches. Adaptation is induced using a novel paradigm in which feedback of reach endpoints is perturbed following a sinewave pattern over trials; the perturbed dimensions of the feedback were the axes of a Cartesian coordinate system in one session and a polar coordinate system in another session. For center-out reaches to randomly chosen target locations, reach errors observed at one target will require different corrections at other targets within Cartesian- and polar-coded systems. The sinewave adaptation technique allowed us to simultaneously adapt both dimensions of each coordinate system (x-y, or reach gain and angle), and identify the contributions of each perturbed dimension by adapting each at a distinct temporal frequency. The efficiency of this technique further allowed us to employ perturbations that were a fraction the size normally used, which avoids confounding automatic adaptive processes with deliberate adjustments made in response to obvious experimental manipulations. Subjects independently corrected errors in each coordinate in both sessions, suggesting that the nervous system encodes both a Cartesian- and polar-coordinate-based internal representation for motor adaptation. The gains and phase lags of the adaptive responses are not readily explained by current theories of sensory-motor adaptation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. 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...

  12. 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 ...

  13. A New Approach to Adaptive Control of Multiple Scales in Plasma Simulations

    Science.gov (United States)

    Omelchenko, Yuri

    2007-04-01

    A new approach to temporal refinement of kinetic (Particle-in-Cell, Vlasov) and fluid (MHD, two-fluid) simulations of plasmas is presented: Discrete-Event Simulation (DES). DES adaptively distributes CPU resources in accordance with local time scales and enables asynchronous integration of inhomogeneous nonlinear systems with multiple time scales on meshes of arbitrary topologies. This removes computational penalties usually incurred in explicit codes due to the global Courant-Friedrich-Levy (CFL) restriction on a time-step size. DES stands apart from multiple time-stepping algorithms in that it requires neither selecting a global synchronization time step nor pre-determining a sequence of time-integration operations for individual parts of the system (local time increments need not bear any integer multiple relations). Instead, elements of a mesh-distributed solution self-adaptively predict and synchronize their temporal trajectories by directly enforcing local causality (accuracy) constraints, which are formulated in terms of incremental changes to the evolving solution. Together with flux-conservative propagation of information, this new paradigm ensures stable and fast asynchronous runs, where idle computation is automatically eliminated. DES is parallelized via a novel Preemptive Event Processing (PEP) technique, which automatically synchronizes elements with similar update rates. In this mode, events with close execution times are projected onto time levels, which are adaptively determined by the program. PEP allows reuse of standard message-passing algorithms on distributed architectures. For optimum accuracy, DES can be combined with adaptive mesh refinement (AMR) techniques for structured and unstructured meshes. Current examples of event-driven models range from electrostatic, hybrid particle-in-cell plasma systems to reactive fluid dynamics simulations. They demonstrate the superior performance of DES in terms of accuracy, speed and robustness.

  14. 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.

  15. Multiple Indicator Stationary Time Series Models.

    Science.gov (United States)

    Sivo, Stephen A.

    2001-01-01

    Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

  16. Modeling Multiple Causes of Carcinogenesis

    Energy Technology Data Exchange (ETDEWEB)

    Jones, T D

    1999-01-24

    An array of epidemiological results and databases on test animal indicate that risk of cancer and atherosclerosis can be up- or down-regulated by diet through a range of 200%. Other factors contribute incrementally and include the natural terrestrial environment and various human activities that jointly produce complex exposures to endotoxin-producing microorganisms, ionizing radiations, and chemicals. Ordinary personal habits and simple physical irritants have been demonstrated to affect the immune response and risk of disease. There tends to be poor statistical correlation of long-term risk with single agent exposures incurred throughout working careers. However, Agency recommendations for control of hazardous exposures to humans has been substance-specific instead of contextually realistic even though there is consistent evidence for common mechanisms of toxicological and carcinogenic action. That behavior seems to be best explained by molecular stresses from cellular oxygen metabolism and phagocytosis of antigenic invasion as well as breakdown of normal metabolic compounds associated with homeostatic- and injury-related renewal of cells. There is continually mounting evidence that marrow stroma, comprised largely of monocyte-macrophages and fibroblasts, is important to phagocytic and cytokinetic response, but the complex action of the immune process is difficult to infer from first-principle logic or biomarkers of toxic injury. The many diverse database studies all seem to implicate two important processes, i.e., the univalent reduction of molecular oxygen and breakdown of aginuine, an amino acid, by hydrolysis or digestion of protein which is attendant to normal antigen-antibody action. This behavior indicates that protection guidelines and risk coefficients should be context dependent to include reference considerations of the composite action of parameters that mediate oxygen metabolism. A logic of this type permits the realistic common-scale modeling of

  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. 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…

  1. 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.

  2. Multiple Maximum Exposure Rates in Computerized Adaptive Testing

    Science.gov (United States)

    Ramon Barrada, Juan; Veldkamp, Bernard P.; Olea, Julio

    2009-01-01

    Computerized adaptive testing is subject to security problems, as the item bank content remains operative over long periods and administration time is flexible for examinees. Spreading the content of a part of the item bank could lead to an overestimation of the examinees' trait level. The most common way of reducing this risk is to impose a…

  3. Adaptive responses to salinity stress across multiple life stages in anuran amphibians.

    Science.gov (United States)

    Albecker, Molly A; McCoy, Michael W

    2017-01-01

    In many regions, freshwater wetlands are increasing in salinity at rates exceeding historic levels. Some freshwater organisms, like amphibians, may be able to adapt and persist in salt-contaminated wetlands by developing salt tolerance. Yet adaptive responses may be more challenging for organisms with complex life histories, because the same environmental stressor can require responses across different ontogenetic stages. Here we investigated responses to salinity in anuran amphibians: a common, freshwater taxon with a complex life cycle. We conducted a meta-analysis to define how the lethality of saltwater exposure changes across multiple life stages, surveyed wetlands in a coastal region experiencing progressive salinization for the presence of anurans, and used common garden experiments to investigate whether chronic salt exposure alters responses in three sequential life stages (reproductive, egg, and tadpole life stages) in Hyla cinerea , a species repeatedly observed in saline wetlands. Meta-analysis revealed differential vulnerability to salt stress across life stages with the egg stage as the most salt-sensitive. Field surveys revealed that 25% of the species known to occur in the focal region were detected in salt-intruded habitats. Remarkably, Hyla cinerea was found in large abundances in multiple wetlands with salinity concentrations 450% higher than the tadpole-stage LC 50 . Common garden experiments showed that coastal (chronically salt exposed) populations of H. cinerea lay more eggs, have higher hatching success, and greater tadpole survival in higher salinities compared to inland (salt naïve) populations. Collectively, our data suggest that some species of anuran amphibians have divergent and adaptive responses to salt exposure across populations and across different life stages. We propose that anuran amphibians may be a novel and amenable natural model system for empirical explorations of adaptive responses to environmental change.

  4. Combined adaptive multiple subtraction based on optimized event tracing and extended wiener filtering

    Science.gov (United States)

    Tan, Jun; Song, Peng; Li, Jinshan; Wang, Lei; Zhong, Mengxuan; Zhang, Xiaobo

    2017-06-01

    The surface-related multiple elimination (SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the predicted multiples and those in the source seismic records, which may result in conventional adaptive multiple subtraction methods being barely able to effectively suppress multiples in actual production. This paper introduces a combined adaptive multiple attenuation method based on the optimized event tracing technique and extended Wiener filtering. The method firstly uses multiple records predicted by SRME to generate a multiple velocity spectrum, then separates the original record to an approximate primary record and an approximate multiple record by applying the optimized event tracing method and short-time window FK filtering method. After applying the extended Wiener filtering method, residual multiples in the approximate primary record can then be eliminated and the damaged primary can be restored from the approximate multiple record. This method combines the advantages of multiple elimination based on the optimized event tracing method and the extended Wiener filtering technique. It is an ideal method for suppressing typical hyperbolic and other types of multiples, with the advantage of minimizing damage of the primary. Synthetic and field data tests show that this method produces better multiple elimination results than the traditional multi-channel Wiener filter method and is more suitable for multiple elimination in complicated geological areas.

  5. 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...

  6. Optimizing the passenger air bag of an adaptive restraint system for multiple size occupants.

    Science.gov (United States)

    Bai, Zhonghao; Jiang, Binhui; Zhu, Feng; Cao, Libo

    2014-01-01

    The development of the adaptive occupant restraint system (AORS) has led to an innovative way to optimize such systems for multiple size occupants. An AORS consists of multiple units such as adaptive air bags, seat belts, etc. During a collision, as a supplemental protective device, air bags can provide constraint force and play a role in dissipating the crash energy of the occupants' head and thorax. This article presents an investigation into an adaptive passenger air bag (PAB). The purpose of this study is to develop a base shape of a PAB for different size occupants using an optimization method. Four typical base shapes of a PAB were designed based on geometric data on the passenger side. Then 4 PAB finite element (FE) models and a validated sled with different size dummy models were developed in MADYMO (TNO, Rijswijk, The Netherlands) to conduct the optimization to obtain the best baseline PAB that would be used in the AORS. The objective functions-that is, the minimum total probability of injuries (∑Pcomb) of the 5th percentile female and 50th and 95th percentile male dummies-were adopted to evaluate the optimal configurations. The injury probability (Pcomb) for each dummy was adopted from the U.S. New Car Assessment Program (US-NCAP). The parameters of the AORS were first optimized for different types of PAB base shapes in a frontal impact. Then, contact time duration and force between the PAB and dummy head/chest were optimized by adjusting the parameters of the PAB, such as the number and position of tethers, lower the Pcomb of the 95th percentile male dummy. According to the optimization results, 4 typical PABs could provide effective protection to 5th and 50th percentile dummies. However, due to the heavy and large torsos of the 95th percentile occupants, the current occupant restraint system does not demonstrate satisfactory protective function, particularly for the thorax.

  7. 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.

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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)

  15. Vibrio Iron Transport: Evolutionary Adaptation to Life in Multiple Environments

    Science.gov (United States)

    Mey, Alexandra R.; Wyckoff, Elizabeth E.

    2015-01-01

    SUMMARY Iron is an essential element for Vibrio spp., but the acquisition of iron is complicated by its tendency to form insoluble ferric complexes in nature and its association with high-affinity iron-binding proteins in the host. Vibrios occupy a variety of different niches, and each of these niches presents particular challenges for acquiring sufficient iron. Vibrio species have evolved a wide array of iron transport systems that allow the bacteria to compete for this essential element in each of its habitats. These systems include the secretion and uptake of high-affinity iron-binding compounds (siderophores) as well as transport systems for iron bound to host complexes. Transporters for ferric and ferrous iron not complexed to siderophores are also common to Vibrio species. Some of the genes encoding these systems show evidence of horizontal transmission, and the ability to acquire and incorporate additional iron transport systems may have allowed Vibrio species to more rapidly adapt to new environmental niches. While too little iron prevents growth of the bacteria, too much can be lethal. The appropriate balance is maintained in vibrios through complex regulatory networks involving transcriptional repressors and activators and small RNAs (sRNAs) that act posttranscriptionally. Examination of the number and variety of iron transport systems found in Vibrio spp. offers insights into how this group of bacteria has adapted to such a wide range of habitats. PMID:26658001

  16. 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

  17. Adaptive Waveform Design for Cognitive Radar in Multiple Targets Situations

    Directory of Open Access Journals (Sweden)

    Xiaowen Zhang

    2018-02-01

    Full Text Available In this paper, the problem of cognitive radar (CR waveform optimization design for target detection and estimation in multiple extended targets situations is investigated. This problem is analyzed in signal-dependent interference, as well as additive channel noise for extended targets with unknown target impulse response (TIR. To address this problem, an improved algorithm is employed for target detection by maximizing the detection probability of the received echo on the promise of ensuring the TIR estimation precision. In this algorithm, an additional weight vector is introduced to achieve a trade-off among different targets. Both the estimate of TIR and transmit waveform can be updated at each step based on the previous step. Under the same constraint on waveform energy and bandwidth, the information theoretical approach is also considered. In addition, the relationship between the waveforms that are designed based on the two criteria is discussed. Unlike most existing works that only consider single target with temporally correlated characteristics, waveform design for multiple extended targets is considered in this method. Simulation results demonstrate that compared with linear frequency modulated (LFM signal, waveforms designed based on maximum detection probability and maximum mutual information (MI criteria can make radar echoes contain more multiple-target information and improve radar performance as a result.

  18. 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…

  19. 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.

  20. Multiplicity Control in Structural Equation Modeling

    Science.gov (United States)

    Cribbie, Robert A.

    2007-01-01

    Researchers conducting structural equation modeling analyses rarely, if ever, control for the inflated probability of Type I errors when evaluating the statistical significance of multiple parameters in a model. In this study, the Type I error control, power and true model rates of famsilywise and false discovery rate controlling procedures were…

  1. 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

  2. Adaptive Portfolio Optimization for Multiple Electricity Markets Participation

    DEFF Research Database (Denmark)

    Pinto, Tiago; Morais, Hugo; Sousa, Tiago M.

    2016-01-01

    as the most suitable solution to facilitate the small players' participation in electric power negotiations while improving energy efficiency. The opportunity for players' participation in multiple energy negotiation environments (smart grid negotiation in addition to the already implemented market types......, such as day-ahead spot markets, balancing markets, intraday negotiations, bilateral contracts, forward and futures negotiations, and among other) requires players to take suitable decisions on whether to, and how to participate in each market type. This paper proposes a portfolio optimization methodology......, which provides the best investment profile for a market player, considering different market opportunities. The amount of power that each supported player should negotiate in each available market type in order to maximize its profits, considers the prices that are expected to be achieved in each market...

  3. 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....

  4. 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

  5. An Adaptive Multiobjective Particle Swarm Optimization Based on Multiple Adaptive Methods.

    Science.gov (United States)

    Han, Honggui; Lu, Wei; Qiao, Junfei

    2017-09-01

    Multiobjective particle swarm optimization (MOPSO) algorithms have attracted much attention for their promising performance in solving multiobjective optimization problems (MOPs). In this paper, an adaptive MOPSO (AMOPSO) algorithm, based on a hybrid framework of the solution distribution entropy and population spacing (SP) information, is developed to improve the search performance in terms of convergent speed and precision. First, an adaptive global best (gBest) selection mechanism, based on the solution distribution entropy, is introduced to analyze the evolutionary tendency and balance the diversity and convergence of nondominated solutions in the archive. Second, an adaptive flight parameter adjustment mechanism, using the population SP information, is proposed to obtain the distribution of particles with suitable diversity and convergence, which can balance the global exploration and local exploitation abilities of the particles. Third, based on the gBest selection mechanism and the adaptive flight parameter mechanism, this proposed AMOPSO algorithm not only has high accuracy, but also attain a set of optimal solutions with better diversity. Finally, the performance of the proposed AMOPSO algorithm is validated and compared with other five state-of-the-art algorithms on a number of benchmark problems and water distribution system. The experimental results validate the effectiveness of the proposed AMOPSO algorithm, as well as demonstrate that AMOPSO outperforms other MOPSO algorithms in solving MOPs.

  6. 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.

  7. Adaptive Portfolio Optimization for Multiple Electricity Markets Participation.

    Science.gov (United States)

    Pinto, Tiago; Morais, Hugo; Sousa, Tiago M; Sousa, Tiago; Vale, Zita; Praca, Isabel; Faia, Ricardo; Pires, Eduardo Jose Solteiro

    2016-08-01

    The increase of distributed energy resources, mainly based on renewable sources, requires new solutions that are able to deal with this type of resources' particular characteristics (namely, the renewable energy sources intermittent nature). The smart grid concept is increasing its consensus as the most suitable solution to facilitate the small players' participation in electric power negotiations while improving energy efficiency. The opportunity for players' participation in multiple energy negotiation environments (smart grid negotiation in addition to the already implemented market types, such as day-ahead spot markets, balancing markets, intraday negotiations, bilateral contracts, forward and futures negotiations, and among other) requires players to take suitable decisions on whether to, and how to participate in each market type. This paper proposes a portfolio optimization methodology, which provides the best investment profile for a market player, considering different market opportunities. The amount of power that each supported player should negotiate in each available market type in order to maximize its profits, considers the prices that are expected to be achieved in each market, in different contexts. The price forecasts are performed using artificial neural networks, providing a specific database with the expected prices in the different market types, at each time. This database is then used as input by an evolutionary particle swarm optimization process, which originates the most advantage participation portfolio for the market player. The proposed approach is tested and validated with simulations performed in multiagent simulator of competitive electricity markets, using real electricity markets data from the Iberian operator-MIBEL.

  8. Multiple Kernel Learning for adaptive graph regularized nonnegative matrix factorization

    KAUST Repository

    Wang, Jim Jing-Yan; AbdulJabbar, Mustafa Abdulmajeed

    2012-01-01

    Nonnegative Matrix Factorization (NMF) has been continuously evolving in several areas like pattern recognition and information retrieval methods. It factorizes a matrix into a product of 2 low-rank non-negative matrices that will define parts-based, and linear representation of non-negative data. Recently, Graph regularized NMF (GrNMF) is proposed to find a compact representation, which uncovers the hidden semantics and simultaneously respects the intrinsic geometric structure. In GNMF, an affinity graph is constructed from the original data space to encode the geometrical information. In this paper, we propose a novel idea which engages a Multiple Kernel Learning approach into refining the graph structure that reflects the factorization of the matrix and the new data space. The GrNMF is improved by utilizing the graph refined by the kernel learning, and then a novel kernel learning method is introduced under the GrNMF framework. Our approach shows encouraging results of the proposed algorithm in comparison to the state-of-the-art clustering algorithms like NMF, GrNMF, SVD etc.

  9. Numerical Computation of Underground Inundation in Multiple Layers Using the Adaptive Transfer Method

    Directory of Open Access Journals (Sweden)

    Hyung-Jun Kim

    2018-01-01

    Full Text Available Extreme rainfall causes surface runoff to flow towards lowlands and subterranean facilities, such as subway stations and buildings with underground spaces in densely packed urban areas. These facilities and areas are therefore vulnerable to catastrophic submergence. However, flood modeling of underground space has not yet been adequately studied because there are difficulties in reproducing the associated multiple horizontal layers connected with staircases or elevators. This study proposes a convenient approach to simulate underground inundation when two layers are connected. The main facet of this approach is to compute the flow flux passing through staircases in an upper layer and to transfer the equivalent quantity to a lower layer. This is defined as the ‘adaptive transfer method’. This method overcomes the limitations of 2D modeling by introducing layers connecting concepts to prevent large variations in mesh sizes caused by complicated underlying obstacles or local details. Consequently, this study aims to contribute to the numerical analysis of flow in inundated underground spaces with multiple floors.

  10. Relationship between Psychological Hardiness and Social Support with Adaptation: A Study on Individuals with Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    N hasan neghad

    2013-10-01

    Full Text Available Introduction: Psychological hardiness is a personal factor and social support is regarded as an environmental factor that can facilitate adjustment to disease. This study aimed to investigate the relationship between adaptation with psychological hardiness and social support in individuals with Multiple sclerosis (MS. Methods: Seventy two females with MS and 25 males with MSwere selected through randomized sampling from two MS centers. Main variables of the study including adaptation, psychological hardiness, and social supportwere assessed respectively by Adaptation Inventory, Personal Attitudes Survey, and Social Support Questionnaire. Results: Spearman correlation coefficients revealed that there are significant relationships between adaptation and psychological hardiness (p<0.0001, as well as between adaptation and social support (p<0.0001. In addition, Multiple linear Regression showed that psychological hardiness (β= -0.483 and social support (β= -0.240 can explain 35/1% of adaptation variance in individuals with MS. Psychological hardinessproved to have a more important role in adaptation of individuals with MS. Conclusion: The study data demonstrated that personal factors like psychological hardiness and environmental factors such as social support can predict adjustment in individuals with MS. In order to clarify mechanisms of these factors on adaptation in individuals with MS, morelongitudinal and experimental studiesare required. These results are alsoapplicable in designing therapeutic programs for individuals with MS.

  11. A collaborative scheduling model for the supply-hub with multiple suppliers and multiple manufacturers.

    Science.gov (United States)

    Li, Guo; Lv, Fei; Guan, Xu

    2014-01-01

    This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.

  12. A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers

    Directory of Open Access Journals (Sweden)

    Guo Li

    2014-01-01

    Full Text Available This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.

  13. A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers

    Science.gov (United States)

    Lv, Fei; Guan, Xu

    2014-01-01

    This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment. PMID:24892104

  14. Adaptive modified function projective synchronization of multiple time-delayed chaotic Rossler system

    International Nuclear Information System (INIS)

    Sudheer, K. Sebastian; Sabir, M.

    2011-01-01

    In this Letter we consider modified function projective synchronization of unidirectionally coupled multiple time-delayed Rossler chaotic systems using adaptive controls. Recently, delay differential equations have attracted much attention in the field of nonlinear dynamics. The high complexity of the multiple time-delayed systems can provide a new architecture for enhancing message security in chaos based encryption systems. Adaptive control can be used for synchronization when the parameters of the system are unknown. Based on Lyapunov stability theory, the adaptive control law and the parameter update law are derived to make the state of two chaotic systems are function projective synchronized. Numerical simulations are presented to demonstrate the effectiveness of the proposed adaptive controllers.

  15. 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.

  16. Particle Swarm Social Adaptive Model for Multi-Agent Based Insurgency Warfare Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Xiaohui [ORNL; Potok, Thomas E [ORNL

    2009-12-01

    To better understand insurgent activities and asymmetric warfare, a social adaptive model for modeling multiple insurgent groups attacking multiple military and civilian targets is proposed and investigated. This report presents a pilot study using the particle swarm modeling, a widely used non-linear optimal tool to model the emergence of insurgency campaign. The objective of this research is to apply the particle swarm metaphor as a model of insurgent social adaptation for the dynamically changing environment and to provide insight and understanding of insurgency warfare. Our results show that unified leadership, strategic planning, and effective communication between insurgent groups are not the necessary requirements for insurgents to efficiently attain their objective.

  17. Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

    Science.gov (United States)

    Li, Zhijun; Su, Chun-Yi

    2013-09-01

    In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.

  18. Adaptation to Climate Change in Forestry: A Multiple Correspondence Analysis (MCA

    Directory of Open Access Journals (Sweden)

    Marielle Brunette

    2018-01-01

    Full Text Available We analyze economic perspectives of forest adaptation to risk attributes, caused mostly by climate change. We construct a database with 89 systematically chosen articles, dealing simultaneously with climate, adaptation, risk and economy. We classify the database with regard to 18 variables bearing on the characteristics of the paper, the description of the risk and the adaptation strategy, the topic and the corresponding results. To achieve a “high level-of-evidence”, we realize a multiple correspondence analysis (MCA to identify which variables were found in combination with one other in the literature and make distinct groupings affecting adaptive decisions. We identify three groups: (i profit and production; (ii microeconomic risk-handling; and (iii decision and behavior. The first group includes economic costs and benefits as the driver of adaptation and prioritizes simulation, and a mix of theoretical and empirical economic approach. The second group distinctly involves risk-related issues, in particular its management by adaptation. The third group gathers a large set of social and behavioral variables affecting management decisions collected through questionnaires. Such an approach allows the identification of gaps in the literature, concerning the impact of owners’ preferences towards risk and uncertainty regarding adaptation decisions, the fact that adaptation was often reduced in an attempt to adapt to the increasing risk of wildfire, or the existence of a regional bias.

  19. 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.

  20. 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

  1. 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

  2. Design of Xen Hybrid Multiple Police Model

    Science.gov (United States)

    Sun, Lei; Lin, Renhao; Zhu, Xianwei

    2017-10-01

    Virtualization Technology has attracted more and more attention. As a popular open-source virtualization tools, XEN is used more and more frequently. Xsm, XEN security model, has also been widespread concern. The safety status classification has not been established in the XSM, and it uses the virtual machine as a managed object to make Dom0 a unique administrative domain that does not meet the minimum privilege. According to these questions, we design a Hybrid multiple police model named SV_HMPMD that organically integrates multiple single security policy models include DTE,RBAC,BLP. It can fullfill the requirement of confidentiality and integrity for security model and use different particle size to different domain. In order to improve BLP’s practicability, the model introduce multi-level security labels. In order to divide the privilege in detail, we combine DTE with RBAC. In order to oversize privilege, we limit the privilege of domain0.

  3. Multiple Model Approaches to Modelling and Control,

    DEFF Research Database (Denmark)

    on the ease with which prior knowledge can be incorporated. It is interesting to note that researchers in Control Theory, Neural Networks,Statistics, Artificial Intelligence and Fuzzy Logic have more or less independently developed very similar modelling methods, calling them Local ModelNetworks, Operating......, and allows direct incorporation of high-level and qualitative plant knowledge into themodel. These advantages have proven to be very appealing for industrial applications, and the practical, intuitively appealing nature of the framework isdemonstrated in chapters describing applications of local methods...... to problems in the process industries, biomedical applications and autonomoussystems. The successful application of the ideas to demanding problems is already encouraging, but creative development of the basic framework isneeded to better allow the integration of human knowledge with automated learning...

  4. Multiple model cardinalized probability hypothesis density filter

    Science.gov (United States)

    Georgescu, Ramona; Willett, Peter

    2011-09-01

    The Probability Hypothesis Density (PHD) filter propagates the first-moment approximation to the multi-target Bayesian posterior distribution while the Cardinalized PHD (CPHD) filter propagates both the posterior likelihood of (an unlabeled) target state and the posterior probability mass function of the number of targets. Extensions of the PHD filter to the multiple model (MM) framework have been published and were implemented either with a Sequential Monte Carlo or a Gaussian Mixture approach. In this work, we introduce the multiple model version of the more elaborate CPHD filter. We present the derivation of the prediction and update steps of the MMCPHD particularized for the case of two target motion models and proceed to show that in the case of a single model, the new MMCPHD equations reduce to the original CPHD equations.

  5. An adaptive Multiplicative Extened Kalman Filter for Attitude Estimation of Marine Satellite Tracking Antenna

    DEFF Research Database (Denmark)

    Wang, Yunlong; Soltani, Mohsen; Hussain, Dil muhammed Akbar

    2016-01-01

    , an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves...

  6. Predictive performance models and multiple task performance

    Science.gov (United States)

    Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

    1989-01-01

    Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

  7. Single image super-resolution using locally adaptive multiple linear regression.

    Science.gov (United States)

    Yu, Soohwan; Kang, Wonseok; Ko, Seungyong; Paik, Joonki

    2015-12-01

    This paper presents a regularized superresolution (SR) reconstruction method using locally adaptive multiple linear regression to overcome the limitation of spatial resolution of digital images. In order to make the SR problem better-posed, the proposed method incorporates the locally adaptive multiple linear regression into the regularization process as a local prior. The local regularization prior assumes that the target high-resolution (HR) pixel is generated by a linear combination of similar pixels in differently scaled patches and optimum weight parameters. In addition, we adapt a modified version of the nonlocal means filter as a smoothness prior to utilize the patch redundancy. Experimental results show that the proposed algorithm better restores HR images than existing state-of-the-art methods in the sense of the most objective measures in the literature.

  8. 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.

  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. 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...

  11. Functional adaptation to loading of a single bone is neuronally regulated and involves multiple bones.

    Science.gov (United States)

    Sample, Susannah J; Behan, Mary; Smith, Lesley; Oldenhoff, William E; Markel, Mark D; Kalscheur, Vicki L; Hao, Zhengling; Miletic, Vjekoslav; Muir, Peter

    2008-09-01

    Regulation of load-induced bone formation is considered a local phenomenon controlled by osteocytes, although it has also been hypothesized that functional adaptation may be neuronally regulated. The aim of this study was to examine bone formation in multiple bones, in response to loading of a single bone, and to determine whether adaptation may be neuronally regulated. Load-induced responses in the left and right ulnas and humeri were determined after loading of the right ulna in male Sprague-Dawley rats (69 +/- 16 days of age). After a single period of loading at -760-, -2000-, or -3750-microepsilon initial peak strain, rats were given calcein to label new bone formation. Bone formation and bone neuropeptide concentrations were determined at 10 days. In one group, temporary neuronal blocking was achieved by perineural anesthesia of the brachial plexus with bupivicaine during loading. We found right ulna loading induces adaptive responses in other bones in both thoracic limbs compared with Sham controls and that neuronal blocking during loading abrogated bone formation in the loaded ulna and other thoracic limb bones. Skeletal adaptation was more evident in distal long bones compared with proximal long bones. We also found that the single period of loading modulated bone neuropeptide concentrations persistently for 10 days. We conclude that functional adaptation to loading of a single bone in young rapidly growing rats is neuronally regulated and involves multiple bones. Persistent changes in bone neuropeptide concentrations after a single loading period suggest that plasticity exists in the innervation of bone.

  12. 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.

  13. 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.

  14. 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.

  15. Towards Increased Relevance: Context-Adapted Models of the Learning Organization

    Science.gov (United States)

    Örtenblad, Anders

    2015-01-01

    Purpose: The purposes of this paper are to take a closer look at the relevance of the idea of the learning organization for organizations in different generalized organizational contexts; to open up for the existence of multiple, context-adapted models of the learning organization; and to suggest a number of such models.…

  16. Application of Multiple Evaluation Models in Brazil

    Directory of Open Access Journals (Sweden)

    Rafael Victal Saliba

    2008-07-01

    Full Text Available Based on two different samples, this article tests the performance of a number of Value Drivers commonly used for evaluating companies by finance practitioners, through simple regression models of cross-section type which estimate the parameters associated to each Value Driver, denominated Market Multiples. We are able to diagnose the behavior of several multiples in the period 1994-2004, with an outlook also on the particularities of the economic activities performed by the sample companies (and their impacts on the performance through a subsequent analysis with segregation of companies in the sample by sectors. Extrapolating simple multiples evaluation standards from analysts of the main financial institutions in Brazil, we find that adjusting the ratio formulation to allow for an intercept does not provide satisfactory results in terms of pricing errors reduction. Results found, in spite of evidencing certain relative and absolute superiority among the multiples, may not be generically representative, given samples limitation.

  17. Adaptation of Boynton's mathematical model to hydrogen isotope separation column by cryogenic distillation

    International Nuclear Information System (INIS)

    Kinoshita, Masahiro; Naruse, Yuji

    1981-08-01

    Boynton's mathematical simulation procedure for multi-component distillation calculations has the advantage that the Jacobian matrix is calculated analytically. The purpose of the present study is to adapt this procedure to hydrogen isotope separation columns by cryogenic distillation. The Boynton's model is modified so that the model can incorporate decay heat of tritium, nonideality of the hydrogen isotope solutions, multiple feeds and multiple sidestreams. Basic equations are derived and the mathematical simulation procedure is briefly explained. (author)

  18. 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...

  19. Multiple wall-reflection effect in adaptive-array differential-phase reflectometry on QUEST

    International Nuclear Information System (INIS)

    Idei, H.; Fujisawa, A.; Nagashima, Y.; Onchi, T.; Hanada, K.; Zushi, H.; Mishra, K.; Hamasaki, M.; Hayashi, Y.; Yamamoto, M.K.

    2016-01-01

    A phased array antenna and Software-Defined Radio (SDR) heterodyne-detection systems have been developed for adaptive array approaches in reflectometry on the QUEST. In the QUEST device considered as a large oversized cavity, standing wave (multiple wall-reflection) effect was significantly observed with distorted amplitude and phase evolution even if the adaptive array analyses were applied. The distorted fields were analyzed by Fast Fourier Transform (FFT) in wavenumber domain to treat separately the components with and without wall reflections. The differential phase evolution was properly obtained from the distorted field evolution by the FFT procedures. A frequency derivative method has been proposed to overcome the multiple-wall reflection effect, and SDR super-heterodyned components with small frequency difference for the derivative method were correctly obtained using the FFT analysis

  20. 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

  1. Feedback structure based entropy approach for multiple-model estimation

    Institute of Scientific and Technical Information of China (English)

    Shen-tu Han; Xue Anke; Guo Yunfei

    2013-01-01

    The variable-structure multiple-model (VSMM) approach, one of the multiple-model (MM) methods, is a popular and effective approach in handling problems with mode uncertainties. The model sequence set adaptation (MSA) is the key to design a better VSMM. However, MSA methods in the literature have big room to improve both theoretically and practically. To this end, we propose a feedback structure based entropy approach that could find the model sequence sets with the smallest size under certain conditions. The filtered data are fed back in real time and can be used by the minimum entropy (ME) based VSMM algorithms, i.e., MEVSMM. Firstly, the full Markov chains are used to achieve optimal solutions. Secondly, the myopic method together with particle filter (PF) and the challenge match algorithm are also used to achieve sub-optimal solutions, a trade-off between practicability and optimality. The numerical results show that the proposed algorithm provides not only refined model sets but also a good robustness margin and very high accuracy.

  2. 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)

  3. Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

    OpenAIRE

    Edy Legowo

    2017-01-01

    Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilita...

  4. 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...

  5. 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...

  6. 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...

  7. Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

    KAUST Repository

    Najibi, Seyed Morteza

    2017-02-08

    Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

  8. A multiple relevance feedback strategy with positive and negative models.

    Directory of Open Access Journals (Sweden)

    Yunlong Ma

    Full Text Available A commonly used strategy to improve search accuracy is through feedback techniques. Most existing work on feedback relies on positive information, and has been extensively studied in information retrieval. However, when a query topic is difficult and the results from the first-pass retrieval are very poor, it is impossible to extract enough useful terms from a few positive documents. Therefore, the positive feedback strategy is incapable to improve retrieval in this situation. Contrarily, there is a relatively large number of negative documents in the top of the result list, and it has been confirmed that negative feedback strategy is an important and useful way for adapting this scenario by several recent studies. In this paper, we consider a scenario when the search results are so poor that there are at most three relevant documents in the top twenty documents. Then, we conduct a novel study of multiple strategies for relevance feedback using both positive and negative examples from the first-pass retrieval to improve retrieval accuracy for such difficult queries. Experimental results on these TREC collections show that the proposed language model based multiple model feedback method which is generally more effective than both the baseline method and the methods using only positive or negative model.

  9. Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

    KAUST Repository

    Najibi, Seyed Morteza; Maadooliat, Mehdi; Zhou, Lan; Huang, Jianhua Z.; Gao, Xin

    2017-01-01

    Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

  10. 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

  11. 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...

  12. 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.

  13. A decision analysis approach to climate adaptation: comparing multiple pathways for multi-decadal decision making

    Science.gov (United States)

    Lin, B. B.; Little, L.

    2013-12-01

    Policy planners around the world are required to consider the implications of adapting to climatic change across spatial contexts and decadal timeframes. However, local level information for planning is often poorly defined, even though climate adaptation decision-making is made at this scale. This is especially true when considering sea level rise and coastal impacts of climate change. We present a simple approach using sea level rise simulations paired with adaptation scenarios to assess a range of adaptation options available to local councils dealing with issues of beach recession under present and future sea level rise and storm surge. Erosion and beach recession pose a large socioeconomic risk to coastal communities because of the loss of key coastal infrastructure. We examine the well-known adaptation technique of beach nourishment and assess various timings and amounts of beach nourishment at decadal time spans in relation to beach recession impacts. The objective was to identify an adaptation strategy that would allow for a low frequency of management interventions, the maintenance of beach width, and the ability to minimize variation in beach width over the 2010 to 2100 simulation period. 1000 replications of each adaptation option were produced against the 90 year simulation in order to model the ability each adaptation option to achieve the three key objectives. Three sets of adaptation scenarios were identified. Within each scenario, a number of adaptation options were tested. The three scenarios were: 1) Fixed periodic beach replenishment of specific amounts at 20 and 50 year intervals, 2) Beach replenishment to the initial beach width based on trigger levels of recession (5m, 10m, 20m), and 3) Fixed period beach replenishment of a variable amount at decadal intervals (every 10, 20, 30, 40, 50 years). For each adaptation option, we show the effectiveness of each beach replenishment scenario to maintain beach width and consider the implications of more

  14. Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

    Directory of Open Access Journals (Sweden)

    Edy Legowo

    2017-03-01

    Full Text Available Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilitasi guru dapat menstimulasi multiple intelligences siswa. Evaluasi hasil belajar siswa dari pandangan penerapan teori multiple intelligences seharusnya dilakukan menggunakan authentic assessment dan portofolio yang lebih memfasilitasi para siswa mengungkapkan atau mengaktualisasikan hasil belajarnya melalui berbagai cara sesuai dengan kekuatan jenis inteligensinya.

  15. Firing patterns in the adaptive exponential integrate-and-fire model.

    Science.gov (United States)

    Naud, Richard; Marcille, Nicolas; Clopath, Claudia; Gerstner, Wulfram

    2008-11-01

    For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulations.

  16. Multiple Temperature Model for Near Continuum Flows

    International Nuclear Information System (INIS)

    XU, Kun; Liu, Hongwei; Jiang, Jianzheng

    2007-01-01

    In the near continuum flow regime, the flow may have different translational temperatures in different directions. It is well known that for increasingly rarefied flow fields, the predictions from continuum formulation, such as the Navier-Stokes equations, lose accuracy. These inaccuracies may be partially due to the single temperature assumption in the Navier-Stokes equations. Here, based on the gas-kinetic Bhatnagar-Gross-Krook (BGK) equation, a multitranslational temperature model is proposed and used in the flow calculations. In order to fix all three translational temperatures, two constraints are additionally proposed to model the energy exchange in different directions. Based on the multiple temperature assumption, the Navier-Stokes relation between the stress and strain is replaced by the temperature relaxation term, and the Navier-Stokes assumption is recovered only in the limiting case when the flow is close to the equilibrium with the same temperature in different directions. In order to validate the current model, both the Couette and Poiseuille flows are studied in the transition flow regime

  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. 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 ...

  19. 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…

  20. 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.

  1. 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

  2. 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.

  3. The Multiple Use of Tropical Forests by Indigenous Peoples in Mexico: a Case of Adaptive Management

    Directory of Open Access Journals (Sweden)

    Víctor M. Toledo

    2003-12-01

    Full Text Available The quest for an appropriate system of management for tropical ecosystems necessitates that ecologists consider the accumulated experiences of indigenous peoples in their long-term management of local resources, a subject of current ethnoecology. This paper provides data and empirical evidence of an indigenous multiple-use strategy (MUS of tropical forest management existing in Mexico, that can be considered a case of adaptive management. This conclusion is based on the observation that some indigenous communities avoid common modernization routes toward specialized, unsustainable, and ecologically disruptive systems of production, and yet probably achieve the most successful tropical forest utilization design, in terms of biodiversity conservation, resilience, and sustainability. This analysis relies on an exhaustive review of the literature and the authors' field research. Apparently, this MUS represents an endogenous reaction of indigenous communities to the intensification of natural resource use, responding to technological, demographic, cultural, and economic changes in the contemporary world. This transforms traditional shifting cultivators into multiple-use strategists. Based on a case study, three main features (biodiversity, resilience, and permanence considered relevant to achieving adaptive and sustainable management of tropical ecosystems are discussed.

  4. A Context-Aware Adaptive Streaming Media Distribution System in a Heterogeneous Network with Multiple Terminals

    Directory of Open Access Journals (Sweden)

    Yepeng Ni

    2016-01-01

    Full Text Available We consider the problem of streaming media transmission in a heterogeneous network from a multisource server to home multiple terminals. In wired network, the transmission performance is limited by network state (e.g., the bandwidth variation, jitter, and packet loss. In wireless network, the multiple user terminals can cause bandwidth competition. Thus, the streaming media distribution in a heterogeneous network becomes a severe challenge which is critical for QoS guarantee. In this paper, we propose a context-aware adaptive streaming media distribution system (CAASS, which implements the context-aware module to perceive the environment parameters and use the strategy analysis (SA module to deduce the most suitable service level. This approach is able to improve the video quality for guarantying streaming QoS. We formulate the optimization problem of QoS relationship with the environment parameters based on the QoS testing algorithm for IPTV in ITU-T G.1070. We evaluate the performance of the proposed CAASS through 12 types of experimental environments using a prototype system. Experimental results show that CAASS can dynamically adjust the service level according to the environment variation (e.g., network state and terminal performances and outperforms the existing streaming approaches in adaptive streaming media distribution according to peak signal-to-noise ratio (PSNR.

  5. On decentralized adaptive full-order sliding mode control of multiple UAVs.

    Science.gov (United States)

    Xiang, Xianbo; Liu, Chao; Su, Housheng; Zhang, Qin

    2017-11-01

    In this study, a novel decentralized adaptive full-order sliding mode control framework is proposed for the robust synchronized formation motion of multiple unmanned aerial vehicles (UAVs) subject to system uncertainty. First, a full-order sliding mode surface in a decentralized manner is designed to incorporate both the individual position tracking error and the synchronized formation error while the UAV group is engaged in building a certain desired geometric pattern in three dimensional space. Second, a decentralized virtual plant controller is constructed which allows the embedded low-pass filter to attain the chattering free property of the sliding mode controller. In addition, robust adaptive technique is integrated in the decentralized chattering free sliding control design in order to handle unknown bounded uncertainties, without requirements for assuming a priori knowledge of bounds on the system uncertainties as stated in conventional chattering free control methods. Subsequently, system robustness as well as stability of the decentralized full-order sliding mode control of multiple UAVs is synthesized. Numerical simulation results illustrate the effectiveness of the proposed control framework to achieve robust 3D formation flight of the multi-UAV system. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Genre-adaptive Semantic Computing and Audio-based Modelling for Music Mood Annotation

    DEFF Research Database (Denmark)

    Saari, Pasi; Fazekas, György; Eerola, Tuomas

    2016-01-01

    This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling are prop......This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling...... related to a set of 600 popular music tracks spanning multiple genres. The results show that ACTwg outperforms a semantic computing technique that does not exploit genre information, and ACTwg-SLPwg outperforms conventional techniques and other genre-adaptive alternatives. In particular, improvements......-based genre representation for genre-adaptive music mood analysis....

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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...

  2. 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 ...

  3. 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.

  4. Multiple Scattering Model for Optical Coherence Tomography with Rytov Approximation

    KAUST Repository

    Li, Muxingzi

    2017-01-01

    of speckles due to multiple scatterers within the coherence length, and other random noise. Motivated by the above two challenges, a multiple scattering model based on Rytov approximation and Gaussian beam optics is proposed for the OCT setup. Some previous

  5. New perspective on single-radiator multiple-port antennas for adaptive beamforming applications.

    Science.gov (United States)

    Byun, Gangil; Choo, Hosung

    2017-01-01

    One of the most challenging problems in recent antenna engineering fields is to achieve highly reliable beamforming capabilities in an extremely restricted space of small handheld devices. In this paper, we introduce a new perspective on single-radiator multiple-port (SRMP) antenna to alter the traditional approach of multiple-antenna arrays for improving beamforming performances with reduced aperture sizes. The major contribution of this paper is to demonstrate the beamforming capability of the SRMP antenna for use as an extremely miniaturized front-end component in more sophisticated beamforming applications. To examine the beamforming capability, the radiation properties and the array factor of the SRMP antenna are theoretically formulated for electromagnetic characterization and are used as complex weights to form adaptive array patterns. Then, its fundamental performance limits are rigorously explored through enumerative studies by varying the dielectric constant of the substrate, and field tests are conducted using a beamforming hardware to confirm the feasibility. The results demonstrate that the new perspective of the SRMP antenna allows for improved beamforming performances with the ability of maintaining consistently smaller aperture sizes compared to the traditional multiple-antenna arrays.

  6. New perspective on single-radiator multiple-port antennas for adaptive beamforming applications.

    Directory of Open Access Journals (Sweden)

    Gangil Byun

    Full Text Available One of the most challenging problems in recent antenna engineering fields is to achieve highly reliable beamforming capabilities in an extremely restricted space of small handheld devices. In this paper, we introduce a new perspective on single-radiator multiple-port (SRMP antenna to alter the traditional approach of multiple-antenna arrays for improving beamforming performances with reduced aperture sizes. The major contribution of this paper is to demonstrate the beamforming capability of the SRMP antenna for use as an extremely miniaturized front-end component in more sophisticated beamforming applications. To examine the beamforming capability, the radiation properties and the array factor of the SRMP antenna are theoretically formulated for electromagnetic characterization and are used as complex weights to form adaptive array patterns. Then, its fundamental performance limits are rigorously explored through enumerative studies by varying the dielectric constant of the substrate, and field tests are conducted using a beamforming hardware to confirm the feasibility. The results demonstrate that the new perspective of the SRMP antenna allows for improved beamforming performances with the ability of maintaining consistently smaller aperture sizes compared to the traditional multiple-antenna arrays.

  7. 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.

  8. 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.

  9. 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

  10. 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,

  11. 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

  12. 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.

  13. 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.

  14. Testing for Nonuniform Differential Item Functioning with Multiple Indicator Multiple Cause Models

    Science.gov (United States)

    Woods, Carol M.; Grimm, Kevin J.

    2011-01-01

    In extant literature, multiple indicator multiple cause (MIMIC) models have been presented for identifying items that display uniform differential item functioning (DIF) only, not nonuniform DIF. This article addresses, for apparently the first time, the use of MIMIC models for testing both uniform and nonuniform DIF with categorical indicators. A…

  15. Multiplicity distributions in the dual parton model

    International Nuclear Information System (INIS)

    Batunin, A.V.; Tolstenkov, A.N.

    1985-01-01

    Multiplicity distributions are calculated by means of a new mechanism of production of hadrons in a string, which was proposed previously by the authors and takes into account explicitly the valence character of the ends of the string. It is shown that allowance for this greatly improves the description of the low-energy multiplicity distributions. At superhigh energies, the contribution of the ends of the strings becomes negligibly small, but in this case multi-Pomeron contributions must be taken into account

  16. Adaptive Control Design for Autonomous Operation of Multiple Energy Storage Systems in Power Smoothing Applications

    DEFF Research Database (Denmark)

    Meng, Lexuan; Dragicevic, Tomislav; Guerrero, Josep M.

    2018-01-01

    -pass-filter (HPF) structure. It generates the power reference according to the fluctuating power and provides a stabilization effect. The power and energy supplied by ESS are majorly configured by the cut-off frequency and gain of the HPF. Considering the operational limits on ESS state-of-charge (SoC), this paper...... proposes an adaptive cut-off frequency design method to realize communication-less and autonomous operation of a system with multiple distributed ESS. The experimental results demonstrate that the SoCs of all ESS units are kept within safe margins, while the SoC level and power of the paralleled units...... converge to the final state, providing a natural plug-and-play function....

  17. 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.

  18. Introduction to n-adaptive fuzzy models to analyze public opinion on AIDS

    CERN Document Server

    Kandasamy, D W B V; Kandasamy, Dr.W.B.Vasantha; Smarandache, Dr.Florentin

    2006-01-01

    There are many fuzzy models like Fuzzy matrices, Fuzzy Cognitive Maps, Fuzzy relational Maps, Fuzzy Associative Memories, Bidirectional Associative memories and so on. But almost all these models can give only one sided solution like hidden pattern or a resultant output vector dependent on the input vector depending in the problem at hand. So for the first time we have defined a n-adaptive fuzzy model which can view or analyze the problem in n ways (n >=2) Though we have defined these n- adaptive fuzzy models theorectically we are not in a position to get a n-adaptive fuzzy model for n > 2 for practical real world problems. The highlight of this model is its capacity to analyze the same problem in different ways thereby arriving at various solutions that mirror multiple perspectives. We have used the 2-adaptive fuzzy model having the two fuzzy models, fuzzy matrices model and BAMs viz. model to analyze the views of public about HIV/ AIDS disease, patient and the awareness program. This book has five chapters ...

  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. Combined therapy of interferon plus ribavirin promotes multiple adaptive solutions in hepatitis C virus.

    Science.gov (United States)

    Cuevas, José M; Torres-Puente, Manuela; Jiménez-Hernández, Nuria; Bracho, María A; García-Robles, Inmaculada; Carnicer, Fernando; Olmo, Juan Del; Ortega, Enrique; González-Candelas, Fernando; Moya, Andrés

    2009-04-01

    Hepatitis C virus (HCV) presents several regions involved potentially in evading antiviral treatment and host immune system. Two regions, known as PKR-BD and V3 domains, have been proposed to be involved in resistance to interferon. Additionally, hypervariable regions in the envelope E2 glycoprotein are also good candidates to participate in evasion from the immune system. In this study, we have used a cohort of 22 non-responder patients to combined therapy (interferon alpha-2a plus ribavirin) for which samples obtained just before initiation of therapy and after 6 or/and 12 months of treatment were available. A range of 25-100 clones per patient, genome region and time sample were obtained. The predominant amino acid sequences for each time sample and patient were determined. Next, the sequences of the PKR-BD and V3 domains and the hypervariable regions from different time samples were compared for each patient. The highest levels of variability were detected at the three hypervariable regions of the E2 protein and, to a lower extent, at the V3 domain of the NS5A protein. However, no clear patterns of adaptation to the host immune system or to antiviral treatment were detected. In summary, although high levels of variability are correlated to viral adaptive response, antiviral treatment does not seem to promote convergent adaptive changes. Consequently, other regions must be involved in evasion strategies likely based on a combination of multiple mechanisms, in which pools of changes along the HCV genome could confer viruses the ability to overcome strong selective pressures. (c) 2009 Wiley-Liss, Inc.

  1. Dynamics of habitat selection in birds: adaptive response to nest predation depends on multiple factors.

    Science.gov (United States)

    Devries, J H; Clark, R G; Armstrong, L M

    2018-05-01

    According to theory, habitat selection by organisms should reflect underlying habitat-specific fitness consequences and, in birds, reproductive success has a strong impact on population growth in many species. Understanding processes affecting habitat selection also is critically important for guiding conservation initiatives. Northern pintails (Anas acuta) are migratory, temperate-nesting birds that breed in greatest concentrations in the prairies of North America and their population remains below conservation goals. Habitat loss and changing land use practices may have decoupled formerly reliable fitness cues with respect to nest habitat choices. We used data from 62 waterfowl nesting study sites across prairie Canada (1997-2009) to examine nest survival, a primary fitness metric, at multiple scales, in combination with estimates of habitat selection (i.e., nests versus random points), to test for evidence of adaptive habitat choices. We used the same habitat covariates in both analyses. Pintail nest survival varied with nest initiation date, nest habitat, pintail breeding pair density, landscape composition and annual moisture. Selection of nesting habitat reflected patterns in nest survival in some cases, indicating adaptive selection, but strength of habitat selection varied seasonally and depended on population density and landscape composition. Adaptive selection was most evident late in the breeding season, at low breeding densities and in cropland-dominated landscapes. Strikingly, at high breeding density, habitat choice appears to become maladaptive relative to nest predation. At larger spatial scales, the relative availability of habitats with low versus high nest survival, and changing land use practices, may limit the reproductive potential of pintails.

  2. An adaptive optics multiplicity census of young stars in Upper Scorpius

    Energy Technology Data Exchange (ETDEWEB)

    Lafrenière, David [Département de Physique, Université de Montréal, C.P. 6128 Succ. Centre-Ville, Montréal, QC H3C 3J7 (Canada); Jayawardhana, Ray; Van Kerkwijk, Marten H. [Department of Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON M5S 3H4 (Canada); Brandeker, Alexis [Department of Astronomy, Stockholm University, SE-106 91 Stockholm (Sweden); Janson, Markus, E-mail: david@astro.umontreal.ca [Astrophysics Research Center, Queen' s University Belfast, BT7 1NN Belfast (United Kingdom)

    2014-04-10

    We present the results of a multiplicity survey of 91 stars spanning masses of ∼0.2-10 M {sub ☉} in the Upper Scorpius star-forming region, based on adaptive optics imaging with the Gemini North telescope. Our observations identified 29 binaries, 5 triples, and no higher order multiples. The corresponding raw multiplicity frequency is 0.37 ± 0.05. In the regime where our observations are complete—companion separations of 0.''1-5'' (∼15-800 AU) with magnitude limits ranging from K < 9.3 at 0.''1 to K < 15.8 at 5''—the multiplicity frequency is 0.27{sub −0.04}{sup +0.05}. For similar separations, the multiplicity frequency in Upper Scorpius is comparable to that in other dispersed star-forming regions, but is a factor of two to three higher than in denser star-forming regions or in the field. Our sample displays a constant multiplicity frequency as a function of stellar mass. Among our sample of binaries, we find that both wider (>100 AU) and higher-mass systems tend to have companions with lower companion-to-primary mass ratios. Three of the companions identified in our survey are unambiguously substellar and have estimated masses below 0.04 M {sub ☉} (two of them are new discoveries from this survey—1RXS J160929.1–210524b and HIP 78530B—although we have reported them separately in earlier papers). These three companions have projected orbital separations of 300-900 AU. Based on a statistical analysis factoring in sensitivity limits, we calculate an occurrence rate of 5-40 M {sub Jup} companions of ∼4.0% for orbital separations of 250-1000 AU, compared to <1.8% at smaller separations, suggesting that such companions are more frequent on wider orbits.

  3. Evolving Four Part Harmony Using a Multiple Worlds Model

    DEFF Research Database (Denmark)

    Scirea, Marco; Brown, Joseph Alexander

    2015-01-01

    This application of the Multiple Worlds Model examines a collaborative fitness model for generating four part harmonies. In this model we have multiple populations and the fitness of the individuals is based on the ability of a member from each population to work with the members of other...

  4. 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

  5. Explaining clinical behaviors using multiple theoretical models

    Directory of Open Access Journals (Sweden)

    Eccles Martin P

    2012-10-01

    the five surveys. For the predictor variables, the mean construct scores were above the mid-point on the scale with median values across the five behaviors generally being above four out of seven and the range being from 1.53 to 6.01. Across all of the theories, the highest proportion of the variance explained was always for intention and the lowest was for behavior. The Knowledge-Attitudes-Behavior Model performed poorly across all behaviors and dependent variables; CSSRM also performed poorly. For TPB, SCT, II, and LT across the five behaviors, we predicted median R2 of 25% to 42.6% for intention, 6.2% to 16% for behavioral simulation, and 2.4% to 6.3% for behavior. Conclusions We operationalized multiple theories measuring across five behaviors. Continuing challenges that emerge from our work are: better specification of behaviors, better operationalization of theories; how best to appropriately extend the range of theories; further assessment of the value of theories in different settings and groups; exploring the implications of these methods for the management of chronic diseases; and moving to experimental designs to allow an understanding of behavior change.

  6. Explaining clinical behaviors using multiple theoretical models.

    Science.gov (United States)

    Eccles, Martin P; Grimshaw, Jeremy M; MacLennan, Graeme; Bonetti, Debbie; Glidewell, Liz; Pitts, Nigel B; Steen, Nick; Thomas, Ruth; Walker, Anne; Johnston, Marie

    2012-10-17

    , the mean construct scores were above the mid-point on the scale with median values across the five behaviors generally being above four out of seven and the range being from 1.53 to 6.01. Across all of the theories, the highest proportion of the variance explained was always for intention and the lowest was for behavior. The Knowledge-Attitudes-Behavior Model performed poorly across all behaviors and dependent variables; CSSRM also performed poorly. For TPB, SCT, II, and LT across the five behaviors, we predicted median R2 of 25% to 42.6% for intention, 6.2% to 16% for behavioral simulation, and 2.4% to 6.3% for behavior. We operationalized multiple theories measuring across five behaviors. Continuing challenges that emerge from our work are: better specification of behaviors, better operationalization of theories; how best to appropriately extend the range of theories; further assessment of the value of theories in different settings and groups; exploring the implications of these methods for the management of chronic diseases; and moving to experimental designs to allow an understanding of behavior change.

  7. 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.

  8. 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)

  9. The Swedish version of the Acceptance of Chronic Health Conditions Scale for people with multiple sclerosis: Translation, cultural adaptation and psychometric properties.

    Science.gov (United States)

    Forslin, Mia; Kottorp, Anders; Kierkegaard, Marie; Johansson, Sverker

    2016-11-11

    To translate and culturally adapt the Acceptance of Chronic Health Conditions (ACHC) Scale for people with multiple sclerosis into Swedish, and to analyse the psychometric properties of the Swedish version. Ten people with multiple sclerosis participated in translation and cultural adaptation of the ACHC Scale; 148 people with multiple sclerosis were included in evaluation of the psychometric properties of the scale. Translation and cultural adaptation were carried out through translation and back-translation, by expert committee evaluation and pre-test with cognitive interviews in people with multiple sclerosis. The psychometric properties of the Swedish version were evaluated using Rasch analysis. The Swedish version of the ACHC Scale was an acceptable equivalent to the original version. Seven of the original 10 items fitted the Rasch model and demonstrated ability to separate between groups. A 5-item version, including 2 items and 3 super-items, demonstrated better psychometric properties, but lower ability to separate between groups. The Swedish version of the ACHC Scale with the original 10 items did not fit the Rasch model. Two solutions, either with 7 items (ACHC-7) or with 2 items and 3 super-items (ACHC-5), demonstrated acceptable psychometric properties. Use of the ACHC-5 Scale with super-items is recommended, since this solution adjusts for local dependency among items.

  10. 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.

  11. 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...

  12. Cooperative and Adaptive Network Coding for Gradient Based Routing in Wireless Sensor Networks with Multiple Sinks

    Directory of Open Access Journals (Sweden)

    M. E. Migabo

    2017-01-01

    Full Text Available Despite its low computational cost, the Gradient Based Routing (GBR broadcast of interest messages in Wireless Sensor Networks (WSNs causes significant packets duplications and unnecessary packets transmissions. This results in energy wastage, traffic load imbalance, high network traffic, and low throughput. Thanks to the emergence of fast and powerful processors, the development of efficient network coding strategies is expected to enable efficient packets aggregations and reduce packets retransmissions. For multiple sinks WSNs, the challenge consists of efficiently selecting a suitable network coding scheme. This article proposes a Cooperative and Adaptive Network Coding for GBR (CoAdNC-GBR technique which considers the network density as dynamically defined by the average number of neighbouring nodes, to efficiently aggregate interest messages. The aggregation is performed by means of linear combinations of random coefficients of a finite Galois Field of variable size GF(2S at each node and the decoding is performed by means of Gaussian elimination. The obtained results reveal that, by exploiting the cooperation of the multiple sinks, the CoAdNC-GBR not only improves the transmission reliability of links and lowers the number of transmissions and the propagation latency, but also enhances the energy efficiency of the network when compared to the GBR-network coding (GBR-NC techniques.

  13. A multiple objective test assembly approach for exposure control problems in Computerized Adaptive Testing

    Directory of Open Access Journals (Sweden)

    Theo J.H.M. Eggen

    2010-01-01

    Full Text Available Overexposure and underexposure of items in the bank are serious problems in operational computerized adaptive testing (CAT systems. These exposure problems might result in item compromise, or point at a waste of investments. The exposure control problem can be viewed as a test assembly problem with multiple objectives. Information in the test has to be maximized, item compromise has to be minimized, and pool usage has to be optimized. In this paper, a multiple objectives method is developed to deal with both types of exposure problems. In this method, exposure control parameters based on observed exposure rates are implemented as weights for the information in the item selection procedure. The method does not need time consuming simulation studies, and it can be implemented conditional on ability level. The method is compared with Sympson Hetter method for exposure control, with the Progressive method and with alphastratified testing. The results show that the method is successful in dealing with both kinds of exposure problems.

  14. 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

  15. 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.

  16. Integration of multiple, excess, backup, and expected covering models

    OpenAIRE

    M S Daskin; K Hogan; C ReVelle

    1988-01-01

    The concepts of multiple, excess, backup, and expected coverage are defined. Model formulations using these constructs are reviewed and contrasted to illustrate the relationships between them. Several new formulations are presented as is a new derivation of the expected covering model which indicates more clearly the relationship of the model to other multi-state covering models. An expected covering model with multiple time standards is also presented.

  17. 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...

  18. Multiple flood vulnerability assessment approach based on fuzzy comprehensive evaluation method and coordinated development degree model.

    Science.gov (United States)

    Yang, Weichao; Xu, Kui; Lian, Jijian; Bin, Lingling; Ma, Chao

    2018-05-01

    Flood is a serious challenge that increasingly affects the residents as well as policymakers. Flood vulnerability assessment is becoming gradually relevant in the world. The purpose of this study is to develop an approach to reveal the relationship between exposure, sensitivity and adaptive capacity for better flood vulnerability assessment, based on the fuzzy comprehensive evaluation method (FCEM) and coordinated development degree model (CDDM). The approach is organized into three parts: establishment of index system, assessment of exposure, sensitivity and adaptive capacity, and multiple flood vulnerability assessment. Hydrodynamic model and statistical data are employed for the establishment of index system; FCEM is used to evaluate exposure, sensitivity and adaptive capacity; and CDDM is applied to express the relationship of the three components of vulnerability. Six multiple flood vulnerability types and four levels are proposed to assess flood vulnerability from multiple perspectives. Then the approach is applied to assess the spatiality of flood vulnerability in Hainan's eastern area, China. Based on the results of multiple flood vulnerability, a decision-making process for rational allocation of limited resources is proposed and applied to the study area. The study shows that multiple flood vulnerability assessment can evaluate vulnerability more completely, and help decision makers learn more information about making decisions in a more comprehensive way. In summary, this study provides a new way for flood vulnerability assessment and disaster prevention decision. Copyright © 2018 Elsevier Ltd. All rights reserved.

  19. 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)

  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. 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.

  2. 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...

  3. 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....

  4. 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 $x_1, \\ldots, x_n$.

  5. Multiple Signaling Pathways Coordinately Regulate Forgetting of Olfactory Adaptation through Control of Sensory Responses in Caenorhabditis elegans.

    Science.gov (United States)

    Kitazono, Tomohiro; Hara-Kuge, Sayuri; Matsuda, Osamu; Inoue, Akitoshi; Fujiwara, Manabi; Ishihara, Takeshi

    2017-10-18

    Forgetting memories is important for animals to properly respond to continuously changing environments. To elucidate the mechanisms of forgetting, we used one of the behavioral plasticities of Caenorhabditis elegans hermaphrodite, olfactory adaptation to an attractive odorant, diacetyl, as a simple model of learning. In C. elegans, the TIR-1/JNK-1 pathway accelerates forgetting of olfactory adaptation by facilitating neural secretion from AWC sensory neurons. In this study, to identify the downstream effectors of the TIR-1/JNK-1 pathway, we conducted a genetic screen for suppressors of the gain-of-function mutant of tir-1 ( ok1052 ), which shows excessive forgetting. Our screening showed that three proteins-a membrane protein, MACO-1; a receptor tyrosine kinase, SCD-2; and its putative ligand, HEN-1-regulated forgetting downstream of the TIR-1/JNK-1 pathway. We further demonstrated that MACO-1 and SCD-2/HEN-1 functioned in parallel genetic pathways, and only MACO-1 regulated forgetting of olfactory adaptation to isoamyl alcohol, which is an attractive odorant sensed by different types of sensory neurons. In olfactory adaptation, odor-evoked Ca 2+ responses in olfactory neurons are attenuated by conditioning and recovered thereafter. A Ca 2+ imaging study revealed that this attenuation is sustained longer in maco-1 and scd-2 mutant animals than in wild-type animals like the TIR-1/JNK-1 pathway mutants. Furthermore, temporal silencing by histamine-gated chloride channels revealed that the neuronal activity of AWC neurons after conditioning is important for proper forgetting. We propose that distinct signaling pathways, each of which has a specific function, may coordinately and temporally regulate forgetting by controlling sensory responses. SIGNIFICANCE STATEMENT Active forgetting is an important process to understand the whole mechanisms of memories. Recent papers have reported that the noncell autonomous regulations are required for proper forgetting in

  6. 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.

  7. 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

  8. 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.

  9. Rotational Kinematics Model Based Adaptive Particle Filter for Robust Human Tracking in Thermal Omnidirectional Vision

    Directory of Open Access Journals (Sweden)

    Yazhe Tang

    2015-01-01

    Full Text Available This paper presents a novel surveillance system named thermal omnidirectional vision (TOV system which can work in total darkness with a wild field of view. Different to the conventional thermal vision sensor, the proposed vision system exhibits serious nonlinear distortion due to the effect of the quadratic mirror. To effectively model the inherent distortion of omnidirectional vision, an equivalent sphere projection is employed to adaptively calculate parameterized distorted neighborhood of an object in the image plane. With the equivalent projection based adaptive neighborhood calculation, a distortion-invariant gradient coding feature is proposed for thermal catadioptric vision. For robust tracking purpose, a rotational kinematic modeled adaptive particle filter is proposed based on the characteristic of omnidirectional vision, which can handle multiple movements effectively, including the rapid motions. Finally, the experiments are given to verify the performance of the proposed algorithm for human tracking in TOV system.

  10. Testing a multiple mediation model of Asian American college students' willingness to see a counselor.

    Science.gov (United States)

    Kim, Paul Youngbin; Park, Irene J K

    2009-07-01

    Adapting the theory of reasoned action, the present study examined help-seeking beliefs, attitudes, and intent among Asian American college students (N = 110). A multiple mediation model was tested to see if the relation between Asian values and willingness to see a counselor was mediated by attitudes toward seeking professional psychological help and subjective norm. A bootstrapping procedure was used to test the multiple mediation model. Results indicated that subjective norm was the sole significant mediator of the effect of Asian values on willingness to see a counselor. The findings highlight the importance of social influences on help-seeking intent among Asian American college students.

  11. A test for the parameters of multiple linear regression models ...

    African Journals Online (AJOL)

    A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...

  12. 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

  13. Medicare capitation model, functional status, and multiple comorbidities: model accuracy

    Science.gov (United States)

    Noyes, Katia; Liu, Hangsheng; Temkin-Greener, Helena

    2012-01-01

    Objective This study examined financial implications of CMS-Hierarchical Condition Categories (HCC) risk-adjustment model on Medicare payments for individuals with comorbid chronic conditions. Study Design The study used 1992-2000 data from the Medicare Current Beneficiary Survey and corresponding Medicare claims. The pairs of comorbidities were formed based on the prior evidence about possible synergy between these conditions and activities of daily living (ADL) deficiencies and included heart disease and cancer, lung disease and cancer, stroke and hypertension, stroke and arthritis, congestive heart failure (CHF) and osteoporosis, diabetes and coronary artery disease, CHF and dementia. Methods For each beneficiary, we calculated the actual Medicare cost ratio as the ratio of the individual’s annualized costs to the mean annual Medicare cost of all people in the study. The actual Medicare cost ratios, by ADLs, were compared to the HCC ratios under the CMS-HCC payment model. Using multivariate regression models, we tested whether having the identified pairs of comorbidities affects the accuracy of CMS-HCC model predictions. Results The CMS-HCC model underpredicted Medicare capitation payments for patients with hypertension, lung disease, congestive heart failure and dementia. The difference between the actual costs and predicted payments was partially explained by beneficiary functional status and less than optimal adjustment for these chronic conditions. Conclusions Information about beneficiary functional status should be incorporated in reimbursement models since underpaying providers for caring for population with multiple comorbidities may provide severe disincentives for managed care plans to enroll such individuals and to appropriately manage their complex and costly conditions. PMID:18837646

  14. Multiple linear combination (MLC) regression tests for common variants adapted to linkage disequilibrium structure.

    Science.gov (United States)

    Yoo, Yun Joo; Sun, Lei; Poirier, Julia G; Paterson, Andrew D; Bull, Shelley B

    2017-02-01

    By jointly analyzing multiple variants within a gene, instead of one at a time, gene-based multiple regression can improve power, robustness, and interpretation in genetic association analysis. We investigate multiple linear combination (MLC) test statistics for analysis of common variants under realistic trait models with linkage disequilibrium (LD) based on HapMap Asian haplotypes. MLC is a directional test that exploits LD structure in a gene to construct clusters of closely correlated variants recoded such that the majority of pairwise correlations are positive. It combines variant effects within the same cluster linearly, and aggregates cluster-specific effects in a quadratic sum of squares and cross-products, producing a test statistic with reduced degrees of freedom (df) equal to the number of clusters. By simulation studies of 1000 genes from across the genome, we demonstrate that MLC is a well-powered and robust choice among existing methods across a broad range of gene structures. Compared to minimum P-value, variance-component, and principal-component methods, the mean power of MLC is never much lower than that of other methods, and can be higher, particularly with multiple causal variants. Moreover, the variation in gene-specific MLC test size and power across 1000 genes is less than that of other methods, suggesting it is a complementary approach for discovery in genome-wide analysis. The cluster construction of the MLC test statistics helps reveal within-gene LD structure, allowing interpretation of clustered variants as haplotypic effects, while multiple regression helps to distinguish direct and indirect associations. © 2016 The Authors Genetic Epidemiology Published by Wiley Periodicals, Inc.

  15. 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.

  16. Multiple Scenario Generation of Subsurface Models

    DEFF Research Database (Denmark)

    Cordua, Knud Skou

    of information is obeyed such that no unknown assumptions and biases influence the solution to the inverse problem. This involves a definition of the probabilistically formulated inverse problem, a discussion about how prior models can be established based on statistical information from sample models...... of the probabilistic formulation of the inverse problem. This function is based on an uncertainty model that describes the uncertainties related to the observed data. In a similar way, a formulation of the prior probability distribution that takes into account uncertainties related to the sample model statistics...... similar to observation uncertainties. We refer to the effect of these approximations as modeling errors. Examples that show how the modeling error is estimated are provided. Moreover, it is shown how these effects can be taken into account in the formulation of the posterior probability distribution...

  17. 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.

  18. 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

  19. Multiple system modelling of waste management

    International Nuclear Information System (INIS)

    Eriksson, Ola; Bisaillon, Mattias

    2011-01-01

    Highlights: → Linking of models will provide a more complete, correct and credible picture of the systems. → The linking procedure is easy to perform and also leads to activation of project partners. → The simulation procedure is a bit more complicated and calls for the ability to run both models. - Abstract: Due to increased environmental awareness, planning and performance of waste management has become more and more complex. Therefore waste management has early been subject to different types of modelling. Another field with long experience of modelling and systems perspective is energy systems. The two modelling traditions have developed side by side, but so far there are very few attempts to combine them. Waste management systems can be linked together with energy systems through incineration plants. The models for waste management can be modelled on a quite detailed level whereas surrounding systems are modelled in a more simplistic way. This is a problem, as previous studies have shown that assumptions on the surrounding system often tend to be important for the conclusions. In this paper it is shown how two models, one for the district heating system (MARTES) and another one for the waste management system (ORWARE), can be linked together. The strengths and weaknesses with model linking are discussed when compared to simplistic assumptions on effects in the energy and waste management systems. It is concluded that the linking of models will provide a more complete, correct and credible picture of the consequences of different simultaneous changes in the systems. The linking procedure is easy to perform and also leads to activation of project partners. However, the simulation procedure is a bit more complicated and calls for the ability to run both models.

  20. Highly adaptable triple-negative breast cancer cells as a functional model for testing anticancer agents.

    Directory of Open Access Journals (Sweden)

    Balraj Singh

    Full Text Available A major obstacle in developing effective therapies against solid tumors stems from an inability to adequately model the rare subpopulation of panresistant cancer cells that may often drive the disease. We describe a strategy for optimally modeling highly abnormal and highly adaptable human triple-negative breast cancer cells, and evaluating therapies for their ability to eradicate such cells. To overcome the shortcomings often associated with cell culture models, we incorporated several features in our model including a selection of highly adaptable cancer cells based on their ability to survive a metabolic challenge. We have previously shown that metabolically adaptable cancer cells efficiently metastasize to multiple organs in nude mice. Here we show that the cancer cells modeled in our system feature an embryo-like gene expression and amplification of the fat mass and obesity associated gene FTO. We also provide evidence of upregulation of ZEB1 and downregulation of GRHL2 indicating increased epithelial to mesenchymal transition in metabolically adaptable cancer cells. Our results obtained with a variety of anticancer agents support the validity of the model of realistic panresistance and suggest that it could be used for developing anticancer agents that would overcome panresistance.

  1. Mean multiplicity in the Regge models with rising cross sections

    International Nuclear Information System (INIS)

    Chikovani, Z.E.; Kobylisky, N.A.; Martynov, E.S.

    1979-01-01

    Behaviour of the mean multiplicity and the total cross section σsub(t) of hadron-hadron interactions is considered in the framework of the Regge models at high energies. Generating function was plotted for models of dipole and froissaron, and the mean multiplicity and multiplicity moments were calculated. It is shown that approximately ln 2 S (energy square) in the dipole model, which is in good agreement with the experiment. It is also found that in various Regge models approximately σsub(t)lnS

  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. Discrete choice models with multiplicative error terms

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Bierlaire, Michel

    2009-01-01

    The conditional indirect utility of many random utility maximization (RUM) discrete choice models is specified as a sum of an index V depending on observables and an independent random term ε. In general, the universe of RUM consistent models is much larger, even fixing some specification of V due...

  4. An Adaptive Time-Spread Multiple-Access Policy for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Konstantinos Oikonomou

    2007-05-01

    Full Text Available Sensor networks require a simple and efficient medium access control policy achieving high system throughput with no or limited control overhead in order to increase the network lifetime by minimizing the energy consumed during transmission attempts. Time-spread multiple-access (TSMA policies that have been proposed for ad hoc network environments, can also be employed in sensor networks, since no control overhead is introduced. However, they do not take advantage of any cross-layer information in order to exploit the idiosyncrasies of the particular sensor network environment such as the presence of typically static nodes and a common destination for the forwarded data. An adaptive probabilistic TSMA-based policy, that is proposed and analyzed in this paper, exploits these idiosyncrasies and achieves higher system throughput than the existing TSMA-based policies without any need for extra control overhead. As it is analytically shown in this paper, the proposed policy always outperforms the existing TSMA-based policies, if certain parameter values are properly set; the analysis also provides for these proper values. It is also shown that the proposed policy is characterized by a certain convergence period and that high system throughput is achieved for long convergence periods. The claims and expectations of the provided analysis are supported by simulation results presented in this paper.

  5. Wheat multiple synthetic derivatives: a new source for heat stress tolerance adaptive traits

    Science.gov (United States)

    Elbashir, Awad Ahmed Elawad; Gorafi, Yasir Serag Alnor; Tahir, Izzat Sidahmed Ali; Kim, June-Sik; Tsujimoto, Hisashi

    2017-01-01

    Heat stress is detrimental to wheat (Triticum aestivum L.) productivity. In this study, we aimed to select heat-tolerant plants from a multiple synthetic derivatives (MSD) population and evaluate their agronomic and physiological traits. We selected six tolerant plants from the population with the background of the cultivar ‘Norin 61’ (N61) and established six MNH (MSD population of N61 selected as heat stress-tolerant) lines. We grew these lines with N61 in the field and growth chamber. In the field, we used optimum and late sowings to ensure plant exposure to heat. In the growth chamber, in addition to N61, we used the heat-tolerant cultivars ‘Gelenson’ and ‘Bacanora’. We confirmed that MNH2 and MNH5 lines acquired heat tolerance. These lines had higher photosynthesis and stomata conductance and exhibited no reduction in grain yield and biomass under heat stress compared to N61. We noticed that N61 had relatively good adaptability to heat stress. Our results indicate that the MSD population includes the diversity of Aegilops tauschii and is a promising resource to uncover useful quantitative traits derived from this wild species. Selected lines could be useful for heat stress tolerance breeding. PMID:28744178

  6. Idiopathic Pulmonary Fibrosis: The Association between the Adaptive Multiple Features Method and Fibrosis Outcomes.

    Science.gov (United States)

    Salisbury, Margaret L; Lynch, David A; van Beek, Edwin J R; Kazerooni, Ella A; Guo, Junfeng; Xia, Meng; Murray, Susan; Anstrom, Kevin J; Yow, Eric; Martinez, Fernando J; Hoffman, Eric A; Flaherty, Kevin R

    2017-04-01

    Adaptive multiple features method (AMFM) lung texture analysis software recognizes high-resolution computed tomography (HRCT) patterns. To evaluate AMFM and visual quantification of HRCT patterns and their relationship with disease progression in idiopathic pulmonary fibrosis. Patients with idiopathic pulmonary fibrosis in a clinical trial of prednisone, azathioprine, and N-acetylcysteine underwent HRCT at study start and finish. Proportion of lung occupied by ground glass, ground glass-reticular (GGR), honeycombing, emphysema, and normal lung densities were measured by AMFM and three radiologists, documenting baseline disease extent and postbaseline change. Disease progression includes composite mortality, hospitalization, and 10% FVC decline. Agreement between visual and AMFM measurements was moderate for GGR (Pearson's correlation r = 0.60, P fibrosis (as measured by GGR densities) is independently associated with elevated hazard for disease progression. Postbaseline change in AMFM-measured and visually measured GGR densities are modestly correlated with change in FVC. AMFM-measured fibrosis is an automated adjunct to existing prognostic markers and may allow for study enrichment with subjects at increased disease progression risk.

  7. Adaptation of a Counseling Intervention to Address Multiple Cancer Risk Factors among Overweight/Obese Latino Smokers

    Science.gov (United States)

    Castro, Yessenia; Fernández, Maria E.; Strong, Larkin L.; Stewart, Diana W.; Krasny, Sarah; Hernandez Robles, Eden; Heredia, Natalia; Spears, Claire A.; Correa-Fernández, Virmarie; Eakin, Elizabeth; Resnicow, Ken; Basen-Engquist, Karen; Wetter, David W.

    2015-01-01

    More than 60% of cancer-related deaths in the United States are attributable to tobacco use, poor nutrition, and physical inactivity, and these risk factors tend to cluster together. Thus, strategies for cancer risk reduction would benefit from addressing multiple health risk behaviors. We adapted an evidence-based intervention grounded in social…

  8. A comparison of the adaptations of strains of Lymantria dispar multiple nucleopolyhedrovirus to hosts from spatially isolated populations

    Science.gov (United States)

    V.V. Martemyanov; J.D. Podgwaite; I.A. Belousova; S.V. Pavlushin; J.M. Slavicek; O.A. Baturina; M.R. Kabilov; A.V. Ilyinykh

    2017-01-01

    The adaptation of pathogens to either their hosts or to environmental conditions is the focus of many current ecological studies. In this work we compared the ability of six spatially-distant Lymantria dispar (gypsy moth) multiple nucleopolyhedrovirus (LdMNPV) strains (three from eastern North America and three from central Asia) to induce acute...

  9. 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 ...

  10. Structural model analysis of multiple quantitative traits.

    Directory of Open Access Journals (Sweden)

    Renhua Li

    2006-07-01

    Full Text Available We introduce a method for the analysis of multilocus, multitrait genetic data that provides an intuitive and precise characterization of genetic architecture. We show that it is possible to infer the magnitude and direction of causal relationships among multiple correlated phenotypes and illustrate the technique using body composition and bone density data from mouse intercross populations. Using these techniques we are able to distinguish genetic loci that affect adiposity from those that affect overall body size and thus reveal a shortcoming of standardized measures such as body mass index that are widely used in obesity research. The identification of causal networks sheds light on the nature of genetic heterogeneity and pleiotropy in complex genetic systems.

  11. Testing the Nanoparticle-Allostatic Cross Adaptation-Sensitization Model for Homeopathic Remedy Effects

    Science.gov (United States)

    Bell, Iris R.; Koithan, Mary; Brooks, Audrey J.

    2012-01-01

    Key concepts of the Nanoparticle-Allostatic Cross-Adaptation-Sensitization (NPCAS) Model for the action of homeopathic remedies in living systems include source nanoparticles as low level environmental stressors, heterotypic hormesis, cross-adaptation, allostasis (stress response network), time-dependent sensitization with endogenous amplification and bidirectional change, and self-organizing complex adaptive systems. The model accommodates the requirement for measurable physical agents in the remedy (source nanoparticles and/or source adsorbed to silica nanoparticles). Hormetic adaptive responses in the organism, triggered by nanoparticles; bipolar, metaplastic change, dependent on the history of the organism. Clinical matching of the patient’s symptom picture, including modalities, to the symptom pattern that the source material can cause (cross-adaptation and cross-sensitization). Evidence for nanoparticle-related quantum macro-entanglement in homeopathic pathogenetic trials. This paper examines research implications of the model, discussing the following hypotheses: Variability in nanoparticle size, morphology, and aggregation affects remedy properties and reproducibility of findings. Homeopathic remedies modulate adaptive allostatic responses, with multiple dynamic short- and long-term effects. Simillimum remedy nanoparticles, as novel mild stressors corresponding to the organism’s dysfunction initiate time-dependent cross-sensitization, reversing the direction of dysfunctional reactivity to environmental stressors. The NPCAS model suggests a way forward for systematic research on homeopathy. The central proposition is that homeopathic treatment is a form of nanomedicine acting by modulation of endogenous adaptation and metaplastic amplification processes in the organism to enhance long-term systemic resilience and health. PMID:23290882

  12. Multiple-lesion track-structure model

    International Nuclear Information System (INIS)

    Wilson, J.W.; Cucinotta, F.A.; Shinn, J.L.

    1992-03-01

    A multilesion cell kinetic model is derived, and radiation kinetic coefficients are related to the Katz track structure model. The repair-related coefficients are determined from the delayed plating experiments of Yang et al. for the C3H10T1/2 cell system. The model agrees well with the x ray and heavy ion experiments of Yang et al. for the immediate plating, delaying plating, and fractionated exposure protocols employed by Yang. A study is made of the effects of target fragments in energetic proton exposures and of the repair-deficient target-fragment-induced lesions

  13. 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.

  14. 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

  15. A chimera grid scheme. [multiple overset body-conforming mesh system for finite difference adaptation to complex aircraft configurations

    Science.gov (United States)

    Steger, J. L.; Dougherty, F. C.; Benek, J. A.

    1983-01-01

    A mesh system composed of multiple overset body-conforming grids is described for adapting finite-difference procedures to complex aircraft configurations. In this so-called 'chimera mesh,' a major grid is generated about a main component of the configuration and overset minor grids are used to resolve all other features. Methods for connecting overset multiple grids and modifications of flow-simulation algorithms are discussed. Computational tests in two dimensions indicate that the use of multiple overset grids can simplify the task of grid generation without an adverse effect on flow-field algorithms and computer code complexity.

  16. Affine LIBOR Models with Multiple Curves

    DEFF Research Database (Denmark)

    Grbac, Zorana; Papapantoleon, Antonis; Schoenmakers, John

    2015-01-01

    are specified following the methodology of the affine LIBOR models and are driven by the wide and flexible class of affine processes. The affine property is preserved under forward measures, which allows us to derive Fourier pricing formulas for caps, swaptions, and basis swaptions. A model specification...... with dependent LIBOR rates is developed that allows for an efficient and accurate calibration to a system of caplet prices....

  17. 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

  18. Applying the ADAPT Psychosocial Model to War-Affected Children and Adolescents

    Directory of Open Access Journals (Sweden)

    Sophie Yohani

    2015-09-01

    Full Text Available Multiple individual, social, and environmental factors have long been recognized as influencing a child’s response to traumatic experiences. However, there remain few socio-ecological frameworks to guide researchers and practitioners working with war-affected children. This article examines Silove’s psychosocial model of adaptation and development after trauma and persecution (ADAPT model in relation to war-affected children. The utility of the model is explored by examining whether the systems of safety, attachment, identity, justice, and existential meaning described in the ADAPT model are represented in a narrative review of research from the last 20 years on the experiences of war-affected children and adolescents. Results suggest that research with war-affected children has covered all five psychosocial pillars in the model, but with overemphasis on the safety, followed by the attachment, domains. This review highlights that need for research and psychosocial interventions that focus on adaptation of war-affected children’s identity development, sense of justice, and meaning systems.

  19. 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

  20. 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.…

  1. 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…

  2. 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 ...

  3. Cystic fibrosis-niche adaptation of Pseudomonas aeruginosa reduces virulence in multiple infection hosts.

    Directory of Open Access Journals (Sweden)

    Nicola Ivan Lorè

    Full Text Available The opportunistic pathogen Pseudomonas aeruginosa is able to thrive in diverse ecological niches and to cause serious human infection. P. aeruginosa environmental strains are producing various virulence factors that are required for establishing acute infections in several host organisms; however, the P. aeruginosa phenotypic variants favour long-term persistence in the cystic fibrosis (CF airways. Whether P. aeruginosa strains, which have adapted to the CF-niche, have lost their competitive fitness in the other environment remains to be investigated. In this paper, three P. aeruginosa clonal lineages, including early strains isolated at the onset of infection, and late strains, isolated after several years of chronic lung infection from patients with CF, were analysed in multi-host model systems of acute infection. P. aeruginosa early isolates caused lethality in the three non-mammalian hosts, namely Caenorhabditis elegans, Galleria mellonella, and Drosophila melanogaster, while late adapted clonal isolates were attenuated in acute virulence. When two different mouse genetic background strains, namely C57Bl/6NCrl and Balb/cAnNCrl, were used as acute infection models, early P. aeruginosa CF isolates were lethal, while late isolates exhibited reduced or abolished acute virulence. Severe histopathological lesions, including high leukocytes recruitment and bacterial load, were detected in the lungs of mice infected with P. aeruginosa CF early isolates, while late isolates were progressively cleared. In addition, systemic bacterial spread and invasion of epithelial cells, which were detected for P. aeruginosa CF early strains, were not observed with late strains. Our findings indicate that niche-specific selection in P. aeruginosa reduced its ability to cause acute infections across a broad range of hosts while maintaining the capacity for chronic infection in the CF host.

  4. SDG and qualitative trend based model multiple scale validation

    Science.gov (United States)

    Gao, Dong; Xu, Xin; Yin, Jianjin; Zhang, Hongyu; Zhang, Beike

    2017-09-01

    Verification, Validation and Accreditation (VV&A) is key technology of simulation and modelling. For the traditional model validation methods, the completeness is weak; it is carried out in one scale; it depends on human experience. The SDG (Signed Directed Graph) and qualitative trend based multiple scale validation is proposed. First the SDG model is built and qualitative trends are added to the model. And then complete testing scenarios are produced by positive inference. The multiple scale validation is carried out by comparing the testing scenarios with outputs of simulation model in different scales. Finally, the effectiveness is proved by carrying out validation for a reactor model.

  5. Modelling of rate effects at multiple scales

    DEFF Research Database (Denmark)

    Pedersen, R.R.; Simone, A.; Sluys, L. J.

    2008-01-01

    , the length scale in the meso-model and the macro-model can be coupled. In this fashion, a bridging of length scales can be established. A computational analysis of  a Split Hopkinson bar test at medium and high impact load is carried out at macro-scale and meso-scale including information from  the micro-scale.......At the macro- and meso-scales a rate dependent constitutive model is used in which visco-elasticity is coupled to visco-plasticity and damage. A viscous length scale effect is introduced to control the size of the fracture process zone. By comparison of the widths of the fracture process zone...

  6. 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.

  7. 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.

  8. Meeting multiple demands: Water transaction opportunities for environmental benefits promoting adaptation to climate change

    Science.gov (United States)

    McCoy, Amy

    2015-04-01

    In arid regions, the challenge of balancing water use among a diversity of sectors expands in lock step with conditions of water stress that are exacerbated by climate variability, prolonged drought, and growing water-use demands. The elusiveness of achieving a sustainable balance under conditions of environmental change in the southwestern United States is evidenced by reductions in both overall water availability and freshwater ecosystem health, as well as by recent projections of shortages on the Colorado River within the next five years. The water sustainability challenge in this region, as well as drylands throughout the world, can therefore be viewed through the lens of water stress, a condition wherein demands on land and water -- including the needs of freshwater ecosystems -- exceed reliable supplies, and the full range of water needs cannot be met without tradeoffs across multiple uses. Water stress influences not only ecosystems, but a region's economy, land management, quality of life, and cultural heritage -- each of which requires water to thrive. With respect to promoting successful adaptation to climate change, achieving full water sustainability would allow for water to be successfully divided among water users -- including municipalities, agriculture, and freshwater ecosystems -- at a level that meets the goals of water users and the governing body. Over the last ten to fifteen years, the use of transactional approaches in the western U.S., Mexico, and Australia has proven to be a viable management tool for achieving stream flow and shallow aquifer restoration. By broad definition, environmental water transactions are an equitable and adaptable tool that brings diverse stakeholders to the table to facilitate a fair-market exchange of rights to use water in a manner that benefits both water users and the environment. This talk will present a basic framework of necessary stakeholder engagement, hydrologic conditions, enabling laws and policies

  9. 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.

  10. New experimental model of multiple myeloma.

    Science.gov (United States)

    Telegin, G B; Kalinina, A R; Ponomarenko, N A; Ovsepyan, A A; Smirnov, S V; Tsybenko, V V; Homeriki, S G

    2001-06-01

    NSO/1 (P3x63Ay 8Ut) and SP20 myeloma cells were inoculated to BALB/c OlaHsd mice. NSO/1 cells allowed adequate stage-by-stage monitoring of tumor development. The adequacy of this model was confirmed in experiments with conventional cytostatics: prospidium and cytarabine caused necrosis of tumor cells and reduced animal mortality.

  11. Animal model of human disease. Multiple myeloma

    NARCIS (Netherlands)

    Radl, J.; Croese, J.W.; Zurcher, C.; Enden-Vieveen, M.H.M. van den; Leeuw, A.M. de

    1988-01-01

    Animal models of spontaneous and induced plasmacytomas in some inbred strains of mice have proven to be useful tools for different studies on tumorigenesis and immunoregulation. Their wide applicability and the fact that after their intravenous transplantation, the recipient mice developed bone

  12. 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

  13. 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 ...

  14. Multiple Social Networks, Data Models and Measures for

    DEFF Research Database (Denmark)

    Magnani, Matteo; Rossi, Luca

    2017-01-01

    Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...

  15. Modeling Rabbit Responses to Single and Multiple Aerosol ...

    Science.gov (United States)

    Journal Article Survival models are developed here to predict response and time-to-response for mortality in rabbits following exposures to single or multiple aerosol doses of Bacillus anthracis spores. Hazard function models were developed for a multiple dose dataset to predict the probability of death through specifying dose-response functions and the time between exposure and the time-to-death (TTD). Among the models developed, the best-fitting survival model (baseline model) has an exponential dose-response model with a Weibull TTD distribution. Alternative models assessed employ different underlying dose-response functions and use the assumption that, in a multiple dose scenario, earlier doses affect the hazard functions of each subsequent dose. In addition, published mechanistic models are analyzed and compared with models developed in this paper. None of the alternative models that were assessed provided a statistically significant improvement in fit over the baseline model. The general approach utilizes simple empirical data analysis to develop parsimonious models with limited reliance on mechanistic assumptions. The baseline model predicts TTDs consistent with reported results from three independent high-dose rabbit datasets. More accurate survival models depend upon future development of dose-response datasets specifically designed to assess potential multiple dose effects on response and time-to-response. The process used in this paper to dev

  16. 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.

  17. Explaining clinical behaviors using multiple theoretical models

    OpenAIRE

    Eccles, Martin P; Grimshaw, Jeremy M; MacLennan, Graeme; Bonetti, Debbie; Glidewell, Liz; Pitts, Nigel B; Steen, Nick; Thomas, Ruth; Walker, Anne; Johnston, Marie

    2012-01-01

    Abstract Background In the field of implementation research, there is an increased interest in use of theory when designing implementation research studies involving behavior change. In 2003, we initiated a series of five studies to establish a scientific rationale for interventions to translate research findings into clinical practice by exploring the performance of a number of different, commonly used, overlapping behavioral theories and models. We reflect on the strengths and weaknesses of...

  18. Airport choice model in multiple airport regions

    Directory of Open Access Journals (Sweden)

    Claudia Muñoz

    2017-02-01

    Full Text Available Purpose: This study aims to analyze travel choices made by air transportation users in multi airport regions because it is a crucial component when planning passenger redistribution policies. The purpose of this study is to find a utility function which makes it possible to know the variables that influence users’ choice of the airports on routes to the main cities in the Colombian territory. Design/methodology/approach: This research generates a Multinomial Logit Model (MNL, which is based on the theory of maximizing utility, and it is based on the data obtained on revealed and stated preference surveys applied to users who reside in the metropolitan area of Aburrá Valley (Colombia. This zone is the only one in the Colombian territory which has two neighboring airports for domestic flights. The airports included in the modeling process were Enrique Olaya Herrera (EOH Airport and José María Córdova (JMC Airport. Several structure models were tested, and the MNL proved to be the most significant revealing the common variables that affect passenger airport choice include the airfare, the price to travel the airport, and the time to get to the airport. Findings and Originality/value: The airport choice model which was calibrated corresponds to a valid powerful tool used to calculate the probability of each analyzed airport of being chosen for domestic flights in the Colombian territory. This is done bearing in mind specific characteristic of each of the attributes contained in the utility function. In addition, these probabilities will be used to calculate future market shares of the two airports considered in this study, and this will be done generating a support tool for airport and airline marketing policies.

  19. Multiple simultaneous event model for radiation carcinogenesis

    International Nuclear Information System (INIS)

    Baum, J.W.

    1976-01-01

    A mathematical model is proposed which postulates that cancer induction is a multi-event process, that these events occur naturally, usually one at a time in any cell, and that radiation frequently causes two of these events to occur simultaneously. Microdosimetric considerations dictate that for high LET radiations the simultaneous events are associated with a single particle or track. The model predicts: (a) linear dose-effect relations for early times after irradiation with small doses, (b) approximate power functions of dose (i.e. Dsup(x)) having exponent less than one for populations of mixed age examined at short times after irradiation with small doses, (c) saturation of effect at either long times after irradiation with small doses or for all times after irradiation with large doses, and (d) a net increase in incidence which is dependent on age of observation but independent of age at irradiation. Data of Vogel, for neutron induced mammary tumors in rats, are used to illustrate the validity of the formulation. This model provides a quantitative framework to explain several unexpected results obtained by Vogel. It also provides a logical framework to explain the dose-effect relations observed in the Japanese survivors of the atomic bombs. (author)

  20. 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.

  1. Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention.

    Directory of Open Access Journals (Sweden)

    Cécile Aenishaenslin

    Full Text Available Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or

  2. Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention.

    Science.gov (United States)

    Aenishaenslin, Cécile; Gern, Lise; Michel, Pascal; Ravel, André; Hongoh, Valérie; Waaub, Jean-Philippe; Milord, François; Bélanger, Denise

    2015-01-01

    Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector

  3. 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.

  4. Multiple Imputation of Predictor Variables Using Generalized Additive Models

    NARCIS (Netherlands)

    de Jong, Roel; van Buuren, Stef; Spiess, Martin

    2016-01-01

    The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The

  5. 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.

  6. Predictive analytics of environmental adaptability in multi-omic network models.

    Science.gov (United States)

    Angione, Claudio; Lió, Pietro

    2015-10-20

    Bacterial phenotypic traits and lifestyles in response to diverse environmental conditions depend on changes in the internal molecular environment. However, predicting bacterial adaptability is still difficult outside of laboratory controlled conditions. Many molecular levels can contribute to the adaptation to a changing environment: pathway structure, codon usage, metabolism. To measure adaptability to changing environmental conditions and over time, we develop a multi-omic model of Escherichia coli that accounts for metabolism, gene expression and codon usage at both transcription and translation levels. After the integration of multiple omics into the model, we propose a multiobjective optimization algorithm to find the allowable and optimal metabolic phenotypes through concurrent maximization or minimization of multiple metabolic markers. In the condition space, we propose Pareto hypervolume and spectral analysis as estimators of short term multi-omic (transcriptomic and metabolic) evolution, thus enabling comparative analysis of metabolic conditions. We therefore compare, evaluate and cluster different experimental conditions, models and bacterial strains according to their metabolic response in a multidimensional objective space, rather than in the original space of microarray data. We finally validate our methods on a phenomics dataset of growth conditions. Our framework, named METRADE, is freely available as a MATLAB toolbox.

  7. Maximizing effectiveness of adaptation action in Pacific Island communities using coastal wave attenuation models

    Science.gov (United States)

    Jung, H.; Carruthers, T.; Allison, M. A.; Weathers, D.; Moss, L.; Timmermans, H.

    2017-12-01

    Pacific Island communities are highly vulnerable to the effects of climate change, specifically accelerating rates of sea level rise, changes to storm intensity and associated rainfall patterns resulting in flooding and shoreline erosion. Nature-based adaptation is being planned not only to reduce the risk from shoreline erosion, but also to support benefits of a healthy ecosystem (e.g., supporting fisheries or coral reefs). In order to assess potential effectiveness of the nature-based actions to dissipate wave energy, two-dimensional X-Beach models were developed to predict the wave attenuation effect of coastal adaptation actions at the pilot sites—the villages of Naselesele and Somosomo on Taveuni island, Fiji. Both sites are experiencing serious shoreline erosion due to sea level rise and storm wave. The water depth (single-beam bathymetry), land elevation (truck-based LiDAR), and vegetation data including stem density and height were collected in both locations in a June 2017 field experiment. Wave height and water velocity were also measured for the model setup and calibration using a series of bottom-mounted instruments deployed in the 0-15 m water depth portions of the study grid. The calibrated model will be used to evaluate a range of possible adaptation actions identified by the community members of Naselesele and Somosomo. Particularly, multiple storm scenario runs with management-relevant shoreline restoration/adaptation options will be implemented to evaluate efficiencies of each adaptation action (e.g., no action, with additional planted trees, with sand mining, with seawalls constructed with natural materials, etc.). These model results will help to better understand how proposed adaption actions may influence future shoreline change and maximize benefits to communities in island nations across the SW Pacific.

  8. Entrepreneurial intention modeling using hierarchical multiple regression

    Directory of Open Access Journals (Sweden)

    Marina Jeger

    2014-12-01

    Full Text Available The goal of this study is to identify the contribution of effectuation dimensions to the predictive power of the entrepreneurial intention model over and above that which can be accounted for by other predictors selected and confirmed in previous studies. As is often the case in social and behavioral studies, some variables are likely to be highly correlated with each other. Therefore, the relative amount of variance in the criterion variable explained by each of the predictors depends on several factors such as the order of variable entry and sample specifics. The results show the modest predictive power of two dimensions of effectuation prior to the introduction of the theory of planned behavior elements. The article highlights the main advantages of applying hierarchical regression in social sciences as well as in the specific context of entrepreneurial intention formation, and addresses some of the potential pitfalls that this type of analysis entails.

  9. Multiple Time Series Ising Model for Financial Market Simulations

    International Nuclear Information System (INIS)

    Takaishi, Tetsuya

    2015-01-01

    In this paper we propose an Ising model which simulates multiple financial time series. Our model introduces the interaction which couples to spins of other systems. Simulations from our model show that time series exhibit the volatility clustering that is often observed in the real financial markets. Furthermore we also find non-zero cross correlations between the volatilities from our model. Thus our model can simulate stock markets where volatilities of stocks are mutually correlated

  10. 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

  11. 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...

  12. 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.

  13. 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)

  14. 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.

  15. 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.

  16. Model-on-Demand Predictive Control for Nonlinear Hybrid Systems With Application to Adaptive Behavioral Interventions

    Science.gov (United States)

    Nandola, Naresh N.; Rivera, Daniel E.

    2011-01-01

    This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem because model parameters depend on the mode or operating point of the system. The proposed algorithm applies Model-on-Demand (MoD) estimation to generate a local linear approximation of the nonlinear hybrid system at each time step, using a small subset of data selected by an adaptive bandwidth selector. The appeal of the MoD approach lies in the fact that model parameters are estimated based on a current operating point; hence estimation of locations or modes governed by autonomous discrete events is achieved automatically. The local MoD model is then converted into a mixed logical dynamical (MLD) system representation which can be used directly in a model predictive control (MPC) law for hybrid systems using multiple-degree-of-freedom tuning. The effectiveness of the proposed MoD predictive control algorithm for nonlinear hybrid systems is demonstrated on a hypothetical adaptive behavioral intervention problem inspired by Fast Track, a real-life preventive intervention for improving parental function and reducing conduct disorder in at-risk children. Simulation results demonstrate that the proposed algorithm can be useful for adaptive intervention problems exhibiting both nonlinear and hybrid character. PMID:21874087

  17. Kathoey, un genre multiple Kathoey, Multiple Gender : Identity Adaptation and Negotiation Process among Thai MTF Transsexuals in Thailand

    Directory of Open Access Journals (Sweden)

    Cheera Thongkrajai

    2010-07-01

    Full Text Available Les kathoey, transgenres et transsexuels Male-to-Female thaïlandais s’adaptent pour trouver le rôle ou la présentation identitaire convenant aux contextes et aux interactions auxquels elles doivent faire face. Elles peuvent adopter une apparence ou un rôle plus masculin lorsque la situation dans laquelle elles se trouvent ne leur permet pas d’affirmer leur féminité ou que celle-ci pourrait leur nuire socialement. Elles peuvent également accentuer leur féminité pour exprimer leur sentiment identitaire. Les kathoey négocient leur place en faisant preuve de leurs qualités personnelles et de leurs compétences et en mettant également en évidence leurs autres privilèges : statut socio-économique, beauté, etc. pour gagner une reconnaissance sociale. Malgré leur marginalité due à leur différence de genre, elles tentent de s’intégrer dans leurs milieux sociaux en adaptant leur image identitaire, en assumant leurs responsabilités et en réussissant leur vie familiale et professionnelle.Thai male-to-female transsexuals, “kathoey” adapt themselves and adjust their roles and their physical identity i.e., their appearances to different interactional situations. They can adopt their appearance and play masculine roles in the situation in which revealing femininity would be inacceptable or would cause them problem socially. Occasionally, in some situations, they can do the opposite by showing off their femininity they confirm to others who they really are. Kathoey negotiate their identity and their social position by proving and emphasizing on their personal qualities, capacities and others privileges such as social and economical status, beauty, professional competency etc. to gain social acceptation and admiration. Even though they have been marginalized by the society, they tend to reintegrate themselves in their social environment by using different strategies of such as personal identities, showing of their professional

  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. Multi-view 3D human pose estimation combining single-frame recovery, temporal integration and model adaptation

    NARCIS (Netherlands)

    Hofmann, K.M.; Gavrilla, D.M.

    2009-01-01

    We present a system for the estimation of unconstrained 3D human upper body movement from multiple cameras. Its main novelty lies in the integration of three components: single frame pose recovery, temporal integration and model adaptation. Single frame pose recovery consists of a hypothesis

  20. Career Adaptability Development in Adolescence: Multiple Predictors and Effect on Sense of Power and Life Satisfaction

    Science.gov (United States)

    Hirschi, Andreas

    2009-01-01

    This longitudinal panel study investigated predictors of career adaptability development and its effect on development of sense of power and experience of life satisfaction among 330 Swiss eighth graders. A multivariate measure of career adaptability consisting of career choice readiness, planning, exploration, and confidence was applied. Based on…

  1. 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.

  2. Nonlinear adaptive synchronization rule for identification of a large amount of parameters in dynamical models

    International Nuclear Information System (INIS)

    Ma Huanfei; Lin Wei

    2009-01-01

    The existing adaptive synchronization technique based on the stability theory and invariance principle of dynamical systems, though theoretically proved to be valid for parameters identification in specific models, is always showing slow convergence rate and even failed in practice when the number of parameters becomes large. Here, for parameters update, a novel nonlinear adaptive rule is proposed to accelerate the rate. Its feasibility is validated by analytical arguments as well as by specific parameters identification in the Lotka-Volterra model with multiple species. Two adjustable factors in this rule influence the identification accuracy, which means that a proper choice of these factors leads to an optimal performance of this rule. In addition, a feasible method for avoiding the occurrence of the approximate linear dependence among terms with parameters on the synchronized manifold is also proposed.

  3. Hybrid models for the simulation of microstructural evolution influenced by coupled, multiple physical processes

    Energy Technology Data Exchange (ETDEWEB)

    Tikare, Veena [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hernandez-Rivera, Efrain [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Madison, Jonathan D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Holm, Elizabeth Ann [Carnegie Mellon Univ., Pittsburgh, PA (United States); Patterson, Burton R. [Univ. of Florida, Gainesville, FL (United States). Dept. of Materials Science and Engineering; Homer, Eric R. [Brigham Young Univ., Provo, UT (United States). Dept. of Mechanical Engineering

    2013-09-01

    Most materials microstructural evolution processes progress with multiple processes occurring simultaneously. In this work, we have concentrated on the processes that are active in nuclear materials, in particular, nuclear fuels. These processes are coarsening, nucleation, differential diffusion, phase transformation, radiation-induced defect formation and swelling, often with temperature gradients present. All these couple and contribute to evolution that is unique to nuclear fuels and materials. Hybrid model that combines elements from the Potts Monte Carlo, phase-field models and others have been developed to address these multiple physical processes. These models are described and applied to several processes in this report. An important feature of the models developed are that they are coded as applications within SPPARKS, a Sandiadeveloped framework for simulation at the mesoscale of microstructural evolution processes by kinetic Monte Carlo methods. This makes these codes readily accessible and adaptable for future applications.

  4. 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.

  5. Correlations in multiple production on nuclei and Glauber model of multiple scattering

    International Nuclear Information System (INIS)

    Zoller, V.R.; Nikolaev, N.N.

    1982-01-01

    Critical analysis of possibility for describing correlation phenomena during multiple production on nuclei within the framework of the Glauber multiple seattering model generalized for particle production processes with Capella, Krziwinski and Shabelsky has been performed. It was mainly concluded that the suggested generalization of the Glauber model gives dependences on Ng(Np) (where Ng-the number of ''grey'' tracess, and Np-the number of protons flying out of nucleus) and, eventually, on #betta# (where #betta#-the number of intranuclear interactions) contradicting experience. Independent of choice of relation between #betta# and Ng(Np) in the model the rapidity corrletor Rsub(eta) is overstated in the central region and understated in the region of nucleus fragmentation. In mean multiplicities these two contradictions of experience are disguised with random compensation and agreement with experience in Nsub(S) (function of Ng) cannot be an argument in favour of the model. It is concluded that eiconal model doesn't permit to quantitatively describe correlation phenomena during the multiple production on nuclei

  6. Adaptive Optics Simulation for the World's Largest Telescope on Multicore Architectures with Multiple GPUs

    KAUST Repository

    Ltaief, Hatem

    2016-06-02

    We present a high performance comprehensive implementation of a multi-object adaptive optics (MOAO) simulation on multicore architectures with hardware accelerators in the context of computational astronomy. This implementation will be used as an operational testbed for simulating the de- sign of new instruments for the European Extremely Large Telescope project (E-ELT), the world\\'s biggest eye and one of Europe\\'s highest priorities in ground-based astronomy. The simulation corresponds to a multi-step multi-stage pro- cedure, which is fed, near real-time, by system and turbulence data coming from the telescope environment. Based on the PLASMA library powered by the OmpSs dynamic runtime system, our implementation relies on a task-based programming model to permit an asynchronous out-of-order execution. Using modern multicore architectures associated with the enormous computing power of GPUS, the resulting data-driven compute-intensive simulation of the entire MOAO application, composed of the tomographic reconstructor and the observing sequence, is capable of coping with the aforementioned real-time challenge and stands as a reference implementation for the computational astronomy community.

  7. 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.

  8. Multiple Decoupled CPGs with Local Sensory Feedback for Adaptive Locomotion Behaviors of Bio-inspired Walking Robots

    DEFF Research Database (Denmark)

    Shaker Barikhan, Subhi; Wörgötter, Florentin; Manoonpong, Poramate

    2014-01-01

    , and their interactions during body and leg movements through the environment. Based on this concept, we present here an artificial bio-inspired walking system. Its intralimb coordination is formed by multiple decoupled CPGs while its interlimb coordination is attained by the interactions between body dynamics...... and the environment through local sensory feedback of each leg. Simulation results show that this bio-inspired approach generates self-organizing emergent locomotion allowing the robot to adaptively form regular patterns, to stably walk while pushing an object with its front legs or performing multiple stepping...

  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. Multiple Response Regression for Gaussian Mixture Models with Known Labels.

    Science.gov (United States)

    Lee, Wonyul; Du, Ying; Sun, Wei; Hayes, D Neil; Liu, Yufeng

    2012-12-01

    Multiple response regression is a useful regression technique to model multiple response variables using the same set of predictor variables. Most existing methods for multiple response regression are designed for modeling homogeneous data. In many applications, however, one may have heterogeneous data where the samples are divided into multiple groups. Our motivating example is a cancer dataset where the samples belong to multiple cancer subtypes. In this paper, we consider modeling the data coming from a mixture of several Gaussian distributions with known group labels. A naive approach is to split the data into several groups according to the labels and model each group separately. Although it is simple, this approach ignores potential common structures across different groups. We propose new penalized methods to model all groups jointly in which the common and unique structures can be identified. The proposed methods estimate the regression coefficient matrix, as well as the conditional inverse covariance matrix of response variables. Asymptotic properties of the proposed methods are explored. Through numerical examples, we demonstrate that both estimation and prediction can be improved by modeling all groups jointly using the proposed methods. An application to a glioblastoma cancer dataset reveals some interesting common and unique gene relationships across different cancer subtypes.

  12. 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

  13. 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

  14. Efficient Adoption and Assessment of Multiple Process Improvement Reference Models

    Directory of Open Access Journals (Sweden)

    Simona Jeners

    2013-06-01

    Full Text Available A variety of reference models such as CMMI, COBIT or ITIL support IT organizations to improve their processes. These process improvement reference models (IRMs cover different domains such as IT development, IT Services or IT Governance but also share some similarities. As there are organizations that address multiple domains and need to coordinate their processes in their improvement we present MoSaIC, an approach to support organizations to efficiently adopt and conform to multiple IRMs. Our solution realizes a semantic integration of IRMs based on common meta-models. The resulting IRM integration model enables organizations to efficiently implement and asses multiple IRMs and to benefit from synergy effects.

  15. 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.

  16. 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.

  17. 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...

  18. 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

  19. Adapting crop rotations to climate change in regional impact modelling assessments.

    Science.gov (United States)

    Teixeira, Edmar I; de Ruiter, John; Ausseil, Anne-Gaelle; Daigneault, Adam; Johnstone, Paul; Holmes, Allister; Tait, Andrew; Ewert, Frank

    2018-03-01

    The environmental and economic sustainability of future cropping systems depends on adaptation to climate change. Adaptation studies commonly rely on agricultural systems models to integrate multiple components of production systems such as crops, weather, soil and farmers' management decisions. Previous adaptation studies have mostly focused on isolated monocultures. However, in many agricultural regions worldwide, multi-crop rotations better represent local production systems. It is unclear how adaptation interventions influence crops grown in sequences. We develop a catchment-scale assessment to investigate the effects of tactical adaptations (choice of genotype and sowing date) on yield and underlying crop-soil factors of rotations. Based on locally surveyed data, a silage-maize followed by catch-crop-wheat rotation was simulated with the APSIM model for the RCP 8.5 emission scenario, two time periods (1985-2004 and 2080-2100) and six climate models across the Kaituna catchment in New Zealand. Results showed that direction and magnitude of climate change impacts, and the response to adaptation, varied spatially and were affected by rotation carryover effects due to agronomical (e.g. timing of sowing and harvesting) and soil (e.g. residual nitrogen, N) aspects. For example, by adapting maize to early-sowing dates under a warmer climate, there was an advance in catch crop establishment which enhanced residual soil N uptake. This dynamics, however, differed with local environment and choice of short- or long-cycle maize genotypes. Adaptation was insufficient to neutralize rotation yield losses in lowlands but consistently enhanced yield gains in highlands, where other constraints limited arable cropping. The positive responses to adaptation were mainly due to increases in solar radiation interception across the entire growth season. These results provide deeper insights on the dynamics of climate change impacts for crop rotation systems. Such knowledge can be used

  20. Model Seleksi Premi Asuransi Jiwa Dwiguna untuk Kasus Multiple Decrement

    OpenAIRE

    Cita, Devi Ramana; Pane, Rolan; ', Harison

    2015-01-01

    This article discusses a select survival model for the case of multiple decrements in evaluating endowment life insurance premium for person currently aged ( + ) years, who is selected at age with ℎ years selection period. The case of multiple decrements in this case is limited to two cases. The calculation of the annual premium is done by prior evaluating of the single premium, and the present value of annuity depends on theconstant force assumption.

  1. Adaptive Optics Simulation for the World's Largest Telescope on Multicore Architectures with Multiple GPUs

    KAUST Repository

    Ltaief, Hatem; Gratadour, Damien; Charara, Ali; Gendron, Eric

    2016-01-01

    We present a high performance comprehensive implementation of a multi-object adaptive optics (MOAO) simulation on multicore architectures with hardware accelerators in the context of computational astronomy. This implementation will be used

  2. Adaptive aspirations and performance heterogeneity : Attention allocation among multiple reference points

    NARCIS (Netherlands)

    Blettner, D.P.; He, Z.; Hu, S.; Bettis, R.

    Organizations learn and adapt their aspiration levels based on reference points (prior aspiration, prior performance, and prior performance of reference groups). The relative attention that organizations allocate to these reference points impacts organizational search and strategic decisions.

  3. 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.

  4. 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.)

  5. 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.

  6. Semiautomatic bladder segmentation on CBCT using a population-based model for multiple-plan ART of bladder cancer

    NARCIS (Netherlands)

    Chai, Xiangfei; van Herk, Marcel; Betgen, Anja; Hulshof, Maarten; Bel, Arjan

    2012-01-01

    The aim of this study is to develop a novel semiautomatic bladder segmentation approach for selecting the appropriate plan from the library of plans for a multiple-plan adaptive radiotherapy (ART) procedure. A population-based statistical bladder model was first built from a training data set (95

  7. AgMIP Training in Multiple Crop Models and Tools

    Science.gov (United States)

    Boote, Kenneth J.; Porter, Cheryl H.; Hargreaves, John; Hoogenboom, Gerrit; Thornburn, Peter; Mutter, Carolyn

    2015-01-01

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) has the goal of using multiple crop models to evaluate climate impacts on agricultural production and food security in developed and developing countries. There are several major limitations that must be overcome to achieve this goal, including the need to train AgMIP regional research team (RRT) crop modelers to use models other than the ones they are currently familiar with, plus the need to harmonize and interconvert the disparate input file formats used for the various models. Two activities were followed to address these shortcomings among AgMIP RRTs to enable them to use multiple models to evaluate climate impacts on crop production and food security. We designed and conducted courses in which participants trained on two different sets of crop models, with emphasis on the model of least experience. In a second activity, the AgMIP IT group created templates for inputting data on soils, management, weather, and crops into AgMIP harmonized databases, and developed translation tools for converting the harmonized data into files that are ready for multiple crop model simulations. The strategies for creating and conducting the multi-model course and developing entry and translation tools are reviewed in this chapter.

  8. 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

  9. 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.

  10. 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

  11. Second-order sliding mode controller with model reference adaptation for automatic train operation

    Science.gov (United States)

    Ganesan, M.; Ezhilarasi, D.; Benni, Jijo

    2017-11-01

    In this paper, a new approach to model reference based adaptive second-order sliding mode control together with adaptive state feedback is presented to control the longitudinal dynamic motion of a high speed train for automatic train operation with the objective of minimal jerk travel by the passengers. The nonlinear dynamic model for the longitudinal motion of the train comprises of a locomotive and coach subsystems is constructed using multiple point-mass model by considering the forces acting on the vehicle. An adaptation scheme using Lyapunov criterion is derived to tune the controller gains by considering a linear, stable reference model that ensures the stability of the system in closed loop. The effectiveness of the controller tracking performance is tested under uncertain passenger load, coupler-draft gear parameters, propulsion resistance coefficients variations and environmental disturbances due to side wind and wet rail conditions. The results demonstrate improved tracking performance of the proposed control scheme with a least jerk under maximum parameter uncertainties when compared to constant gain second-order sliding mode control.

  12. A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk

    Directory of Open Access Journals (Sweden)

    Lewei Duan

    2013-01-01

    Full Text Available A variety of methods have been proposed for studying the association of multiple genes thought to be involved in a common pathway for a particular disease. Here, we present an extension of a Bayesian hierarchical modeling strategy that allows for multiple SNPs within each gene, with external prior information at either the SNP or gene level. The model involves variable selection at the SNP level through latent indicator variables and Bayesian shrinkage at the gene level towards a prior mean vector and covariance matrix that depend on external information. The entire model is fitted using Markov chain Monte Carlo methods. Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects. The method is applied to data on 504 SNPs in 38 candidate genes involved in DNA damage response in the WECARE study of second breast cancers in relation to radiotherapy exposure.

  13. 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:

  14. 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.

  15. [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.

  16. Assessment applicability of selected models of multiple discriminant analyses to forecast financial situation of Polish wood sector enterprises

    Directory of Open Access Journals (Sweden)

    Adamowicz Krzysztof

    2017-03-01

    Full Text Available In the last three decades forecasting bankruptcy of enterprises has been an important and difficult problem, used as an impulse for many research projects (Ribeiro et al. 2012. At present many methods of bankruptcy prediction are available. In view of the specific character of economic activity in individual sectors, specialised methods adapted to a given branch of industry are being used increasingly often. For this reason an important scientific problem is related with the indication of an appropriate model or group of models to prepare forecasts for a given branch of industry. Thus research has been conducted to select an appropriate model of Multiple Discriminant Analysis (MDA, best adapted to forecasting changes in the wood industry. This study analyses 10 prediction models popular in Poland. Effectiveness of the model proposed by Jagiełło, developed for all industrial enterprises, may be labelled accidental. That model is not adapted to predict financial changes in wood sector companies in Poland.

  17. 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

  18. Offline multiple adaptive planning strategy for concurrent irradiation of the prostate and pelvic lymph nodes

    International Nuclear Information System (INIS)

    Qi, Peng; Xia, Ping; Pouliot, Jean; Roach, Mack

    2014-01-01

    Purpose: Concurrent irradiation of the prostate and pelvic lymph nodes (PLNs) can be challenging due to the independent motion of the two target volumes. To address this challenge, the authors have proposed a strategy referred to as Multiple Adaptive Planning (MAP). To minimize the number of MAP plans, the authors’ previous work only considered the prostate motion in one major direction. After analyzing the pattern of the prostate motion, the authors investigated a practical number of intensity-modulated radiotherapy (IMRT) plans needed to accommodate the prostate motion in two major directions simultaneously. Methods: Six patients, who received concurrent irradiation of the prostate and PLNs, were selected for this study. Nine MAP-IMRT plans were created for each patient with nine prostate contours that represented the prostate at nine locations with respect to the PLNs, including the original prostate contour and eight contours shifted either 5 mm in a single anterior-posterior (A-P), or superior-inferior (S-I) direction, or 5 mm in both A-P and S-I directions simultaneously. From archived megavoltage cone beam CT (MV-CBCT) and a dual imaging registration, 17 MV-CBCTs from 33 available MV-CBCT from these patients showed large prostate displacements (>3 mm in any direction) with respect to the pelvic bones. For each of these 17 fractions, one of nine MAP-IMRT plans was retrospectively selected and applied to the MV-CBCT for dose calculation. For comparison, a simulated isocenter-shifting plan and a reoptimized plan were also created for each of these 17 fractions. The doses to 95% (D95) of the prostate and PLNs, and the doses to 5% (D5) of the rectum and bladder were calculated and analyzed. Results: For the prostate, D95 > 97% of the prescription dose was observed in 16, 16, and 17 of 17 fractions for the MAP, isocenter-shifted, and reoptimized plans, respectively. For PLNs, D95 > 97% of the prescription doses was observed in 10, 3, and 17 of 17 fractions for

  19. Parametric modeling for damped sinusoids from multiple channels

    DEFF Research Database (Denmark)

    Zhou, Zhenhua; So, Hing Cheung; Christensen, Mads Græsbøll

    2013-01-01

    frequencies and damping factors are then computed with the multi-channel weighted linear prediction method. The estimated sinusoidal poles are then matched to each channel according to the extreme value theory of distribution of random fields. Simulations are performed to show the performance advantages......The problem of parametric modeling for noisy damped sinusoidal signals from multiple channels is addressed. Utilizing the shift invariance property of the signal subspace, the number of distinct sinusoidal poles in the multiple channels is first determined. With the estimated number, the distinct...... of the proposed multi-channel sinusoidal modeling methodology compared with existing methods....

  20. A Multiple Model Prediction Algorithm for CNC Machine Wear PHM

    Directory of Open Access Journals (Sweden)

    Huimin Chen

    2011-01-01

    Full Text Available The 2010 PHM data challenge focuses on the remaining useful life (RUL estimation for cutters of a high speed CNC milling machine using measurements from dynamometer, accelerometer, and acoustic emission sensors. We present a multiple model approach for wear depth estimation of milling machine cutters using the provided data. The feature selection, initial wear estimation and multiple model fusion components of the proposed algorithm are explained in details and compared with several alternative methods using the training data. The final submission ranked #2 among professional and student participants and the method is applicable to other data driven PHM problems.

  1. Climate change adaptation and forests in South Asia: Policy for multiple stakeholders

    Energy Technology Data Exchange (ETDEWEB)

    Deshingkar, P.

    1997-12-31

    Moving from a general understanding of the potential dangers of climate change to real policy and investment requires changes in priorities at the level of government as well as the individual. Information should be disseminated through regional technical co-operation as well as improved communication between relevant institutions within countries. Besides fulfilling scientific and economic criteria for sustainability, forest adaption strategies in South asian countries should aim to be participatory and low cost. In the short term, maximizing the utility of existing institutions and skills may be more practical. The removal of market distortions will also enhance adaptive capacity. Continued research and technological innovation must accompany efforts to change management practices. The immediate priority for donor assistance in this area is to conduct vulnerability assessments, evaluate the constraints and develop a menu of adaption options based on multi criteria analysis of different objectives

  2. 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.

  3. Cross-cultural adaptation and validation of the 12-item Multiple Sclerosis Walking Scale (MSWS-12 for the Brazilian population

    Directory of Open Access Journals (Sweden)

    Bruna E. M. Marangoni

    2012-12-01

    Full Text Available Gait impairment is reported by 85% of patients with multiple sclerosis (MS as main complaint. In 2003, Hobart et al. developed a scale for walking known as The 12-item Multiple Sclerosis Walking Scale (MSWS-12, which combines the perspectives of patients with psychometric methods. OBJECTIVE: This study aimed to cross-culturally adapt and validate the MSWS-12 for the Brazilian population with MS. METHODS: This study included 116 individuals diagnosed with MS, in accordance with McDonald's criteria. The steps of the adaptation process included translation, back-translation, review by an expert committee and pretesting. A test and retest of MSWS-12/BR was made for validation, with comparison with another scale (MSIS-29/BR and another test (T25FW. RESULTS: The Brazilian version of MSWS-12/BR was shown to be similar to the original. The results indicate that MSWS-12/BR is a reliable and reproducible scale. CONCLUSIONS: MSWS-12/BR has been adapted and validated, and it is a reliable tool for the Brazilian population.

  4. Understanding Migration as an Adaptation in Deltas Using a Bayesian Network Model

    Science.gov (United States)

    Lázár, A. N.; Adams, H.; de Campos, R. S.; Mortreux, C. C.; Clarke, D.; Nicholls, R. J.; Amisigo, B. A.

    2016-12-01

    Deltas are hotspots of high population density, fertile lands and dramatic environmental and anthropogenic pressures and changes. Amongst other environmental factors, sea level rise, soil salinization, water shortages and erosion threaten people's livelihoods and wellbeing. As a result, there is a growing concern that significant environmental change induced migration might occur from these areas. Migration, however, is already happening for economic, education and other reasons (e.g. livelihood change, marriage, planned relocation, etc.). Migration hence has multiple, interlinked drivers and depending on the perspective, can be considered as a positive or negative phenomenon. The DECCMA project (Deltas, Vulnerability & Climate Change: Migration & Adaptation) studies migration as part of a suite of adaptation options available to the coastal populations in the Ganges delta in Bangladesh, the Mahanadi delta in India and the Volta delta in Ghana. It aims to develop a holistic framework of analysis that assesses the impact of climate and environmental change on the migration patterns of these areas. This assessment framework will couple environmental, socio-economics and governance dimensions in an attempt to synthesise drivers and barriers and allow testing of plausible future scenarios. One of the integrative methods of DECCMA is a Bayesian Belief Network (BBN) model describing the decision-making of a coastal household. BBN models are built on qualitative and quantitative observations/expert knowledge and describe the probability of different events/responses etc. BBN models are especially useful to capture uncertainties of large systems and engaging with stakeholders. The DECCMA BBN model is based on household survey results from delta migrant sending areas. This presentation will describe model elements (livelihood sensitivity to climate change, local and national adaptation options, household characteristics/attitude, social networks, household decision) and

  5. Multiple regression and beyond an introduction to multiple regression and structural equation modeling

    CERN Document Server

    Keith, Timothy Z

    2014-01-01

    Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. Covers both MR and SEM, while explaining their relevance to one another Also includes path analysis, confirmatory factor analysis, and latent growth modeling Figures and tables throughout provide examples and illustrate key concepts and techniques For additional resources, please visit: http://tzkeith.com/.

  6. 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.

  7. 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...

  8. 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.

  9. 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.

  10. 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...

  11. 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.

  12. 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

  13. Automatic Query Generation and Query Relevance Measurement for Unsupervised Language Model Adaptation of Speech Recognition

    Directory of Open Access Journals (Sweden)

    Suzuki Motoyuki

    2009-01-01

    Full Text Available Abstract We are developing a method of Web-based unsupervised language model adaptation for recognition of spoken documents. The proposed method chooses keywords from the preliminary recognition result and retrieves Web documents using the chosen keywords. A problem is that the selected keywords tend to contain misrecognized words. The proposed method introduces two new ideas for avoiding the effects of keywords derived from misrecognized words. The first idea is to compose multiple queries from selected keyword candidates so that the misrecognized words and correct words do not fall into one query. The second idea is that the number of Web documents downloaded for each query is determined according to the "query relevance." Combining these two ideas, we can alleviate bad effect of misrecognized keywords by decreasing the number of downloaded Web documents from queries that contain misrecognized keywords. Finally, we examine a method of determining the number of iterative adaptations based on the recognition likelihood. Experiments have shown that the proposed stopping criterion can determine almost the optimum number of iterations. In the final experiment, the word accuracy without adaptation (55.29% was improved to 60.38%, which was 1.13 point better than the result of the conventional unsupervised adaptation method (59.25%.

  14. Automatic Query Generation and Query Relevance Measurement for Unsupervised Language Model Adaptation of Speech Recognition

    Directory of Open Access Journals (Sweden)

    Akinori Ito

    2009-01-01

    Full Text Available We are developing a method of Web-based unsupervised language model adaptation for recognition of spoken documents. The proposed method chooses keywords from the preliminary recognition result and retrieves Web documents using the chosen keywords. A problem is that the selected keywords tend to contain misrecognized words. The proposed method introduces two new ideas for avoiding the effects of keywords derived from misrecognized words. The first idea is to compose multiple queries from selected keyword candidates so that the misrecognized words and correct words do not fall into one query. The second idea is that the number of Web documents downloaded for each query is determined according to the “query relevance.” Combining these two ideas, we can alleviate bad effect of misrecognized keywords by decreasing the number of downloaded Web documents from queries that contain misrecognized keywords. Finally, we examine a method of determining the number of iterative adaptations based on the recognition likelihood. Experiments have shown that the proposed stopping criterion can determine almost the optimum number of iterations. In the final experiment, the word accuracy without adaptation (55.29% was improved to 60.38%, which was 1.13 point better than the result of the conventional unsupervised adaptation method (59.25%.

  15. Double-multiple streamtube model for Darrieus in turbines

    Science.gov (United States)

    Paraschivoiu, I.

    1981-01-01

    An analytical model is proposed for calculating the rotor performance and aerodynamic blade forces for Darrieus wind turbines with curved blades. The method of analysis uses a multiple-streamtube model, divided into two parts: one modeling the upstream half-cycle of the rotor and the other, the downstream half-cycle. The upwind and downwind components of the induced velocities at each level of the rotor were obtained using the principle of two actuator disks in tandem. Variation of the induced velocities in the two parts of the rotor produces larger forces in the upstream zone and smaller forces in the downstream zone. Comparisons of the overall rotor performance with previous methods and field test data show the important improvement obtained with the present model. The calculations were made using the computer code CARDAA developed at IREQ. The double-multiple streamtube model presented has two major advantages: it requires a much shorter computer time than the three-dimensional vortex model and is more accurate than multiple-streamtube model in predicting the aerodynamic blade loads.

  16. Sparse Signal Reconstruction with Multiple Side Information using Adaptive Weights for Multiview Sources

    DEFF Research Database (Denmark)

    Luong, Huynh Van; Seiler, Jürgen; Kaup, André

    2016-01-01

    weights by solving a proposed weighted $n$-$\\ell_{1}$ minimization.The proposed algorithm computes the adaptive weights in two levels, first eachindividual intra-SI and then inter-SI weights are iteratively updated at everyreconstructed iteration. This two-level optimization leads...

  17. Cross-layer optimized rate adaptation and scheduling for multiple-user wireless video streaming

    NARCIS (Netherlands)

    Ozcelebi, T.; Sunay, M.O.; Tekalp, A.M.; Civanlar, M.R.

    2007-01-01

    We present a cross-layer optimized video rate adaptation and user scheduling scheme for multi-user wireless video streaming aiming for maximum quality of service (QoS) for each user,, maximum system video throughput, and QoS fairness among users. These objectives are jointly optimized using a

  18. 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

  19. Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system

    Science.gov (United States)

    Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.; Rocky, Durrans S.

    2000-01-01

    Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorial data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

  20. Multiple commodities in statistical microeconomics: Model and market

    Science.gov (United States)

    Baaquie, Belal E.; Yu, Miao; Du, Xin

    2016-11-01

    A statistical generalization of microeconomics has been made in Baaquie (2013). In Baaquie et al. (2015), the market behavior of single commodities was analyzed and it was shown that market data provides strong support for the statistical microeconomic description of commodity prices. The case of multiple commodities is studied and a parsimonious generalization of the single commodity model is made for the multiple commodities case. Market data shows that the generalization can accurately model the simultaneous correlation functions of up to four commodities. To accurately model five or more commodities, further terms have to be included in the model. This study shows that the statistical microeconomics approach is a comprehensive and complete formulation of microeconomics, and which is independent to the mainstream formulation of microeconomics.

  1. Risk Prediction Models for Other Cancers or Multiple Sites

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing other multiple cancers over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  2. An extension of the multiple-trapping model

    International Nuclear Information System (INIS)

    Shkilev, V. P.

    2012-01-01

    The hopping charge transport in disordered semiconductors is considered. Using the concept of the transport energy level, macroscopic equations are derived that extend a multiple-trapping model to the case of semiconductors with both energy and spatial disorders. It is shown that, although both types of disorder can cause dispersive transport, the frequency dependence of conductivity is determined exclusively by the spatial disorder.

  3. Selecting Tools to Model Integer and Binomial Multiplication

    Science.gov (United States)

    Pratt, Sarah Smitherman; Eddy, Colleen M.

    2017-01-01

    Mathematics teachers frequently provide concrete manipulatives to students during instruction; however, the rationale for using certain manipulatives in conjunction with concepts may not be explored. This article focuses on area models that are currently used in classrooms to provide concrete examples of integer and binomial multiplication. The…

  4. Modeling single versus multiple systems in implicit and explicit memory.

    Science.gov (United States)

    Starns, Jeffrey J; Ratcliff, Roger; McKoon, Gail

    2012-04-01

    It is currently controversial whether priming on implicit tasks and discrimination on explicit recognition tests are supported by a single memory system or by multiple, independent systems. In a Psychological Review article, Berry and colleagues used mathematical modeling to address this question and provide compelling evidence against the independent-systems approach. Copyright © 2012 Elsevier Ltd. All rights reserved.

  5. 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.

  6. Green communication: The enabler to multiple business models

    DEFF Research Database (Denmark)

    Lindgren, Peter; Clemmensen, Suberia; Taran, Yariv

    2010-01-01

    Companies stand at the forefront of a new business model reality with new potentials - that will change their basic understanding and practice of running their business models radically. One of the drivers to this change is green communication, its strong relation to green business models and its...... possibility to enable lower energy consumption. This paper shows how green communication enables innovation of green business models and multiple business models running simultaneously in different markets to different customers.......Companies stand at the forefront of a new business model reality with new potentials - that will change their basic understanding and practice of running their business models radically. One of the drivers to this change is green communication, its strong relation to green business models and its...

  7. Infinite Multiple Membership Relational Modeling for Complex Networks

    DEFF Research Database (Denmark)

    Mørup, Morten; Schmidt, Mikkel Nørgaard; Hansen, Lars Kai

    Learning latent structure in complex networks has become an important problem fueled by many types of networked data originating from practically all fields of science. In this paper, we propose a new non-parametric Bayesian multiplemembership latent feature model for networks. Contrary to existing...... multiplemembership models that scale quadratically in the number of vertices the proposedmodel scales linearly in the number of links admittingmultiple-membership analysis in large scale networks. We demonstrate a connection between the single membership relational model and multiple membership models and show...

  8. 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.

  9. 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

  10. The multiple sclerosis work difficulties questionnaire: translation and cross-cultural adaptation to Turkish and assessment of validity and reliability.

    Science.gov (United States)

    Kahraman, Turhan; Özdoğar, Asiye Tuba; Honan, Cynthia Alison; Ertekin, Özge; Özakbaş, Serkan

    2018-05-09

    To linguistically and culturally adapt the Multiple Sclerosis Work Difficulties Questionnaire-23 (MSWDQ-23) for use in Turkey, and to examine its reliability and validity. Following standard forward-back translation of the MSWDQ-23, it was administered to 124 people with multiple sclerosis (MS). Validity was evaluated using related outcome measures including those related to employment status and expectations, disability level, fatigue, walking, and quality of life. Randomly selected participants were asked to complete the MSWDQ-23 again to assess test-retest reliability. Confirmatory factor analysis on the MSWDQ-23 demonstrated a good fit for the data, and the internal consistency of each subscale was excellent. The test-retest reliability for the total score, psychological/cognitive barriers, physical barriers, and external barriers subscales were high. The MSWDQ-23 and its subscales were positively correlated with the employment, disability level, walking, and fatigue outcome measures. This study suggests that the Turkish version of MSWDQ-23 has high reliability and adequate validity, and it can be used to determine the difficulties faced by people with multiple sclerosis in workplace. Moreover, the study provides evidence about the test-retest reliability of the questionnaire. Implications for rehabilitation Multiple sclerosis affects young people of working age. Understanding work-related problems is crucial to enhance people with multiple sclerosis likelihood of maintaining their job. The Multiple Sclerosis Work Difficulties Questionnaire-23 (MSWDQ-23) is a valid and reliable measure of perceived workplace difficulties in people with multiple sclerosis: we presented its validation to Turkish. Professionals working in the field of vocational rehabilitation may benefit from using the MSWDQ-23 to predict the current work outcomes and future employment expectations.

  11. Vehicle coordinated transportation dispatching model base on multiple crisis locations

    Science.gov (United States)

    Tian, Ran; Li, Shanwei; Yang, Guoying

    2018-05-01

    Many disastrous events are often caused after unconventional emergencies occur, and the requirements of disasters are often different. It is difficult for a single emergency resource center to satisfy such requirements at the same time. Therefore, how to coordinate the emergency resources stored by multiple emergency resource centers to various disaster sites requires the coordinated transportation of emergency vehicles. In this paper, according to the problem of emergency logistics coordination scheduling, based on the related constraints of emergency logistics transportation, an emergency resource scheduling model based on multiple disasters is established.

  12. Low adolescent self-esteem leads to multiple interpersonal problems: a test a social-adaptation theory.

    Science.gov (United States)

    Kahle, L R; Kulka, R A; Klingel, D M

    1980-09-01

    This article reports the results of a study that annually monitored the self-esteem and interpersonal problems of over 100 boys during their sophomore, junior, and senior years of high school. Cross-lagged panel correlation differences show that low self-esteem leads to interpersonal problems in all three time lags when multiple interpersonal problems constitute the dependent variable but not when single interpersonal problem criteria constitute the dependent variable. These results are interpreted as supporting social-adaptation theory rather than self-perception theory. Implications for the conceptual status of personality variables as causal antecedents and for the assessment of individual differences are discussed.

  13. 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.

  14. Multiple Surrogate Modeling for Wire-Wrapped Fuel Assembly Optimization

    International Nuclear Information System (INIS)

    Raza, Wasim; Kim, Kwang-Yong

    2007-01-01

    In this work, shape optimization of seven pin wire wrapped fuel assembly has been carried out in conjunction with RANS analysis in order to evaluate the performances of surrogate models. Previously, Ahmad and Kim performed the flow and heat transfer analysis based on the three-dimensional RANS analysis. But numerical optimization has not been applied to the design of wire-wrapped fuel assembly, yet. Surrogate models are being widely used in multidisciplinary optimization. Queipo et al. reviewed various surrogates based models used in aerospace applications. Goel et al. developed weighted average surrogate model based on response surface approximation (RSA), radial basis neural network (RBNN) and Krigging (KRG) models. In addition to the three basic models, RSA, RBNN and KRG, the multiple surrogate model, PBA also has been employed. Two geometric design variables and a multi-objective function with a weighting factor have been considered for this problem

  15. 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.

  16. 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.

  17. A model for diagnosing and explaining multiple disorders.

    Science.gov (United States)

    Jamieson, P W

    1991-08-01

    The ability to diagnose multiple interacting disorders and explain them in a coherent causal framework has only partially been achieved in medical expert systems. This paper proposes a causal model for diagnosing and explaining multiple disorders whose key elements are: physician-directed hypotheses generation, object-oriented knowledge representation, and novel explanation heuristics. The heuristics modify and link the explanations to make the physician aware of diagnostic complexities. A computer program incorporating the model currently is in use for diagnosing peripheral nerve and muscle disorders. The program successfully diagnoses and explains interactions between diseases in terms of underlying pathophysiologic concepts. The model offers a new architecture for medical domains where reasoning from first principles is difficult but explanation of disease interactions is crucial for the system's operation.

  18. 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.

  19. Effects of Adaptation on Discrimination of Whisker Deflection Velocity and Angular Direction in a Model of the Barrel Cortex

    Directory of Open Access Journals (Sweden)

    Mainak J. Patel

    2018-06-01

    Full Text Available Two important stimulus features represented within the rodent barrel cortex are velocity and angular direction of whisker deflection. Each cortical barrel receives information from thalamocortical (TC cells that relay information from a single whisker, and TC input is decoded by barrel regular-spiking (RS cells through a feedforward inhibitory architecture (with inhibition delivered by cortical fast-spiking or FS cells. TC cells encode deflection velocity through population synchrony, while deflection direction is encoded through the distribution of spike counts across the TC population. Barrel RS cells encode both deflection direction and velocity with spike rate, and are divided into functional domains by direction preference. Following repetitive whisker stimulation, system adaptation causes a weakening of synaptic inputs to RS cells and diminishes RS cell spike responses, though evidence suggests that stimulus discrimination may improve following adaptation. In this work, I construct a model of the TC, FS, and RS cells comprising a single barrel system—the model incorporates realistic synaptic connectivity and dynamics and simulates both angular direction (through the spatial pattern of TC activation and velocity (through synchrony of the TC population spikes of a deflection of the primary whisker, and I use the model to examine direction and velocity selectivity of barrel RS cells before and after adaptation. I find that velocity and direction selectivity of individual RS cells (measured over multiple trials sharpens following adaptation, but stimulus discrimination using a simple linear classifier by the RS population response during a single trial (a more biologically meaningful measure than single cell discrimination over multiple trials exhibits strikingly different behavior—velocity discrimination is similar both before and after adaptation, while direction classification improves substantially following adaptation. This is the

  20. Comparison of Multiple-Microphone and Single-Loudspeaker Adaptive Feedback/Echo Cancellation Systems

    DEFF Research Database (Denmark)

    Guo, Meng; Elmedyb, Thomas Bo; Jensen, Søren Holdt

    2011-01-01

    Recently, we introduced a frequency domain measure - the power transfer function - to predict the convergence rate, system stability bound and the steady-state behavior across time and frequency of a least mean square based feedback/echo cancellation algorithm in a general multiple-microphone and......Recently, we introduced a frequency domain measure - the power transfer function - to predict the convergence rate, system stability bound and the steady-state behavior across time and frequency of a least mean square based feedback/echo cancellation algorithm in a general multiple...

  1. 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.

  2. 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:

  3. A PDP model of the simultaneous perception of multiple objects

    Science.gov (United States)

    Henderson, Cynthia M.; McClelland, James L.

    2011-06-01

    Illusory conjunctions in normal and simultanagnosic subjects are two instances where the visual features of multiple objects are incorrectly 'bound' together. A connectionist model explores how multiple objects could be perceived correctly in normal subjects given sufficient time, but could give rise to illusory conjunctions with damage or time pressure. In this model, perception of two objects benefits from lateral connections between hidden layers modelling aspects of the ventral and dorsal visual pathways. As with simultanagnosia, simulations of dorsal lesions impair multi-object recognition. In contrast, a large ventral lesion has minimal effect on dorsal functioning, akin to dissociations between simple object manipulation (retained in visual form agnosia and semantic dementia) and object discrimination (impaired in these disorders) [Hodges, J.R., Bozeat, S., Lambon Ralph, M.A., Patterson, K., and Spatt, J. (2000), 'The Role of Conceptual Knowledge: Evidence from Semantic Dementia', Brain, 123, 1913-1925; Milner, A.D., and Goodale, M.A. (2006), The Visual Brain in Action (2nd ed.), New York: Oxford]. It is hoped that the functioning of this model might suggest potential processes underlying dorsal and ventral contributions to the correct perception of multiple objects.

  4. Supersymmetric U(1)' model with multiple dark matters

    International Nuclear Information System (INIS)

    Hur, Taeil; Lee, Hye-Sung; Nasri, Salah

    2008-01-01

    We consider a scenario where a supersymmetric model has multiple dark matter particles. Adding a U(1) ' gauge symmetry is a well-motivated extension of the minimal supersymmetric standard model (MSSM). It can cure the problems of the MSSM such as the μ problem or the proton decay problem with high-dimensional lepton number and baryon number violating operators which R parity allows. An extra parity (U parity) may arise as a residual discrete symmetry after U(1) ' gauge symmetry is spontaneously broken. The lightest U-parity particle (LUP) is stable under the new parity becoming a new dark matter candidate. Up to three massive particles can be stable in the presence of the R parity and the U parity. We numerically illustrate that multiple stable particles in our model can satisfy both constraints from the relic density and the direct detection, thus providing a specific scenario where a supersymmetric model has well-motivated multiple dark matters consistent with experimental constraints. The scenario provides new possibilities in the present and upcoming dark matter searches in the direct detection and collider experiments

  5. High-resolution adaptive optics scanning laser ophthalmoscope with multiple deformable mirrors

    Science.gov (United States)

    Chen, Diana C.; Olivier, Scot S.; Jones; Steven M.

    2010-02-23

    An adaptive optics scanning laser ophthalmoscopes is introduced to produce non-invasive views of the human retina. The use of dual deformable mirrors improved the dynamic range for correction of the wavefront aberrations compared with the use of the MEMS mirror alone, and improved the quality of the wavefront correction compared with the use of the bimorph mirror alone. The large-stroke bimorph deformable mirror improved the capability for axial sectioning with the confocal imaging system by providing an easier way to move the focus axially through different layers of the retina.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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...

  11. Adaptation of tick-borne encephalitis virus from human brain to different cell cultures induces multiple genomic substitutions.

    Science.gov (United States)

    Ponomareva, Eugenia P; Ternovoi, Vladimir A; Mikryukova, Tamara P; Protopopova, Elena V; Gladysheva, Anastasia V; Shvalov, Alexander N; Konovalova, Svetlana N; Chausov, Eugene V; Loktev, Valery B

    2017-10-01

    The C11-13 strain from the Siberian subtype of tick-borne encephalitis virus (TBEV) was isolated from human brain using pig embryo kidney (PEK), 293, and Neuro-2a cells. Analysis of the complete viral genome of the C11-13 variants during six passages in these cells revealed that the cell-adapted C11-13 variants had multiple amino acid substitutions as compared to TBEV from human brain. Seven out of eight amino acids substitutions in the high-replicating C11-13(PEK) variant mapped to non-structural proteins; 13 out of 14 substitutions in the well-replicating C11-13(293) variant, and all four substitutions in the low-replicating C11-13(Neuro-2a) variant were also localized in non-structural proteins, predominantly in the NS2a (2), NS3 (6) and NS5 (3) proteins. The substitutions NS2a 1067 (Asn → Asp), NS2a 1168 (Leu → Val) in the N-terminus of NS2a and NS3 1745 (His → Gln) in the helicase domain of NS3 were found in all selected variants. We postulate that multiple substitutions in the NS2a, NS3 and NS5 genes play a key role in adaptation of TBEV to different cells.

  12. A multi-scale adaptive model of residential energy demand

    International Nuclear Information System (INIS)

    Farzan, Farbod; Jafari, Mohsen A.; Gong, Jie; Farzan, Farnaz; Stryker, Andrew

    2015-01-01

    Highlights: • We extend an energy demand model to investigate changes in behavioral and usage patterns. • The model is capable of analyzing why demand behaves the way it does. • The model empowers decision makers to investigate DSM strategies and effectiveness. • The model provides means to measure the effect of energy prices on daily profile. • The model considers the coupling effects of adopting multiple new technologies. - Abstract: In this paper, we extend a previously developed bottom-up energy demand model such that the model can be used to determine changes in behavioral and energy usage patterns of a community when: (i) new load patterns from Plug-in Electrical Vehicles (PEV) or other devices are introduced; (ii) new technologies and smart devices are used within premises; and (iii) new Demand Side Management (DSM) strategies, such as price responsive demand are implemented. Unlike time series forecasting methods that solely rely on historical data, the model only uses a minimal amount of data at the atomic level for its basic constructs. These basic constructs can be integrated into a household unit or a community model using rules and connectors that are, in principle, flexible and can be altered according to the type of questions that need to be answered. Furthermore, the embedded dynamics of the model works on the basis of: (i) Markovian stochastic model for simulating human activities, (ii) Bayesian and logistic technology adoption models, and (iii) optimization, and rule-based models to respond to price signals without compromising users’ comfort. The proposed model is not intended to replace traditional forecasting models. Instead it provides an analytical framework that can be used at the design stage of new products and communities to evaluate design alternatives. The framework can also be used to answer questions such as why demand behaves the way it does by examining demands at different scales and by playing What-If games. These

  13. 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.

  14. 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.

  15. An object-oriented approach to evaluating multiple spectral models

    International Nuclear Information System (INIS)

    Majoras, R.E.; Richardson, W.M.; Seymour, R.S.

    1995-01-01

    A versatile, spectroscopy analysis engine has been developed by using object-oriented design and analysis techniques coupled with an object-oriented language, C++. This engine provides the spectroscopist with the choice of several different peak shape models that are tailored to the type of spectroscopy being performed. It also allows ease of development in adapting the engine to other analytical methods requiring more complex peak fitting in the future. This results in a program that can currently be used across a wide range of spectroscopy applications and anticipates inclusion of future advances in the field. (author) 6 refs.; 1 fig

  16. Challenges in LCA modelling of multiple loops for aluminium cans

    DEFF Research Database (Denmark)

    Niero, Monia; Olsen, Stig Irving

    considered the case of closed-loop recycling for aluminium cans, where body and lid are different alloys, and discussed the abovementioned challenge. The Life Cycle Inventory (LCI) modelling of aluminium processes is traditionally based on a pure aluminium flow, therefore neglecting the presence of alloying...... elements. We included the effect of alloying elements on the LCA modelling of aluminium can recycling. First, we performed a mass balance of the main alloying elements (Mn, Fe, Si, Cu) in aluminium can recycling at increasing levels of recycling rate. The analysis distinguished between different aluminium...... packaging scrap sources (i.e. used beverage can and mixed aluminium packaging) to understand the limiting factors for multiple loop aluminium can recycling. Secondly, we performed a comparative LCA of aluminium can production and recycling in multiple loops considering the two aluminium packaging scrap...

  17. 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.

  18. 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.

  19. 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.

  20. 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...

  1. 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.

  2. Dealing with Multiple Solutions in Structural Vector Autoregressive Models.

    Science.gov (United States)

    Beltz, Adriene M; Molenaar, Peter C M

    2016-01-01

    Structural vector autoregressive models (VARs) hold great potential for psychological science, particularly for time series data analysis. They capture the magnitude, direction of influence, and temporal (lagged and contemporaneous) nature of relations among variables. Unified structural equation modeling (uSEM) is an optimal structural VAR instantiation, according to large-scale simulation studies, and it is implemented within an SEM framework. However, little is known about the uniqueness of uSEM results. Thus, the goal of this study was to investigate whether multiple solutions result from uSEM analysis and, if so, to demonstrate ways to select an optimal solution. This was accomplished with two simulated data sets, an empirical data set concerning children's dyadic play, and modifications to the group iterative multiple model estimation (GIMME) program, which implements uSEMs with group- and individual-level relations in a data-driven manner. Results revealed multiple solutions when there were large contemporaneous relations among variables. Results also verified several ways to select the correct solution when the complete solution set was generated, such as the use of cross-validation, maximum standardized residuals, and information criteria. This work has immediate and direct implications for the analysis of time series data and for the inferences drawn from those data concerning human behavior.

  3. 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.

  4. Relative Quantitative Proteomic Analysis of Brucella abortus Reveals Metabolic Adaptation to Multiple Environmental Stresses.

    Science.gov (United States)

    Zai, Xiaodong; Yang, Qiaoling; Yin, Ying; Li, Ruihua; Qian, Mengying; Zhao, Taoran; Li, Yaohui; Zhang, Jun; Fu, Ling; Xu, Junjie; Chen, Wei

    2017-01-01

    Brucella spp. are facultative intracellular pathogens that cause chronic brucellosis in humans and animals. The virulence of Brucella primarily depends on its successful survival and replication in host cells. During invasion of the host tissue, Brucella is simultaneously subjected to a variety of harsh conditions, including nutrient limitation, low pH, antimicrobial defenses, and extreme levels of reactive oxygen species (ROS) via the host immune response. This suggests that Brucella may be able to regulate its metabolic adaptation in response to the distinct stresses encountered during its intracellular infection of the host. An investigation into the differential proteome expression patterns of Brucella grown under the relevant stress conditions may contribute toward a better understanding of its pathogenesis and adaptive response. Here, we utilized a mass spectrometry-based label-free relative quantitative proteomics approach to investigate and compare global proteomic changes in B. abortus in response to eight different stress treatments. The 3 h short-term in vitro single-stress and multi-stress conditions mimicked the in vivo conditions of B. abortus under intracellular infection, with survival rates ranging from 3.17 to 73.17%. The proteomic analysis identified and quantified a total of 2,272 proteins and 74% of the theoretical proteome, thereby providing wide coverage of the B. abortus proteome. By including eight distinct growth conditions and comparing these with a control condition, we identified a total of 1,221 differentially expressed proteins (DEPs) that were significantly changed under the stress treatments. Pathway analysis revealed that most of the proteins were involved in oxidative phosphorylation, ABC transporters, two-component systems, biosynthesis of secondary metabolites, the citrate cycle, thiamine metabolism, and nitrogen metabolism; constituting major response mechanisms toward the reconstruction of cellular homeostasis and metabolic

  5. Relative Quantitative Proteomic Analysis of Brucella abortus Reveals Metabolic Adaptation to Multiple Environmental Stresses

    Directory of Open Access Journals (Sweden)

    Xiaodong Zai

    2017-11-01

    Full Text Available Brucella spp. are facultative intracellular pathogens that cause chronic brucellosis in humans and animals. The virulence of Brucella primarily depends on its successful survival and replication in host cells. During invasion of the host tissue, Brucella is simultaneously subjected to a variety of harsh conditions, including nutrient limitation, low pH, antimicrobial defenses, and extreme levels of reactive oxygen species (ROS via the host immune response. This suggests that Brucella may be able to regulate its metabolic adaptation in response to the distinct stresses encountered during its intracellular infection of the host. An investigation into the differential proteome expression patterns of Brucella grown under the relevant stress conditions may contribute toward a better understanding of its pathogenesis and adaptive response. Here, we utilized a mass spectrometry-based label-free relative quantitative proteomics approach to investigate and compare global proteomic changes in B. abortus in response to eight different stress treatments. The 3 h short-term in vitro single-stress and multi-stress conditions mimicked the in vivo conditions of B. abortus under intracellular infection, with survival rates ranging from 3.17 to 73.17%. The proteomic analysis identified and quantified a total of 2,272 proteins and 74% of the theoretical proteome, thereby providing wide coverage of the B. abortus proteome. By including eight distinct growth conditions and comparing these with a control condition, we identified a total of 1,221 differentially expressed proteins (DEPs that were significantly changed under the stress treatments. Pathway analysis revealed that most of the proteins were involved in oxidative phosphorylation, ABC transporters, two-component systems, biosynthesis of secondary metabolites, the citrate cycle, thiamine metabolism, and nitrogen metabolism; constituting major response mechanisms toward the reconstruction of cellular

  6. IMAGING WITH MULTIMODAL ADAPTIVE-OPTICS OPTICAL COHERENCE TOMOGRAPHY IN MULTIPLE EVANESCENT WHITE DOT SYNDROME: THE STRUCTURE AND FUNCTIONAL RELATIONSHIP.

    Science.gov (United States)

    Labriola, Leanne T; Legarreta, Andrew D; Legarreta, John E; Nadler, Zach; Gallagher, Denise; Hammer, Daniel X; Ferguson, R Daniel; Iftimia, Nicusor; Wollstein, Gadi; Schuman, Joel S

    2016-01-01

    To elucidate the location of pathological changes in multiple evanescent white dot syndrome (MEWDS) with the use of multimodal adaptive optics (AO) imaging. A 5-year observational case study of a 24-year-old female with recurrent MEWDS. Full examination included history, Snellen chart visual acuity, pupil assessment, intraocular pressures, slit lamp evaluation, dilated fundoscopic exam, imaging with Fourier-domain optical coherence tomography (FD-OCT), blue-light fundus autofluorescence (FAF), fundus photography, fluorescein angiography, and adaptive-optics optical coherence tomography. Three distinct acute episodes of MEWDS occurred during the period of follow-up. Fourier-domain optical coherence tomography and adaptive-optics imaging showed disturbance in the photoreceptor outer segments (PR OS) in the posterior pole with each flare. The degree of disturbance at the photoreceptor level corresponded to size and extent of the visual field changes. All findings were transient with delineation of the photoreceptor recovery from the outer edges of the lesion inward. Hyperautofluorescence was seen during acute flares. Increase in choroidal thickness did occur with each active flare but resolved. Although changes in the choroid and RPE can be observed in MEWDS, Fourier-domain optical coherence tomography, and multimodal adaptive optics imaging localized the visually significant changes seen in this disease at the level of the photoreceptors. These transient retinal changes specifically occur at the level of the inner segment ellipsoid and OS/RPE line. En face optical coherence tomography imaging provides a detailed, yet noninvasive method for following the convalescence of MEWDS and provides insight into the structural and functional relationship of this transient inflammatory retinal disease.

  7. Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

    Science.gov (United States)

    Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

    2018-04-01

    In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

  8. Automatic Generation of 3D Building Models with Multiple Roofs

    Institute of Scientific and Technical Information of China (English)

    Kenichi Sugihara; Yoshitugu Hayashi

    2008-01-01

    Based on building footprints (building polygons) on digital maps, we are proposing the GIS and CG integrated system that automatically generates 3D building models with multiple roofs. Most building polygons' edges meet at right angles (orthogonal polygon). The integrated system partitions orthogonal building polygons into a set of rectangles and places rectangular roofs and box-shaped building bodies on these rectangles. In order to partition an orthogonal polygon, we proposed a useful polygon expression in deciding from which vertex a dividing line is drawn. In this paper, we propose a new scheme for partitioning building polygons and show the process of creating 3D roof models.

  9. A tactical supply chain planning model with multiple flexibility options

    DEFF Research Database (Denmark)

    Esmaeilikia, Masoud; Fahimnia, Behnam; Sarkis, Joeseph

    2016-01-01

    Supply chain flexibility is widely recognized as an approach to manage uncertainty. Uncertainty in the supply chain may arise from a number of sources such as demand and supply interruptions and lead time variability. A tactical supply chain planning model with multiple flexibility options...... incorporated in sourcing, manufacturing and logistics functions can be used for the analysis of flexibility adjustment in an existing supply chain. This paper develops such a tactical supply chain planning model incorporating a realistic range of flexibility options. A novel solution method is designed...

  10. Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

    Czech Academy of Sciences Publication Activity Database

    Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

    2009-01-01

    Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

  11. 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.

  12. 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.

  13. 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

  14. 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).

  15. Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

    Science.gov (United States)

    Lane, Peter C. R.; Gobet, Fernand

    2013-03-01

    Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.

  16. 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].

  17. Modelling of diffuse solar fraction with multiple predictors

    Energy Technology Data Exchange (ETDEWEB)

    Ridley, Barbara; Boland, John [Centre for Industrial and Applied Mathematics, University of South Australia, Mawson Lakes Boulevard, Mawson Lakes, SA 5095 (Australia); Lauret, Philippe [Laboratoire de Physique du Batiment et des Systemes, University of La Reunion, Reunion (France)

    2010-02-15

    For some locations both global and diffuse solar radiation are measured. However, for many locations, only global radiation is measured, or inferred from satellite data. For modelling solar energy applications, the amount of radiation on a tilted surface is needed. Since only the direct component on a tilted surface can be calculated from direct on some other plane using trigonometry, we need to have diffuse radiation on the horizontal plane available. There are regression relationships for estimating the diffuse on a tilted surface from diffuse on the horizontal. Models for estimating the diffuse on the horizontal from horizontal global that have been developed in Europe or North America have proved to be inadequate for Australia. Boland et al. developed a validated model for Australian conditions. Boland et al. detailed our recent advances in developing the theoretical framework for the use of the logistic function instead of piecewise linear or simple nonlinear functions and was the first step in identifying the means for developing a generic model for estimating diffuse from global and other predictors. We have developed a multiple predictor model, which is much simpler than previous models, and uses hourly clearness index, daily clearness index, solar altitude, apparent solar time and a measure of persistence of global radiation level as predictors. This model performs marginally better than currently used models for locations in the Northern Hemisphere and substantially better for Southern Hemisphere locations. We suggest it can be used as a universal model. (author)

  18. 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

  19. Adaptive Code Division Multiple Access Protocol for Wireless Network-on-Chip Architectures

    Science.gov (United States)

    Vijayakumaran, Vineeth

    Massive levels of integration following Moore's Law ushered in a paradigm shift in the way on-chip interconnections were designed. With higher and higher number of cores on the same die traditional bus based interconnections are no longer a scalable communication infrastructure. On-chip networks were proposed enabled a scalable plug-and-play mechanism for interconnecting hundreds of cores on the same chip. Wired interconnects between the cores in a traditional Network-on-Chip (NoC) system, becomes a bottleneck with increase in the number of cores thereby increasing the latency and energy to transmit signals over them. Hence, there has been many alternative emerging interconnect technologies proposed, namely, 3D, photonic and multi-band RF interconnects. Although they provide better connectivity, higher speed and higher bandwidth compared to wired interconnects; they also face challenges with heat dissipation and manufacturing difficulties. On-chip wireless interconnects is one other alternative proposed which doesn't need physical interconnection layout as data travels over the wireless medium. They are integrated into a hybrid NOC architecture consisting of both wired and wireless links, which provides higher bandwidth, lower latency, lesser area overhead and reduced energy dissipation in communication. However, as the bandwidth of the wireless channels is limited, an efficient media access control (MAC) scheme is required to enhance the utilization of the available bandwidth. This thesis proposes using a multiple access mechanism such as Code Division Multiple Access (CDMA) to enable multiple transmitter-receiver pairs to send data over the wireless channel simultaneously. It will be shown that such a hybrid wireless NoC with an efficient CDMA based MAC protocol can significantly increase the performance of the system while lowering the energy dissipation in data transfer. In this work it is shown that the wireless NoC with the proposed CDMA based MAC protocol

  20. Rapidity correlations at fixed multiplicity in cluster emission models

    CERN Document Server

    Berger, M C

    1975-01-01

    Rapidity correlations in the central region among hadrons produced in proton-proton collisions of fixed final state multiplicity n at NAL and ISR energies are investigated in a two-step framework in which clusters of hadrons are emitted essentially independently, via a multiperipheral-like model, and decay isotropically. For n>or approximately=/sup 1///sub 2/(n), these semi-inclusive distributions are controlled by the reaction mechanism which dominates production in the central region. Thus, data offer cleaner insight into the properties of this mechanism than can be obtained from fully inclusive spectra. A method of experimental analysis is suggested to facilitate the extraction of new dynamical information. It is shown that the n independence of the magnitude of semi-inclusive correlation functions reflects directly the structure of the internal cluster multiplicity distribution. This conclusion is independent of certain assumptions concerning the form of the single cluster density in rapidity space. (23 r...

  1. Motor programme activating therapy influences adaptive brain functions in multiple sclerosis: clinical and MRI study.

    Science.gov (United States)

    Rasova, Kamila; Prochazkova, Marie; Tintera, Jaroslav; Ibrahim, Ibrahim; Zimova, Denisa; Stetkarova, Ivana

    2015-03-01

    There is still little scientific evidence for the efficacy of neurofacilitation approaches and their possible influence on brain plasticity and adaptability. In this study, the outcome of a new kind of neurofacilitation approach, motor programme activating therapy (MPAT), was evaluated on the basis of a set of clinical functions and with MRI. Eighteen patients were examined four times with standardized clinical tests and diffusion tensor imaging to monitor changes without therapy, immediately after therapy and 1 month after therapy. Moreover, the strength of effective connectivity was analysed before and after therapy. Patients underwent a 1-h session of MPAT twice a week for 2 months. The data were analysed by nonparametric tests of association and were subsequently statistically evaluated. The therapy led to significant improvement in clinical functions, significant increment of fractional anisotropy and significant decrement of mean diffusivity, and decrement of effective connectivity at supplementary motor areas was observed immediately after the therapy. Changes in clinical functions and diffusion tensor images persisted 1 month after completing the programme. No statistically significant changes in clinical functions and no differences in MRI-diffusion tensor images were observed without physiotherapy. Positive immediate and long-term effects of MPAT on clinical and brain functions, as well as brain microstructure, were confirmed.

  2. Multiplicative Attribute Graph Model of Real-World Networks

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Myunghwan [Stanford Univ., CA (United States); Leskovec, Jure [Stanford Univ., CA (United States)

    2010-10-20

    Large scale real-world network data, such as social networks, Internet andWeb graphs, is ubiquitous in a variety of scientific domains. The study of such social and information networks commonly finds patterns and explain their emergence through tractable models. In most networks, especially in social networks, nodes also have a rich set of attributes (e.g., age, gender) associatedwith them. However, most of the existing network models focus only on modeling the network structure while ignoring the features of nodes in the network. Here we present a class of network models that we refer to as the Multiplicative Attribute Graphs (MAG), which naturally captures the interactions between the network structure and node attributes. We consider a model where each node has a vector of categorical features associated with it. The probability of an edge between a pair of nodes then depends on the product of individual attributeattribute similarities. The model yields itself to mathematical analysis as well as fit to real data. We derive thresholds for the connectivity, the emergence of the giant connected component, and show that the model gives rise to graphs with a constant diameter. Moreover, we analyze the degree distribution to show that the model can produce networks with either lognormal or power-law degree distribution depending on certain conditions.

  3. 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.

  4. 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.

  5. 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.

  6. Theoretical Models of Protostellar Binary and Multiple Systems with AMR Simulations

    Science.gov (United States)

    Matsumoto, Tomoaki; Tokuda, Kazuki; Onishi, Toshikazu; Inutsuka, Shu-ichiro; Saigo, Kazuya; Takakuwa, Shigehisa

    2017-05-01

    We present theoretical models for protostellar binary and multiple systems based on the high-resolution numerical simulation with an adaptive mesh refinement (AMR) code, SFUMATO. The recent ALMA observations have revealed early phases of the binary and multiple star formation with high spatial resolutions. These observations should be compared with theoretical models with high spatial resolutions. We present two theoretical models for (1) a high density molecular cloud core, MC27/L1521F, and (2) a protobinary system, L1551 NE. For the model for MC27, we performed numerical simulations for gravitational collapse of a turbulent cloud core. The cloud core exhibits fragmentation during the collapse, and dynamical interaction between the fragments produces an arc-like structure, which is one of the prominent structures observed by ALMA. For the model for L1551 NE, we performed numerical simulations of gas accretion onto protobinary. The simulations exhibit asymmetry of a circumbinary disk. Such asymmetry has been also observed by ALMA in the circumbinary disk of L1551 NE.

  7. Dynamic coordinated control laws in multiple agent models

    International Nuclear Information System (INIS)

    Morgan, David S.; Schwartz, Ira B.

    2005-01-01

    We present an active control scheme of a kinetic model of swarming. It has been shown previously that the global control scheme for the model, presented in [Systems Control Lett. 52 (2004) 25], gives rise to spontaneous collective organization of agents into a unified coherent swarm, via steering controls and utilizing long-range attractive and short-range repulsive interactions. We extend these results by presenting control laws whereby a single swarm is broken into independently functioning subswarm clusters. The transition between one coordinated swarm and multiple clustered subswarms is managed simply with a homotopy parameter. Additionally, we present as an alternate formulation, a local control law for the same model, which implements dynamic barrier avoidance behavior, and in which swarm coherence emerges spontaneously

  8. Laplace transform analysis of a multiplicative asset transfer model

    Science.gov (United States)

    Sokolov, Andrey; Melatos, Andrew; Kieu, Tien

    2010-07-01

    We analyze a simple asset transfer model in which the transfer amount is a fixed fraction f of the giver’s wealth. The model is analyzed in a new way by Laplace transforming the master equation, solving it analytically and numerically for the steady-state distribution, and exploring the solutions for various values of f∈(0,1). The Laplace transform analysis is superior to agent-based simulations as it does not depend on the number of agents, enabling us to study entropy and inequality in regimes that are costly to address with simulations. We demonstrate that Boltzmann entropy is not a suitable (e.g. non-monotonic) measure of disorder in a multiplicative asset transfer system and suggest an asymmetric stochastic process that is equivalent to the asset transfer model.

  9. Treatment Sequencing for Childhood ADHD: A Multiple-Randomization Study of Adaptive Medication and Behavioral Interventions.

    Science.gov (United States)

    Pelham, William E; Fabiano, Gregory A; Waxmonsky, James G; Greiner, Andrew R; Gnagy, Elizabeth M; Pelham, William E; Coxe, Stefany; Verley, Jessica; Bhatia, Ira; Hart, Katie; Karch, Kathryn; Konijnendijk, Evelien; Tresco, Katy; Nahum-Shani, Inbal; Murphy, Susan A

    2016-01-01

    Behavioral and pharmacological treatments for children with attention deficit/hyperactivity disorder (ADHD) were evaluated to address whether endpoint outcomes are better depending on which treatment is initiated first and, in case of insufficient response to initial treatment, whether increasing dose of initial treatment or adding the other treatment modality is superior. Children with ADHD (ages 5-12, N = 146, 76% male) were treated for 1 school year. Children were randomized to initiate treatment with low doses of either (a) behavioral parent training (8 group sessions) and brief teacher consultation to establish a Daily Report Card or (b) extended-release methylphenidate (equivalent to .15 mg/kg/dose bid). After 8 weeks or at later monthly intervals as necessary, insufficient responders were rerandomized to secondary interventions that either increased the dose/intensity of the initial treatment or added the other treatment modality, with adaptive adjustments monthly as needed to these secondary treatments. The group beginning with behavioral treatment displayed significantly lower rates of observed classroom rule violations (the primary outcome) at study endpoint and tended to have fewer out-of-class disciplinary events. Further, adding medication secondary to initial behavior modification resulted in better outcomes on the primary outcomes and parent/teacher ratings of oppositional behavior than adding behavior modification to initial medication. Normalization rates on teacher and parent ratings were generally high. Parents who began treatment with behavioral parent training had substantially better attendance than those assigned to receive training following medication. Beginning treatment with behavioral intervention produced better outcomes overall than beginning treatment with medication.

  10. Performance analysis of two-way amplify and forward relaying with adaptive modulation over multiple relay network

    KAUST Repository

    Hwang, Kyusung

    2011-02-01

    In this letter, we propose two-way amplify-and-forward relaying in conjunction with adaptive modulation in order to improve spectral efficiency of relayed communication systems while monitoring the required error performance. We also consider a multiple relay network where only the best relay node is utilized so that the diversity order increases while maintaining a low complexity of implementation as the number of relays increases. Based on the best relay selection criterion, we offer an upper bound on the signal-to-noise ratio to keep the performance analysis tractable. Our numerical examples show that the proposed system offers a considerable gain in spectral efficiency while satisfying the error rate requirements. © 2011 IEEE.

  11. DOA Estimation of Low Altitude Target Based on Adaptive Step Glowworm Swarm Optimization-multiple Signal Classification Algorithm

    Directory of Open Access Journals (Sweden)

    Zhou Hao

    2015-06-01

    Full Text Available The traditional MUltiple SIgnal Classification (MUSIC algorithm requires significant computational effort and can not be employed for the Direction Of Arrival (DOA estimation of targets in a low-altitude multipath environment. As such, a novel MUSIC approach is proposed on the basis of the algorithm of Adaptive Step Glowworm Swarm Optimization (ASGSO. The virtual spatial smoothing of the matrix formed by each snapshot is used to realize the decorrelation of the multipath signal and the establishment of a fullorder correlation matrix. ASGSO optimizes the function and estimates the elevation of the target. The simulation results suggest that the proposed method can overcome the low altitude multipath effect and estimate the DOA of target readily and precisely without radar effective aperture loss.

  12. Performance analysis of two-way amplify and forward relaying with adaptive modulation over multiple relay network

    KAUST Repository

    Hwang, Kyusung; Ko, Youngchai; Alouini, Mohamed-Slim

    2011-01-01

    In this letter, we propose two-way amplify-and-forward relaying in conjunction with adaptive modulation in order to improve spectral efficiency of relayed communication systems while monitoring the required error performance. We also consider a multiple relay network where only the best relay node is utilized so that the diversity order increases while maintaining a low complexity of implementation as the number of relays increases. Based on the best relay selection criterion, we offer an upper bound on the signal-to-noise ratio to keep the performance analysis tractable. Our numerical examples show that the proposed system offers a considerable gain in spectral efficiency while satisfying the error rate requirements. © 2011 IEEE.

  13. Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations

    Science.gov (United States)

    Le, Phuong Dong; Leonard, Michael; Westra, Seth

    2018-03-01

    Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.

  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. The collapsed cone algorithm for (192)Ir dosimetry using phantom-size adaptive multiple-scatter point kernels.

    Science.gov (United States)

    Tedgren, Åsa Carlsson; Plamondon, Mathieu; Beaulieu, Luc

    2015-07-07

    /phantom for which low doses at phantom edges can be overestimated by 2-5 %. It would be possible to improve the situation by using a point kernel for multiple-scatter dose adapted to the patient/phantom dimensions at hand.

  16. Many-electron model for multiple ionization in atomic collisions

    International Nuclear Information System (INIS)

    Archubi, C D; Montanari, C C; Miraglia, J E

    2007-01-01

    We have developed a many-electron model for multiple ionization of heavy atoms bombarded by bare ions. It is based on the transport equation for an ion in an inhomogeneous electronic density. Ionization probabilities are obtained by employing the shell-to-shell local plasma approximation with the Levine and Louie dielectric function to take into account the binding energy of each shell. Post-collisional contributions due to Auger-like processes are taken into account by employing recent photoemission data. Results for single-to-quadruple ionization of Ne, Ar, Kr and Xe by protons are presented showing a very good agreement with experimental data

  17. Many-electron model for multiple ionization in atomic collisions

    Energy Technology Data Exchange (ETDEWEB)

    Archubi, C D [Instituto de AstronomIa y Fisica del Espacio, Casilla de Correo 67, Sucursal 28 (C1428EGA) Buenos Aires (Argentina); Montanari, C C [Instituto de AstronomIa y Fisica del Espacio, Casilla de Correo 67, Sucursal 28 (C1428EGA) Buenos Aires (Argentina); Miraglia, J E [Instituto de AstronomIa y Fisica del Espacio, Casilla de Correo 67, Sucursal 28 (C1428EGA) Buenos Aires (Argentina)

    2007-03-14

    We have developed a many-electron model for multiple ionization of heavy atoms bombarded by bare ions. It is based on the transport equation for an ion in an inhomogeneous electronic density. Ionization probabilities are obtained by employing the shell-to-shell local plasma approximation with the Levine and Louie dielectric function to take into account the binding energy of each shell. Post-collisional contributions due to Auger-like processes are taken into account by employing recent photoemission data. Results for single-to-quadruple ionization of Ne, Ar, Kr and Xe by protons are presented showing a very good agreement with experimental data.

  18. Model selection in Bayesian segmentation of multiple DNA alignments.

    Science.gov (United States)

    Oldmeadow, Christopher; Keith, Jonathan M

    2011-03-01

    The analysis of multiple sequence alignments is allowing researchers to glean valuable insights into evolution, as well as identify genomic regions that may be functional, or discover novel classes of functional elements. Understanding the distribution of conservation levels that constitutes the evolutionary landscape is crucial to distinguishing functional regions from non-functional. Recent evidence suggests that a binary classification of evolutionary rates is inappropriate for this purpose and finds only highly conserved functional elements. Given that the distribution of evolutionary rates is multi-modal, determining the number of modes is of paramount concern. Through simulation, we evaluate the performance of a number of information criterion approaches derived from MCMC simulations in determining the dimension of a model. We utilize a deviance information criterion (DIC) approximation that is more robust than the approximations from other information criteria, and show our information criteria approximations do not produce superfluous modes when estimating conservation distributions under a variety of circumstances. We analyse the distribution of conservation for a multiple alignment comprising four primate species and mouse, and repeat this on two additional multiple alignments of similar species. We find evidence of six distinct classes of evolutionary rates that appear to be robust to the species used. Source code and data are available at http://dl.dropbox.com/u/477240/changept.zip.

  19. 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

  20. 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.

  1. A multiple-location model for natural gas forward curves

    International Nuclear Information System (INIS)

    Buffington, J.C.

    1999-06-01

    This thesis presents an approach for financial modelling of natural gas in which connections between locations are incorporated and the complexities of forward curves in natural gas are considered. Apart from electricity, natural gas is the most volatile commodity traded. Its price is often dependent on the weather and price shocks can be felt across several geographic locations. This modelling approach incorporates multiple risk factors that correspond to various locations. One of the objectives was to determine if the model could be used for closed-form option prices. It was suggested that an adequate model for natural gas must consider 3 statistical properties: volatility term structure, backwardation and contango, and stochastic basis. Data from gas forward prices at Chicago, NYMEX and AECO were empirically tested to better understand these 3 statistical properties at each location and to verify if the proposed model truly incorporates these properties. In addition, this study examined the time series property of the difference of two locations (the basis) and determines that these empirical properties are consistent with the model properties. Closed-form option solutions were also developed for call options of forward contracts and call options on forward basis. The options were calibrated and compared to other models. The proposed model is capable of pricing options, but the prices derived did not pass the test of economic reasonableness. However, the model was able to capture the effect of transportation as well as aspects of seasonality which is a benefit over other existing models. It was determined that modifications will be needed regarding the estimation of the convenience yields. 57 refs., 2 tabs., 7 figs., 1 append

  2. Adaptive Urban Stormwater Management Using a Two-stage Stochastic Optimization Model

    Science.gov (United States)

    Hung, F.; Hobbs, B. F.; McGarity, A. E.

    2014-12-01

    In many older cities, stormwater results in combined sewer overflows (CSOs) and consequent water quality impairments. Because of the expense of traditional approaches for controlling CSOs, cities are considering the use of green infrastructure (GI) to reduce runoff and pollutants. Examples of GI include tree trenches, rain gardens, green roofs, and rain barrels. However, the cost and effectiveness of GI are uncertain, especially at the watershed scale. We present a two-stage stochastic extension of the Stormwater Investment Strategy Evaluation (StormWISE) model (A. McGarity, JWRPM, 2012, 111-24) to explicitly model and optimize these uncertainties in an adaptive management framework. A two-stage model represents the immediate commitment of resources ("here & now") followed by later investment and adaptation decisions ("wait & see"). A case study is presented for Philadelphia, which intends to extensively deploy GI over the next two decades (PWD, "Green City, Clean Water - Implementation and Adaptive Management Plan," 2011). After first-stage decisions are made, the model updates the stochastic objective and constraints (learning). We model two types of "learning" about GI cost and performance. One assumes that learning occurs over time, is automatic, and does not depend on what has been done in stage one (basic model). The other considers learning resulting from active experimentation and learning-by-doing (advanced model). Both require expert probability elicitations, and learning from research and monitoring is modelled by Bayesian updating (as in S. Jacobi et al., JWRPM, 2013, 534-43). The model allocates limited financial resources to GI investments over time to achieve multiple objectives with a given reliability. Objectives include minimizing construction and O&M costs; achieving nutrient, sediment, and runoff volume targets; and community concerns, such as aesthetics, CO2 emissions, heat islands, and recreational values. CVaR (Conditional Value at Risk) and

  3. Multiplicative point process as a model of trading activity

    Science.gov (United States)

    Gontis, V.; Kaulakys, B.

    2004-11-01

    Signals consisting of a sequence of pulses show that inherent origin of the 1/ f noise is a Brownian fluctuation of the average interevent time between subsequent pulses of the pulse sequence. In this paper, we generalize the model of interevent time to reproduce a variety of self-affine time series exhibiting power spectral density S( f) scaling as a power of the frequency f. Furthermore, we analyze the relation between the power-law correlations and the origin of the power-law probability distribution of the signal intensity. We introduce a stochastic multiplicative model for the time intervals between point events and analyze the statistical properties of the signal analytically and numerically. Such model system exhibits power-law spectral density S( f)∼1/ fβ for various values of β, including β= {1}/{2}, 1 and {3}/{2}. Explicit expressions for the power spectra in the low-frequency limit and for the distribution density of the interevent time are obtained. The counting statistics of the events is analyzed analytically and numerically, as well. The specific interest of our analysis is related with the financial markets, where long-range correlations of price fluctuations largely depend on the number of transactions. We analyze the spectral density and counting statistics of the number of transactions. The model reproduces spectral properties of the real markets and explains the mechanism of power-law distribution of trading activity. The study provides evidence that the statistical properties of the financial markets are enclosed in the statistics of the time interval between trades. A multiplicative point process serves as a consistent model generating this statistics.

  4. Guideline validation in multiple trauma care through business process modeling.

    Science.gov (United States)

    Stausberg, Jürgen; Bilir, Hüseyin; Waydhas, Christian; Ruchholtz, Steffen

    2003-07-01

    Clinical guidelines can improve the quality of care in multiple trauma. In our Department of Trauma Surgery a specific guideline is available paper-based as a set of flowcharts. This format is appropriate for the use by experienced physicians but insufficient for electronic support of learning, workflow and process optimization. A formal and logically consistent version represented with a standardized meta-model is necessary for automatic processing. In our project we transferred the paper-based into an electronic format and analyzed the structure with respect to formal errors. Several errors were detected in seven error categories. The errors were corrected to reach a formally and logically consistent process model. In a second step the clinical content of the guideline was revised interactively using a process-modeling tool. Our study reveals that guideline development should be assisted by process modeling tools, which check the content in comparison to a meta-model. The meta-model itself could support the domain experts in formulating their knowledge systematically. To assure sustainability of guideline development a representation independent of specific applications or specific provider is necessary. Then, clinical guidelines could be used for eLearning, process optimization and workflow management additionally.

  5. Rank-based model selection for multiple ions quantum tomography

    International Nuclear Information System (INIS)

    Guţă, Mădălin; Kypraios, Theodore; Dryden, Ian

    2012-01-01

    The statistical analysis of measurement data has become a key component of many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional quantum systems, one needs to exploit prior information and the ‘sparsity’ properties of the experimental state in order to reduce the dimensionality of the estimation problem. In this paper we propose model selection as a general principle for finding the simplest, or most parsimonious explanation of the data, by fitting different models and choosing the estimator with the best trade-off between likelihood fit and model complexity. We apply two well established model selection methods—the Akaike information criterion (AIC) and the Bayesian information criterion (BIC)—two models consisting of states of fixed rank and datasets such as are currently produced in multiple ions experiments. We test the performance of AIC and BIC on randomly chosen low rank states of four ions, and study the dependence of the selected rank with the number of measurement repetitions for one ion states. We then apply the methods to real data from a four ions experiment aimed at creating a Smolin state of rank 4. By applying the two methods together with the Pearson χ 2 test we conclude that the data can be suitably described with a model whose rank is between 7 and 9. Additionally we find that the mean square error of the maximum likelihood estimator for pure states is close to that of the optimal over all possible measurements. (paper)

  6. Adaptations of a Yucatec Maya Multiple-Use Ecological Management Strategy to Ecotourism

    Directory of Open Access Journals (Sweden)

    Eduardo García-Frapolli

    2008-12-01

    Full Text Available Over the last 40 years, the Yucatan Peninsula has experienced the implementation and promotion of development programs that have economically and ecologically shaped this region of Mexico. Nowadays, tourist development has become the principal catalyst of social, economic, and ecological changes in the region. All these programs, which are based on a specialization rationale, have historically clashed with traditional Yucatec Maya management of natural resources. Using participant observation, informal and semi-structured interviews, and life-history interviews, we carried out an assessment of a Yucatec Maya natural resources management system implemented by three indigenous communities located within a natural protected area. The assessment, intended as an examination of the land-use practices and productive strategies currently implemented by households, was framed within an ecological-economic approach to ecosystems appropriation. To examine the influence of tourism on the multiple-use strategy, we contrasted productive activities among households engaged primarily in ecotourism with those more oriented toward traditional agriculture. Results show that households from these communities allocated an annual average of 586 work days to implement a total of 15 activities in five different land-use units, and that those figures vary significantly in accordance with households' productive strategy (agriculture oriented or service oriented. As the region is quickly becoming an important tourist destination and ecotourism is replacing many traditional activities, we discuss the need for a balance between traditional and alternative economic activities that will allow Yucatec Maya communities to diversify their economic options without compromising existing local management practices.

  7. Multiple Sclerosis Walking Scale-12, translation, adaptation and validation for the Persian language population.

    Science.gov (United States)

    Nakhostin Ansari, Noureddin; Naghdi, Soofia; Mohammadi, Roghaye; Hasson, Scott

    2015-02-01

    The Multiple Sclerosis Walking Scale-12 (MSWS-12) is a multi-item rating scale used to assess the perspectives of patients about the impact of MS on their walking ability. The aim of this study was to examine the reliability and validity of the MSWS-12 in Persian speaking patients with MS. The MSWS-12 questionnaire was translated into Persian language according to internationally adopted standards involving forward-backward translation, reviewed by an expert committee and tested on the pre-final version. In this cross-sectional study, 100 participants (50 patients with MS and 50 healthy subjects) were included. The MSWS-12 was administered twice 7 days apart to 30 patients with MS for test and retest reliability. Internal consistency reliability was Cronbach's α 0.96 for test and 0.97 for retest. There were no significant floor or ceiling effects. Test-retest reliability was excellent (intraclass correlation coefficient [ICC] agreement of 0.98, 95% CI, 0.95-0.99) confirming the reproducibility of the Persian MSWS-12. Construct validity using known group methods was demonstrated through a significant difference in the Persian MSWS-12 total score between the patients with MS and healthy subjects. Factor analysis extracted 2 latent factors (79.24% of the total variance). A second factor analysis suggested the 9-item Persian MSWS as a unidimensional scale for patients with MS. The Persian MSWS-12 was found to be valid and reliable for assessing walking ability in Persian speaking patients with MS. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. 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...

  9. Immunomodulatory effects and adaptive immune response to daratumumab in multiple myeloma

    DEFF Research Database (Denmark)

    Krejcik, Jakub; Casneuf, T.; Nijhof, I.

    2015-01-01

    (range) was 64 (31-84) years and median time from diagnosis was 5.12 (0.77-23.77) years. Seventy-six percent of patients had received >3 prior therapies and 91% were refractory to their last treatment. Clinical response was evaluated using IMWG consensus recommendations. Peripheral blood (PB) samples...... assays. T-cell subpopulation counts were modelled over time with linear mixed modelling. Two group comparisons were performed using non-parametric Wilcoxon rank sum tests. Results: Data from 148 patients receiving 16 mg/kg DARA in GEN501 (n = 42) and Sirius (n = 106) were analyzed for changes in immune...... response. In PB, robust mean increases in CD3+ (44%), CD4+ (32%) and CD8+ (62%) T-cell counts per 100 days were seen with DARA treatment. However, responding evaluable patients (n = 45) showed significantly greater increases from baseline than nonresponders (n = 93) in CD3+ (P = 0.00012), CD4+ (P = 0...

  10. A study of single multiplicative neuron model with nonlinear filters for hourly wind speed prediction

    International Nuclear Information System (INIS)

    Wu, Xuedong; Zhu, Zhiyu; Su, Xunliang; Fan, Shaosheng; Du, Zhaoping; Chang, Yanchao; Zeng, Qingjun

    2015-01-01

    Wind speed prediction is one important methods to guarantee the wind energy integrated into the whole power system smoothly. However, wind power has a non–schedulable nature due to the strong stochastic nature and dynamic uncertainty nature of wind speed. Therefore, wind speed prediction is an indispensable requirement for power system operators. Two new approaches for hourly wind speed prediction are developed in this study by integrating the single multiplicative neuron model and the iterated nonlinear filters for updating the wind speed sequence accurately. In the presented methods, a nonlinear state–space model is first formed based on the single multiplicative neuron model and then the iterated nonlinear filters are employed to perform dynamic state estimation on wind speed sequence with stochastic uncertainty. The suggested approaches are demonstrated using three cases wind speed data and are compared with autoregressive moving average, artificial neural network, kernel ridge regression based residual active learning and single multiplicative neuron model methods. Three types of prediction errors, mean absolute error improvement ratio and running time are employed for different models’ performance comparison. Comparison results from Tables 1–3 indicate that the presented strategies have much better performance for hourly wind speed prediction than other technologies. - Highlights: • Developed two novel hybrid modeling methods for hourly wind speed prediction. • Uncertainty and fluctuations of wind speed can be better explained by novel methods. • Proposed strategies have online adaptive learning ability. • Proposed approaches have shown better performance compared with existed approaches. • Comparison and analysis of two proposed novel models for three cases are provided

  11. 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.

  12. Assessments of Future Maize Yield Potential Changes in the Korean Peninsula Using Multiple Crop Models

    Science.gov (United States)

    Kim, S. H.; Lim, C. H.; Kim, J.; Lee, W. K.; Kafatos, M.

    2016-12-01

    The Korean Peninsula has unique agricultural environment due to the differences of political and socio-economical system between Republic of Korea (SK, hereafter) and Democratic Peoples' Republic of Korea (NK, hereafter). NK has been suffering lack of food supplies caused by natural disasters, land degradation and political failure. The neighboring developed country SK has better agricultural system but very low food self-sufficiency rate. Maize is an important crop in both countries since it is staple food for NK and SK is No. 2 maize importing country in the world after Japan. Therefore, evaluating maize yield potential (Yp) in the two distinct regions is essential to assess food security under climate change and variability. In this study, we utilized multiple process-based crop models, having ability of regional scale assessment, to evaluate maize Yp and assess the model uncertainties -EPIC, GEPIC, DSSAT, and APSIM model that has capability of regional scale expansion (apsimRegions). First we evaluated each crop model for 3 years from 2012 to 2014 using reanalysis data (RDAPS; Regional Data Assimilation and Prediction System produced by Korea Meteorological Agency) and observed yield data. Each model performances were compared over the different regions in the Korean Peninsula having different local climate characteristics. To quantify of the major influence of at each climate variables, we also conducted sensitivity test using 20 years of climatology in historical period from 1981 to 2000. Lastly, the multi-crop model ensemble analysis was performed for future period from 2031 to 2050. The required weather variables projected for mid-century were employed from COordinated Regional climate Downscaling EXperiment (CORDEX) East Asia. The high-resolution climate data were obtained from multiple regional climate models (RCM) driven by multiple climate scenarios projected from multiple global climate models (GCMs) in conjunction with multiple greenhouse gas

  13. Sparse Adaptive Iteratively-Weighted Thresholding Algorithm (SAITA for L p -Regularization Using the Multiple Sub-Dictionary Representation

    Directory of Open Access Journals (Sweden)

    Yunyi Li

    2017-12-01

    Full Text Available Both L 1 / 2 and L 2 / 3 are two typical non-convex regularizations of L p ( 0 < p < 1 , which can be employed to obtain a sparser solution than the L 1 regularization. Recently, the multiple-state sparse transformation strategy has been developed to exploit the sparsity in L 1 regularization for sparse signal recovery, which combines the iterative reweighted algorithms. To further exploit the sparse structure of signal and image, this paper adopts multiple dictionary sparse transform strategies for the two typical cases p ∈ { 1 / 2 ,   2 / 3 } based on an iterative L p thresholding algorithm and then proposes a sparse adaptive iterative-weighted L p thresholding algorithm (SAITA. Moreover, a simple yet effective regularization parameter is proposed to weight each sub-dictionary-based L p regularizer. Simulation results have shown that the proposed SAITA not only performs better than the corresponding L 1 algorithms but can also obtain a better recovery performance and achieve faster convergence than the conventional single-dictionary sparse transform-based L p case. Moreover, we conduct some applications about sparse image recovery and obtain good results by comparison with relative work.

  14. Validation and cross-cultural adaptation of sexual dysfunction modified scale in multiple sclerosis for Brazilian population

    Directory of Open Access Journals (Sweden)

    Raquel Ataíde Peres da Silva

    2015-08-01

    Full Text Available Multiple sclerosis (MS is a chronic inflammatory disease of the central nervous system (CNS. These patients suffer from various comorbidities, including sexual dysfunction (SD. The lesions of MS may affect regions of the CNS along the pathway of sexual response. The Multiple Sclerosis Intimacy and Sexuality Questionnaire-19 (MSISQ-19 is a scale that assesses sexual dysfunction. Adapt and validate the MSISQ-19 to Brazilian patients with MS. 204 individuals were evaluated, 134 patients with MS and 70 healthy persons for the control group. It was determined reproducibility, validity, internal consistency and sensitivity of the MSISQ-19-BR. Among patients with MS, 54.3% of male and 71.7% of female presented some kind of SD. In the control group the results were 12.5% and 19.5%, respectively. The MSISQ-19-BR is reproducible, reliable and valid for the Brazilian population and may be used as a tool for assessing the impact of sexual dysfunction in patients with MS.

  15. 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

  16. 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

  17. 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.

  18. A Hybrid Multiple Criteria Decision Making Model for Supplier Selection

    Directory of Open Access Journals (Sweden)

    Chung-Min Wu

    2013-01-01

    Full Text Available The sustainable supplier selection would be the vital part in the management of a sustainable supply chain. In this study, a hybrid multiple criteria decision making (MCDM model is applied to select optimal supplier. The fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Considering the interdependence among the selection criteria, analytic network process (ANP is then used to obtain their weights. To avoid calculation and additional pairwise comparisons of ANP, a technique for order preference by similarity to ideal solution (TOPSIS is used to rank the alternatives. The use of a combination of the fuzzy Delphi method, ANP, and TOPSIS, proposing an MCDM model for supplier selection, and applying these to a real case are the unique features of this study.

  19. 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.

  20. Multiple Scattering Model for Optical Coherence Tomography with Rytov Approximation

    KAUST Repository

    Li, Muxingzi

    2017-04-24

    Optical Coherence Tomography (OCT) is a coherence-gated, micrometer-resolution imaging technique that focuses a broadband near-infrared laser beam to penetrate into optical scattering media, e.g. biological tissues. The OCT resolution is split into two parts, with the axial resolution defined by half the coherence length, and the depth-dependent lateral resolution determined by the beam geometry, which is well described by a Gaussian beam model. The depth dependence of lateral resolution directly results in the defocusing effect outside the confocal region and restricts current OCT probes to small numerical aperture (NA) at the expense of lateral resolution near the focus. Another limitation on OCT development is the presence of a mixture of speckles due to multiple scatterers within the coherence length, and other random noise. Motivated by the above two challenges, a multiple scattering model based on Rytov approximation and Gaussian beam optics is proposed for the OCT setup. Some previous papers have adopted the first Born approximation with the assumption of small perturbation of the incident field in inhomogeneous media. The Rytov method of the same order with smooth phase perturbation assumption benefits from a wider spatial range of validity. A deconvolution method for solving the inverse problem associated with the first Rytov approximation is developed, significantly reducing the defocusing effect through depth and therefore extending the feasible range of NA.

  1. Resveratrol Neuroprotection in a Chronic Mouse Model of Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    Zoe eFonseca-Kelly

    2012-05-01

    Full Text Available Resveratrol is a naturally-occurring polyphenol that activates SIRT1, an NAD-dependent deacetylase. SRT501, a pharmaceutical formulation of resveratrol with enhanced systemic absorption, prevents neuronal loss without suppressing inflammation in mice with relapsing experimental autoimmune encephalomyelitis (EAE, a model of multiple sclerosis. In contrast, resveratrol has been reported to suppress inflammation in chronic EAE, although neuroprotective effects were not evaluated. The current studies examine potential neuroprotective and immunomodulatory effects of resveratrol in chronic EAE induced by immunization with myelin oligodendroglial glycoprotein peptide in C57/Bl6 mice. Effects of two distinct formulations of resveratrol administered daily orally were compared. Resveratrol delayed the onset of EAE compared to vehicle-treated EAE mice, but did not prevent or alter the phenotype of inflammation in spinal cords or optic nerves. Significant neuroprotective effects were observed, with higher numbers of retinal ganglion cells found in eyes of resveratrol-treated EAE mice with optic nerve inflammation. Results demonstrate that resveratrol prevents neuronal loss in this chronic demyelinating disease model, similar to its effects in relapsing EAE. Differences in immunosuppression compared with prior studies suggest that immunomodulatory effects may be limited and may depend on specific immunization parameters or timing of treatment. Importantly, neuroprotective effects can occur without immunosuppression, suggesting a potential additive benefit of resveratrol in combination with anti-inflammatory therapies for multiple sclerosis.

  2. Model for CO2 leakage including multiple geological layers and multiple leaky wells.

    Science.gov (United States)

    Nordbotten, Jan M; Kavetski, Dmitri; Celia, Michael A; Bachu, Stefan

    2009-02-01

    Geological storage of carbon dioxide (CO2) is likely to be an integral component of any realistic plan to reduce anthropogenic greenhouse gas emissions. In conjunction with large-scale deployment of carbon storage as a technology, there is an urgent need for tools which provide reliable and quick assessments of aquifer storage performance. Previously, abandoned wells from over a century of oil and gas exploration and production have been identified as critical potential leakage paths. The practical importance of abandoned wells is emphasized by the correlation of heavy CO2 emitters (typically associated with industrialized areas) to oil and gas producing regions in North America. Herein, we describe a novel framework for predicting the leakage from large numbers of abandoned wells, forming leakage paths connecting multiple subsurface permeable formations. The framework is designed to exploit analytical solutions to various components of the problem and, ultimately, leads to a grid-free approximation to CO2 and brine leakage rates, as well as fluid distributions. We apply our model in a comparison to an established numerical solverforthe underlying governing equations. Thereafter, we demonstrate the capabilities of the model on typical field data taken from the vicinity of Edmonton, Alberta. This data set consists of over 500 wells and 7 permeable formations. Results show the flexibility and utility of the solution methods, and highlight the role that analytical and semianalytical solutions can play in this important problem.

  3. Cultural adaptation and validation of a peninsular Spanish version of the MSTCQ© (Multiple Sclerosis Treatment Concerns Questionnaire).

    Science.gov (United States)

    Muntéis Olivas, E; Navarro Mascarell, G; Meca Lallana, J; Maestre Martínez, A; Pérez Sempere, Á; Gracia Gil, J; Pato Pato, A

    Although subcutaneous treatments for multiple sclerosis (MS) have been shown to be effective, adverse reactions and pain may adversely affect treatment satisfaction and adherence. This study presents an adapted and validated Spanish version of the Multiple Sclerosis Treatment Concerns Questionnaire © (MSTCQ), which evaluates satisfaction with the injection device (ID) across 4 domains: injection system (A), side effects (B) (flu-like symptoms, reactions, and satisfaction), experience with treatment (C) and benefits (D). Two study phases: 1) Cultural adaptation process with input from experts (n=6) and patients (n=30). 2) Validation obtained by means of an observational, cross-sectional, multi-centre study evaluating 143 adult MS patients using an ID. Tools employed: MSTCQ © , Patient-Reported Indices for Multiple Sclerosis (PRIMUS © ), and Treatment Satisfaction Questionnaire for Medication (TSQM © ). Psychometric properties: Feasibility (percentage of valid cases and floor/ceiling effects); Reliability (Cronbach α) and test-retest correlation (n=41, intraclass correlation coefficient, ICC); and construct validity (factor analysis of domains A and B) and convergent validity (Spearman rank-order correlation for MSTCQ © vs TSQM © ). Mean age (SD) was 41.94 (10.47) years, 63% of the group were women, and 88.11% presented relapsing-remitting MS. Mean (SD) EDSS score was 2.68 (1.82) points. MSTCQ © completion was high (0%-2.80% missing data). Internal consistency was high at α=0.89 for the total score (A+B) and α=0.76, 0.89, and 0.92 for domains A, B, and C, respectively. The version demonstrated excellent test-retest reliability for the total (ICC=0.98) and for domains A, B, and C: ICC=0.82, 0.97, and 0.89, respectively. Factor analysis corroborated the internal structure of the original questionnaire. The association between total and domain scores on both the MSTCQ © and the TSQM © was moderately strong (Rho=0.42-0.74) and significant (P<.05 and P<.01

  4. 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.

  5. 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

  6. 3D fluid-structure modelling and vibration analysis for fault diagnosis of Francis turbine using multiple ANN and multiple ANFIS

    Science.gov (United States)

    Saeed, R. A.; Galybin, A. N.; Popov, V.

    2013-01-01

    This paper discusses condition monitoring and fault diagnosis in Francis turbine based on integration of numerical modelling with several different artificial intelligence (AI) techniques. In this study, a numerical approach for fluid-structure (turbine runner) analysis is presented. The results of numerical analysis provide frequency response functions (FRFs) data sets along x-, y- and z-directions under different operating load and different position and size of faults in the structure. To extract features and reduce the dimensionality of the obtained FRF data, the principal component analysis (PCA) has been applied. Subsequently, the extracted features are formulated and fed into multiple artificial neural networks (ANN) and multiple adaptive neuro-fuzzy inference systems (ANFIS) in order to identify the size and position of the damage in the runner and estimate the turbine operating conditions. The results demonstrated the effectiveness of this approach and provide satisfactory accuracy even when the input data are corrupted with certain level of noise.

  7. A Multiple Indicators Multiple Causes (MIMIC) model of internal barriers to drug treatment in China.

    Science.gov (United States)

    Qi, Chang; Kelly, Brian C; Liao, Yanhui; He, Haoyu; Luo, Tao; Deng, Huiqiong; Liu, Tieqiao; Hao, Wei; Wang, Jichuan

    2015-03-01

    Although evidence exists for distinct barriers to drug abuse treatment (BDATs), investigations of their inter-relationships and the effect of individual characteristics on the barrier factors have been sparse, especially in China. A Multiple Indicators Multiple Causes (MIMIC) model is applied for this target. A sample of 262 drug users were recruited from three drug rehabilitation centers in Hunan Province, China. We applied a MIMIC approach to investigate the effect of gender, age, marital status, education, primary substance use, duration of primary drug use, and drug treatment experience on the internal barrier factors: absence of problem (AP), negative social support (NSS), fear of treatment (FT), and privacy concerns (PC). Drug users of various characteristics were found to report different internal barrier factors. Younger participants were more likely to report NSS (-0.19, p=0.038) and PC (-0.31, p<0.001). Compared to other drug users, ice users were more likely to report AP (0.44, p<0.001) and NSS (0.25, p=0.010). Drug treatment experiences related to AP (0.20, p=0.012). In addition, differential item functioning (DIF) occurred in three items when participant from groups with different duration of drug use, ice use, or marital status. Individual characteristics had significant effects on internal barriers to drug treatment. On this basis, BDAT perceived by different individuals could be assessed before tactics were utilized to successfully remove perceived barriers to drug treatment. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  8. Multiple-relaxation-time lattice Boltzmann model for compressible fluids

    International Nuclear Information System (INIS)

    Chen Feng; Xu Aiguo; Zhang Guangcai; Li Yingjun

    2011-01-01

    We present an energy-conserving multiple-relaxation-time finite difference lattice Boltzmann model for compressible flows. The collision step is first calculated in the moment space and then mapped back to the velocity space. The moment space and corresponding transformation matrix are constructed according to the group representation theory. Equilibria of the nonconserved moments are chosen according to the need of recovering compressible Navier-Stokes equations through the Chapman-Enskog expansion. Numerical experiments showed that compressible flows with strong shocks can be well simulated by the present model. The new model works for both low and high speeds compressible flows. It contains more physical information and has better numerical stability and accuracy than its single-relaxation-time version. - Highlights: → We present an energy-conserving MRT finite-difference LB model. → The moment space is constructed according to the group representation theory. → The new model works for both low and high speeds compressible flows. → It has better numerical stability and wider applicable range than its SRT version.

  9. Optimal Retail Price Model for Partial Consignment to Multiple Retailers

    Directory of Open Access Journals (Sweden)

    Po-Yu Chen

    2017-01-01

    Full Text Available This paper investigates the product pricing decision-making problem under a consignment stock policy in a two-level supply chain composed of one supplier and multiple retailers. The effects of the supplier’s wholesale prices and its partial inventory cost absorption of the retail prices of retailers with different market shares are investigated. In the partial product consignment model this paper proposes, the seller and the retailers each absorb part of the inventory costs. This model also provides general solutions for the complete product consignment and the traditional policy that adopts no product consignment. In other words, both the complete consignment and nonconsignment models are extensions of the proposed model (i.e., special cases. Research results indicated that the optimal retail price must be between 1/2 (50% and 2/3 (66.67% times the upper limit of the gross profit. This study also explored the results and influence of parameter variations on optimal retail price in the model.

  10. 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

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. Metabolomic analysis reveals key metabolites related to the rapid adaptation of Saccharomyce cerevisiae to multiple inhibitors of furfural, acetic acid, and phenol.

    Science.gov (United States)

    Wang, Xin; Li, Bing-Zhi; Ding, Ming-Zhu; Zhang, Wei-Wen; Yuan, Ying-Jin

    2013-03-01

    During hydrolysis of lignocellulosic biomass, a broad range of inhibitors are generated, which interfere with yeast growth and bioethanol production. In order to improve the strain tolerance to multiple inhibitors--acetic acid, furfural, and phenol (three representative lignocellulose-derived inhibitors) and uncover the underlying tolerant mechanism, an adaptation experiment was performed in which the industrial Saccharomyces cerevisiae was cultivated repeatedly in a medium containing multiple inhibitors. The adaptation occurred quickly, accompanied with distinct increase in growth rate, glucose utilization rate, furfural metabolism rate, and ethanol yield, only after the first transfer. A similar rapid adaptation was also observed for the lab strains of BY4742 and BY4743. The metabolomic analysis was employed to investigate the responses of the industrial S. cereviaise to three inhibitors during the adaptation. The results showed that higher levels of 2-furoic acid, 2, 3-butanediol, intermediates in glycolytic pathway, and amino acids derived from glycolysis, were discovered in the adapted strains, suggesting that enhanced metabolic activity in these pathways may relate to resistance against inhibitors. Additionally, through single-gene knockouts, several genes related to alanine metabolism, GABA shunt, and glycerol metabolism were verified to be crucial for the resistance to multiple inhibitors. This study provides new insights into the tolerance mechanism against multiple inhibitors, and guides for the improvement of tolerant ethanologenic yeast strains for lignocellulose-bioethanol fermentation.

  16. A latent class multiple constraint multiple discrete-continuous extreme value model of time use and goods consumption.

    Science.gov (United States)

    2016-06-01

    This paper develops a microeconomic theory-based multiple discrete continuous choice model that considers: (a) that both goods consumption and time allocations (to work and non-work activities) enter separately as decision variables in the utility fu...

  17. Using hidden Markov models to align multiple sequences.

    Science.gov (United States)

    Mount, David W

    2009-07-01

    A hidden Markov model (HMM) is a probabilistic model of a multiple sequence alignment (msa) of proteins. In the model, each column of symbols in the alignment is represented by a frequency distribution of the symbols (called a "state"), and insertions and deletions are represented by other states. One moves through the model along a particular path from state to state in a Markov chain (i.e., random choice of next move), trying to match a given sequence. The next matching symbol is chosen from each state, recording its probability (frequency) and also the probability of going to that state from a previous one (the transition probability). State and transition probabilities are multiplied to obtain a probability of the given sequence. The hidden nature of the HMM is due to the lack of information about the value of a specific state, which is instead represented by a probability distribution over all possible values. This article discusses the advantages and disadvantages of HMMs in msa and presents algorithms for calculating an HMM and the conditions for producing the best HMM.

  18. Analysis and application of opinion model with multiple topic interactions.

    Science.gov (United States)

    Xiong, Fei; Liu, Yun; Wang, Liang; Wang, Ximeng

    2017-08-01

    To reveal heterogeneous behaviors of opinion evolution in different scenarios, we propose an opinion model with topic interactions. Individual opinions and topic features are represented by a multidimensional vector. We measure an agent's action towards a specific topic by the product of opinion and topic feature. When pairs of agents interact for a topic, their actions are introduced to opinion updates with bounded confidence. Simulation results show that a transition from a disordered state to a consensus state occurs at a critical point of the tolerance threshold, which depends on the opinion dimension. The critical point increases as the dimension of opinions increases. Multiple topics promote opinion interactions and lead to the formation of macroscopic opinion clusters. In addition, more topics accelerate the evolutionary process and weaken the effect of network topology. We use two sets of large-scale real data to evaluate the model, and the results prove its effectiveness in characterizing a real evolutionary process. Our model achieves high performance in individual action prediction and even outperforms state-of-the-art methods. Meanwhile, our model has much smaller computational complexity. This paper provides a demonstration for possible practical applications of theoretical opinion dynamics.

  19. 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.

  20. 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

  1. 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

  2. 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…

  3. 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)

  4. Improving the use of crop models for risk assessment and climate change adaptation.

    Science.gov (United States)

    Challinor, Andrew J; Müller, Christoph; Asseng, Senthold; Deva, Chetan; Nicklin, Kathryn Jane; Wallach, Daniel; Vanuytrecht, Eline; Whitfield, Stephen; Ramirez-Villegas, Julian; Koehler, Ann-Kristin

    2018-01-01

    Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Our analysis drew on the other papers in this special issue, and on our experience in the UK Climate Change Risk Assessment 2017 and the MACSUR, AgMIP and ISIMIP projects. The criteria were used to assess how improvements could be made to the framing of climate change risks, and to outline the good practice and new developments that are needed to improve risk assessment. Key areas of good practice include: i. the development, running and documentation of crop models, with attention given to issues of spatial scale and complexity; ii. the methods used to form crop-climate ensembles, which can be based on model skill and/or spread; iii. the methods used to assess adaptation, which need broadening to account for technological development and to reflect the full range options available. The analysis highlights the limitations of focussing only on projections of future impacts and adaptation options using pre-determined time slices. Whilst this long-standing approach may remain an essential component of risk assessments, we identify three further key components: 1.Working with stakeholders to identify the timing of risks. What are the key vulnerabilities of food systems and what does crop-climate modelling tell us about when those systems are at risk?2.Use of multiple methods that critically assess the use of climate model output and avoid any presumption that analyses should begin and end with gridded output.3.Increasing transparency and inter-comparability in risk assessments. Whilst studies frequently produce ranges that quantify uncertainty, the assumptions

  5. Direction of Effects in Multiple Linear Regression Models.

    Science.gov (United States)

    Wiedermann, Wolfgang; von Eye, Alexander

    2015-01-01

    Previous studies analyzed asymmetric properties of the Pearson correlation coefficient using higher than second order moments. These asymmetric properties can be used to determine the direction of dependence in a linear regression setting (i.e., establish which of two variables is more likely to be on the outcome side) within the framework of cross-sectional observational data. Extant approaches are restricted to the bivariate regression case. The present contribution extends the direction of dependence methodology to a multiple linear regression setting by analyzing distributional properties of residuals of competing multiple regression models. It is shown that, under certain conditions, the third central moments of estimated regression residuals can be used to decide upon direction of effects. In addition, three different approaches for statistical inference are discussed: a combined D'Agostino normality test, a skewness difference test, and a bootstrap difference test. Type I error and power of the procedures are assessed using Monte Carlo simulations, and an empirical example is provided for illustrative purposes. In the discussion, issues concerning the quality of psychological data, possible extensions of the proposed methods to the fourth central moment of regression residuals, and potential applications are addressed.

  6. Investigating multiple solutions in the constrained minimal supersymmetric standard model

    Energy Technology Data Exchange (ETDEWEB)

    Allanach, B.C. [DAMTP, CMS, University of Cambridge,Wilberforce Road, Cambridge, CB3 0HA (United Kingdom); George, Damien P. [DAMTP, CMS, University of Cambridge,Wilberforce Road, Cambridge, CB3 0HA (United Kingdom); Cavendish Laboratory, University of Cambridge,JJ Thomson Avenue, Cambridge, CB3 0HE (United Kingdom); Nachman, Benjamin [SLAC, Stanford University,2575 Sand Hill Rd, Menlo Park, CA 94025 (United States)

    2014-02-07

    Recent work has shown that the Constrained Minimal Supersymmetric Standard Model (CMSSM) can possess several distinct solutions for certain values of its parameters. The extra solutions were not previously found by public supersymmetric spectrum generators because fixed point iteration (the algorithm used by the generators) is unstable in the neighbourhood of these solutions. The existence of the additional solutions calls into question the robustness of exclusion limits derived from collider experiments and cosmological observations upon the CMSSM, because limits were only placed on one of the solutions. Here, we map the CMSSM by exploring its multi-dimensional parameter space using the shooting method, which is not subject to the stability issues which can plague fixed point iteration. We are able to find multiple solutions where in all previous literature only one was found. The multiple solutions are of two distinct classes. One class, close to the border of bad electroweak symmetry breaking, is disfavoured by LEP2 searches for neutralinos and charginos. The other class has sparticles that are heavy enough to evade the LEP2 bounds. Chargino masses may differ by up to around 10% between the different solutions, whereas other sparticle masses differ at the sub-percent level. The prediction for the dark matter relic density can vary by a hundred percent or more between the different solutions, so analyses employing the dark matter constraint are incomplete without their inclusion.

  7. Adaption of Ulva pertusa to multiple-contamination of heavy metals and nutrients: Biological mechanism of outbreak of Ulva sp. green tide.

    Science.gov (United States)

    Ge, Changzi; Yu, Xiru; Kan, Manman; Qu, Chunfeng

    2017-12-15

    The multiple-contamination of heavy metals and nutrients worsens increasingly and Ulva sp. green tide occurs almost simultaneously. To reveal the biological mechanism for outbreak of the green tide, Ulva pertusa was exposed to seven-day-multiple-contamination. The relation between pH variation (V pH ), Chl a content, ratio of (Chl a content)/(Chl b content) (R chla/chlb ), SOD activity of U. pertusa (A SOD ) and contamination concentration is [Formula: see text] (pcontamination concentrations of seawaters where Ulva sp. green tide occurred and the contamination concentrations set in the present work, U. pertusa can adapt to multiple-contaminations in these waters. Thus, the adaption to multiple-contamination may be one biological mechanism for the outbreak of Ulva sp. green tide. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Beating Heart Motion Accurate Prediction Method Based on Interactive Multiple Model: An Information Fusion Approach

    Science.gov (United States)

    Xie, Weihong; Yu, Yang

    2017-01-01

    Robot-assisted motion compensated beating heart surgery has the advantage over the conventional Coronary Artery Bypass Graft (CABG) in terms of reduced trauma to the surrounding structures that leads to shortened recovery time. The severe nonlinear and diverse nature of irregular heart rhythm causes enormous difficulty for the robot to realize the clinic requirements, especially under arrhythmias. In this paper, we propose a fusion prediction framework based on Interactive Multiple Model (IMM) estimator, allowing each model to cover a distinguishing feature of the heart motion in underlying dynamics. We find that, at normal state, the nonlinearity of the heart motion with slow time-variant changing dominates the beating process. When an arrhythmia occurs, the irregularity mode, the fast uncertainties with random patterns become the leading factor of the heart motion. We deal with prediction problem in the case of arrhythmias by estimating the state with two behavior modes which can adaptively “switch” from one to the other. Also, we employed the signal quality index to adaptively determine the switch transition probability in the framework of IMM. We conduct comparative experiments to evaluate the proposed approach with four distinguished datasets. The test results indicate that the new proposed approach reduces prediction errors significantly. PMID:29124062

  9. Beating Heart Motion Accurate Prediction Method Based on Interactive Multiple Model: An Information Fusion Approach

    Directory of Open Access Journals (Sweden)

    Fan Liang

    2017-01-01

    Full Text Available Robot-assisted motion compensated beating heart surgery has the advantage over the conventional Coronary Artery Bypass Graft (CABG in terms of reduced trauma to the surrounding structures that leads to shortened recovery time. The severe nonlinear and diverse nature of irregular heart rhythm causes enormous difficulty for the robot to realize the clinic requirements, especially under arrhythmias. In this paper, we propose a fusion prediction framework based on Interactive Multiple Model (IMM estimator, allowing each model to cover a distinguishing feature of the heart motion in underlying dynamics. We find that, at normal state, the nonlinearity of the heart motion with slow time-variant changing dominates the beating process. When an arrhythmia occurs, the irregularity mode, the fast uncertainties with random patterns become the leading factor of the heart motion. We deal with prediction problem in the case of arrhythmias by estimating the state with two behavior modes which can adaptively “switch” from one to the other. Also, we employed the signal quality index to adaptively determine the switch transition probability in the framework of IMM. We conduct comparative experiments to evaluate the proposed approach with four distinguished datasets. The test results indicate that the new proposed approach reduces prediction errors significantly.

  10. Characterising and modelling regolith stratigraphy using multiple geophysical techniques

    Science.gov (United States)

    Thomas, M.; Cremasco, D.; Fotheringham, T.; Hatch, M. A.; Triantifillis, J.; Wilford, J.

    2013-12-01

    Regolith is the weathered, typically mineral-rich layer from fresh bedrock to land surface. It encompasses soil (A, E and B horizons) that has undergone pedogenesis. Below is the weathered C horizon that retains at least some of the original rocky fabric and structure. At the base of this is the lower regolith boundary of continuous hard bedrock (the R horizon). Regolith may be absent, e.g. at rocky outcrops, or may be many 10's of metres deep. Comparatively little is known about regolith, and critical questions remain regarding composition and characteristics - especially deeper where the challenge of collecting reliable data increases with depth. In Australia research is underway to characterise and map regolith using consistent methods at scales ranging from local (e.g. hillslope) to continental scales. These efforts are driven by many research needs, including Critical Zone modelling and simulation. Pilot research in South Australia using digitally-based environmental correlation techniques modelled the depth to bedrock to 9 m for an upland area of 128 000 ha. One finding was the inability to reliably model local scale depth variations over horizontal distances of 2 - 3 m and vertical distances of 1 - 2 m. The need to better characterise variations in regolith to strengthen models at these fine scales was discussed. Addressing this need, we describe high intensity, ground-based multi-sensor geophysical profiling of three hillslope transects in different regolith-landscape settings to characterise fine resolution (i.e. a number of frequencies; multiple frequency, multiple coil electromagnetic induction; and high resolution resistivity. These were accompanied by georeferenced, closely spaced deep cores to 9 m - or to core refusal. The intact cores were sub-sampled to standard depths and analysed for regolith properties to compile core datasets consisting of: water content; texture; electrical conductivity; and weathered state. After preprocessing (filtering, geo

  11. Interaction of multiple biomimetic antimicrobial polymers with model bacterial membranes

    Energy Technology Data Exchange (ETDEWEB)

    Baul, Upayan, E-mail: upayanb@imsc.res.in; Vemparala, Satyavani, E-mail: vani@imsc.res.in [The Institute of Mathematical Sciences, C.I.T. Campus, Taramani, Chennai 600113 (India); Kuroda, Kenichi, E-mail: kkuroda@umich.edu [Department of Biologic and Materials Sciences, University of Michigan School of Dentistry, Ann Arbor, Michigan 48109 (United States)

    2014-08-28

    Using atomistic molecular dynamics simulations, interaction of multiple synthetic random copolymers based on methacrylates on prototypical bacterial membranes is investigated. The simulations show that the cationic polymers form a micellar aggregate in water phase and the aggregate, when interacting with the bacterial membrane, induces clustering of oppositely charged anionic lipid molecules to form clusters and enhances ordering of lipid chains. The model bacterial membrane, consequently, develops lateral inhomogeneity in membrane thickness profile compared to polymer-free system. The individual polymers in the aggregate are released into the bacterial membrane in a phased manner and the simulations suggest that the most probable location of the partitioned polymers is near the 1-palmitoyl-2-oleoyl-phosphatidylglycerol (POPG) clusters. The partitioned polymers preferentially adopt facially amphiphilic conformations at lipid-water interface, despite lacking intrinsic secondary structures such as α-helix or β-sheet found in naturally occurring antimicrobial peptides.

  12. The intergenerational multiple deficit model and the case of dyslexia

    Directory of Open Access Journals (Sweden)

    Elsje evan Bergen

    2014-06-01

    Full Text Available Which children go on to develop dyslexia? Since dyslexia has a multifactorial aetiology, this question can be restated as: What are the factors that put children at high risk for developing dyslexia? It is argued that a useful theoretical framework to address this question is Pennington’s (2006 multiple deficit model (MDM. This model replaces models that attribute dyslexia to a single underlying cause. Subsequently, the generalist genes hypothesis for learning (disabilities (Plomin & Kovas, 2005 is described and integrated with the MDM. Finally, findings are presented from a longitudinal study with children at family risk for dyslexia. Such studies can contribute to testing and specifying the MDM. In this study, risk factors at both the child and family level were investigated. This led to the proposed intergenerational MDM, in which both parents confer liability via intertwined genetic and environmental pathways. Future scientific directions are discussed to investigate parent-offspring resemblance and transmission patterns, which will shed new light on disorder aetiology.

  13. An Advanced N -body Model for Interacting Multiple Stellar Systems

    Energy Technology Data Exchange (ETDEWEB)

    Brož, Miroslav [Astronomical Institute of the Charles University, Faculty of Mathematics and Physics, V Holešovičkách 2, CZ-18000 Praha 8 (Czech Republic)

    2017-06-01

    We construct an advanced model for interacting multiple stellar systems in which we compute all trajectories with a numerical N -body integrator, namely the Bulirsch–Stoer from the SWIFT package. We can then derive various observables: astrometric positions, radial velocities, minima timings (TTVs), eclipse durations, interferometric visibilities, closure phases, synthetic spectra, spectral energy distribution, and even complete light curves. We use a modified version of the Wilson–Devinney code for the latter, in which the instantaneous true phase and inclination of the eclipsing binary are governed by the N -body integration. If all of these types of observations are at one’s disposal, a joint χ {sup 2} metric and an optimization algorithm (a simplex or simulated annealing) allow one to search for a global minimum and construct very robust models of stellar systems. At the same time, our N -body model is free from artifacts that may arise if mutual gravitational interactions among all components are not self-consistently accounted for. Finally, we present a number of examples showing dynamical effects that can be studied with our code and we discuss how systematic errors may affect the results (and how to prevent this from happening).

  14. Negative binomial models for abundance estimation of multiple closed populations

    Science.gov (United States)

    Boyce, Mark S.; MacKenzie, Darry I.; Manly, Bryan F.J.; Haroldson, Mark A.; Moody, David W.

    2001-01-01

    Counts of uniquely identified individuals in a population offer opportunities to estimate abundance. However, for various reasons such counts may be burdened by heterogeneity in the probability of being detected. Theoretical arguments and empirical evidence demonstrate that the negative binomial distribution (NBD) is a useful characterization for counts from biological populations with heterogeneity. We propose a method that focuses on estimating multiple populations by simultaneously using a suite of models derived from the NBD. We used this approach to estimate the number of female grizzly bears (Ursus arctos) with cubs-of-the-year in the Yellowstone ecosystem, for each year, 1986-1998. Akaike's Information Criteria (AIC) indicated that a negative binomial model with a constant level of heterogeneity across all years was best for characterizing the sighting frequencies of female grizzly bears. A lack-of-fit test indicated the model adequately described the collected data. Bootstrap techniques were used to estimate standard errors and 95% confidence intervals. We provide a Monte Carlo technique, which confirms that the Yellowstone ecosystem grizzly bear population increased during the period 1986-1998.

  15. A diagnostic tree model for polytomous responses with multiple strategies.

    Science.gov (United States)

    Ma, Wenchao

    2018-04-23

    Constructed-response items have been shown to be appropriate for cognitively diagnostic assessments because students' problem-solving procedures can be observed, providing direct evidence for making inferences about their proficiency. However, multiple strategies used by students make item scoring and psychometric analyses challenging. This study introduces the so-called two-digit scoring scheme into diagnostic assessments to record both students' partial credits and their strategies. This study also proposes a diagnostic tree model (DTM) by integrating the cognitive diagnosis models with the tree model to analyse the items scored using the two-digit rubrics. Both convergent and divergent tree structures are considered to accommodate various scoring rules. The MMLE/EM algorithm is used for item parameter estimation of the DTM, and has been shown to provide good parameter recovery under varied conditions in a simulation study. A set of data from TIMSS 2007 mathematics assessment is analysed to illustrate the use of the two-digit scoring scheme and the DTM. © 2018 The British Psychological Society.

  16. A minimal model for multiple epidemics and immunity spreading.

    Directory of Open Access Journals (Sweden)

    Kim Sneppen

    Full Text Available Pathogens and parasites are ubiquitous in the living world, being limited only by availability of suitable hosts. The ability to transmit a particular disease depends on competing infections as well as on the status of host immunity. Multiple diseases compete for the same resource and their fate is coupled to each other. Such couplings have many facets, for example cross-immunization between related influenza strains, mutual inhibition by killing the host, or possible even a mutual catalytic effect if host immunity is impaired. We here introduce a minimal model for an unlimited number of unrelated pathogens whose interaction is simplified to simple mutual exclusion. The model incorporates an ongoing development of host immunity to past diseases, while leaving the system open for emergence of new diseases. The model exhibits a rich dynamical behavior with interacting infection waves, leaving broad trails of immunization in the host population. This obtained immunization pattern depends only on the system size and on the mutation rate that initiates new diseases.

  17. A minimal model for multiple epidemics and immunity spreading.

    Science.gov (United States)

    Sneppen, Kim; Trusina, Ala; Jensen, Mogens H; Bornholdt, Stefan

    2010-10-18

    Pathogens and parasites are ubiquitous in the living world, being limited only by availability of suitable hosts. The ability to transmit a particular disease depends on competing infections as well as on the status of host immunity. Multiple diseases compete for the same resource and their fate is coupled to each other. Such couplings have many facets, for example cross-immunization between related influenza strains, mutual inhibition by killing the host, or possible even a mutual catalytic effect if host immunity is impaired. We here introduce a minimal model for an unlimited number of unrelated pathogens whose interaction is simplified to simple mutual exclusion. The model incorporates an ongoing development of host immunity to past diseases, while leaving the system open for emergence of new diseases. The model exhibits a rich dynamical behavior with interacting infection waves, leaving broad trails of immunization in the host population. This obtained immunization pattern depends only on the system size and on the mutation rate that initiates new diseases.

  18. Modeling Pan Evaporation for Kuwait by Multiple Linear Regression

    Science.gov (United States)

    Almedeij, Jaber

    2012-01-01

    Evaporation is an important parameter for many projects related to hydrology and water resources systems. This paper constitutes the first study conducted in Kuwait to obtain empirical relations for the estimation of daily and monthly pan evaporation as functions of available meteorological data of temperature, relative humidity, and wind speed. The data used here for the modeling are daily measurements of substantial continuity coverage, within a period of 17 years between January 1993 and December 2009, which can be considered representative of the desert climate of the urban zone of the country. Multiple linear regression technique is used with a procedure of variable selection for fitting the best model forms. The correlations of evaporation with temperature and relative humidity are also transformed in order to linearize the existing curvilinear patterns of the data by using power and exponential functions, respectively. The evaporation models suggested with the best variable combinations were shown to produce results that are in a reasonable agreement with observation values. PMID:23226984

  19. Hyperspectral material identification on radiance data using single-atmosphere or multiple-atmosphere modeling

    Science.gov (United States)

    Mariano, Adrian V.; Grossmann, John M.

    2010-11-01

    Reflectance-domain methods convert hyperspectral data from radiance to reflectance using an atmospheric compensation model. Material detection and identification are performed by comparing the compensated data to target reflectance spectra. We introduce two radiance-domain approaches, Single atmosphere Adaptive Cosine Estimator (SACE) and Multiple atmosphere ACE (MACE) in which the target reflectance spectra are instead converted into sensor-reaching radiance using physics-based models. For SACE, known illumination and atmospheric conditions are incorporated in a single atmospheric model. For MACE the conditions are unknown so the algorithm uses many atmospheric models to cover the range of environmental variability, and it approximates the result using a subspace model. This approach is sometimes called the invariant method, and requires the choice of a subspace dimension for the model. We compare these two radiance-domain approaches to a Reflectance-domain ACE (RACE) approach on a HYDICE image featuring concealed materials. All three algorithms use the ACE detector, and all three techniques are able to detect most of the hidden materials in the imagery. For MACE we observe a strong dependence on the choice of the material subspace dimension. Increasing this value can lead to a decline in performance.

  20. 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.

  1. 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.

  2. Decreasing Multicollinearity: A Method for Models with Multiplicative Functions.

    Science.gov (United States)

    Smith, Kent W.; Sasaki, M. S.

    1979-01-01

    A method is proposed for overcoming the problem of multicollinearity in multiple regression equations where multiplicative independent terms are entered. The method is not a ridge regression solution. (JKS)

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  7. 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%.

  8. 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

  9. Shared mental models of integrated care: aligning multiple stakeholder perspectives.

    Science.gov (United States)

    Evans, Jenna M; Baker, G Ross

    2012-01-01

    Health service organizations and professionals are under increasing pressure to work together to deliver integrated patient care. A common understanding of integration strategies may facilitate the delivery of integrated care across inter-organizational and inter-professional boundaries. This paper aims to build a framework for exploring and potentially aligning multiple stakeholder perspectives of systems integration. The authors draw from the literature on shared mental models, strategic management and change, framing, stakeholder management, and systems theory to develop a new construct, Mental Models of Integrated Care (MMIC), which consists of three types of mental models, i.e. integration-task, system-role, and integration-belief. The MMIC construct encompasses many of the known barriers and enablers to integrating care while also providing a comprehensive, theory-based framework of psychological factors that may influence inter-organizational and inter-professional relations. While the existing literature on integration focuses on optimizing structures and processes, the MMIC construct emphasizes the convergence and divergence of stakeholders' knowledge and beliefs, and how these underlying cognitions influence interactions (or lack thereof) across the continuum of care. MMIC may help to: explain what differentiates effective from ineffective integration initiatives; determine system readiness to integrate; diagnose integration problems; and develop interventions for enhancing integrative processes and ultimately the delivery of integrated care. Global interest and ongoing challenges in integrating care underline the need for research on the mental models that characterize the behaviors of actors within health systems; the proposed framework offers a starting point for applying a cognitive perspective to health systems integration.

  10. 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

  11. 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

  12. Therapeutic effects of D-aspartate in a mouse model of multiple sclerosis

    Directory of Open Access Journals (Sweden)

    Sanaz Afraei

    2017-07-01

    Full Text Available Experimental autoimmune encephalomyelitis (EAE is an animal model of multiple sclerosis. EAE is mainly mediated by adaptive and innate immune responses that leads to an inflammatory demyelization and axonal damage. The aim of the present research was to examine the therapeutic efficacy of D-aspartic acid (D-Asp on a mouse EAE model. EAE induction was performed in female C57BL/6 mice by myelin 40 oligodendrocyte glycoprotein (35-55 in a complete Freund's adjuvant emulsion, and D-Asp was used to test its efficiency in the reduction of EAE. During the course of study, clinical evaluation was assessed, and on Day 21, post-immunization blood samples were taken from the heart of mice for the evaluation of interleukin 6 and other chemical molecules. The mice were sacrificed, and their brain and cerebellum were removed for histological analysis. Our findings indicated that D-Asp had beneficial effects on EAE by attenuation in the severity and delay in the onset of the disease. Histological analysis showed that treatment with D-Asp can reduce inflammation. Moreover, in D-Asp-treated mice, the serum level of interleukin 6 was significantly lower than that in control animals, whereas the total antioxidant capacity was significantly higher. The data indicates that D-Asp possess neuroprotective property to prevent the onset of the multiple sclerosis.

  13. 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.

  14. Eye Movement Abnormalities in Multiple Sclerosis: Pathogenesis, Modeling, and Treatment

    Directory of Open Access Journals (Sweden)

    Alessandro Serra

    2018-02-01

    Full Text Available Multiple sclerosis (MS commonly causes eye movement abnormalities that may have a significant impact on patients’ disability. Inflammatory demyelinating lesions, especially occurring in the posterior fossa, result in a wide range of disorders, spanning from acquired pendular nystagmus (APN to internuclear ophthalmoplegia (INO, among the most common. As the control of eye movements is well understood in terms of anatomical substrate and underlying physiological network, studying ocular motor abnormalities in MS provides a unique opportunity to gain insights into mechanisms of disease. Quantitative measurement and modeling of eye movement disorders, such as INO, may lead to a better understanding of common symptoms encountered in MS, such as Uhthoff’s phenomenon and fatigue. In turn, the pathophysiology of a range of eye movement abnormalities, such as APN, has been clarified based on correlation of experimental model with lesion localization by neuroimaging in MS. Eye movement disorders have the potential of being utilized as structural and functional biomarkers of early cognitive deficit, and possibly help in assessing disease status and progression, and to serve as platform and functional outcome to test novel therapeutic agents for MS. Knowledge of neuropharmacology applied to eye movement dysfunction has guided testing and use of a number of pharmacological agents to treat some eye movement disorders found in MS, such as APN and other forms of central nystagmus.

  15. Building Adaptive Capacity of Pathways in Technology Early College High School Stakeholders: A Multiple-Case Study on the Influence of Performance, Leadership, and Organizational Learning

    Science.gov (United States)

    Michaud-Wells, Amy

    2016-01-01

    The purpose of this qualitative study was to explore the perceptions and beliefs of Pathways in Technology Early College High School (P-TECH) leaders and stakeholders regarding the personal and professional experiences that contributed to the development of adaptive capacity. This embedded multiple-case study was anchored by the interrelated…

  16. Is it Possible to Actively and Purposely make use of Plasticity and Adaptibility in the Neurorehabilitation Treatment of Multiple Sclerosis Patients? A Pilot Project

    Czech Academy of Sciences Publication Activity Database

    Řasová, K.; Krásenský, J.; Havrdová, E.; Obenberger, J.; Seidel, Z.; Doležal, O.; Rexová, Patrícia; Zálišová, M.

    2005-01-01

    Roč. 19, - (2005), s. 170-181 ISSN 0269-2155 Institutional research plan: CEZ:AV0Z10300504; CEZ:MSM 111100001 Keywords : neurorehabilitation * multiple sclerosis * functional magnetic resonance * CNS plasticity and adaptability * motor learning Subject RIV: FA - Cardiovascular Diseases incl. Cardiotharic Surgery Impact factor: 1.447, year: 2005

  17. 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.

  18. 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…

  19. 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...

  20. Modeling water scarcity and droughts for policy adaptation to climate change in arid and semiarid regions

    Science.gov (United States)

    Kahil, Mohamed Taher; Dinar, Ariel; Albiac, Jose

    2015-03-01

    Growing water extractions combined with emerging demands for environment protection increase competition for scarce water resources worldwide, especially in arid and semiarid regions. In those regions, climate change is projected to exacerbate water scarcity and increase the recurrence and intensity of droughts. These circumstances call for methodologies that can support the design of sustainable water management. This paper presents a hydro-economic model that links a reduced form hydrological component, with economic and environmental components. The model is applied to an arid and semiarid basin in Southeastern Spain to analyze the effects of droughts and to assess alternative adaptation policies. Results indicate that drought events have large impacts on social welfare, with the main adjustments sustained by irrigation and the environment. The water market policy seems to be a suitable option to overcome the negative economic effects of droughts, although the environmental effects may weaken its advantages for society. The environmental water market policy, where water is acquired for the environment, is an appealing policy to reap the private benefits of markets while protecting ecosystems. The current water management approach in Spain, based on stakeholders' cooperation, achieves almost the same economic outcomes and better environmental outcomes compared to a pure water market. These findings call for a reconsideration of the current management in arid and semiarid basins around the world. The paper illustrates the potential of hydro-economic modeling for integrating the multiple dimensions of water resources, becoming a valuable tool in the advancement of sustainable water management policies.