Mathematical models for plant-herbivore interactions

Science.gov (United States)

Feng, Zhilan; DeAngelis, Donald L.

2017-01-01

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

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

Science.gov (United States)

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

2012-09-01

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

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

Directory of Open Access Journals (Sweden)

Fritzie Arce

2010-01-01

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

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

Science.gov (United States)

Carrard, Valérie; Schmid Mast, Marianne

2015-10-01

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

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...

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.

Immigrants' Adaptation and Interracial/Interethnic Interactions in Natural Environments

NARCIS (Netherlands)

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

2017-01-01

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

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

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

Science.gov (United States)

Bruce Shindler; Kristin Aldred Cheek; George H. Stankey

1999-01-01

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

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

Science.gov (United States)

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

2018-01-21

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

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

OpenAIRE

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

2013-01-01

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

Interactive ontology-based user modelling for personalized learning content management

NARCIS (Netherlands)

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

2004-01-01

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

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

International Nuclear Information System (INIS)

Etienne, S.; Pelletier, D.

2003-01-01

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

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

Directory of Open Access Journals (Sweden)

David Griol

2016-01-01

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

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

Science.gov (United States)

Griol, David; Callejas, Zoraida

2016-01-01

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

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

International Nuclear Information System (INIS)

Alyushin, S.A.

2011-01-01

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

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...

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.

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

Science.gov (United States)

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

2012-03-01

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

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).

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

DEFF Research Database (Denmark)

León Sobrino, Carlos

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

Contemporary Ecological Interactions Improve Models of Past Trait Evolution.

Science.gov (United States)

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

2018-02-20

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

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

Science.gov (United States)

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

2015-10-28

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

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

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

Science.gov (United States)

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

2015-01-01

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

Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

Energy Technology Data Exchange (ETDEWEB)

Jablonowski, Christiane [Univ. of Michigan, Ann Arbor, MI (United States)

2015-07-14

The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively with advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project

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

Science.gov (United States)

Telis, Natalie; Petrov, Dmitri A.

2017-01-01

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

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.

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.

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.

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

DEFF Research Database (Denmark)

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

2018-01-01

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

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 ...

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

Science.gov (United States)

Mathe, Nathalie; Chen, James

1994-01-01

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

Adaptive versus Non-Adaptive Security of Multi-Party Protocols

DEFF Research Database (Denmark)

Canetti, Ran; Damgård, Ivan Bjerre; Dziembowski, Stefan

2004-01-01

Security analysis of multi-party cryptographic protocols distinguishes between two types of adversarial settings: In the non-adaptive setting the set of corrupted parties is chosen in advance, before the interaction begins. In the adaptive setting the adversary chooses who to corrupt during...... the course of the computation. We study the relations between adaptive security (i.e., security in the adaptive setting) and nonadaptive security, according to two definitions and in several models of computation....

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

NARCIS (Netherlands)

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

2013-01-01

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

The joy of interactive modeling

Science.gov (United States)

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

2013-04-01

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

On Adaptive vs. Non-adaptive Security of Multiparty Protocols

DEFF Research Database (Denmark)

Canetti, Ran; Damgård, Ivan Bjerre; Dziembowski, Stefan

2001-01-01

highlights of our results are: – - According to the definition of Dodis-Micali-Rogaway (which is set in the information-theoretic model), adaptive and non-adaptive security are equivalent. This holds for both honest-but-curious and Byzantine adversaries, and for any number of parties. – - According......Security analysis of multiparty cryptographic protocols distinguishes between two types of adversarialsettings: In the non-adaptive setting, the set of corrupted parties is chosen in advance, before the interaction begins. In the adaptive setting, the adversary chooses who to corrupt during...... the course of the computation. We study the relations between adaptive security (i.e., security in the adaptive setting) and non-adaptive security, according to two definitions and in several models of computation. While affirming some prevailing beliefs, we also obtain some unexpected results. Some...

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.

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.

A model of mechanical interactions between heart and lungs.

Science.gov (United States)

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

2009-12-13

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

Interactive physically-based structural modeling of hydrocarbon systems

International Nuclear Information System (INIS)

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

2012-01-01

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

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

Science.gov (United States)

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

2006-12-01

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

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

Directory of Open Access Journals (Sweden)

Kathrine L. Nygård

2015-09-01

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

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.

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

International Nuclear Information System (INIS)

Nowak, Stefan; Krug, Joachim

2015-01-01

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

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

Science.gov (United States)

Wu, Chia-Chou; Chen, Bor-Sen

2016-01-01

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

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...

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

Science.gov (United States)

Mościcka-Teske, Agnieszka; Merecz, Dorota

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

Priti eGupta

2014-04-01

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

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

Science.gov (United States)

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

2016-01-01

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

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

Science.gov (United States)

Haer, Toon; Aerts, Jeroen

2015-04-01

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

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

Science.gov (United States)

Pontarp, Mikael; Petchey, Owen L

2018-03-14

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

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

Science.gov (United States)

Wheeler, Alfred G; Krimmel, Billy A

2015-01-07

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

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

Science.gov (United States)

Bartolucci, Silvia; Mozeika, Alexander; Annibale, Alessia

2016-08-01

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

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)

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.

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

International Nuclear Information System (INIS)

Fukuda, Ryoichi; Ehara, Masahiro

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Hwisoo Eom

2015-06-01

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

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

Science.gov (United States)

Eom, Hwisoo; Lee, Sang Hun

2015-06-12

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

Pose Estimation and Adaptive Robot Behaviour for Human-Robot Interaction

DEFF Research Database (Denmark)

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

2009-01-01

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

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

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

Science.gov (United States)

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

2015-01-01

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

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...

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.

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

Science.gov (United States)

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

2018-03-01

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

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

Science.gov (United States)

Chemuturi, Radhika; Amirabdollahian, Farshid; Dautenhahn, Kerstin

2013-09-28

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

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

Science.gov (United States)

Gopalan, Suresh; Ausubel, Frederick M

2008-01-01

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

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

Science.gov (United States)

Salter, Tamie; Michaud, François; Létourneau, Dominic

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

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

Directory of Open Access Journals (Sweden)

David Fouchet

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

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...

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

Science.gov (United States)

Burrow, H M

2012-05-01

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

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

CERN Document Server

Payne, Stephen J

2013-01-01

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

Adaptive vehicle motion estimation and prediction

Science.gov (United States)

Zhao, Liang; Thorpe, Chuck E.

1999-01-01

Accurate motion estimation and reliable maneuver prediction enable an automated car to react quickly and correctly to the rapid maneuvers of the other vehicles, and so allow safe and efficient navigation. In this paper, we present a car tracking system which provides motion estimation, maneuver prediction and detection of the tracked car. The three strategies employed - adaptive motion modeling, adaptive data sampling, and adaptive model switching probabilities - result in an adaptive interacting multiple model algorithm (AIMM). The experimental results on simulated and real data demonstrate that our tracking system is reliable, flexible, and robust. The adaptive tracking makes the system intelligent and useful in various autonomous driving tasks.

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

Science.gov (United States)

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

2017-05-01

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

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

Science.gov (United States)

Ben Dhia, Hachmi; Du, Shuimiao

2018-05-01

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

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

Science.gov (United States)

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

2016-01-01

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

Intelligent adaptive systems an interaction-centered design perspective

CERN Document Server

Hou, Ming; Burns, Catherine

2014-01-01

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

Interactive Dimensioning of Parametric Models

KAUST Repository

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

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Adem Karahoca

2018-04-01

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

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.

Adaptive resolution simulation of salt solutions

International Nuclear Information System (INIS)

Bevc, Staš; Praprotnik, Matej; Junghans, Christoph; Kremer, Kurt

2013-01-01

We present an adaptive resolution simulation of aqueous salt (NaCl) solutions at ambient conditions using the adaptive resolution scheme. Our multiscale approach concurrently couples the atomistic and coarse-grained models of the aqueous NaCl, where water molecules and ions change their resolution while moving from one resolution domain to the other. We employ standard extended simple point charge (SPC/E) and simple point charge (SPC) water models in combination with AMBER and GROMOS force fields for ion interactions in the atomistic domain. Electrostatics in our model are described by the generalized reaction field method. The effective interactions for water–water and water–ion interactions in the coarse-grained model are derived using structure-based coarse-graining approach while the Coulomb interactions between ions are appropriately screened. To ensure an even distribution of water molecules and ions across the simulation box we employ thermodynamic forces. We demonstrate that the equilibrium structural, e.g. radial distribution functions and density distributions of all the species, and dynamical properties are correctly reproduced by our adaptive resolution method. Our multiscale approach, which is general and can be used for any classical non-polarizable force-field and/or types of ions, will significantly speed up biomolecular simulation involving aqueous salt. (paper)

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 ...

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.

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

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

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.

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

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...

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.

Intelligent Context-Aware and Adaptive Interface for Mobile LBS.

Science.gov (United States)

Feng, Jiangfan; Liu, Yanhong

2015-01-01

Context-aware user interface plays an important role in many human-computer Interaction tasks of location based services. Although spatial models for context-aware systems have been studied extensively, how to locate specific spatial information for users is still not well resolved, which is important in the mobile environment where location based services users are impeded by device limitations. Better context-aware human-computer interaction models of mobile location based services are needed not just to predict performance outcomes, such as whether people will be able to find the information needed to complete a human-computer interaction task, but to understand human processes that interact in spatial query, which will in turn inform the detailed design of better user interfaces in mobile location based services. In this study, a context-aware adaptive model for mobile location based services interface is proposed, which contains three major sections: purpose, adjustment, and adaptation. Based on this model we try to describe the process of user operation and interface adaptation clearly through the dynamic interaction between users and the interface. Then we show how the model applies users' demands in a complicated environment and suggested the feasibility by the experimental results.

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

Science.gov (United States)

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

2014-12-01

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

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.

Adaptability and stability of maize varieties using mixed model methodology

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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.

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

Science.gov (United States)

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

2012-01-01

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

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...

Modeling adaptation of carbon use efficiency in microbial communities

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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.

Accessing Wireless Sensor Networks Via Dynamically Reconfigurable Interaction Models

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Maria Cecília Gomes

2012-12-01

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

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...

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.

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

Demography-based adaptive network model reproduces the spatial organization of human linguistic groups

Science.gov (United States)

Capitán, José A.; Manrubia, Susanna

2015-12-01

The distribution of human linguistic groups presents a number of interesting and nontrivial patterns. The distributions of the number of speakers per language and the area each group covers follow log-normal distributions, while population and area fulfill an allometric relationship. The topology of networks of spatial contacts between different linguistic groups has been recently characterized, showing atypical properties of the degree distribution and clustering, among others. Human demography, spatial conflicts, and the construction of networks of contacts between linguistic groups are mutually dependent processes. Here we introduce an adaptive network model that takes all of them into account and successfully reproduces, using only four model parameters, not only those features of linguistic groups already described in the literature, but also correlations between demographic and topological properties uncovered in this work. Besides their relevance when modeling and understanding processes related to human biogeography, our adaptive network model admits a number of generalizations that broaden its scope and make it suitable to represent interactions between agents based on population dynamics and competition for space.

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...

Intelligent Context-Aware and Adaptive Interface for Mobile LBS

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Jiangfan Feng

2015-01-01

Full Text Available Context-aware user interface plays an important role in many human-computer Interaction tasks of location based services. Although spatial models for context-aware systems have been studied extensively, how to locate specific spatial information for users is still not well resolved, which is important in the mobile environment where location based services users are impeded by device limitations. Better context-aware human-computer interaction models of mobile location based services are needed not just to predict performance outcomes, such as whether people will be able to find the information needed to complete a human-computer interaction task, but to understand human processes that interact in spatial query, which will in turn inform the detailed design of better user interfaces in mobile location based services. In this study, a context-aware adaptive model for mobile location based services interface is proposed, which contains three major sections: purpose, adjustment, and adaptation. Based on this model we try to describe the process of user operation and interface adaptation clearly through the dynamic interaction between users and the interface. Then we show how the model applies users’ demands in a complicated environment and suggested the feasibility by the experimental results.

Emotion model of interactive virtual humans on the basis of MDP

Institute of Scientific and Technical Information of China (English)

WANG Guojiang; WANG Zhiliang; TENG Shaodong; XIE Yinggang; WANG Yujie

2007-01-01

Emotion plays an essential role in the adaptation and social communication of organisms.Similarly,an appropriately timed and clearly expressed emotion is a central requirement for believable interactive virtual humans.Presently,incorporating emotion into virtual humans has gained increasing attention in the academia and industry.This strong interest is driven by a wide spectrum of promising applications in many areas such as virtual reality,e-learning,entertainment,etc.This paper introduces an emotion model of artificial psychology,in which the transition of emotion can be viewed as a Markov process and the relation of emotion,external incentive and personality can be described by a Markov decision process (MDP).In order to demonstrate the approach,this paper integrates the emotion model into a system composed of voice recognition and a realistic facial model.Thus,the model could be used for generating a variety of emotional expressions of autonomous,interactive virtual human beings.

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)

Modeling leukocyte-leukocyte non-contact interactions in a lymph node.

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Nicola Gritti

Full Text Available The interaction among leukocytes is at the basis of the innate and adaptive immune-response and it is largely ascribed to direct cell-cell contacts. However, the exchange of a number of chemical stimuli (chemokines allows also non-contact interaction during the immunological response. We want here to evaluate the extent of the effect of the non-contact interactions on the observed leukocyte-leukocyte kinematics and their interaction duration. To this aim we adopt a simplified mean field description inspired by the Keller-Segel chemotaxis model, of which we report an analytical solution suited for slowly varying sources of chemokines. Since our focus is on the non-contact interactions, leukocyte-leukocyte contact interactions are simulated only by means of a space dependent friction coefficient of the cells. The analytical solution of the Keller-Segel model is then taken as the basis of numerical simulations of interactions between leukocytes and their duration. The mean field interaction force that we derive has a time-space separable form and depends on the chemotaxis sensitivity parameter as well as on the chemokines diffusion coefficient and their degradation rate. All these parameters affect the distribution of the interaction durations. We draw a successful qualitative comparison between simulated data and sets of experimental data for DC-NK cells interaction duration and other kinematic parameters. Remarkably, the predicted percentage of the leukocyte-leukocyte interactions falls in the experimental range and depends (~25% increase upon the chemotactic parameter indicating a non-negligible direct effect of the non-contact interaction on the leukocyte interactions.

Modeling leukocyte-leukocyte non-contact interactions in a lymph node.

Science.gov (United States)

Gritti, Nicola; Caccia, Michele; Sironi, Laura; Collini, Maddalena; D'Alfonso, Laura; Granucci, Francesca; Zanoni, Ivan; Chirico, Giuseppe

2013-01-01

The interaction among leukocytes is at the basis of the innate and adaptive immune-response and it is largely ascribed to direct cell-cell contacts. However, the exchange of a number of chemical stimuli (chemokines) allows also non-contact interaction during the immunological response. We want here to evaluate the extent of the effect of the non-contact interactions on the observed leukocyte-leukocyte kinematics and their interaction duration. To this aim we adopt a simplified mean field description inspired by the Keller-Segel chemotaxis model, of which we report an analytical solution suited for slowly varying sources of chemokines. Since our focus is on the non-contact interactions, leukocyte-leukocyte contact interactions are simulated only by means of a space dependent friction coefficient of the cells. The analytical solution of the Keller-Segel model is then taken as the basis of numerical simulations of interactions between leukocytes and their duration. The mean field interaction force that we derive has a time-space separable form and depends on the chemotaxis sensitivity parameter as well as on the chemokines diffusion coefficient and their degradation rate. All these parameters affect the distribution of the interaction durations. We draw a successful qualitative comparison between simulated data and sets of experimental data for DC-NK cells interaction duration and other kinematic parameters. Remarkably, the predicted percentage of the leukocyte-leukocyte interactions falls in the experimental range and depends (~25% increase) upon the chemotactic parameter indicating a non-negligible direct effect of the non-contact interaction on the leukocyte interactions.

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...

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.

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

Science.gov (United States)

Depreeuw, E; Lens, W; Horebeek, W

1995-01-01

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

Adaptive emotional memory: the key hippocampal-amygdalar interaction.

Science.gov (United States)

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

2015-01-01

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

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.

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

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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.

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.

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.

Adaptation in Living Systems

Science.gov (United States)

Tu, Yuhai; Rappel, Wouter-Jan

2018-03-01

Adaptation refers to the biological phenomenon where living systems change their internal states in response to changes in their environments in order to maintain certain key functions critical for their survival and fitness. Adaptation is one of the most ubiquitous and arguably one of the most fundamental properties of living systems. It occurs throughout all biological scales, from adaptation of populations of species over evolutionary time to adaptation of a single cell to different environmental stresses during its life span. In this article, we review some of the recent progress made in understanding molecular mechanisms of cellular-level adaptation. We take the minimalist (or the physicist) approach and study the simplest systems that exhibit generic adaptive behaviors, namely chemotaxis in bacterium cells (Escherichia coli) and eukaryotic cells (Dictyostelium). We focus on understanding the basic biochemical interaction networks that are responsible for adaptation dynamics. By combining theoretical modeling with quantitative experimentation, we demonstrate universal features in adaptation as well as important differences in different cellular systems. Future work in extending the modeling framework to study adaptation in more complex systems such as sensory neurons is also discussed.

SynechoNET: integrated protein-protein interaction database of a model cyanobacterium Synechocystis sp. PCC 6803

OpenAIRE

Kim, Woo-Yeon; Kang, Sungsoo; Kim, Byoung-Chul; Oh, Jeehyun; Cho, Seongwoong; Bhak, Jong; Choi, Jong-Soon

2008-01-01

Background Cyanobacteria are model organisms for studying photosynthesis, carbon and nitrogen assimilation, evolution of plant plastids, and adaptability to environmental stresses. Despite many studies on cyanobacteria, there is no web-based database of their regulatory and signaling protein-protein interaction networks to date. Description We report a database and website SynechoNET that provides predicted protein-protein interactions. SynechoNET shows cyanobacterial domain-domain interactio...

Adaptive Modular Playware

DEFF Research Database (Denmark)

Lund, Henrik Hautop; Þorsteinsson, Arnar Tumi

2011-01-01

In this paper, we describe the concept of adaptive modular playware, where the playware adapts to the interaction of the individual user. We hypothesize that there are individual differences in user interaction capabilities and styles, and that adaptive playware may adapt to the individual user...

On Organizational Adaptation via Dynamic Process Selection

National Research Council Canada - National Science Library

Handley, Holly A; Levis, Alexander H

2000-01-01

.... An executable organizational model composed of individual models of a five stage interacting decision maker is used to evaluate the effectiveness of the different adaptation strategies on organizational performance...

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.

A longitudinal examination of the Adaptation to Poverty-Related Stress Model: predicting child and adolescent adjustment over time.

Science.gov (United States)

Wadsworth, Martha E; Rindlaub, Laura; Hurwich-Reiss, Eliana; Rienks, Shauna; Bianco, Hannah; Markman, Howard J

2013-01-01

This study tests key tenets of the Adaptation to Poverty-related Stress Model. This model (Wadsworth, Raviv, Santiago, & Etter, 2011 ) builds on Conger and Elder's family stress model by proposing that primary control coping and secondary control coping can help reduce the negative effects of economic strain on parental behaviors central to the family stress model, namely, parental depressive symptoms and parent-child interactions, which together can decrease child internalizing and externalizing problems. Two hundred seventy-five co-parenting couples with children between the ages of 1 and 18 participated in an evaluation of a brief family strengthening intervention, aimed at preventing economic strain's negative cascade of influence on parents, and ultimately their children. The longitudinal path model, analyzed at the couple dyad level with mothers and fathers nested within couple, showed very good fit, and was not moderated by child gender or ethnicity. Analyses revealed direct positive effects of primary control coping and secondary control coping on mothers' and fathers' depressive symptoms. Decreased economic strain predicted more positive father-child interactions, whereas increased secondary control coping predicted less negative mother-child interactions. Positive parent-child interactions, along with decreased parent depression and economic strain, predicted child internalizing and externalizing over the course of 18 months. Multiple-group models analyzed separately by parent gender revealed, however, that child age moderated father effects. Findings provide support for the adaptation to poverty-related stress model and suggest that prevention and clinical interventions for families affected by poverty-related stress may be strengthened by including modules that address economic strain and efficacious strategies for coping with strain.

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

Science.gov (United States)

Cukras, Janusz; Sadlej, Joanna

2008-06-01

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

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.

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.

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.

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...

Socio-hydrological modelling of floods: investigating community resilience, adaptation capacity and risk

Science.gov (United States)

Ciullo, Alessio; Viglione, Alberto; Castellarin, Attilio

2016-04-01

Changes in flood risk occur because of changes in climate and hydrology, and in societal exposure and vulnerability. Research on change in flood risk has demonstrated that the mutual interactions and continuous feedbacks between floods and societies has to be taken into account in flood risk management. The present work builds on an existing conceptual model of an hypothetical city located in the proximity of a river, along whose floodplains the community evolves over time. The model reproduces the dynamic co-evolution of four variables: flooding, population density of the flooplain, amount of structural protection measures and memory of floods. These variables are then combined in a way to mimic the temporal change of community resilience, defined as the (inverse of the) amount of time for the community to recover from a shock, and adaptation capacity, defined as ratio between damages due to subsequent events. Also, temporal changing exposure, vulnerability and probability of flooding are also modelled, which results in a dynamically varying flood-risk. Examples are provided that show how factors such as collective memory and risk taking attitude influence the dynamics of community resilience, adaptation capacity and risk.

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.

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.;

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

Science.gov (United States)

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

2017-09-01

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

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

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

Epidemics in adaptive networks with community structure

Science.gov (United States)

Shaw, Leah; Tunc, Ilker

2010-03-01

Models for epidemic spread on static social networks do not account for changes in individuals' social interactions. Recent studies of adaptive networks have modeled avoidance behavior, as non-infected individuals try to avoid contact with infectives. Such models have not generally included realistic social structure. Here we study epidemic spread on an adaptive network with community structure. We model the effect of heterogeneous communities on infection levels and epidemic extinction. We also show how an epidemic can alter the community structure.

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

Science.gov (United States)

Albalawi, Yousef; Sixsmith, Jane

2015-01-01

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

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

Science.gov (United States)

2015-01-01

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

AdOn HDP-HMM: An Adaptive Online Model for Segmentation and Classification of Sequential Data.

Science.gov (United States)

Bargi, Ava; Xu, Richard Yi Da; Piccardi, Massimo

2017-09-21

Recent years have witnessed an increasing need for the automated classification of sequential data, such as activities of daily living, social media interactions, financial series, and others. With the continuous flow of new data, it is critical to classify the observations on-the-fly and without being limited by a predetermined number of classes. In addition, a model should be able to update its parameters in response to a possible evolution in the distributions of the classes. This compelling problem, however, does not seem to have been adequately addressed in the literature, since most studies focus on offline classification over predefined class sets. In this paper, we present a principled solution for this problem based on an adaptive online system leveraging Markov switching models and hierarchical Dirichlet process priors. This adaptive online approach is capable of classifying the sequential data over an unlimited number of classes while meeting the memory and delay constraints typical of streaming contexts. In this paper, we introduce an adaptive ''learning rate'' that is responsible for balancing the extent to which the model retains its previous parameters or adapts to new observations. Experimental results on stationary and evolving synthetic data and two video data sets, TUM Assistive Kitchen and collated Weizmann, show a remarkable performance in terms of segmentation and classification, particularly for sequences from evolutionary distributions and/or those containing previously unseen classes.

Strategic Adaptation

DEFF Research Database (Denmark)

Andersen, Torben Juul

2015-01-01

This article provides an overview of theoretical contributions that have influenced the discourse around strategic adaptation including contingency perspectives, strategic fit reasoning, decision structure, information processing, corporate entrepreneurship, and strategy process. The related...... concepts of strategic renewal, dynamic managerial capabilities, dynamic capabilities, and strategic response capabilities are discussed and contextualized against strategic responsiveness. The insights derived from this article are used to outline the contours of a dynamic process of strategic adaptation....... This model incorporates elements of central strategizing, autonomous entrepreneurial behavior, interactive information processing, and open communication systems that enhance the organization's ability to observe exogenous changes and respond effectively to them....

Modelling human interactions in the assessment of man-made hazards

International Nuclear Information System (INIS)

Nitoi, M.; Farcasiu, M.; Apostol, M.

2016-01-01

The human reliability assessment tools are not currently capable to model adequately the human ability to adapt, to innovate and to manage under extreme situations. The paper presents the results obtained by ICN PSA team in the frame of FP7 Advanced Safety Assessment Methodologies: extended PSA (ASAMPSA_E) project regarding the investigation of conducting HRA in human-made hazards. The paper proposes to use a 4-steps methodology for the assessment of human interactions in the external events (Definition and modelling of human interactions; Quantification of human failure events; Recovery analysis; Review). The most relevant factors with respect to HRA for man-made hazards (response execution complexity; existence of procedures with respect to the scenario in question; time available for action; timing of cues; accessibility of equipment; harsh environmental conditions) are presented and discussed thoroughly. The challenges identified in relation to man-made hazards HRA are highlighted. (authors)

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

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

OpenAIRE

Ismail, Md. Rosli bin

2013-01-01

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

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

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

Science.gov (United States)

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

2017-10-01

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

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

Science.gov (United States)

Bagarello, F; Haven, E; Khrennikov, A

2017-11-13

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

A Model-Driven Approach to Graphical User Interface Runtime Adaptation

OpenAIRE

Criado, Javier; Vicente Chicote, Cristina; Iribarne, Luis; Padilla, Nicolás

2010-01-01

Graphical user interfaces play a key role in human-computer interaction, as they link the system with its end-users, allowing information exchange and improving communication. Nowadays, users increasingly demand applications with adaptive interfaces that dynamically evolve in response to their specific needs. Thus, providing graphical user interfaces with runtime adaptation capabilities is becoming more and more an important issue. To address this problem, this paper proposes a componen...

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

Energy Technology Data Exchange (ETDEWEB)

Mabius, L.E.

1982-09-15

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

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.

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

Directory of Open Access Journals (Sweden)

Инесса Анатольевна Воробьёва

2014-12-01

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

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

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.

When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems.

Science.gov (United States)

Sauterey, Boris; Ward, Ben A; Follows, Michael J; Bowler, Chris; Claessen, David

2015-01-01

The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that "Everything is everywhere, but the environment selects", we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean.

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.

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

Science.gov (United States)

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

2016-04-29

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

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

Science.gov (United States)

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

2018-04-01

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

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.

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.

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.

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

NARCIS (Netherlands)

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

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

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.

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.

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

Selective adaptation in networks of heterogeneous populations: model, simulation, and experiment.

Directory of Open Access Journals (Sweden)

Avner Wallach

2008-02-01

Full Text Available Biological systems often change their responsiveness when subject to persistent stimulation, a phenomenon termed adaptation. In neural systems, this process is often selective, allowing the system to adapt to one stimulus while preserving its sensitivity to another. In some studies, it has been shown that adaptation to a frequent stimulus increases the system's sensitivity to rare stimuli. These phenomena were explained in previous work as a result of complex interactions between the various subpopulations of the network. A formal description and analysis of neuronal systems, however, is hindered by the network's heterogeneity and by the multitude of processes taking place at different time-scales. Viewing neural networks as populations of interacting elements, we develop a framework that facilitates a formal analysis of complex, structured, heterogeneous networks. The formulation developed is based on an analysis of the availability of activity dependent resources, and their effects on network responsiveness. This approach offers a simple mechanistic explanation for selective adaptation, and leads to several predictions that were corroborated in both computer simulations and in cultures of cortical neurons developing in vitro. The framework is sufficiently general to apply to different biological systems, and was demonstrated in two different cases.

[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.

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)

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...

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...

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

OpenAIRE

MART, Dürdane

2015-01-01

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

An adaptable navigation strategy for Virtual Microscopy from mobile platforms.

Science.gov (United States)

Corredor, Germán; Romero, Eduardo; Iregui, Marcela

2015-04-01

Real integration of Virtual Microscopy with the pathologist service workflow requires the design of adaptable strategies for any hospital service to interact with a set of Whole Slide Images. Nowadays, mobile devices have the actual potential of supporting an online pervasive network of specialists working together. However, such devices are still very limited. This article introduces a novel highly adaptable strategy for streaming and visualizing WSI from mobile devices. The presented approach effectively exploits and extends the granularity of the JPEG2000 standard and integrates it with different strategies to achieve a lossless, loosely-coupled, decoder and platform independent implementation, adaptable to any interaction model. The performance was evaluated by two expert pathologists interacting with a set of 20 virtual slides. The method efficiently uses the available device resources: the memory usage did not exceed a 7% of the device capacity while the decoding times were smaller than the 200 ms per Region of Interest, i.e., a window of 256×256 pixels. This model is easily adaptable to other medical imaging scenarios. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

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...

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...

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

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.

Adapting Agricultural Production Systems to Climate Change—What’s the Use of Models?

Directory of Open Access Journals (Sweden)

Annelie Holzkämper

2017-10-01

Full Text Available Climate change poses a challenge to agricultural production and its impacts vary depending on regional focus and on the type of production system. To avoid production losses and make use of emerging potentials, adaptations in agricultural management will inevitably be required. Adaptation responses can broadly be distinguished into (1 short-term incremental responses that farmers often choose autonomously in response to observed changes and based on local knowledge and experiences, and (2 long-term transformative responses that require strategic planning, and which are usually implemented at a larger spatial scale. Models can be used to support decision making at both response levels; thereby, different features of models prove more or less valuable depending on the type of adaptation response. This paper presents a systematic literature review on the state-of-the-art in modelling for adaptation planning in agricultural production systems, investigating the question of which model types can be distinguished and how these types differ in the way they support decision making in agricultural adaptation planning. Five types of models are distinguished: (1 empirical crop models; (2 regional suitability models; (3 biophysical models; (4 meta-models; and (5 decision models. The potential and limitations of these model types for providing decision-support to short- and long-term adaptation planning are discussed. The risk of maladaptation—adaptation that implies negative consequences either in the long term or in a wider context—is identified as a key challenge of adaptation planning that needs more attention. Maladaptation is not only a risk of decision making in the face of incomplete knowledge of future climate impacts on the agricultural production system; but it can also be a threat if the connectedness of the agroecosystem is not sufficiently acknowledged when management adaptations are implemented. Future research supporting climate change

LandCaRe DSS--an interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies.

Science.gov (United States)

Wenkel, Karl-Otto; Berg, Michael; Mirschel, Wilfried; Wieland, Ralf; Nendel, Claas; Köstner, Barbara

2013-09-01

Decision support to develop viable climate change adaptation strategies for agriculture and regional land use management encompasses a wide range of options and issues. Up to now, only a few suitable tools and methods have existed for farmers and regional stakeholders that support the process of decision-making in this field. The interactive model-based spatial information and decision support system LandCaRe DSS attempts to close the existing methodical gap. This system supports interactive spatial scenario simulations, multi-ensemble and multi-model simulations at the regional scale, as well as the complex impact assessment of potential land use adaptation strategies at the local scale. The system is connected to a local geo-database and via the internet to a climate data server. LandCaRe DSS uses a multitude of scale-specific ecological impact models, which are linked in various ways. At the local scale (farm scale), biophysical models are directly coupled with a farm economy calculator. New or alternative simulation models can easily be added, thanks to the innovative architecture and design of the DSS. Scenario simulations can be conducted with a reasonable amount of effort. The interactive LandCaRe DSS prototype also offers a variety of data analysis and visualisation tools, a help system for users and a farmer information system for climate adaptation in agriculture. This paper presents the theoretical background, the conceptual framework, and the structure and methodology behind LandCaRe DSS. Scenario studies at the regional and local scale for the two Eastern German regions of Uckermark (dry lowlands, 2600 km(2)) and Weißeritz (humid mountain area, 400 km(2)) were conducted in close cooperation with stakeholders to test the functionality of the DSS prototype. The system is gradually being transformed into a web version (http://www.landcare-dss.de) to ensure the broadest possible distribution of LandCaRe DSS to the public. The system will be continuously

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

Distributed Recurrent Neural Forward Models with Synaptic Adaptation and CPG-based control for Complex Behaviors of Walking Robots

Directory of Open Access Journals (Sweden)

Sakyasingha eDasgupta

2015-09-01

Full Text Available Walking animals, like stick insects, cockroaches or ants, demonstrate a fascinating range of locomotive abilities and complex behaviors. The locomotive behaviors can consist of a variety of walking patterns along with adaptation that allow the animals to deal with changes in environmental conditions, like uneven terrains, gaps, obstacles etc. Biological study has revealed that such complex behaviors are a result of a combination of biomechanics and neural mechanism thus representing the true nature of embodied interactions. While the biomechanics helps maintain flexibility and sustain a variety of movements, the neural mechanisms generate movements while making appropriate predictions crucial for achieving adaptation. Such predictions or planning ahead can be achieved by way of internal models that are grounded in the overall behavior of the animal. Inspired by these findings, we present here, an artificial bio-inspired walking system which effectively combines biomechanics (in terms of the body and leg structures with the underlying neural mechanisms. The neural mechanisms consist of 1 central pattern generator based control for generating basic rhythmic patterns and coordinated movements, 2 distributed (at each leg recurrent neural network based adaptive forward models with efference copies as internal models for sensory predictions and instantaneous state estimations, and 3 searching and elevation control for adapting the movement of an individual leg to deal with different environmental conditions. Using simulations we show that this bio-inspired approach with adaptive internal models allows the walking robot to perform complex locomotive behaviors as observed in insects, including walking on undulated terrains, crossing large gaps as well as climbing over high obstacles. Furthermore we demonstrate that the newly developed recurrent network based approach to sensorimotor prediction outperforms the previous state of the art adaptive neuron

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)

A Probabilistic Model of Social Working Memory for Information Retrieval in Social Interactions.

Science.gov (United States)

Li, Liyuan; Xu, Qianli; Gan, Tian; Tan, Cheston; Lim, Joo-Hwee

2018-05-01

Social working memory (SWM) plays an important role in navigating social interactions. Inspired by studies in psychology, neuroscience, cognitive science, and machine learning, we propose a probabilistic model of SWM to mimic human social intelligence for personal information retrieval (IR) in social interactions. First, we establish a semantic hierarchy as social long-term memory to encode personal information. Next, we propose a semantic Bayesian network as the SWM, which integrates the cognitive functions of accessibility and self-regulation. One subgraphical model implements the accessibility function to learn the social consensus about IR-based on social information concept, clustering, social context, and similarity between persons. Beyond accessibility, one more layer is added to simulate the function of self-regulation to perform the personal adaptation to the consensus based on human personality. Two learning algorithms are proposed to train the probabilistic SWM model on a raw dataset of high uncertainty and incompleteness. One is an efficient learning algorithm of Newton's method, and the other is a genetic algorithm. Systematic evaluations show that the proposed SWM model is able to learn human social intelligence effectively and outperforms the baseline Bayesian cognitive model. Toward real-world applications, we implement our model on Google Glass as a wearable assistant for social interaction.

An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud

Directory of Open Access Journals (Sweden)

Thanh Dinh

2016-06-01

Full Text Available This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud.

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.

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.

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.

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

Novel Fuzzy-Modeling-Based Adaptive Synchronization of Nonlinear Dynamic Systems

Directory of Open Access Journals (Sweden)

Shih-Yu Li

2017-01-01

Full Text Available In this paper, a novel fuzzy-model-based adaptive synchronization scheme and its fuzzy update laws of parameters are proposed to address the adaptive synchronization problem. The proposed fuzzy controller does not share the same premise of fuzzy system, and the numbers of fuzzy controllers is reduced effectively through the novel modeling strategy. In addition, based on the adaptive synchronization scheme, the error dynamic system can be guaranteed to be asymptotically stable and the true values of unknown parameters can be obtained. Two identical complicated dynamic systems, Mathieu-Van der pol system (M-V system with uncertainties, are illustrated for numerical simulation example to show the effectiveness and feasibility of the proposed novel adaptive control strategy.

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.

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

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

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....

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

Science.gov (United States)

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

2014-11-01

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

Uncovering transcriptional interactions via an adaptive fuzzy logic approach

Directory of Open Access Journals (Sweden)

Chen Chung-Ming

2009-12-01

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

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.

Adaptive nodes enrich nonlinear cooperative learning beyond traditional adaptation by links.

Science.gov (United States)

Sardi, Shira; Vardi, Roni; Goldental, Amir; Sheinin, Anton; Uzan, Herut; Kanter, Ido

2018-03-23

Physical models typically assume time-independent interactions, whereas neural networks and machine learning incorporate interactions that function as adjustable parameters. Here we demonstrate a new type of abundant cooperative nonlinear dynamics where learning is attributed solely to the nodes, instead of the network links which their number is significantly larger. The nodal, neuronal, fast adaptation follows its relative anisotropic (dendritic) input timings, as indicated experimentally, similarly to the slow learning mechanism currently attributed to the links, synapses. It represents a non-local learning rule, where effectively many incoming links to a node concurrently undergo the same adaptation. The network dynamics is now counterintuitively governed by the weak links, which previously were assumed to be insignificant. This cooperative nonlinear dynamic adaptation presents a self-controlled mechanism to prevent divergence or vanishing of the learning parameters, as opposed to learning by links, and also supports self-oscillations of the effective learning parameters. It hints on a hierarchical computational complexity of nodes, following their number of anisotropic inputs and opens new horizons for advanced deep learning algorithms and artificial intelligence based applications, as well as a new mechanism for enhanced and fast learning by neural networks.

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%.

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...

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...

A Direct Adaptive Control Approach in the Presence of Model Mismatch

Science.gov (United States)

Joshi, Suresh M.; Tao, Gang; Khong, Thuan

2009-01-01

This paper considers the problem of direct model reference adaptive control when the plant-model matching conditions are violated due to abnormal changes in the plant or incorrect knowledge of the plant's mathematical structure. The approach consists of direct adaptation of state feedback gains for state tracking, and simultaneous estimation of the plant-model mismatch. Because of the mismatch, the plant can no longer track the state of the original reference model, but may be able to track a new reference model that still provides satisfactory performance. The reference model is updated if the estimated plant-model mismatch exceeds a bound that is determined via robust stability and/or performance criteria. The resulting controller is a hybrid direct-indirect adaptive controller that offers asymptotic state tracking in the presence of plant-model mismatch as well as parameter deviations.

Enhanced vaccine control of epidemics in adaptive networks

Science.gov (United States)

Shaw, Leah B.; Schwartz, Ira B.

2010-04-01

We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson-distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to feedback interaction between the adaptive network rewiring and the vaccine application. When compared to extinction rates in static social networks, we find that the amount of vaccine resources required to sustain similar rates of extinction are as much as two orders of magnitude lower in adaptive networks.

Sensorimotor synchronization with tempo-changing auditory sequences: Modeling temporal adaptation and anticipation.

Science.gov (United States)

van der Steen, M C Marieke; Jacoby, Nori; Fairhurst, Merle T; Keller, Peter E

2015-11-11

The current study investigated the human ability to synchronize movements with event sequences containing continuous tempo changes. This capacity is evident, for example, in ensemble musicians who maintain precise interpersonal coordination while modulating the performance tempo for expressive purposes. Here we tested an ADaptation and Anticipation Model (ADAM) that was developed to account for such behavior by combining error correction processes (adaptation) with a predictive temporal extrapolation process (anticipation). While previous computational models of synchronization incorporate error correction, they do not account for prediction during tempo-changing behavior. The fit between behavioral data and computer simulations based on four versions of ADAM was assessed. These versions included a model with adaptation only, one in which adaptation and anticipation act in combination (error correction is applied on the basis of predicted tempo changes), and two models in which adaptation and anticipation were linked in a joint module that corrects for predicted discrepancies between the outcomes of adaptive and anticipatory processes. The behavioral experiment required participants to tap their finger in time with three auditory pacing sequences containing tempo changes that differed in the rate of change and the number of turning points. Behavioral results indicated that sensorimotor synchronization accuracy and precision, while generally high, decreased with increases in the rate of tempo change and number of turning points. Simulations and model-based parameter estimates showed that adaptation mechanisms alone could not fully explain the observed precision of sensorimotor synchronization. Including anticipation in the model increased the precision of simulated sensorimotor synchronization and improved the fit of model to behavioral data, especially when adaptation and anticipation mechanisms were linked via a joint module based on the notion of joint internal

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

On the role of model-based monitoring for adaptive planning under uncertainty

Science.gov (United States)

Raso, Luciano; Kwakkel, Jan; Timmermans, Jos; Haasnoot, Mariolijn

2016-04-01

, triggered by the challenge of uncertainty in operational control, may offer solutions from which monitoring for adaptive planning can benefit. Specifically: (i) in control, observations are incorporated into the model through data assimilation, updating the present state, boundary conditions, and parameters based on new observations, diminishing the shadow of the past; (ii) adaptive control is a way to modify the characteristics of the internal model, incorporating new knowledge on the system, countervailing the inhibition of learning; and (iii) in closed-loop control, a continuous system update equips the controller with "inherent robustness", i.e. to capacity to adapts to new conditions even when these were not initially considered. We aim to explore how inherent robustness addresses the challenge of surprise. Innovations in model-based control might help to improve and adapt the models used to support adaptive delta management to new information (reducing uncertainty). Moreover, this would offer a starting point for using these models not only in the design of adaptive plans, but also as part of the monitoring. The proposed research requires multidisciplinary cooperation between control theory, the policy sciences, and integrated assessment modeling.

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

Parent-Adolescent Collaboration: An Interpersonal Model for Understanding Optimal Interactions

Science.gov (United States)

Beveridge, Ryan M.; Berg, Cynthia A.

2007-01-01

Current parent-adolescent behavioral interaction research highlights the importance of three elements of behavior in defining adaptive interactions: autonomy, control, and warmth vs. hostility. However, this research has largely addressed the developmental needs and psychosocial outcomes of adolescents, as opposed to parents, with a focus on how…

Modeling the Interaction of Europa with the Jovian Magnetosphere

Science.gov (United States)

Rubin, M.; Combi, M. R.; Daldorff, L.; Gombosi, T. I.; Hansen, K. C.; Jia, X.; Kivelson, M. G.; Tenishev, V.

2011-12-01

The interaction of Jupiter's corotating magnetosphere with Europa's subsurface water ocean is responsible for the observed induced dipolar magnetic field. Furthermore the pick-up process of newly ionized particles from Europa's neutral atmosphere alters the magnetic and electric field topology around the moon. We use the Block-Adaptive-Tree-Solarwind-Roe-Upwind-Scheme (BATS-R-US) of the Space Weather Modeling Framework (SWMF) to model the interaction of Europa with the Jovian magnetosphere. The BATS-R-US code solves the governing equations of magnetohydrodynamics (MHD) in a fully 3D adaptive mesh. In our approach we solve the equations for one single ion species, starting from the work by Kabin et al. (J. Geophys. Res., 104, A9, 19983-19992, 1999) accounting for the exospheric mass loading, ion-neutral charge exchange, and ion-electron recombination. We continue by separately solving the electron pressure equation and furthermore extend the magnetic induction equation by the resistive and Hall terms. The resistive term accounts for the finite electron diffusivity and thus allows a more adequate description of the effect of magnetic diffusion due to collisions [Ledvina et al., Sp. Sci. Rev., 139:143-189, 2008]. For this purpose we use ion-electron and electron-neutral collision rates presented by Schunk and Nagy (Ionospheres, Cambridge University Press, 2000). The Hall term allows ions and electrons to move at different velocities while the magnetic field remains frozen to the electrons. The assumed charge neutrality of the ion-electron plasma is maintained everywhere at all times. The model is run at different phases of Jupiter's rotation reflecting the different locations of Europa with respect to the center of the plasma sheet and is compared to measurements obtained by the Galileo magnetometer [Kivelson et al., J. Geophys. Res., 104:4609-4626, 1999]. The resulting influence on the induced magnetic dipolar field is studied and compared to the results from the

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

International Nuclear Information System (INIS)

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

1986-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1986-01-01

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

Adaptive Admittance Control for an Ankle Exoskeleton Using an EMG-Driven Musculoskeletal Model

Directory of Open Access Journals (Sweden)

Shaowei Yao

2018-04-01

Full Text Available Various rehabilitation robots have been employed to recover the motor function of stroke patients. To improve the effect of rehabilitation, robots should promote patient participation and provide compliant assistance. This paper proposes an adaptive admittance control scheme (AACS consisting of an admittance filter, inner position controller, and electromyography (EMG-driven musculoskeletal model (EDMM. The admittance filter generates the subject's intended motion according to the joint torque estimated by the EDMM. The inner position controller tracks the intended motion, and its parameters are adjusted according to the estimated joint stiffness. Eight healthy subjects were instructed to wear the ankle exoskeleton robot, and they completed a series of sinusoidal tracking tasks involving ankle dorsiflexion and plantarflexion. The robot was controlled by the AACS and a non-adaptive admittance control scheme (NAACS at four fixed parameter levels. The tracking performance was evaluated using the jerk value, position error, interaction torque, and EMG levels of the tibialis anterior (TA and gastrocnemius (GAS. For the NAACS, the jerk value and position error increased with the parameter levels, and the interaction torque and EMG levels of the TA tended to decrease. In contrast, the AACS could maintain a moderate jerk value, position error, interaction torque, and TA EMG level. These results demonstrate that the AACS achieves a good tradeoff between accurate tracking and compliant assistance because it can produce a real-time response to stiffness changes in the ankle joint. The AACS can alleviate the conflict between accurate tracking and compliant assistance and has potential for application in robot-assisted rehabilitation.

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...

Adaptive Controller Effects on Pilot Behavior

Science.gov (United States)

Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.

2014-01-01

Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.

The adaptive nature of the human neurocognitive architecture: an alternative model.

Science.gov (United States)

La Cerra, P; Bingham, R

1998-09-15

The model of the human neurocognitive architecture proposed by evolutionary psychologists is based on the presumption that the demands of hunter-gatherer life generated a vast array of cognitive adaptations. Here we present an alternative model. We argue that the problems inherent in the biological markets of ancestral hominids and their mammalian predecessors would have required an adaptively flexible, on-line information-processing system, and would have driven the evolution of a functionally plastic neural substrate, the neocortex, rather than a confederation of evolutionarily prespecified social cognitive adaptations. In alignment with recent neuroscientific evidence, we suggest that human cognitive processes result from the activation of constructed cortical representational networks, which reflect probabilistic relationships between sensory inputs, behavioral responses, and adaptive outcomes. The developmental construction and experiential modification of these networks are mediated by subcortical circuitries that are responsive to the life history regulatory system. As a consequence, these networks are intrinsically adaptively constrained. The theoretical and research implications of this alternative evolutionary model are discussed.

Interacting boson model with surface delta interaction between nucleons

International Nuclear Information System (INIS)

Druce, C.; Moszkowski, S.A.

1984-01-01

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

Adaptive Remodeling of Achilles Tendon: A Multi-scale Computational Model.

Directory of Open Access Journals (Sweden)

Stuart R Young

2016-09-01

Full Text Available While it is known that musculotendon units adapt to their load environments, there is only a limited understanding of tendon adaptation in vivo. Here we develop a computational model of tendon remodeling based on the premise that mechanical damage and tenocyte-mediated tendon damage and repair processes modify the distribution of its collagen fiber lengths. We explain how these processes enable the tendon to geometrically adapt to its load conditions. Based on known biological processes, mechanical and strain-dependent proteolytic fiber damage are incorporated into our tendon model. Using a stochastic model of fiber repair, it is assumed that mechanically damaged fibers are repaired longer, whereas proteolytically damaged fibers are repaired shorter, relative to their pre-damage length. To study adaptation of tendon properties to applied load, our model musculotendon unit is a simplified three-component Hill-type model of the human Achilles-soleus unit. Our model results demonstrate that the geometric equilibrium state of the Achilles tendon can coincide with minimization of the total metabolic cost of muscle activation. The proposed tendon model independently predicts rates of collagen fiber turnover that are in general agreement with in vivo experimental measurements. While the computational model here only represents a first step in a new approach to understanding the complex process of tendon remodeling in vivo, given these findings, it appears likely that the proposed framework may itself provide a useful theoretical foundation for developing valuable qualitative and quantitative insights into tendon physiology and pathology.

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 ...

Unsteady CFD modeling of micro-adaptive flow control for an axisymmetric body

International Nuclear Information System (INIS)

Sahu, J.; Heavey, K.R.

2005-01-01

This paper describes a computational study undertaken, as part of a grand challenge project, to consider the aerodynamic effect of micro-adaptive flow control as a means to provide the divert authority needed to maneuver a projectile at a low subsonic speed. A time-accurate Navier-Stokes computational technique has been used to obtain numerical solutions for the unsteady microjet-interaction flow field for the axisymmetric projectile body at subsonic speeds, Mach = 0.11 and 0.24 and angles of attack, 0 o to 4 o . Numerical solutions have been obtained using both Renolds-Averaged Navier-Stokes (RANS) and a hybrid RANS/Large Eddy Simulation (LES) turbulence models. Unsteady numerical results show the effect of the jet on the flow field and the aerodynamic coefficients, in particular the lift force. This research has provided an increased fundamental understanding of the complex, three-dimensional, time-dependent, aerodynamic interactions associated with micro-jet control for yawing spin-stabilized munitions. (author)

Unsteady CFD modeling of micro-adaptive flow control for an axisymmetric body

Energy Technology Data Exchange (ETDEWEB)

Sahu, J.; Heavey, K.R. [U.S. Army Research Laboratory, Aberdeen Proving Ground, MD (United States)]. E-mail: sahu@arl.army.mil

2005-07-01

This paper describes a computational study undertaken, as part of a grand challenge project, to consider the aerodynamic effect of micro-adaptive flow control as a means to provide the divert authority needed to maneuver a projectile at a low subsonic speed. A time-accurate Navier-Stokes computational technique has been used to obtain numerical solutions for the unsteady microjet-interaction flow field for the axisymmetric projectile body at subsonic speeds, Mach = 0.11 and 0.24 and angles of attack, 0{sup o} to 4{sup o}. Numerical solutions have been obtained using both Renolds-Averaged Navier-Stokes (RANS) and a hybrid RANS/Large Eddy Simulation (LES) turbulence models. Unsteady numerical results show the effect of the jet on the flow field and the aerodynamic coefficients, in particular the lift force. This research has provided an increased fundamental understanding of the complex, three-dimensional, time-dependent, aerodynamic interactions associated with micro-jet control for yawing spin-stabilized munitions. (author)

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.

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.

A final state interaction model for K and eta decay into three pions

International Nuclear Information System (INIS)

Angus, A.G.

1973-07-01

The Khuri-Treiman model is adapted in a relativistic formalism with the electromagnetic mass differences of the pions in the final state taken into account to produce new predictions for the relative decay rates and the slope parameters of the four reactions K→3x and the two reactions eta→3x. The pion-pion interaction is investigated in terms of the N/D method and as well as the normal pure pole approximations for the N functions. The Khuri-Treiman equations are solved for the best solutions from both the pure pole and the mixed pole and cut models. (author)

Yeast Colonies: A Model for Studies of Aging, Environmental Adaptation, and Longevity

Directory of Open Access Journals (Sweden)

Libuše Váchová

2012-01-01

Full Text Available When growing on solid surfaces, yeast, like other microorganisms, develops organized multicellular populations (colonies and biofilms that are composed of differentiated cells with specialized functions. Life within these populations is a prevalent form of microbial existence in natural settings that provides the cells with capabilities to effectively defend against environmental attacks as well as efficiently adapt and survive long periods of starvation and other stresses. Under such circumstances, the fate of an individual yeast cell is subordinated to the profit of the whole population. In the past decade, yeast colonies, with their complicated structure and high complexity that are also developed under laboratory conditions, have become an excellent model for studies of various basic cellular processes such as cell interaction, signaling, and differentiation. In this paper, we summarize current knowledge on the processes related to chronological aging, adaptation, and longevity of a colony cell population and of its differentiated cell constituents. These processes contribute to the colony ability to survive long periods of starvation and mostly differ from the survival strategies of individual yeast cells.

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.

Interactive Strategy-Making

DEFF Research Database (Denmark)

Andersen, Torben Juul

2015-01-01

This article outlines an interactive strategy-making model that combines central reasoning with ongoing learning from decentralised responses. The management literature often presents strategy as implementing an optimal plan identified through rational analysis and ascribes potential shortcomings...... to failed communication and execution of the planned actions. However, effective strategy-making comprises both central reasoning from forward-looking planning considerations and decentralised responses to emerging events as interacting elements in a dynamic adaptive system. The interaction between...

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

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.

Adapting Playware to Rehabilitation Practices

DEFF Research Database (Denmark)

Nielsen, Camilla Balslev; Lund, Henrik Hautop

2011-01-01

We describe how playware and games may become adaptive to the interaction of the individual user and how therapists use this adaptation property to apply modular interactive tiles in rehabilitation practices that demand highly individualized training. Therapists may use the interactive modular...... patients modulating exercises and difficulty levels. We also find that in physical games there are individual differences in patient interaction capabilities and styles, and that modularity allows the therapist to adapt exercises to the individual patient’s capabilities....

Collaborative Education in Climate Change Sciences and Adaptation through Interactive Learning

Science.gov (United States)

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

2014-12-01

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

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...

Interactive Teaching of Adaptive Signal Processing

OpenAIRE

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

2000-01-01

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

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

Directory of Open Access Journals (Sweden)

Barbara Lukasch

2017-08-01

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

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

Science.gov (United States)

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

2017-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-11-01

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

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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:

Parent Management Training-Oregon Model (PMTO™) in Mexico City: Integrating Cultural Adaptation Activities in an Implementation Model.

Science.gov (United States)

Baumann, Ana A; Domenech Rodríguez, Melanie M; Amador, Nancy G; Forgatch, Marion S; Parra-Cardona, J Rubén

2014-03-01

This article describes the process of cultural adaptation at the start of the implementation of the Parent Management Training intervention-Oregon model (PMTO) in Mexico City. The implementation process was guided by the model, and the cultural adaptation of PMTO was theoretically guided by the cultural adaptation process (CAP) model. During the process of the adaptation, we uncovered the potential for the CAP to be embedded in the implementation process, taking into account broader training and economic challenges and opportunities. We discuss how cultural adaptation and implementation processes are inextricably linked and iterative and how maintaining a collaborative relationship with the treatment developer has guided our work and has helped expand our research efforts, and how building human capital to implement PMTO in Mexico supported the implementation efforts of PMTO in other places in the United States.

Stresses in faulted tunnel models by photoelasticity and adaptive finite element

International Nuclear Information System (INIS)

Ladkany, S.G.; Huang, Y.

1995-01-01

Research efforts in this area continue to investigate the development of a proper technique to analyze the stresses in the Ghost Dance fault and the effect of the fault on the stability of drifts in the proposed repository. Results from two parallel techniques are being compared to each other - Photoelastic models and Finite Element (FE) models. The Photoelastic plexiglass model (88.89 mm thick ampersand 256.1 mm long and wide) has two adjacent spare openings (57.95 mm long and wide) and a central round opening (57.95 mm diameter) placed at a clear distance approximately equal to its diameter from the square openings. The vertical loading on top of the model is 2269 N (500 lb.). Saw cuts (0.5388 mm wide), representing a fault, are being propagated from the tunnels outward with stress measurements taken at predefined locations, as the saw cuts increase in length. The FE model duplicates exactly the Photoelastic models. The adaptive mesh generation method is used to refine the FE grid at every step of the analysis. This nonlinear interactive computational techniques uses various uses various percent tolerance errors in the convergence of stress values as a measure in ending the iterative process

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

Directory of Open Access Journals (Sweden)

S. I. Samsudin

2014-01-01

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

Cardiorespiratory adaptation to breath-holding in air: Analysis via a cardiopulmonary simulation model.

Science.gov (United States)

Albanese, Antonio; Limei Cheng; Ursino, Mauro; Chbat, Nicolas W

2015-01-01

Apnea via breath-holding (BH) in air induces cardiorespiratory adaptation that involves the activation of several reflex mechanisms and their complex interactions. Hence, the effects of BH in air on cardiorespiratory function can become hardly predictable and difficult to be interpreted. Particularly, the effect on heart rate is not yet completely understood because of the contradicting results of different physiological studies. In this paper we apply our previously developed cardiopulmonary model (CP Model) to a scenario of BH with a twofold intent: (1) further validating the CP Model via comparison against experimental data; (2) gaining insights into the physiological reasoning for such contradicting experimental results. Model predictions agreed with published experimental animal and human data and indicated that heart rate increases during BH in air. Changes in the balance between sympathetic and vagal effects on heart rate within the model proved to be effective in inverting directions of the heart rate changes during BH. Hence, the model suggests that intra-subject differences in such sympatho-vagal balance may be one of the reasons for the contradicting experimental results.

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.

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.

Modeling multimodal human-computer interaction

NARCIS (Netherlands)

Obrenovic, Z.; Starcevic, D.

2004-01-01

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

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…

Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations.

Directory of Open Access Journals (Sweden)

Tatiana Shashkova

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

Piecewise linear approximations to model the dynamics of adaptation to osmotic stress by food-borne pathogens.

Science.gov (United States)

Métris, Aline; George, Susie M; Ropers, Delphine

2017-01-02

Addition of salt to food is one of the most ancient and most common methods of food preservation. However, little is known of how bacterial cells adapt to such conditions. We propose to use piecewise linear approximations to model the regulatory adaptation of Escherichiacoli to osmotic stress. We apply the method to eight selected genes representing the functions known to be at play during osmotic adaptation. The network is centred on the general stress response factor, sigma S, and also includes a module representing the catabolic repressor CRP-cAMP. Glutamate, potassium and supercoiling are combined to represent the intracellular regulatory signal during osmotic stress induced by salt. The output is a module where growth is represented by the concentration of stable RNAs and the transcription of the osmotic gene osmY. The time course of gene expression of transport of osmoprotectant represented by the symporter proP and of the osmY is successfully reproduced by the network. The behaviour of the rpoS mutant predicted by the model is in agreement with experimental data. We discuss the application of the model to food-borne pathogens such as Salmonella; although the genes considered have orthologs, it seems that supercoiling is not regulated in the same way. The model is limited to a few selected genes, but the regulatory interactions are numerous and span different time scales. In addition, they seem to be condition specific: the links that are important during the transition from exponential to stationary phase are not all needed during osmotic stress. This model is one of the first steps towards modelling adaptation to stress in food safety and has scope to be extended to other genes and pathways, other stresses relevant to the food industry, and food-borne pathogens. The method offers a good compromise between systems of ordinary differential equations, which would be unmanageable because of the size of the system and for which insufficient data are available

Interactive indirect illumination using adaptive multiresolution splatting.

Science.gov (United States)

Nichols, Greg; Wyman, Chris

2010-01-01

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

Adaptive Surrogate Modeling for Response Surface Approximations with Application to Bayesian Inference

KAUST Repository

Prudhomme, Serge

2015-01-07

The need for surrogate models and adaptive methods can be best appreciated if one is interested in parameter estimation using a Bayesian calibration procedure for validation purposes. We extend here our latest work on error decomposition and adaptive refinement for response surfaces to the development of surrogate models that can be substituted for the full models to estimate the parameters of Reynolds-averaged Navier-Stokes models. The error estimates and adaptive schemes are driven here by a quantity of interest and are thus based on the approximation of an adjoint problem. We will focus in particular to the accurate estimation of evidences to facilitate model selection. The methodology will be illustrated on the Spalart-Allmaras RANS model for turbulence simulation.

Adaptive Surrogate Modeling for Response Surface Approximations with Application to Bayesian Inference

KAUST Repository

Prudhomme, Serge

2015-01-01

The need for surrogate models and adaptive methods can be best appreciated if one is interested in parameter estimation using a Bayesian calibration procedure for validation purposes. We extend here our latest work on error decomposition and adaptive refinement for response surfaces to the development of surrogate models that can be substituted for the full models to estimate the parameters of Reynolds-averaged Navier-Stokes models. The error estimates and adaptive schemes are driven here by a quantity of interest and are thus based on the approximation of an adjoint problem. We will focus in particular to the accurate estimation of evidences to facilitate model selection. The methodology will be illustrated on the Spalart-Allmaras RANS model for turbulence simulation.

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:

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

Launch Vehicle Manual Steering with Adaptive Augmenting Control In-flight Evaluations of Adverse Interactions Using a Piloted Aircraft

Science.gov (United States)

Hanson, Curt; Miller, Chris; Wall, John H.; Vanzwieten, Tannen S.; Gilligan, Eric; Orr, Jeb S.

2015-01-01

An adaptive augmenting control algorithm for the Space Launch System has been developed at the Marshall Space Flight Center as part of the launch vehicles baseline flight control system. A prototype version of the SLS flight control software was hosted on a piloted aircraft at the Armstrong Flight Research Center to demonstrate the adaptive controller on a full-scale realistic application in a relevant flight environment. Concerns regarding adverse interactions between the adaptive controller and a proposed manual steering mode were investigated by giving the pilot trajectory deviation cues and pitch rate command authority. Two NASA research pilots flew a total of twenty five constant pitch-rate trajectories using a prototype manual steering mode with and without adaptive control.

Overcoming scepticism: Interacting influences of geographical location on perceived climate change adaptation measures to water resources in Spain

Science.gov (United States)

Iglesias, Ana; Garrote, Luis; Bardaji, Isabel; Iglesias, Pedro; Granados, Alfredo

2016-04-01

Though many climate adaptation efforts attempt to be defined with the participation of local communities, these strategies may be ineffective because among citizens affected equally, a local risk perception rather than scientific understanding largely drives adaptation choices. Further, the geographical location may polarize climate risk perceptions, making some adaptation efforts ineffective among sceptics. This study examines how the local degradation of the environment and water resources relates to adaption choices and in turn, climate change risk perception among a range of citizens in the Tagus basin, Spain (n = 300). We find respondents of less degraded areas have individualistic responses, and are significantly less likely to accept adaptation strategies than respondents in water stressed communities. The interaction between climate knowledge and adaptation choices is positively related to acceptance of adaptation choices in both groups, and had a stronger positive relationship among individualists. There is no statistical difference in acceptance of adaptation between individualists and communitarians at high levels of knowledge (top decile). Thus, education efforts specific to climate change may counteract divisions based geographical location and environmental stress.

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

Impact of bile salt adaptation of Lactobacillus delbrueckii subsp. lactis 200 on its interaction capacity with the gut.

Science.gov (United States)

Burns, Patricia; Reinheimer, Jorge; Vinderola, Gabriel

2011-10-01

In a previous work, bile-salt-resistant derivatives were obtained from non-intestinal lactobacilli. The aim of this work was to investigate the impact of bile adaptation of Lactobacillus delbrueckii subsp. lactis 200 on morphology, surface properties, in vivo interaction capacity with the gut and ability to activate the gut immune response. Electron microscopy studies, growth kinetics in the presence of bovine and porcine bile, the capacity to deconjugate bile acids, hydrophobicity, autoaggregation and co-aggregation capacities were studied for the parental strain and its bile-resistant derivative in vitro. Additionally, survival in intestinal fluid, the interaction with the gut and the immunomodulating capacities were studied in mice. Bile salt adaptation conferred upon the adapted strain a higher capacity to withstand physiological concentrations of bile salts and greater survival capacity in intestinal fluid. However, bile salt exposure reduced cell hydrophobicity, autoaggregation and adhesion capacities, resulting in reduced persistence in the intestinal lumen and delayed capacity to activate the gut immune response. Insight into the effects of bile salts upon the interaction and immunomodulating capacity of lactobacilli with the gut is provided, relating in vitro and in vivo results. Copyright © 2011 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

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

Directory of Open Access Journals (Sweden)

Juan M. Gandarias

2018-02-01

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

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

Science.gov (United States)

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

2018-02-26

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

Interaction graphs

DEFF Research Database (Denmark)

Seiller, Thomas

2016-01-01

Interaction graphs were introduced as a general, uniform, construction of dynamic models of linear logic, encompassing all Geometry of Interaction (GoI) constructions introduced so far. This series of work was inspired from Girard's hyperfinite GoI, and develops a quantitative approach that should...... be understood as a dynamic version of weighted relational models. Until now, the interaction graphs framework has been shown to deal with exponentials for the constrained system ELL (Elementary Linear Logic) while keeping its quantitative aspect. Adapting older constructions by Girard, one can clearly define...... "full" exponentials, but at the cost of these quantitative features. We show here that allowing interpretations of proofs to use continuous (yet finite in a measure-theoretic sense) sets of states, as opposed to earlier Interaction Graphs constructions were these sets of states were discrete (and finite...

Interaction Modeling at PROS Research Center

OpenAIRE

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

2011-01-01

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

Enhancing agent safety through autonomous environment adaptation

CSIR Research Space (South Africa)

Rosman, Benjamin S

2015-08-01

Full Text Available limit their ability to interact with and explore their environments. In this work we address this risk through the incorporation of a caregiver robot, and present a model allowing it to autonomously adapt its environment to minimize danger for other...

Adaptive Playware in Physical Games

DEFF Research Database (Denmark)

Lund, Henrik Hautop; Thorsteinsson, Arnar Tumi

2011-01-01

that the activity automatically will match the capability of the individual user. With small test groups, we investigate how different age groups and gender groups physically interact with some playware games, and find indications of differences between the groups. Despite the small test set, the results...... are a proof of existence of differences and of the need for adaptation, and therefore we investigate adaptation as an important issue for playware. With simple playware games, we show that the adaptation will speed the physical game up and down to find the appropriate level that matches the reaction speed......We describe how playware and games may adapt to the interaction of the individual user. We hypothesize that in physical games there are individual differences in user interaction capabilities and styles, and that adaptive playware may adapt to the individual user’s capabilities, so...

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

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

Vector-Interaction-Enhanced Bag Model

Science.gov (United States)

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

2018-02-01

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

Cross-cultural adaptation and validation of the Chinese Comfort, Afford, Respect, and Expect scale of caring nurse-patient interaction competence.

Science.gov (United States)

Chung, Hui-Chun; Hsieh, Tsung-Cheng; Chen, Yueh-Chih; Chang, Shu-Chuan; Hsu, Wen-Lin

2017-11-29

To investigate the construct validity and reliability of the Chinese Comfort, Afford, Respect, and Expect scale, which can be used to determine clinical nurses' competence. The results can also serve to promote nursing competence and improve patient satisfaction. Nurse-patient interaction is critical for improving nursing care quality. However, to date, no relevant validated instrument has been proposed for assessing caring nurse-patient interaction competence in clinical practice. This study adapted and validated the Chinese version of the caring nurse-patient interaction scale. A cross-cultural adaptation and validation study. A psychometric analysis of the four major constructs of the Chinese Comfort, Afford, Respect, and Expect scale was conducted on a sample of 356 nurses from a medical centre in China. Item analysis and exploratory factor analysis were adopted to extract the main components, both the internal consistency and correlation coefficients were used to examine reliability and a confirmatory factor analysis was adopted to verify the construct validity. The goodness-of-fit results of the model were strong. The standardised factor loadings of the Chinese Comfort, Afford, Respect, and Expect scale ranged from 0.73-0.95, indicating that the validity and reliability of this instrument were favourable. Moreover, the 12 extracted items explained 95.9% of the measured content of the Chinese Comfort, Afford, Respect, and Expect scale. The results serve as empirical evidence regarding the validity and reliability of the Chinese Comfort, Afford, Respect, and Expect scale. Hospital nurses increasingly demand help from patients and their family members in identifying health problems and assisting with medical decision-making. Therefore, enhancing nurses' competence in nurse-patient interactions is crucial for nursing and hospital managers to improve nursing care quality. The Chinese caring nurse-patient interaction scale can serve as an effective tool for nursing

Design of a Model Reference Adaptive Controller for an Unmanned Air Vehicle

Science.gov (United States)

Crespo, Luis G.; Matsutani, Megumi; Annaswamy, Anuradha M.

2010-01-01

This paper presents the "Adaptive Control Technology for Safe Flight (ACTS)" architecture, which consists of a non-adaptive controller that provides satisfactory performance under nominal flying conditions, and an adaptive controller that provides robustness under off nominal ones. The design and implementation procedures of both controllers are presented. The aim of these procedures, which encompass both theoretical and practical considerations, is to develop a controller suitable for flight. The ACTS architecture is applied to the Generic Transport Model developed by NASA-Langley Research Center. The GTM is a dynamically scaled test model of a transport aircraft for which a flight-test article and a high-fidelity simulation are available. The nominal controller at the core of the ACTS architecture has a multivariable LQR-PI structure while the adaptive one has a direct, model reference structure. The main control surfaces as well as the throttles are used as control inputs. The inclusion of the latter alleviates the pilot s workload by eliminating the need for cancelling the pitch coupling generated by changes in thrust. Furthermore, the independent usage of the throttles by the adaptive controller enables their use for attitude control. Advantages and potential drawbacks of adaptation are demonstrated by performing high fidelity simulations of a flight-validated controller and of its adaptive augmentation.

Detecting consistent patterns of directional adaptation using differential selection codon models.

Science.gov (United States)

Parto, Sahar; Lartillot, Nicolas

2017-06-23

Phylogenetic codon models are often used to characterize the selective regimes acting on protein-coding sequences. Recent methodological developments have led to models explicitly accounting for the interplay between mutation and selection, by modeling the amino acid fitness landscape along the sequence. However, thus far, most of these models have assumed that the fitness landscape is constant over time. Fluctuations of the fitness landscape may often be random or depend on complex and unknown factors. However, some organisms may be subject to systematic changes in selective pressure, resulting in reproducible molecular adaptations across independent lineages subject to similar conditions. Here, we introduce a codon-based differential selection model, which aims to detect and quantify the fine-grained consistent patterns of adaptation at the protein-coding level, as a function of external conditions experienced by the organism under investigation. The model parameterizes the global mutational pressure, as well as the site- and condition-specific amino acid selective preferences. This phylogenetic model is implemented in a Bayesian MCMC framework. After validation with simulations, we applied our method to a dataset of HIV sequences from patients with known HLA genetic background. Our differential selection model detects and characterizes differentially selected coding positions specifically associated with two different HLA alleles. Our differential selection model is able to identify consistent molecular adaptations as a function of repeated changes in the environment of the organism. These models can be applied to many other problems, ranging from viral adaptation to evolution of life-history strategies in plants or animals.

SELECTION VARIETALE ET MILIEU Sélection pour l’adaptation au milieu et prise en compte des interactions génotype/milieu

Directory of Open Access Journals (Sweden)

Brancourt-Hulmel Maryse

2000-11-01

Full Text Available L’adaptation au milieu est un objectif de sélection recherché pour un grand nombre d’espèces végétales et elle fait le plus souvent appel à l’analyse du rendement. L’améliorateur peut rechercher des génotypes présentant une « adaptation spécifique », c’est-à-dire une adaptation à des milieux spécifiques, ou au contraire une « adaptation générale » à des conditions de milieux variés *1+. L’adaptation spécifique pourra être obtenue pour des stress particuliers, observés en l’occurrence dans des milieux particuliers : citons, par exemple, l’adaptation du maïs à des froids printaniers dans les régions françaises septentrionales, l’adaptation du blé tendre d’hiver à une alimentation azotée sub-optimale, la tolérance de l’orge à la mosaïque modérée, etc. L’adaptation générale, parfois appelée adaptabilité, est conférée par une adaptation simultanée à un ensemble de contraintes du milieu, telles que le froid, la sécheresse, le manque d’eau, le manque ou l’excès d’azote, les maladies, etc. C’est en quelque sorte une somme d’adaptations spécifiques. Mais le nombre de contraintes du milieu est tel qu’il est difficile de les étudier toutes. Il faudrait, en effet, des dispositifs factoriels très lourds à mettre en place car nécessitant l’étude d’un grand nombre de facteurs à la fois, avec toutes les combinaisons entre facteurs. Les conditions naturelles sont, de surcroît, difficiles à reproduire en enceintes contrôlées. Ainsi, l’adaptation générale s’observe le plus souvent en conditions naturelles dans des réseaux d’expérimentation regroupant un ensemble de milieux sur plusieurs années, les « réseaux multilocaux et pluriannuels ». La notion d’adaptation est à replacer dans le contexte des interactions génotype/milieu car des variations d’adaptation se traduisent par des interactions génotype/milieu. Lorsque plusieurs génotypes sont �

Adapting interaction environments to diverse users through online action set selection

CSIR Research Space (South Africa)

Hassan Mahmud, MM

2014-06-01

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

Adaptive user interfaces

CERN Document Server

1990-01-01

This book describes techniques for designing and building adaptive user interfaces developed in the large AID project undertaken by the contributors.Key Features* Describes one of the few large-scale adaptive interface projects in the world* Outlines the principles of adaptivity in human-computer interaction

Genomic Prediction Accounting for Genotype by Environment Interaction Offers an Effective Framework for Breeding Simultaneously for Adaptation to an Abiotic Stress and Performance Under Normal Cropping Conditions in Rice.

Science.gov (United States)

Ben Hassen, Manel; Bartholomé, Jérôme; Valè, Giampiero; Cao, Tuong-Vi; Ahmadi, Nourollah

2018-05-09

Developing rice varieties adapted to alternate wetting and drying water management is crucial for the sustainability of irrigated rice cropping systems. Here we report the first study exploring the feasibility of breeding rice for adaptation to alternate wetting and drying using genomic prediction methods that account for genotype by environment interactions. Two breeding populations (a reference panel of 284 accessions and a progeny population of 97 advanced lines) were evaluated under alternate wetting and drying and continuous flooding management systems. The predictive ability of genomic prediction for response variables (index of relative performance and the slope of the joint regression) and for multi-environment genomic prediction models were compared. For the three traits considered (days to flowering, panicle weight and nitrogen-balance index), significant genotype by environment interactions were observed in both populations. In cross validation, predictive ability for the index was on average lower (0.31) than that of the slope of the joint regression (0.64) whatever the trait considered. Similar results were found for progeny validation. Both cross-validation and progeny validation experiments showed that the performance of multi-environment models predicting unobserved phenotypes of untested entrees was similar to the performance of single environment models with differences in predictive ability ranging from -6% to 4% depending on the trait and on the statistical model concerned. The predictive ability of multi-environment models predicting unobserved phenotypes of entrees evaluated under both water management systems outperformed single environment models by an average of 30%. Practical implications for breeding rice for adaptation to alternate wetting and drying system are discussed. Copyright © 2018, G3: Genes, Genomes, Genetics.

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.

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

Science.gov (United States)

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

2004-05-01

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

User Adaptive and Context-Aware Smart Home Using Pervasive and Semantic Technologies

Directory of Open Access Journals (Sweden)

Aggeliki Vlachostergiou

2016-01-01

Full Text Available Ubiquitous Computing is moving the interaction away from the human-computer paradigm and towards the creation of smart environments that users and things, from the IoT perspective, interact with. User modeling and adaptation is consistently present having the human user as a constant but pervasive interaction introduces the need for context incorporation towards context-aware smart environments. The current article discusses both aspects of the user modeling and adaptation as well as context awareness and incorporation into the smart home domain. Users are modeled as fuzzy personas and these models are semantically related. Context information is collected via sensors and corresponds to various aspects of the pervasive interaction such as temperature and humidity, but also smart city sensors and services. This context information enhances the smart home environment via the incorporation of user defined home rules. Semantic Web technologies support the knowledge representation of this ecosystem while the overall architecture has been experimentally verified using input from the SmartSantander smart city and applying it to the SandS smart home within FIRE and FIWARE frameworks.

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...

Dynamic Adaptation in Child-Adult Language Interaction

Science.gov (United States)

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

2013-01-01

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

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.

Adaptation Decision Support: An Application of System Dynamics Modeling in Coastal Communities

Institute of Scientific and Technical Information of China (English)

Daniel Lane; Shima Beigzadeh; Richard Moll

2017-01-01

This research develops and applies a system dynamics (SD) model for the strategic evaluation of environmental adaptation options for coastal communities.The article defines and estimates asset-based measures for community vulnerability,resilience,and adaptive capacity with respect to the environmental,economic,social,and cultural pillars of the coastal community under threat.The SD model simulates the annual multidimensional dynamic impacts of severe coastal storms and storm surges on the community pillars under alternative adaptation strategies.The calculation of the quantitative measures provides valuable information for decision makers for evaluating the alternative strategies.The adaptation strategies are designed model results illustrated for the specific context of the coastal community of Charlottetown,Prince Edward Island,Canada.The dynamic trend of the measures and model sensitivity analyses for Charlottetown-facing increased frequency of severe storms,storm surges,and sea-level rise-provide impetus for enhanced community strategic planning for the changing coastal environment.This research is presented as part of the International Community-University Research Alliance C-Change project "Managing Adaptation to Environmental Change in Coastal Communities:Canada and the Caribbean" sponsored by the Social Science and Humanities Research Council of Canada and the International Development Resource Centre.

A model-based adaptive state of charge estimator for a lithium-ion battery using an improved adaptive particle filter

International Nuclear Information System (INIS)

Ye, Min; Guo, Hui; Cao, Binggang

2017-01-01

Highlights: • Propose an improved adaptive particle swarm filter method. • The SoC estimation method for the battery based on the adaptive particle swarm filter is presented. • The algorithm is validated by the case study of different aged extent batteries. • The effectiveness and applicability of the algorithm are validated by the LiPB batteries. - Abstract: Obtaining accurate parameters, state of charge (SoC) and capacity of a lithium-ion battery is crucial for a battery management system, and establishing a battery model online is complex. In addition, the errors and perturbations of the battery model dramatically increase throughout the battery lifetime, making it more challenging to model the battery online. To overcome these difficulties, this paper provides three contributions: (1) To improve the robustness of the adaptive particle filter algorithm, an error analysis method is added to the traditional adaptive particle swarm algorithm. (2) An online adaptive SoC estimator based on the improved adaptive particle filter is presented; this estimator can eliminate the estimation error due to battery degradation and initial SoC errors. (3) The effectiveness of the proposed method is verified using various initial states of lithium nickel manganese cobalt oxide (NMC) cells and lithium-ion polymer (LiPB) batteries. The experimental analysis shows that the maximum errors are less than 1% for both the voltage and SoC estimations and that the convergence time of the SoC estimation decreased to 120 s.

Quantifying the relevance of adaptive thermal comfort models in moderate thermal climate zones

Energy Technology Data Exchange (ETDEWEB)

Hoof, Joost van; Hensen, Jan L.M. [Faculty of Architecture, Building and Planning, Technische Universiteit Eindhoven, Vertigo 6.18, P.O. Box 513, 5600 MB Eindhoven (Netherlands)

2007-01-15

Standards governing thermal comfort evaluation are on a constant cycle of revision and public review. One of the main topics being discussed in the latest round was the introduction of an adaptive thermal comfort model, which now forms an optional part of ASHRAE Standard 55. Also on a national level, adaptive thermal comfort guidelines come into being, such as in the Netherlands. This paper discusses two implementations of the adaptive comfort model in terms of usability and energy use for moderate maritime climate zones by means of literature study, a case study comprising temperature measurements, and building performance simulation. It is concluded that for moderate climate zones the adaptive model is only applicable during summer months, and can reduce energy for naturally conditioned buildings. However, the adaptive thermal comfort model has very limited application potential for such climates. Additionally we suggest a temperature parameter with a gradual course to replace the mean monthly outdoor air temperature to avoid step changes in optimum comfort temperatures. (author)

[Development of a structural equation model for children's adaptation in divorced families].

Science.gov (United States)

Shin, Sung Hee

2010-02-01

This study was designed to develop and test a structural model for children's adaptation in divorced families. The hypothetical model was constructed based on the Family Resilience Model by McCubbin and McCubbin. Data were collected using self-report questionnaires from 219 children (3-6th grade) in divorced families. The children attended one of 22 community agencies, 8 after-school programs, 3 elementary schools in three cities in South Korea. The collected data were analyzed using LISREL program to test the hypothetical model. The modified model was constructed by deleting four paths in accordance with the statistical and theoretical criteria. Compared to the hypothetical model, the revised one had a better fit to the data. Self-esteem, and beliefs about parental divorce had direct effects, and family communication and internal control had indirect effects on children's adaptation in divorced families. These variables explained 56% of the variance in children's adaptation. The modified model was supported by empirical data. This model could be applied to family nursing interventions with divorced families or any other suffering family transition. When working with children experiencing parental divorce, it is important for nurses to enhance children's self-esteem, family communication and to decrease children's negative beliefs about parental divorce to help in their adaptation.

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…

Conceptual Modeling for Adaptive Environmental Assessment and Management in the Barycz Valley, Lower Silesia, Poland

Directory of Open Access Journals (Sweden)

Jakub Kronenberg

2005-08-01

Full Text Available The complexity of interactions in socio-ecological systems makes it very difficult to plan and implement policies successfully. Traditional environmental management and assessment techniques produce unsatisfactory results because they often ignore facets of system structure that underlie complexity: delays, feedbacks, and non-linearities. Assuming that causes are linked in a linear chain, they concentrate on technological developments (“hard path” as the only solutions to environmental problems. Adaptive Management is recognized as a promising alternative approach directly addressing links between social and ecological systems and involving stakeholders in the analysis and decision process. This “soft path” requires special tools to facilitate collaboration between “experts” and stakeholders in analyzing complex situations and prioritizing policies and actions. We have applied conceptual modeling to increase communication, understanding and commitment in the project of seven NGOs “Sustainable Regional Development in the Odra Catchment”. The main goal was to help our NGO partners to facilitate their efforts related to developing sustainable policies and practices to respond to large-scale challenges (EU accession, global changes in climate and economy to their natural, economic and socio-cultural heritages. Among the variety of sustainability issues explored by these NGOs, two (extensive agricultural practices and “green” local products were examined by using Adaptive Management (AM as a framework that would link analysis, discussion, research, actions and monitoring. Within the AM framework the project coordinators used tools of systems analysis (Mental Model Mapping to facilitate discussions in which NGO professionals and local stakeholders could graphically diagram and study their understanding of what factors interacted and

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

Czech Academy of Sciences Publication Activity Database

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

2017-01-01

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

dSPACE based adaptive neuro-fuzzy controller of grid interactive inverter

International Nuclear Information System (INIS)

Altin, Necmi; Sefa, İbrahim

2012-01-01

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

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)

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 ...

Domain Modeling for Adaptive Training and Education in Support of the US Army Learning Model-Research Outline

Science.gov (United States)

2015-06-01

Definitions are provided for this section to distinguish between adaptive training and education elements and also to highlight their relationships ...illustrate this point Franke (2011) asserts that through the use of case study examples, instruction can provide the pedagogical foundation for decision...a prime example of an adaptive training and education system: a learner or trainee model, an instructional or pedagogical model, a domain model

Analytic Model Predictive Control of Uncertain Nonlinear Systems: A Fuzzy Adaptive Approach

Directory of Open Access Journals (Sweden)

Xiuyan Peng

2015-01-01

Full Text Available A fuzzy adaptive analytic model predictive control method is proposed in this paper for a class of uncertain nonlinear systems. Specifically, invoking the standard results from the Moore-Penrose inverse of matrix, the unmatched problem which exists commonly in input and output dimensions of systems is firstly solved. Then, recurring to analytic model predictive control law, combined with fuzzy adaptive approach, the fuzzy adaptive predictive controller synthesis for the underlying systems is developed. To further reduce the impact of fuzzy approximation error on the system and improve the robustness of the system, the robust compensation term is introduced. It is shown that by applying the fuzzy adaptive analytic model predictive controller the rudder roll stabilization system is ultimately uniformly bounded stabilized in the H-infinity sense. Finally, simulation results demonstrate the effectiveness of the proposed method.

Adaptive Estimation of Heteroscedastic Money Demand Model of Pakistan

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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.

Using Interaction Scenarios to Model Information Systems

DEFF Research Database (Denmark)

Bækgaard, Lars; Bøgh Andersen, Peter

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

Adapting Parent-Child Interaction Therapy to Foster Care

Science.gov (United States)

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

2016-01-01

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

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

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

Psychosocial Adaptation to Chronic Illness and Disability: A Virtue Based Model.

Science.gov (United States)

Kim, Jeong Han; McMahon, Brian T; Hawley, Carolyn; Brickham, Dana; Gonzalez, Rene; Lee, Dong-Hun

2016-03-01

Psychosocial adaptation to chronic illness and disability (CID) is an area of study where a positive psychology perspective, especially the study of virtues and character strengths, can be implemented within the rehabilitation framework. A carefully developed theory to guide future interdisciplinary research is now timely. A traditional literature review between philosophy and rehabilitation psychology was conducted in order to develop a virtue-based psychosocial adaptation theory, merging important perspectives from the fields of rehabilitation and positive psychology. The virtue-based psychosocial adaptation model (V-PAM) to CID is proposed in the present study. The model involves five qualities or constructs: courage, practical wisdom, commitment to action, integrity and emotional transcendence. Each of these components of virtue contributes to an understanding of psychosocial adaptation. The present study addresses the implications and applications of V-PAM that will advance this understanding.

Model Adaptation for Prognostics in a Particle Filtering Framework

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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.

Adaptive time-variant models for fuzzy-time-series forecasting.

Science.gov (United States)

Wong, Wai-Keung; Bai, Enjian; Chu, Alice Wai-Ching

2010-12-01

A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, and other domains. Related studies mainly focus on three factors, namely, the partition of discourse, the content of forecasting rules, and the methods of defuzzification, all of which greatly influence the prediction accuracy of forecasting models. These studies use fixed analysis window sizes for forecasting. In this paper, an adaptive time-variant fuzzy-time-series forecasting model (ATVF) is proposed to improve forecasting accuracy. The proposed model automatically adapts the analysis window size of fuzzy time series based on the prediction accuracy in the training phase and uses heuristic rules to generate forecasting values in the testing phase. The performance of the ATVF model is tested using both simulated and actual time series including the enrollments at the University of Alabama, Tuscaloosa, and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). The experiment results show that the proposed ATVF model achieves a significant improvement in forecasting accuracy as compared to other fuzzy-time-series forecasting models.

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.

SU-F-BRF-01: A GPU Framework for Developing Interactive High-Resolution Patient-Specific Biomechanical Models

International Nuclear Information System (INIS)

Neylon, J; Qi, S; Sheng, K; Kupelian, P; Santhanam, A

2014-01-01

Purpose: To develop a GPU-based framework that can generate highresolution and patient-specific biomechanical models from a given simulation CT and contoured structures, optimized to run at interactive speeds, for addressing adaptive radiotherapy objectives. Method: A Massspring-damping (MSD) model was generated from a given simulation CT. The model's mass elements were generated for every voxel of anatomy, and positioned in a deformation space in the GPU memory. MSD connections were established between neighboring mass elements in a dense distribution. Contoured internal structures allowed control over elastic material properties of different tissues. Once the model was initialized in GPU memory, skeletal anatomy was actuated using rigid-body transformations, while soft tissues were governed by elastic corrective forces and constraints, which included tensile forces, shear forces, and spring damping forces. The model was validated by applying a known load to a soft tissue block and comparing the observed deformation to ground truth calculations from established elastic mechanics. Results: Our analyses showed that both local and global load experiments yielded results with a correlation coefficient R 2 > 0.98 compared to ground truth. Models were generated for several anatomical regions. Head and neck models accurately simulated posture changes by rotating the skeletal anatomy in three dimensions. Pelvic models were developed for realistic deformations for changes in bladder volume. Thoracic models demonstrated breast deformation due to gravity when changing treatment position from supine to prone. The GPU framework performed at greater than 30 iterations per second for over 1 million mass elements with up to 26 MSD connections each. Conclusions: Realistic simulations of site-specific, complex posture and physiological changes were simulated at interactive speeds using patient data. Incorporating such a model with live patient tracking would facilitate real

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.

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

Connectionist Interaction Information Retrieval.

Science.gov (United States)

Dominich, Sandor

2003-01-01

Discussion of connectionist views for adaptive clustering in information retrieval focuses on a connectionist clustering technique and activation spreading-based information retrieval model using the interaction information retrieval method. Presents theoretical as well as simulation results as regards computational complexity and includes…

Aperiodic dynamics in a deterministic adaptive network model of attitude formation in social groups

Science.gov (United States)

Ward, Jonathan A.; Grindrod, Peter

2014-07-01

Adaptive network models, in which node states and network topology coevolve, arise naturally in models of social dynamics that incorporate homophily and social influence. Homophily relates the similarity between pairs of nodes' states to their network coupling strength, whilst social influence causes coupled nodes' states to convergence. In this paper we propose a deterministic adaptive network model of attitude formation in social groups that includes these effects, and in which the attitudinal dynamics are represented by an activato-inhibitor process. We illustrate that consensus, corresponding to all nodes adopting the same attitudinal state and being fully connected, may destabilise via Turing instability, giving rise to aperiodic dynamics with sensitive dependence on initial conditions. These aperiodic dynamics correspond to the formation and dissolution of sub-groups that adopt contrasting attitudes. We discuss our findings in the context of cultural polarisation phenomena. Social influence. This reflects the fact that people tend to modify their behaviour and attitudes in response to the opinions of others [22-26]. We model social influence via diffusion: agents adjust their state according to a weighted sum (dictated by the evolving network) of the differences between their state and the states of their neighbours. Homophily. This relates the similarity of individuals' states to their frequency and strength of interaction [27]. Thus in our model, homophily drives the evolution of the weighted ‘social' network. A precise formulation of our model is given in Section 2. Social influence and homophily underpin models of social dynamics [21], which cover a wide range of sociological phenomena, including the diffusion of innovations [28-32], complex contagions [33-36], collective action [37-39], opinion dynamics [19,20,40,10,11,13,15,41,16], the emergence of social norms [42-44], group stability [45], social differentiation [46] and, of particular relevance

Combination of Adaptive Feedback Cancellation and Binaural Adaptive Filtering in Hearing Aids

Directory of Open Access Journals (Sweden)

Anthony Lombard

2009-01-01

Full Text Available We study a system combining adaptive feedback cancellation and adaptive filtering connecting inputs from both ears for signal enhancement in hearing aids. For the first time, such a binaural system is analyzed in terms of system stability, convergence of the algorithms, and possible interaction effects. As major outcomes of this study, a new stability condition adapted to the considered binaural scenario is presented, some already existing and commonly used feedback cancellation performance measures for the unilateral case are adapted to the binaural case, and possible interaction effects between the algorithms are identified. For illustration purposes, a blind source separation algorithm has been chosen as an example for adaptive binaural spatial filtering. Experimental results for binaural hearing aids confirm the theoretical findings and the validity of the new measures.

Separating the role of biotic interactions and climate in determining adaptive response of plants to climate change.

Science.gov (United States)

Tomiolo, Sara; Van der Putten, Wim H; Tielbörger, Katja

2015-05-01

Altered rainfall regimes will greatly affect the response of plant species to climate change. However, little is known about how direct effects of changing precipitation on plant performance may depend on other abiotic factors and biotic interactions. We used reciprocal transplants between climatically very different sites with simultaneous manipulation of soil, plant population origin, and neighbor conditions to evaluate local adaptation and possible adaptive response of four Eastern Mediterranean annual plant species to climate change. The effect of site on plant performance was negligible, but soil origin had a strong effect on fecundity, most likely due to differential water retaining ability. Competition by neighbors strongly reduced fitness. We separated the effects of the abiotic and biotic soil properties on plant performance by repeating the field experiment in a greenhouse under homogenous environmental conditions and including a soil biota manipulation treatment. As in the field, plant performance differed among soil origins and neighbor treatments. Moreover, we found plant species-specific responses to soil biota that may be best explained by the differential sensitivity to negative and positive soil biota effects. Overall, under the conditions of our experiment with two contrasting sites, biotic interactions had a strong effect on plant fitness that interacted with and eventually overrode climate. Because climate and biotic interactions covary, reciprocal transplants and climate gradient studies should consider soil biotic interactions and abiotic conditions when evaluating climate change effects on plant performance.

Fuzzy model-based adaptive synchronization of time-delayed chaotic systems

International Nuclear Information System (INIS)

Vasegh, Nastaran; Majd, Vahid Johari

2009-01-01

In this paper, fuzzy model-based synchronization of a class of first order chaotic systems described by delayed-differential equations is addressed. To design the fuzzy controller, the chaotic system is modeled by Takagi-Sugeno fuzzy system considering the properties of the nonlinear part of the system. Assuming that the parameters of the chaotic system are unknown, an adaptive law is derived to estimate these unknown parameters, and the stability of error dynamics is guaranteed by Lyapunov theory. Numerical examples are given to demonstrate the validity of the proposed adaptive synchronization approach.

Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models

International Nuclear Information System (INIS)

Nguyen, Hang T.; Nabney, Ian T.

2010-01-01

This paper presents some forecasting techniques for energy demand and price prediction, one day ahead. These techniques combine wavelet transform (WT) with fixed and adaptive machine learning/time series models (multi-layer perceptron (MLP), radial basis functions, linear regression, or GARCH). To create an adaptive model, we use an extended Kalman filter or particle filter to update the parameters continuously on the test set. The adaptive GARCH model is a new contribution, broadening the applicability of GARCH methods. We empirically compared two approaches of combining the WT with prediction models: multicomponent forecasts and direct forecasts. These techniques are applied to large sets of real data (both stationary and non-stationary) from the UK energy markets, so as to provide comparative results that are statistically stronger than those previously reported. The results showed that the forecasting accuracy is significantly improved by using the WT and adaptive models. The best models on the electricity demand/gas price forecast are the adaptive MLP/GARCH with the multicomponent forecast; their NMSEs are 0.02314 and 0.15384 respectively. (author)

Coastal Adaptation Planning for Sea Level Rise and Extremes: A Global Model for Adaptation Decision-making at the Local Level Given Uncertain Climate Projections

Science.gov (United States)

Turner, D.

2014-12-01

Understanding the potential economic and physical impacts of climate change on coastal resources involves evaluating a number of distinct adaptive responses. This paper presents a tool for such analysis, a spatially-disaggregated optimization model for adaptation to sea level rise (SLR) and storm surge, the Coastal Impact and Adaptation Model (CIAM). This decision-making framework fills a gap between very detailed studies of specific locations and overly aggregate global analyses. While CIAM is global in scope, the optimal adaptation strategy is determined at the local level, evaluating over 12,000 coastal segments as described in the DIVA database (Vafeidis et al. 2006). The decision to pursue a given adaptation measure depends on local socioeconomic factors like income, population, and land values and how they develop over time, relative to the magnitude of potential coastal impacts, based on geophysical attributes like inundation zones and storm surge. For example, the model's decision to protect or retreat considers the costs of constructing and maintaining coastal defenses versus those of relocating people and capital to minimize damages from land inundation and coastal storms. Uncertain storm surge events are modeled with a generalized extreme value distribution calibrated to data on local surge extremes. Adaptation is optimized for the near-term outlook, in an "act then learn then act" framework that is repeated over the model time horizon. This framework allows the adaptation strategy to be flexibly updated, reflecting the process of iterative risk management. CIAM provides new estimates of the economic costs of SLR; moreover, these detailed results can be compactly represented in a set of adaptation and damage functions for use in integrated assessment models. Alongside the optimal result, CIAM evaluates suboptimal cases and finds that global costs could increase by an order of magnitude, illustrating the importance of adaptive capacity and coastal policy.

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

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

A Personalized Predictive Framework for Multivariate Clinical Time Series via Adaptive Model Selection.

Science.gov (United States)

Liu, Zitao; Hauskrecht, Milos

2017-11-01

Building of an accurate predictive model of clinical time series for a patient is critical for understanding of the patient condition, its dynamics, and optimal patient management. Unfortunately, this process is not straightforward. First, patient-specific variations are typically large and population-based models derived or learned from many different patients are often unable to support accurate predictions for each individual patient. Moreover, time series observed for one patient at any point in time may be too short and insufficient to learn a high-quality patient-specific model just from the patient's own data. To address these problems we propose, develop and experiment with a new adaptive forecasting framework for building multivariate clinical time series models for a patient and for supporting patient-specific predictions. The framework relies on the adaptive model switching approach that at any point in time selects the most promising time series model out of the pool of many possible models, and consequently, combines advantages of the population, patient-specific and short-term individualized predictive models. We demonstrate that the adaptive model switching framework is very promising approach to support personalized time series prediction, and that it is able to outperform predictions based on pure population and patient-specific models, as well as, other patient-specific model adaptation strategies.

Interactive differential equations modeling program

International Nuclear Information System (INIS)

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

1976-01-01

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

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.

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.

An analytical model for interactive failures

International Nuclear Information System (INIS)

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

2006-01-01

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

Map Learning with a 3D Printed Interactive Small-Scale Model: Improvement of Space and Text Memorization in Visually Impaired Students

Directory of Open Access Journals (Sweden)

Stéphanie Giraud

2017-06-01

Full Text Available Special education teachers for visually impaired students rely on tools such as raised-line maps (RLMs to teach spatial knowledge. These tools do not fully and adequately meet the needs of the teachers because they are long to produce, expensive, and not versatile enough to provide rapid updating of the content. For instance, the same RLM can barely be used during different lessons. In addition, those maps do not provide any interactivity, which reduces students’ autonomy. With the emergence of 3D printing and low-cost microcontrollers, it is now easy to design affordable interactive small-scale models (SSMs which are adapted to the needs of special education teachers. However, no study has previously been conducted to evaluate non-visual learning using interactive SSMs. In collaboration with a specialized teacher, we designed a SSM and a RLM representing the evolution of the geography and history of a fictitious kingdom. The two conditions were compared in a study with 24 visually impaired students regarding the memorization of the spatial layout and historical contents. The study showed that the interactive SSM improved both space and text memorization as compared to the RLM with braille legend. In conclusion, we argue that affordable home-made interactive small scale models can improve learning for visually impaired students. Interestingly, they are adaptable to any teaching situation including students with specific needs.

Map Learning with a 3D Printed Interactive Small-Scale Model: Improvement of Space and Text Memorization in Visually Impaired Students.

Science.gov (United States)

Giraud, Stéphanie; Brock, Anke M; Macé, Marc J-M; Jouffrais, Christophe

2017-01-01

Special education teachers for visually impaired students rely on tools such as raised-line maps (RLMs) to teach spatial knowledge. These tools do not fully and adequately meet the needs of the teachers because they are long to produce, expensive, and not versatile enough to provide rapid updating of the content. For instance, the same RLM can barely be used during different lessons. In addition, those maps do not provide any interactivity, which reduces students' autonomy. With the emergence of 3D printing and low-cost microcontrollers, it is now easy to design affordable interactive small-scale models (SSMs) which are adapted to the needs of special education teachers. However, no study has previously been conducted to evaluate non-visual learning using interactive SSMs. In collaboration with a specialized teacher, we designed a SSM and a RLM representing the evolution of the geography and history of a fictitious kingdom. The two conditions were compared in a study with 24 visually impaired students regarding the memorization of the spatial layout and historical contents. The study showed that the interactive SSM improved both space and text memorization as compared to the RLM with braille legend. In conclusion, we argue that affordable home-made interactive small scale models can improve learning for visually impaired students. Interestingly, they are adaptable to any teaching situation including students with specific needs.

An adaptive time-stepping strategy for solving the phase field crystal model

International Nuclear Information System (INIS)

Zhang, Zhengru; Ma, Yuan; Qiao, Zhonghua

2013-01-01

In this work, we will propose an adaptive time step method for simulating the dynamics of the phase field crystal (PFC) model. The numerical simulation of the PFC model needs long time to reach steady state, and then large time-stepping method is necessary. Unconditionally energy stable schemes are used to solve the PFC model. The time steps are adaptively determined based on the time derivative of the corresponding energy. It is found that the use of the proposed time step adaptivity cannot only resolve the steady state solution, but also the dynamical development of the solution efficiently and accurately. The numerical experiments demonstrate that the CPU time is significantly saved for long time simulations

Smart plants, smart models? On adaptive responses in vegetation-soil systems

Science.gov (United States)

van der Ploeg, Martine; Teuling, Ryan; van Dam, Nicole; de Rooij, Gerrit

2015-04-01

Hydrological models that will be able to cope with future precipitation and evapotranspiration regimes need a solid base describing the essence of the processes involved [1]. The essence of emerging patterns at large scales often originates from micro-behaviour in the soil-vegetation-atmosphere system. A complicating factor in capturing this behaviour is the constant interaction between vegetation and geology in which water plays a key role. The resilience of the coupled vegetation-soil system critically depends on its sensitivity to environmental changes. To assess root water uptake by plants in a changing soil environment, a direct indication of the amount of energy required by plants to take up water can be obtained by measuring the soil water potential in the vicinity of roots with polymer tensiometers [2]. In a lysimeter experiment with various levels of imposed water stress the polymer tensiometer data suggest maize roots regulate their root water uptake on the derivative of the soil water retention curve, rather than the amount of moisture alone. As a result of environmental changes vegetation may wither and die, or these changes may instead trigger gene adaptation. Constant exposure to environmental stresses, biotic or abiotic, influences plant physiology, gene adaptations, and flexibility in gene adaptation [3-7]. To investigate a possible relation between plant genotype, the plant stress hormone abscisic acid (ABA) and the soil water potential, a proof of principle experiment was set up with Solanum Dulcamare plants. The results showed a significant difference in ABA response between genotypes from a dry and a wet environment, and this response was also reflected in the root water uptake. Adaptive responses may have consequences for the way species are currently being treated in models (single plant to global scale). In particular, model parameters that control root water uptake and plant transpiration are generally assumed to be a property of the plant

Porous models for wave-seabed interactions

Energy Technology Data Exchange (ETDEWEB)

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

2013-02-01

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

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.

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.

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

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

International Nuclear Information System (INIS)

Tanimoto, Jun

2014-01-01

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

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).

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.

Bayesian analysis for exponential random graph models using the adaptive exchange sampler

KAUST Repository

Jin, Ick Hoon

2013-01-01

Exponential random graph models have been widely used in social network analysis. However, these models are extremely difficult to handle from a statistical viewpoint, because of the existence of intractable normalizing constants. In this paper, we consider a fully Bayesian analysis for exponential random graph models using the adaptive exchange sampler, which solves the issue of intractable normalizing constants encountered in Markov chain Monte Carlo (MCMC) simulations. The adaptive exchange sampler can be viewed as a MCMC extension of the exchange algorithm, and it generates auxiliary networks via an importance sampling procedure from an auxiliary Markov chain running in parallel. The convergence of this algorithm is established under mild conditions. The adaptive exchange sampler is illustrated using a few social networks, including the Florentine business network, molecule synthetic network, and dolphins network. The results indicate that the adaptive exchange algorithm can produce more accurate estimates than approximate exchange algorithms, while maintaining the same computational efficiency.

Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm

International Nuclear Information System (INIS)

Sun, Zhe; Wang, Ning; Bi, Yunrui; Srinivasan, Dipti

2015-01-01

In this paper, a HADE (hybrid adaptive differential evolution) algorithm is proposed for the identification problem of PEMFC (proton exchange membrane fuel cell). Inspired by biological genetic strategy, a novel adaptive scaling factor and a dynamic crossover probability are presented to improve the adaptive and dynamic performance of differential evolution algorithm. Moreover, two kinds of neighborhood search operations based on the bee colony foraging mechanism are introduced for enhancing local search efficiency. Through testing the benchmark functions, the proposed algorithm exhibits better performance in convergent accuracy and speed. Finally, the HADE algorithm is applied to identify the nonlinear parameters of PEMFC stack model. Through experimental comparison with other identified methods, the PEMFC model based on the HADE algorithm shows better performance. - Highlights: • We propose a hybrid adaptive differential evolution algorithm (HADE). • The search efficiency is enhanced in low and high dimension search space. • The effectiveness is confirmed by testing benchmark functions. • The identification of the PEMFC model is conducted by adopting HADE.

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...

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.

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.

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

Adapting Activity and Participation (The ADAPT intervention program)

DEFF Research Database (Denmark)

von Bülow, Cecilie

Præsentation af et ergoterapeutisk gruppebaseret program, ADAPT programmet. ADAPT programmet er designet på baggrund af evidens samt understøttet af ergoterapeutiske teorier og modeller......Præsentation af et ergoterapeutisk gruppebaseret program, ADAPT programmet. ADAPT programmet er designet på baggrund af evidens samt understøttet af ergoterapeutiske teorier og modeller...

Stochastic hyperfine interactions modeling library

Science.gov (United States)

Zacate, Matthew O.; Evenson, William E.

2011-04-01

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

Adaptation of the TH Epsilon Mu formalism for the analysis of the equivalence principle in the presence of the weak and electroweak interaction

Science.gov (United States)

Fennelly, A. J.

1981-01-01

The TH epsilon mu formalism, used in analyzing equivalence principle experiments of metric and nonmetric gravity theories, is adapted to the description of the electroweak interaction using the Weinberg-Salam unified SU(2) x U(1) model. The use of the TH epsilon mu formalism is thereby extended to the weak interactions, showing how the gravitational field affects W sub mu (+ or -1) and Z sub mu (0) boson propagation and the rates of interactions mediated by them. The possibility of a similar extension to the strong interactions via SU(5) grand unified theories is briefly discussed. Also, using the effects of the potentials on the baryon and lepton wave functions, the effects of gravity on transition mediated in high-A atoms which are electromagnetically forbidden. Three possible experiments to test the equivalence principle in the presence of the weak interactions, which are technologically feasible, are then briefly outline: (1) K-capture by the FE nucleus (counting the emitted X-ray); (2) forbidden absorption transitions in high-A atoms' vapor; and (3) counting the relative Beta-decay rates in a suitable alpha-beta decay chain, assuming the strong interactions obey the equivalence principle.

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

Modeling of memristor-based chaotic systems using nonlinear Wiener adaptive filters based on backslash operator

International Nuclear Information System (INIS)

Zhao, Yibo; Jiang, Yi; Feng, Jiuchao; Wu, Lifu

2016-01-01

Highlights: • A novel nonlinear Wiener adaptive filters based on the backslash operator are proposed. • The identification approach to the memristor-based chaotic systems using the proposed adaptive filters. • The weight update algorithm and convergence characteristics for the proposed adaptive filters are derived. - Abstract: Memristor-based chaotic systems have complex dynamical behaviors, which are characterized as nonlinear and hysteresis characteristics. Modeling and identification of their nonlinear model is an important premise for analyzing the dynamical behavior of the memristor-based chaotic systems. This paper presents a novel nonlinear Wiener adaptive filtering identification approach to the memristor-based chaotic systems. The linear part of Wiener model consists of the linear transversal adaptive filters, the nonlinear part consists of nonlinear adaptive filters based on the backslash operator for the hysteresis characteristics of the memristor. The weight update algorithms for the linear and nonlinear adaptive filters are derived. Final computer simulation results show the effectiveness as well as fast convergence characteristics. Comparing with the adaptive nonlinear polynomial filters, the proposed nonlinear adaptive filters have less identification error.

Drug-model membrane interactions

International Nuclear Information System (INIS)

Deniz, Usha K.

1994-01-01

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

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

Science.gov (United States)

Symowski, Cornelia; Voehringer, David

2017-01-01

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

Telehealth in Schools Using a Systematic Educational Model Based on Fiction Screenplays, Interactive Documentaries, and Three-Dimensional Computer Graphics.

Science.gov (United States)

Miranda, Diogo Julien; Chao, Lung Wen

2018-03-01

Preliminary studies suggest the need of a global vision in academic reform, leading to education re-invention. This would include problem-based education using transversal topics, developing of thinking skills, social interaction, and information-processing skills. We aimed to develop a new educational model in health with modular components to be broadcast and applied as a tele-education course. We developed a systematic model based on a "Skills and Goals Matrix" to adapt scientific contents on fictional screenplays, three-dimensional (3D) computer graphics of the human body, and interactive documentaries. We selected 13 topics based on youth vulnerabilities in Brazil to be disseminated through a television show with 15 episodes. We developed scientific content for each theme, naturally inserting it into screenplays, together with 3D sequences and interactive documentaries. The modular structure was then adapted to a distance-learning course. The television show was broadcast on national television for two consecutive years to an estimated audience of 30 million homes, and ever since on an Internet Protocol Television (IPTV) channel. It was also reorganized as a tele-education course for 2 years, reaching 1,180 subscriptions from all 27 Brazilian states, resulting in 240 graduates. Positive results indicate the feasibility, acceptability, and effectiveness of a model of modular entertainment audio-visual productions using health and education integrated concepts. This structure also allowed the model to be interconnected with other sources and applied as tele-education course, educating, informing, and stimulating the behavior change. Future works should reinforce this joint structure of telehealth, communication, and education.

Modeling the time--varying subjective quality of HTTP video streams with rate adaptations.

Science.gov (United States)

Chen, Chao; Choi, Lark Kwon; de Veciana, Gustavo; Caramanis, Constantine; Heath, Robert W; Bovik, Alan C

2014-05-01

Newly developed hypertext transfer protocol (HTTP)-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' quality of experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for online TVSQ prediction in HTTP-based streaming.

Modeling adaptation of wetland plants under changing environments

Science.gov (United States)

Muneepeerakul, R.; Muneepeerakul, C. P.

2010-12-01

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

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.

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.

Adaptive control of servo system based on LuGre model

Science.gov (United States)

Jin, Wang; Niancong, Liu; Jianlong, Chen; Weitao, Geng

2018-03-01

This paper established a mechanical model of feed system based on LuGre model. In order to solve the influence of nonlinear factors on the system running stability, a nonlinear single observer is designed to estimate the parameter z in the LuGre model and an adaptive friction compensation controller is designed. Simulink simulation results show that the control method can effectively suppress the adverse effects of friction and external disturbances. The simulation show that the adaptive parameter kz is between 0.11-0.13, and the value of gamma1 is between 1.9-2.1. Position tracking error reaches level 10-3 and is stabilized near 0 values within 0.3 seconds, the compensation method has better tracking accuracy and robustness.

Modeling the Effect of Religion on Human Empathy Based on an Adaptive Temporal-Causal Network Model

OpenAIRE

van Ments, L.I.; Roelofsma, P.H.M.P.; Treur, J.

2018-01-01

Religion is a central aspect of many individuals’ lives around the world, and its influence on human behaviour has been extensively studied from many different perspectives. The current study integrates a number of these perspectives into one adaptive temporal-causal network model describing the mental states involved, their mutual relations, and the adaptation of some of these relations over time due to learning. By first developing a conceptual representation of a network model based on lit...

Adaptive evolution in ecological communities.

Directory of Open Access Journals (Sweden)

Martin M Turcotte

Full Text Available Understanding how natural selection drives evolution is a key challenge in evolutionary biology. Most studies of adaptation focus on how a single environmental factor, such as increased temperature, affects evolution within a single species. The biological relevance of these experiments is limited because nature is infinitely more complex. Most species are embedded within communities containing many species that interact with one another and the physical environment. To understand the evolutionary significance of such ecological complexity, experiments must test the evolutionary impact of interactions among multiple species during adaptation. Here we highlight an experiment that manipulates species composition and tracks evolutionary responses within each species, while testing for the mechanisms by which species interact and adapt to their environment. We also discuss limitations of previous studies of adaptive evolution and emphasize how an experimental evolution approach can circumvent such shortcomings. Understanding how community composition acts as a selective force will improve our ability to predict how species adapt to natural and human-induced environmental change.

Parameter extraction of different fuel cell models with transferred adaptive differential evolution

International Nuclear Information System (INIS)

Gong, Wenyin; Yan, Xuesong; Liu, Xiaobo; Cai, Zhihua

2015-01-01

To improve the design and control of FC (fuel cell) models, it is important to extract their unknown parameters. Generally, the parameter extraction problems of FC models can be transformed as nonlinear and multi-variable optimization problems. To extract the parameters of different FC models exactly and fast, in this paper, we propose a transferred adaptive DE (differential evolution) framework, in which the successful parameters of the adaptive DE solving previous problems are properly transferred to solve new optimization problems in the similar problem-domains. Based on this framework, an improved adaptive DE method (TRADE, in short) is presented as an illustration. To verify the performance of our proposal, TRADE is used to extract the unknown parameters of two types of fuel cell models, i.e., PEMFC (proton exchange membrane fuel cell) and SOFC (solid oxide fuel cell). The results of TRADE are also compared with those of other state-of-the-art EAs (evolutionary algorithms). Even though the modification is very simple, the results indicate that TRADE can extract the parameters of both PEMFC and SOFC models exactly and fast. Moreover, the V–I characteristics obtained by TRADE agree well with the simulated and experimental data in all cases for both types of fuel cell models. Also, it improves the performance of the original adaptive DE significantly in terms of both the quality of final solutions and the convergence speed in all cases. Additionally, TRADE is able to provide better results compared with other EAs. - Highlights: • A framework of transferred adaptive differential evolution is proposed. • Based on the framework, an improved differential evolution (TRADE) is presented. • TRADE obtains very promising results to extract the parameters of PEMFC and SOFC models

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…

Geometric subspace updates with applications to online adaptive nonlinear model reduction

DEFF Research Database (Denmark)

Zimmermann, Ralf; Peherstorfer, Benjamin; Willcox, Karen

2018-01-01

In many scientific applications, including model reduction and image processing, subspaces are used as ansatz spaces for the low-dimensional approximation and reconstruction of the state vectors of interest. We introduce a procedure for adapting an existing subspace based on information from...... Estimation (GROUSE). We establish for GROUSE a closed-form expression for the residual function along the geodesic descent direction. Specific applications of subspace adaptation are discussed in the context of image processing and model reduction of nonlinear partial differential equation systems....

Adaptive control for a PWR using a self-tuning reference model concept

International Nuclear Information System (INIS)

Miley, G.H.; Park, G.T.; Kim, B.S.

1992-01-01

Possible applications of an adaptive control method to a pressurized-water reactor nuclear power plant are investigated. The self-tuning technique with a reference model concept is employed. This control algorithm is developed by combining the self-tuning controller with the model reference adaptive control. This approach overcomes the difficulties in choosing the appropriate weighting polynomials in the cost function of the self-tuning control

A model for generating several adaptive phenotypes from a single genetic event

DEFF Research Database (Denmark)

Møller, Henrik D; Andersen, Kaj S; Regenberg, Birgitte

2013-01-01

Microbial populations adapt to environmental fluctuations through random switching of fitness-related traits in individual cells. This increases the likelihood that a subpopulation will be adaptive in a future milieu. However, populations are particularly challenged when several environment facto...... energy recruitment by trehalose mobilization, and in some cases, adherent biofilm growth. Our proposed model of a hub-switch locus enhances the bet-hedging model of population dynamics....

Adaptive surrogate modeling by ANOVA and sparse polynomial dimensional decomposition for global sensitivity analysis in fluid simulation

Energy Technology Data Exchange (ETDEWEB)

Tang, Kunkun, E-mail: ktg@illinois.edu [The Center for Exascale Simulation of Plasma-Coupled Combustion (XPACC), University of Illinois at Urbana–Champaign, 1308 W Main St, Urbana, IL 61801 (United States); Inria Bordeaux – Sud-Ouest, Team Cardamom, 200 avenue de la Vieille Tour, 33405 Talence (France); Congedo, Pietro M. [Inria Bordeaux – Sud-Ouest, Team Cardamom, 200 avenue de la Vieille Tour, 33405 Talence (France); Abgrall, Rémi [Institut für Mathematik, Universität Zürich, Winterthurerstrasse 190, CH-8057 Zürich (Switzerland)

2016-06-01

The Polynomial Dimensional Decomposition (PDD) is employed in this work for the global sensitivity analysis and uncertainty quantification (UQ) of stochastic systems subject to a moderate to large number of input random variables. Due to the intimate connection between the PDD and the Analysis of Variance (ANOVA) approaches, PDD is able to provide a simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to the Polynomial Chaos expansion (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of standard methods unaffordable for real engineering applications. In order to address the problem of the curse of dimensionality, this work proposes essentially variance-based adaptive strategies aiming to build a cheap meta-model (i.e. surrogate model) by employing the sparse PDD approach with its coefficients computed by regression. Three levels of adaptivity are carried out in this paper: 1) the truncated dimensionality for ANOVA component functions, 2) the active dimension technique especially for second- and higher-order parameter interactions, and 3) the stepwise regression approach designed to retain only the most influential polynomials in the PDD expansion. During this adaptive procedure featuring stepwise regressions, the surrogate model representation keeps containing few terms, so that the cost to resolve repeatedly the linear systems of the least-squares regression problem is negligible. The size of the finally obtained sparse PDD representation is much smaller than the one of the full expansion, since only significant terms are eventually retained. Consequently, a much smaller number of calls to the deterministic model is required to compute the final PDD coefficients.

Adaptive surrogate modeling by ANOVA and sparse polynomial dimensional decomposition for global sensitivity analysis in fluid simulation

International Nuclear Information System (INIS)

Tang, Kunkun; Congedo, Pietro M.; Abgrall, Rémi

2016-01-01

The Polynomial Dimensional Decomposition (PDD) is employed in this work for the global sensitivity analysis and uncertainty quantification (UQ) of stochastic systems subject to a moderate to large number of input random variables. Due to the intimate connection between the PDD and the Analysis of Variance (ANOVA) approaches, PDD is able to provide a simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to the Polynomial Chaos expansion (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of standard methods unaffordable for real engineering applications. In order to address the problem of the curse of dimensionality, this work proposes essentially variance-based adaptive strategies aiming to build a cheap meta-model (i.e. surrogate model) by employing the sparse PDD approach with its coefficients computed by regression. Three levels of adaptivity are carried out in this paper: 1) the truncated dimensionality for ANOVA component functions, 2) the active dimension technique especially for second- and higher-order parameter interactions, and 3) the stepwise regression approach designed to retain only the most influential polynomials in the PDD expansion. During this adaptive procedure featuring stepwise regressions, the surrogate model representation keeps containing few terms, so that the cost to resolve repeatedly the linear systems of the least-squares regression problem is negligible. The size of the finally obtained sparse PDD representation is much smaller than the one of the full expansion, since only significant terms are eventually retained. Consequently, a much smaller number of calls to the deterministic model is required to compute the final PDD coefficients.

Parent Management Training-Oregon Model: Adapting Intervention with Rigorous Research.

Science.gov (United States)

Forgatch, Marion S; Kjøbli, John

2016-09-01

Parent Management Training-Oregon Model (PMTO(®) ) is a set of theory-based parenting programs with status as evidence-based treatments. PMTO has been rigorously tested in efficacy and effectiveness trials in different contexts, cultures, and formats. Parents, the presumed agents of change, learn core parenting practices, specifically skill encouragement, limit setting, monitoring/supervision, interpersonal problem solving, and positive involvement. The intervention effectively prevents and ameliorates children's behavior problems by replacing coercive interactions with positive parenting practices. Delivery format includes sessions with individual families in agencies or families' homes, parent groups, and web-based and telehealth communication. Mediational models have tested parenting practices as mechanisms of change for children's behavior and found support for the theory underlying PMTO programs. Moderating effects include children's age, maternal depression, and social disadvantage. The Norwegian PMTO implementation is presented as an example of how PMTO has been tailored to reach diverse populations as delivered by multiple systems of care throughout the nation. An implementation and research center in Oslo provides infrastructure and promotes collaboration between practitioners and researchers to conduct rigorous intervention research. Although evidence-based and tested within a wide array of contexts and populations, PMTO must continue to adapt to an ever-changing world. © 2016 Family Process Institute.

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.

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

Adaptive Reactive Rich Internet Applications

Science.gov (United States)

Schmidt, Kay-Uwe; Stühmer, Roland; Dörflinger, Jörg; Rahmani, Tirdad; Thomas, Susan; Stojanovic, Ljiljana

Rich Internet Applications significantly raise the user experience compared with legacy page-based Web applications because of their highly responsive user interfaces. Although this is a tremendous advance, it does not solve the problem of the one-size-fits-all approach1 of current Web applications. So although Rich Internet Applications put the user in a position to interact seamlessly with the Web application, they do not adapt to the context in which the user is currently working. In this paper we address the on-the-fly personalization of Rich Internet Applications. We introduce the concept of ARRIAs: Adaptive Reactive Rich Internet Applications and elaborate on how they are able to adapt to the current working context the user is engaged in. An architecture for the ad hoc adaptation of Rich Internet Applications is presented as well as a holistic framework and tools for the realization of our on-the-fly personalization approach. We divided both the architecture and the framework into two levels: offline/design-time and online/run-time. For design-time we explain how to use ontologies in order to annotate Rich Internet Applications and how to use these annotations for conceptual Web usage mining. Furthermore, we describe how to create client-side executable rules from the semantic data mining results. We present our declarative lightweight rule language tailored to the needs of being executed directly on the client. Because of the event-driven nature of the user interfaces of Rich Internet Applications, we designed a lightweight rule language based on the event-condition-action paradigm.2 At run-time the interactions of a user are tracked directly on the client and in real-time a user model is built up. The user model then acts as input to and is evaluated by our client-side complex event processing and rule engine.

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

Science.gov (United States)

Girard, Julien H.; Tourneboeuf, Martin

2016-07-01

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

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 ...

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

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.

Real-Time Robust Adaptive Modeling and Scheduling for an Electronic Commerce Server

Science.gov (United States)

Du, Bing; Ruan, Chun

With the increasing importance and pervasiveness of Internet services, it is becoming a challenge for the proliferation of electronic commerce services to provide performance guarantees under extreme overload. This paper describes a real-time optimization modeling and scheduling approach for performance guarantee of electronic commerce servers. We show that an electronic commerce server may be simulated as a multi-tank system. A robust adaptive server model is subject to unknown additive load disturbances and uncertain model matching. Overload control techniques are based on adaptive admission control to achieve timing guarantees. We evaluate the performance of the model using a complex simulation that is subjected to varying model parameters and massive overload.

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.

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

Science.gov (United States)

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

2007-10-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2007-10-15

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

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

International Nuclear Information System (INIS)

Rybynok, V O; Kyriacou, P A

2007-01-01

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

A model of adaptation for families of elderly patients with dementia: focusing on family resilience.

Science.gov (United States)

Kim, Geun Myun; Lim, Ji Young; Kim, Eun Joo; Kim, Sang Suk

2017-07-19

We constructed a model explaining families' positive adaptation in chronic crisis situations such as the problematic behavior of elderly patients with dementia and attendant caregiving stress, based on the family resilience model. Our aim was to devise an adaptation model for families of elderly patients with dementia. A survey of problematic behavior in elderly patients with dementia, family stress, family resilience, and family adaptation was conducted with 292 consenting individuals. The collected data were analyzed using structural equation modeling. The communication process, family stress, and problematic behavior of elderly patients with dementia had direct and indirect effects on family adaptation, while belief system, organization pattern, and social support had indirect effects. Specifically, family stress and more severe problematic behavior by elderly patients with dementia negatively influenced family adaptation, while greater family resilience improved such adaptation. Interventions aiming to enhance family resilience, based on the results of this study, are required to help families with positive adaptation. Such family programs might involve practical support such as education on the characteristics of elderly persons with dementia and coping methods for their problematic behavior; forming self-help groups for families; revitalizing communication within families; and activating communication channels with experts.

The modeling of predator-prey interactions

OpenAIRE

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

2015-01-01

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

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