WorldWideScience

Sample records for dynamically updated adaptive

  1. Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set

    Directory of Open Access Journals (Sweden)

    Jinna Li

    2012-01-01

    Full Text Available A novel fault detection technique is proposed to explicitly account for the nonlinear, dynamic, and multimodal problems existed in the practical and complex dynamic processes. Just-in-time (JIT detection method and k-nearest neighbor (KNN rule-based statistical process control (SPC approach are integrated to construct a flexible and adaptive detection scheme for the control process with nonlinear, dynamic, and multimodal cases. Mahalanobis distance, representing the correlation among samples, is used to simplify and update the raw data set, which is the first merit in this paper. Based on it, the control limit is computed in terms of both KNN rule and SPC method, such that we can identify whether the current data is normal or not by online approach. Noted that the control limit obtained changes with updating database such that an adaptive fault detection technique that can effectively eliminate the impact of data drift and shift on the performance of detection process is obtained, which is the second merit in this paper. The efficiency of the developed method is demonstrated by the numerical examples and an industrial case.

  2. Towards Dynamic Updates in Service Composition

    Directory of Open Access Journals (Sweden)

    Mario Bravetti

    2015-12-01

    Full Text Available We survey our results about verification of adaptable processes. We present adaptable processes as a way of overcoming the limitations that process calculi have for describing patterns of dynamic process evolution. Such patterns rely on direct ways of controlling the behavior and location of running processes, and so they are at the heart of the adaptation capabilities present in many modern concurrent systems. Adaptable processes have named scopes and are sensible to actions of dynamic update at runtime; this allows to express dynamic and static topologies of adaptable processes as well as different evolvability patterns for concurrent processes. We introduce a core calculus of adaptable processes and consider verification problems for them: first based on specific properties related to error occurrence, that we call bounded and eventual adaptation, and then by considering a simple yet expressive temporal logic over adaptable processes. We provide (undecidability results of such verification problems over adaptable processes considering the spectrum of topologies/evolvability patterns introduced. We then consider distributed adaptability, where a process can update part of a protocol by performing dynamic distributed updates over a set of protocol participants. Dynamic updates in this context are presented as an extension of our work on choreographies and behavioural contracts in multiparty interactions. We show how update mechanisms considered for adaptable processes can be used to extend the theory of choreography and orchestration/contracts, allowing them to be modified at run-time by internal (self-adaptation or external intervention.

  3. Dynamical adaptation in photoreceptors.

    Directory of Open Access Journals (Sweden)

    Damon A Clark

    Full Text Available Adaptation is at the heart of sensation and nowhere is it more salient than in early visual processing. Light adaptation in photoreceptors is doubly dynamical: it depends upon the temporal structure of the input and it affects the temporal structure of the response. We introduce a non-linear dynamical adaptation model of photoreceptors. It is simple enough that it can be solved exactly and simulated with ease; analytical and numerical approaches combined provide both intuition on the behavior of dynamical adaptation and quantitative results to be compared with data. Yet the model is rich enough to capture intricate phenomenology. First, we show that it reproduces the known phenomenology of light response and short-term adaptation. Second, we present new recordings and demonstrate that the model reproduces cone response with great precision. Third, we derive a number of predictions on the response of photoreceptors to sophisticated stimuli such as periodic inputs, various forms of flickering inputs, and natural inputs. In particular, we demonstrate that photoreceptors undergo rapid adaptation of response gain and time scale, over ∼ 300[Formula: see text] ms-i. e., over the time scale of the response itself-and we confirm this prediction with data. For natural inputs, this fast adaptation can modulate the response gain more than tenfold and is hence physiologically relevant.

  4. Optimal updating magnitude in adaptive flat-distribution sampling.

    Science.gov (United States)

    Zhang, Cheng; Drake, Justin A; Ma, Jianpeng; Pettitt, B Montgomery

    2017-11-07

    We present a study on the optimization of the updating magnitude for a class of free energy methods based on flat-distribution sampling, including the Wang-Landau (WL) algorithm and metadynamics. These methods rely on adaptive construction of a bias potential that offsets the potential of mean force by histogram-based updates. The convergence of the bias potential can be improved by decreasing the updating magnitude with an optimal schedule. We show that while the asymptotically optimal schedule for the single-bin updating scheme (commonly used in the WL algorithm) is given by the known inverse-time formula, that for the Gaussian updating scheme (commonly used in metadynamics) is often more complex. We further show that the single-bin updating scheme is optimal for very long simulations, and it can be generalized to a class of bandpass updating schemes that are similarly optimal. These bandpass updating schemes target only a few long-range distribution modes and their optimal schedule is also given by the inverse-time formula. Constructed from orthogonal polynomials, the bandpass updating schemes generalize the WL and Langfeld-Lucini-Rago algorithms as an automatic parameter tuning scheme for umbrella sampling.

  5. Building nonredundant adaptive wavelets by update lifting

    NARCIS (Netherlands)

    H.J.A.M. Heijmans (Henk); B. Pesquet-Popescu; G. Piella (Gema)

    2002-01-01

    textabstractAdaptive wavelet decompositions appear useful in various applications in image and video processing, such as image analysis, compression, feature extraction, denoising and deconvolution, or optic flow estimation. For such tasks it may be important that the multiresolution representations

  6. Partial update least-square adaptive filtering

    CERN Document Server

    Xie, Bei

    2014-01-01

    Adaptive filters play an important role in the fields related to digital signal processing and communication, such as system identification, noise cancellation, channel equalization, and beamforming. In practical applications, the computational complexity of an adaptive filter is an important consideration. The Least Mean Square (LMS) algorithm is widely used because of its low computational complexity (O(N)) and simplicity in implementation. The least squares algorithms, such as Recursive Least Squares (RLS), Conjugate Gradient (CG), and Euclidean Direction Search (EDS), can converge faster a

  7. Brayton dynamic isotope power systems update

    International Nuclear Information System (INIS)

    Davis, K.A.; Pietsch, A.; Casagrande, R.D.

    1986-01-01

    Brayton dynamic power systems are uniquely suited for space applications. They are compact and highly efficient, offer inherent reliability due to only one moving part, and utilize a single phase and inert working fluid. Additional features include gas bearings, constant speed, and operation at essentially constant temperature. The design, utilizing an inert gas working fluid and gas bearing, is unaffected by zero gravity and can be easily started and restarted in space at low temperatures. This paper describes the salient features of the BIPS as a Dynamic Isotope Power System (DIPS), summarizes the development work to date, establishes the maturity of the design, provides an update on materials technology, and reviews systems integration considerations

  8. Opinion dynamics on an adaptive random network

    Science.gov (United States)

    Benczik, I. J.; Benczik, S. Z.; Schmittmann, B.; Zia, R. K. P.

    2009-04-01

    We revisit the classical model for voter dynamics in a two-party system with two basic modifications. In contrast to the original voter model studied in regular lattices, we implement the opinion formation process in a random network of agents in which interactions are no longer restricted by geographical distance. In addition, we incorporate the rapidly changing nature of the interpersonal relations in the model. At each time step, agents can update their relationships. This update is determined by their own opinion, and by their preference to make connections with individuals sharing the same opinion, or rather with opponents. In this way, the network is built in an adaptive manner, in the sense that its structure is correlated and evolves with the dynamics of the agents. The simplicity of the model allows us to examine several issues analytically. We establish criteria to determine whether consensus or polarization will be the outcome of the dynamics and on what time scales these states will be reached. In finite systems consensus is typical, while in infinite systems a disordered metastable state can emerge and persist for infinitely long time before consensus is reached.

  9. The Adaptation Finance Gap Update - with insights from the INDCs

    DEFF Research Database (Denmark)

    Olhoff, Anne; Bee, Skylar; Puig, Daniel

    In 2014 the United Nations Environment Programme (UNEP) published its first global Adaptation Gap Report (AGR 2014) (UNEP, 2014), which put forward a preliminary framework for assessing adaptation gaps along with an initial assessment in three selected areas: finance, technology and knowledge....... Further to the positive reception of this report, several countries requested UNEP to produce follow up reports focusing on specific adaptation gaps. In response to these requests, UNEP has commissioned a new report with a special focus on finance gaps and options to bridge them. The report...... will be published in the spring of 2016. This update is intended as an input to discussions at the 21st session of the Conference of the Parties (COP 21) to the United Nations Framework Convention on Climate Change (UNFCCC). It brings together key findings on adaptation costs and finance from AGR 2014...

  10. Adaptive learning and complex dynamics

    International Nuclear Information System (INIS)

    Gomes, Orlando

    2009-01-01

    In this paper, we explore the dynamic properties of a group of simple deterministic difference equation systems in which the conventional perfect foresight assumption gives place to a mechanism of adaptive learning. These systems have a common feature: under perfect foresight (or rational expectations) they all possess a unique fixed point steady state. This long-term outcome is obtained also under learning if the quality underlying the learning process is high. Otherwise, when the degree of inefficiency of the learning process is relatively strong, nonlinear dynamics (periodic and a-periodic cycles) arise. The specific properties of each one of the proposed systems is explored both in terms of local and global dynamics. One macroeconomic model is used to illustrate how the formation of expectations through learning may eventually lead to awkward long-term outcomes.

  11. Adaptive, dynamic, and resilient systems

    CERN Document Server

    Suri, Niranjan

    2015-01-01

    As the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of networked computers rely on. It introduces the key issues, describes their interrelationships, and presents new research in support of these areas.The book presents the insights of a different group of international experts in each chapter. Reporting on r

  12. State of the art of dynamic software updating in Java

    DEFF Research Database (Denmark)

    Gregersen, Allan Raundahl; Rasmussen, Michael; Jørgensen, Bo Nørregaard

    2014-01-01

    The dynamic software updating system JRebel from Zeroturnaround has proven to be an efficient mean to improve developer productivity, as it allows developers to change the code of their applications while developing and testing them. Hence, developers no longer have to go through the tedious cycle......! with JRebel. The successful integration of these two systems will set a new standard for dynamic software updating in Java....

  13. Agent Communication for Dynamic Belief Update

    Science.gov (United States)

    Kobayashi, Mikito; Tojo, Satoshi

    Thus far, various formalizations of rational / logical agent model have been proposed. In this paper, we include the notion of communication channel and belief modality into update logic, and introduce Belief Update Logic (BUL). First, we discuss that how we can reformalize the inform action of FIPA-ACL into communication channel, which represents a connection between agents. Thus, our agents can send a message only when they believe, and also there actually is, a channel between him / her and a receiver. Then, we present a static belief logic (BL) and show its soundness and completeness. Next, we develop the logic to BUL, which can update Kripke model by the inform action; in which we show that in the updated model the belief operator also satisfies K45. Thereafter, we show that every sentence in BUL can be translated into BL; thus, we can contend that BUL is also sound and complete. Furthermore, we discuss the features of CUL, including the case of inconsistent information, as well as channel transmission. Finally, we summarize our contribution and discuss some future issues.

  14. Map updates in a dynamic Voronoi data structure

    DEFF Research Database (Denmark)

    Mioc, Darka; Antón Castro, Francesc/François; Gold, C. M.

    2006-01-01

    In this paper we are using local and sequential map updates in the Voronoi data structure, which allows us to automatically record each event and performed map updates within the system. These map updates are executed through map construction commands that are composed of atomic actions (geometric...... algorithms for addition, deletion, and motion of spatial objects) on the dynamic Voronoi data structure. The formalization of map commands led to the development of a spatial language comprising a set of atomic operations or constructs on spatial primitives (points and lines), powerful enough to define...

  15. Online Sequential Projection Vector Machine with Adaptive Data Mean Update.

    Science.gov (United States)

    Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

    2016-01-01

    We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.

  16. Online Sequential Projection Vector Machine with Adaptive Data Mean Update

    Directory of Open Access Journals (Sweden)

    Lin Chen

    2016-01-01

    Full Text Available We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1 the projection vectors for dimension reduction, (2 the input weights, biases, and output weights, and (3 the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD approach, adaptive multihyperplane machine (AMM, primal estimated subgradient solver (Pegasos, online sequential extreme learning machine (OSELM, and SVD + OSELM (feature selection based on SVD is performed before OSELM. The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.

  17. Dynamic adaption of vascular morphology

    DEFF Research Database (Denmark)

    Okkels, Fridolin; Jacobsen, Jens Christian Brings

    2012-01-01

    The structure of vascular networks adapts continuously to meet changes in demand of the surrounding tissue. Most of the known vascular adaptation mechanisms are based on local reactions to local stimuli such as pressure and flow, which in turn reflects influence from the surrounding tissue. Here ...

  18. Robust adaptive synchronization of general dynamical networks ...

    Indian Academy of Sciences (India)

    Robust adaptive synchronization; dynamical network; multiple delays; multiple uncertainties. ... Networks such as neural networks, communication transmission networks, social rela- tionship networks etc. ..... a very good effect. Pramana – J.

  19. Dynamic optimization and adaptive controller design

    Science.gov (United States)

    Inamdar, S. R.

    2010-10-01

    In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

  20. Sharp asymptotics for stochastic dynamics with parallel updating rule

    NARCIS (Netherlands)

    Nardi, F.R.; Spitoni, C.

    2012-01-01

    In this paper we study the metastability problem for a stochastic dynamics with a parallel updating rule; in particular we consider a ¿nite volume Probabilistic Cellular Automaton (PCA) in a small external ¿eld at low temperature regime. We are interested in the nucleation of the system, i.e., the

  1. Sharp asymptotics for stochastic dynamics with parallel updating rule

    NARCIS (Netherlands)

    Nardi, F.R.; Spitoni, C.

    2012-01-01

    In this paper we study the metastability problem for a stochastic dynamics with a parallel updating rule; in particular we consider a finite volume Probabilistic Cellular Automaton (PCA) in a small external field at low temperature regime. We are interested in the nucleation of the system, i.e., the

  2. Sharp Asymptotics for Stochastic Dynamics with Parallel Updating Rule

    NARCIS (Netherlands)

    Nardi, F.R.; Spitoni, C.

    2012-01-01

    In this paper we study the metastability problem for a stochastic dynamics with a parallel updating rule; in particular we consider a finite volume Probabilistic Cellular Automaton (PCA) in a small external field at low temperature regime. We are interested in the nucleation of the system, i.e.,

  3. Adaptive Dynamic Programming for Control Algorithms and Stability

    CERN Document Server

    Zhang, Huaguang; Luo, Yanhong; Wang, Ding

    2013-01-01

    There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of  adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and  proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...

  4. 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)

  5. Run-time Phenomena in Dynamic Software Updating: Causes and Effects

    DEFF Research Database (Denmark)

    Gregersen, Allan Raundahl; Jørgensen, Bo Nørregaard

    2011-01-01

    The development of a dynamic software updating system for statically-typed object-oriented programming languages has turned out to be a challenging task. Despite the fact that the present state of the art in dynamic updating systems, like JRebel, Dynamic Code Evolution VM, JVolve and Javeleon, all...... written in statically-typed object-oriented programming languages. In this paper, we present our experience from developing dynamically updatable applications using a state-of-the-art dynamic updating system for Java. We believe that the findings presented in this paper provide an important step towards...... provide very transparent and flexible technical solutions to dynamic updating, case studies have shown that designing dynamically updatable applications still remains a challenging task. This challenge has its roots in a number of run-time phenomena that are inherent to dynamic updating of applications...

  6. Dynamical Adaptation in Terrorist Cells/Networks

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Ahmed, Zaki

    2010-01-01

    Typical terrorist cells/networks have dynamical structure as they evolve or adapt to changes which may occur due to capturing or killing of a member of the cell/network. Analytical measures in graph theory like degree centrality, betweenness and closeness centralities are very common and have long...

  7. Adaptation dynamics of the quasispecies model

    Indian Academy of Sciences (India)

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

  8. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2007-01-01

    We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

  9. Complex and Adaptive Dynamical Systems A Primer

    CERN Document Server

    Gros, Claudius

    2011-01-01

    We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

  10. Adaptive Integration of Nonsmooth Dynamical Systems

    Science.gov (United States)

    2017-10-11

    2017 W911NF-12-R-0012-03: Adaptive Integration of Nonsmooth Dynamical Systems The views, opinions and/or findings contained in this report are those of...Integration of Nonsmooth Dynamical Systems Report Term: 0-Other Email: drum@gwu.edu Distribution Statement: 1-Approved for public release; distribution is...classdrake_1_1systems_1_1_integrator_base.html ; 3) a solver for dynamical systems with arbitrary unilateral and bilateral constraints (the key component of the time stepping systems )- see

  11. Dynamic Information Encoding With Dynamic Synapses in Neural Adaptation

    Science.gov (United States)

    Li, Luozheng; Mi, Yuanyuan; Zhang, Wenhao; Wang, Da-Hui; Wu, Si

    2018-01-01

    Adaptation refers to the general phenomenon that the neural system dynamically adjusts its response property according to the statistics of external inputs. In response to an invariant stimulation, neuronal firing rates first increase dramatically and then decrease gradually to a low level close to the background activity. This prompts a question: during the adaptation, how does the neural system encode the repeated stimulation with attenuated firing rates? It has been suggested that the neural system may employ a dynamical encoding strategy during the adaptation, the information of stimulus is mainly encoded by the strong independent spiking of neurons at the early stage of the adaptation; while the weak but synchronized activity of neurons encodes the stimulus information at the later stage of the adaptation. The previous study demonstrated that short-term facilitation (STF) of electrical synapses, which increases the synchronization between neurons, can provide a mechanism to realize dynamical encoding. In the present study, we further explore whether short-term plasticity (STP) of chemical synapses, an interaction form more common than electrical synapse in the cortex, can support dynamical encoding. We build a large-size network with chemical synapses between neurons. Notably, facilitation of chemical synapses only enhances pair-wise correlations between neurons mildly, but its effect on increasing synchronization of the network can be significant, and hence it can serve as a mechanism to convey the stimulus information. To read-out the stimulus information, we consider that a downstream neuron receives balanced excitatory and inhibitory inputs from the network, so that the downstream neuron only responds to synchronized firings of the network. Therefore, the response of the downstream neuron indicates the presence of the repeated stimulation. Overall, our study demonstrates that STP of chemical synapse can serve as a mechanism to realize dynamical neural

  12. Robust master-slave synchronization for general uncertain delayed dynamical model based on adaptive control scheme.

    Science.gov (United States)

    Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin

    2014-03-01

    In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  13. Adaptive resummation of Markovian quantum dynamics

    International Nuclear Information System (INIS)

    Lucas, Felix

    2014-01-01

    In this thesis we derive a highly convergent, nonperturbative expansion of Markovian open quantum dynamics. It is based on a splitting of the incoherent dynamics into periods of continuous evolution and abrupt jumps and attains its favorable convergence properties from an adaptive resummation of this so-called jump expansion. By means of the long-standing problems of spatial particle detection and Landau-Zener tunneling in the presence of dephasing, we show that this adaptive resummation technique facilitates new highly accurate analytic approximations of Markovian open systems. The open Landau-Zener model leads us to propose an efficient and robust incoherent control technique for the isomerization reaction of the visual pigment protein rhodopsin. Besides leading to approximate analytic descriptions of Markovian open quantum dynamics, the adaptive resummation of the jump expansion implies an efficient numerical simulation method. We spell out the corresponding numerical algorithm by means of Monte Carlo integration of the relevant terms in the jump expansion and demonstrate it in a set of paradigmatic open quantum systems.

  14. Adaptive-network models of collective dynamics

    Science.gov (United States)

    Zschaler, G.

    2012-09-01

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

  15. Community-based adaptation to climate change: an update

    Energy Technology Data Exchange (ETDEWEB)

    Ayers, Jessica; Huq, Saleemul

    2009-06-15

    Over a billion people - the world's poorest and most bulnerable communities – will bear the brunt of climate change. For them, building local capacity to cope is a vital step towards resilience. Community-based adaptation (CBA) is emerging as a key response to this challenge. Tailored to local cultures and conditions, CBA supports and builds on autonomous adaptations to climate variability, such as the traditional baira or floating gardens of Bangladesh, which help small farmers' crops survive climate-driven floods. Above all, CBA is participatory – a process involving both local stakeholders, and development and disaster risk reduction practitioners. As such, it builds on existing cultural norms while addressing local development issues that contribute to climate vulnerability. CBA is now gaining ground in many regions, and is ripe for the reassessment offered here.

  16. Towards Trustworthy Adaptive Case Management with Dynamic Condition Response Graphs

    DEFF Research Database (Denmark)

    Mukkamala, Raghava Rao; Hildebrandt, Thomas; Slaats, Tijs

    2013-01-01

    We describe how the declarative Dynamic Condition Response (DCR) Graphs process model can be used for trustworthy adaptive case management by leveraging the flexible execution, dynamic composition and adaptation supported by DCR Graphs. The dynamically composed and adapted graphs are verified for...

  17. 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.

  18. Shape Morphing Adaptive Radiator Technology (SMART) Updates to Techport Entry

    Science.gov (United States)

    Erickson, Lisa; Bertagne, Christopher; Hartl, Darren; Witcomb, John; Cognata, Thomas

    2017-01-01

    The Shape-Morphing Adaptive Radiator Technology (SMART) project builds off the FY16 research effort that developed a flexible composite radiator panel and demonstrated its ability to actuate from SMA's attached to it. The proposed FY17 Shape-Morphing Adaptive Radiator Technology (SMART) project's goal is to 1) develop a practical radiator design with shape memory alloys (SMAs) bonded to the radiator's panel, and 2) build a multi-panel radiator prototype for subsequent system level thermal vacuum tests. The morphing radiator employs SMA materials to passively change its shape to adapt its rate of heat rejection to vehicle requirements. Conceptually, the radiator panel has a naturally closed position (like a cylinder) in a cold environment. Whenever the radiator's temperature gradually rises, SMA's affixed to the face sheet will pull the face sheet open a commensurate amount - increasing the radiators view to space and causing it to reject more heat. In a vehicle, the radiator's variable heat rejection capabilities would reduce the number of additional heat rejection devices in a vehicle's thermal control system. This technology aims to help achieve the required maximum to minimum heat rejection ratio required for manned space vehicles to adopt a lighter, simpler, single loop thermal control architecture (ATCS). Single loop architectures are viewed as an attractive means to reduce mass and complexity over traditional dual-loop solutions. However, fluids generally considered safe enough to flow within crewed cabins (e.g. propylene glycol-water mixtures) have much higher freezing points and viscosities than those used in the external sides of dual loop ATCSs (e.g. Ammonia and HFE7000).

  19. Adaptive Event-Triggered Control Based on Heuristic Dynamic Programming for Nonlinear Discrete-Time Systems.

    Science.gov (United States)

    Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo

    2017-07-01

    This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.

  20. Adaptation and inertia in dynamic environments

    DEFF Research Database (Denmark)

    Stieglitz, Nils; Knudsen, Thorbjørn; Becker, Markus C.

    2016-01-01

    responses to these dimensions. Our results show how frequent directional changes undermine the value of exploration and decisively shift performance advantages to inert organizations that restrict exploration. In contrast, increased environmental variance rewards exploration. Our results also show that......Research summary: We address conflicting claims and mixed empirical findings about adaptation as a response to increased environmental dynamism. We disentangle distinct dimensions of environmental dynamism—the direction, magnitude, and frequency of change—and identify how selection shapes adaptive...... business environments characterized by persistent trends and by large, infrequently occurring structural shocks reward strategic pursuit of temporary advantage. Thus, exploration and strategic flexibility are preferred strategies. In contrast, the challenge in frequently changing environments with fleeting...

  1. 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)

  2. Choreographies and Behavioural Contracts on the Way to Dynamic Updates

    Directory of Open Access Journals (Sweden)

    Mario Bravetti

    2014-11-01

    Full Text Available We survey our work on choreographies and behavioural contracts in multiparty interactions. In particular theories of behavioural contracts are presented which enable reasoning about correct service composition (contract compliance and service substitutability (contract refinement preorder under different assumptions concerning service communication: synchronous address or name based communication with patient non-preemptable or impatient invocations, or asynchronous communication. Correspondingly relations between behavioural contracts and choreographic descriptions are considered, where a contract for each communicating party is, e.g., derived by projection. The considered relations are induced as the maximal preoders which preserve contract compliance and global traces: we show maximality to hold (permitting services to be discovered/substituted independently for each party when contract refinement preorders with all the above asymmetric communication means are considered and, instead, not to hold if the standard symmetric CCS/pi-calculus communication is considered (or when directly relating choreographies to behavioral contracts via a preorder, no matter the communication mean. The obtained maximal preorders are then characterized in terms of a new form of testing, called compliance testing, where not only tests must succeed but also the system under test (thus relating to controllability theory, and compared with classical preorders such as may/must testing, trace inclusion, etc. Finally, recent work about adaptable choreographies and behavioural contracts is presented, where the theory above is extended to update mechanisms allowing choreographies/contracts to be modified at run-time by internal (self-adaptation or external intervention.

  3. Citation Discovery Tools for Conducting Adaptive Meta-analyses to Update Systematic Reviews.

    Science.gov (United States)

    Bae, Jong-Myon; Kim, Eun Hee

    2016-03-01

    The systematic review (SR) is a research methodology that aims to synthesize related evidence. Updating previously conducted SRs is necessary when new evidence has been produced, but no consensus has yet emerged on the appropriate update methodology. The authors have developed a new SR update method called 'adaptive meta-analysis' (AMA) using the 'cited by', 'similar articles', and 'related articles' citation discovery tools in the PubMed and Scopus databases. This study evaluates the usefulness of these citation discovery tools for updating SRs. Lists were constructed by applying the citation discovery tools in the two databases to the articles analyzed by a published SR. The degree of overlap between the lists and distribution of excluded results were evaluated. The articles ultimately selected for the SR update meta-analysis were found in the lists obtained from the 'cited by' and 'similar' tools in PubMed. Most of the selected articles appeared in both the 'cited by' lists in Scopus and PubMed. The Scopus 'related' tool did not identify the appropriate articles. The AMA, which involves using both citation discovery tools in PubMed, and optionally, the 'related' tool in Scopus, was found to be useful for updating an SR.

  4. Adaptive optics scanning laser ophthalmoscope imaging: technology update

    Directory of Open Access Journals (Sweden)

    Merino D

    2016-04-01

    Full Text Available David Merino, Pablo Loza-Alvarez The Institute of Photonic Sciences (ICFO, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain Abstract: Adaptive optics (AO retinal imaging has become very popular in the past few years, especially within the ophthalmic research community. Several different retinal techniques, such as fundus imaging cameras or optical coherence tomography systems, have been coupled with AO in order to produce impressive images showing individual cell mosaics over different layers of the in vivo human retina. The combination of AO with scanning laser ophthalmoscopy has been extensively used to generate impressive images of the human retina with unprecedented resolution, showing individual photoreceptor cells, retinal pigment epithelium cells, as well as microscopic capillary vessels, or the nerve fiber layer. Over the past few years, the technique has evolved to develop several different applications not only in the clinic but also in different animal models, thanks to technological developments in the field. These developments have specific applications to different fields of investigation, which are not limited to the study of retinal diseases but also to the understanding of the retinal function and vision science. This review is an attempt to summarize these developments in an understandable and brief manner in order to guide the reader into the possibilities that AO scanning laser ophthalmoscopy offers, as well as its limitations, which should be taken into account when planning on using it. Keywords: high-resolution, in vivo retinal imaging, AOSLO

  5. Adaptive control of an exoskeleton robot with uncertainties on kinematics and dynamics.

    Science.gov (United States)

    Brahmi, Brahim; Saad, Maarouf; Ochoa-Luna, Cristobal; Rahman, Mohammad H

    2017-07-01

    In this paper, we propose a new adaptive control technique based on nonlinear sliding mode control (JSTDE) taking into account kinematics and dynamics uncertainties. This approach is applied to an exoskeleton robot with uncertain kinematics and dynamics. The adaptation design is based on Time Delay Estimation (TDE). The proposed strategy does not necessitate the well-defined dynamic and kinematic models of the system robot. The updated laws are designed using Lyapunov-function to solve the adaptation problem systematically, proving the close loop stability and ensuring the convergence asymptotically of the outputs tracking errors. Experiments results show the effectiveness and feasibility of JSTDE technique to deal with the variation of the unknown nonlinear dynamics and kinematics of the exoskeleton model.

  6. Computerized Adaptive Testing with R: Recent Updates of the Package catR

    Directory of Open Access Journals (Sweden)

    David Magis

    2017-01-01

    Full Text Available The purpose of this paper is to list the recent updates of the R package catR. This package allows for generating response patterns under a computerized adaptive testing (CAT framework with underlying item response theory (IRT models. Among the most important updates, well-known polytomous IRT models are now supported by catR; several item selection rules have been added; and it is now possible to perform post-hoc simulations. Some functions were also rewritten or withdrawn to improve the usefulness and performances of the package.

  7. Dynamic model updating based on strain mode shape and natural frequency using hybrid pattern search technique

    Science.gov (United States)

    Guo, Ning; Yang, Zhichun; Wang, Le; Ouyang, Yan; Zhang, Xinping

    2018-05-01

    Aiming at providing a precise dynamic structural finite element (FE) model for dynamic strength evaluation in addition to dynamic analysis. A dynamic FE model updating method is presented to correct the uncertain parameters of the FE model of a structure using strain mode shapes and natural frequencies. The strain mode shape, which is sensitive to local changes in structure, is used instead of the displacement mode for enhancing model updating. The coordinate strain modal assurance criterion is developed to evaluate the correlation level at each coordinate over the experimental and the analytical strain mode shapes. Moreover, the natural frequencies which provide the global information of the structure are used to guarantee the accuracy of modal properties of the global model. Then, the weighted summation of the natural frequency residual and the coordinate strain modal assurance criterion residual is used as the objective function in the proposed dynamic FE model updating procedure. The hybrid genetic/pattern-search optimization algorithm is adopted to perform the dynamic FE model updating procedure. Numerical simulation and model updating experiment for a clamped-clamped beam are performed to validate the feasibility and effectiveness of the present method. The results show that the proposed method can be used to update the uncertain parameters with good robustness. And the updated dynamic FE model of the beam structure, which can correctly predict both the natural frequencies and the local dynamic strains, is reliable for the following dynamic analysis and dynamic strength evaluation.

  8. Adaptive typography for dynamic mapping environments

    Science.gov (United States)

    Bardon, Didier

    1991-08-01

    When typography moves across a map, it passes over areas of different colors, densities, and textures. In such a dynamic environment, the aspect of typography must be constantly adapted to provide disernibility for every new background. Adaptive typography undergoes two adaptive operations: background control and contrast control. The background control prevents the features of the map (edges, lines, abrupt changes of densities) from destroying the integrity of the letterform. This is achieved by smoothing the features of the map in the area where a text label is displayed. The modified area is limited to the space covered by the characters of the label. Dispositions are taken to insure that the smoothing operation does not introduce any new visual noise. The contrast control assures that there are sufficient lightness differences between the typography and its ever-changing background. For every new situation, background color and foreground color are compared and the foreground color lightness is adjusted according to a chosen contrast value. Criteria and methods of choosing the appropriate contrast value are presented as well as the experiments that led to them.

  9. Modulation of neuronal dynamic range using two different adaptation mechanisms

    Directory of Open Access Journals (Sweden)

    Lei Wang

    2017-01-01

    Full Text Available The capability of neurons to discriminate between intensity of external stimulus is measured by its dynamic range. A larger dynamic range indicates a greater probability of neuronal survival. In this study, the potential roles of adaptation mechanisms (ion currents in modulating neuronal dynamic range were numerically investigated. Based on the adaptive exponential integrate-and-fire model, which includes two different adaptation mechanisms, i.e. subthreshold and suprathreshold (spike-triggered adaptation, our results reveal that the two adaptation mechanisms exhibit rather different roles in regulating neuronal dynamic range. Specifically, subthreshold adaptation acts as a negative factor that observably decreases the neuronal dynamic range, while suprathreshold adaptation has little influence on the neuronal dynamic range. Moreover, when stochastic noise was introduced into the adaptation mechanisms, the dynamic range was apparently enhanced, regardless of what state the neuron was in, e.g. adaptive or non-adaptive. Our model results suggested that the neuronal dynamic range can be differentially modulated by different adaptation mechanisms. Additionally, noise was a non-ignorable factor, which could effectively modulate the neuronal dynamic range.

  10. A double-loop adaptive sampling approach for sensitivity-free dynamic reliability analysis

    International Nuclear Information System (INIS)

    Wang, Zequn; Wang, Pingfeng

    2015-01-01

    Dynamic reliability measures reliability of an engineered system considering time-variant operation condition and component deterioration. Due to high computational costs, conducting dynamic reliability analysis at an early system design stage remains challenging. This paper presents a confidence-based meta-modeling approach, referred to as double-loop adaptive sampling (DLAS), for efficient sensitivity-free dynamic reliability analysis. The DLAS builds a Gaussian process (GP) model sequentially to approximate extreme system responses over time, so that Monte Carlo simulation (MCS) can be employed directly to estimate dynamic reliability. A generic confidence measure is developed to evaluate the accuracy of dynamic reliability estimation while using the MCS approach based on developed GP models. A double-loop adaptive sampling scheme is developed to efficiently update the GP model in a sequential manner, by considering system input variables and time concurrently in two sampling loops. The model updating process using the developed sampling scheme can be terminated once the user defined confidence target is satisfied. The developed DLAS approach eliminates computationally expensive sensitivity analysis process, thus substantially improves the efficiency of dynamic reliability analysis. Three case studies are used to demonstrate the efficacy of DLAS for dynamic reliability analysis. - Highlights: • Developed a novel adaptive sampling approach for dynamic reliability analysis. • POD Developed a new metric to quantify the accuracy of dynamic reliability estimation. • Developed a new sequential sampling scheme to efficiently update surrogate models. • Three case studies were used to demonstrate the efficacy of the new approach. • Case study results showed substantially enhanced efficiency with high accuracy

  11. PAQ: Persistent Adaptive Query Middleware for Dynamic Environments

    Science.gov (United States)

    Rajamani, Vasanth; Julien, Christine; Payton, Jamie; Roman, Gruia-Catalin

    Pervasive computing applications often entail continuous monitoring tasks, issuing persistent queries that return continuously updated views of the operational environment. We present PAQ, a middleware that supports applications' needs by approximating a persistent query as a sequence of one-time queries. PAQ introduces an integration strategy abstraction that allows composition of one-time query responses into streams representing sophisticated spatio-temporal phenomena of interest. A distinguishing feature of our middleware is the realization that the suitability of a persistent query's result is a function of the application's tolerance for accuracy weighed against the associated overhead costs. In PAQ, programmers can specify an inquiry strategy that dictates how information is gathered. Since network dynamics impact the suitability of a particular inquiry strategy, PAQ associates an introspection strategy with a persistent query, that evaluates the quality of the query's results. The result of introspection can trigger application-defined adaptation strategies that alter the nature of the query. PAQ's simple API makes developing adaptive querying systems easily realizable. We present the key abstractions, describe their implementations, and demonstrate the middleware's usefulness through application examples and evaluation.

  12. Key Techniques for Dynamic Updating of National Fundamental Geographic Information Database

    Directory of Open Access Journals (Sweden)

    WANG Donghua

    2015-07-01

    Full Text Available One of the most important missions of fundamental surveying and mapping work is to keep the fundamental geographic information fresh. In this respect, National Administration of Surveying, Mapping and Geoinformation has launched the project of dynamic updating of national fundamental geographic information database since 2012, which aims to update 1:50 000, 1:250 000 and 1:1 000 000 national fundamental geographic information database continuously and quickly, by updating and publishing once a year. This paper introduces the general technical thinking of dynamic updating, states main technical methods, such as dynamic updating of fundamental database, linkage updating of derived databases, and multi-tense database management and service and so on, and finally introduces main technical characteristics and engineering applications.

  13. Adaptive optics scanning laser ophthalmoscopy in fundus imaging, a review and update

    Directory of Open Access Journals (Sweden)

    Bing Zhang

    2017-11-01

    Full Text Available Adaptive optics scanning laser ophthalmoscopy (AO-SLO has been a promising technique in funds imaging with growing popularity. This review firstly gives a brief history of adaptive optics (AO and AO-SLO. Then it compares AO-SLO with conventional imaging methods (fundus fluorescein angiography, fundus autofluorescence, indocyanine green angiography and optical coherence tomography and other AO techniques (adaptive optics flood-illumination ophthalmoscopy and adaptive optics optical coherence tomography. Furthermore, an update of current research situation in AO-SLO is made based on different fundus structures as photoreceptors (cones and rods, fundus vessels, retinal pigment epithelium layer, retinal nerve fiber layer, ganglion cell layer and lamina cribrosa. Finally, this review indicates possible research directions of AO-SLO in future.

  14. 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.

  15. Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

    Directory of Open Access Journals (Sweden)

    Lei Qin

    2014-05-01

    Full Text Available We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences.

  16. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2015-01-01

    This primer offers readers an introduction to the central concepts that form our modern understanding of complex and emergent behavior, together with detailed coverage of accompanying mathematical methods. All calculations are presented step by step and are easy to follow. This new fourth edition has been fully reorganized and includes new chapters, figures and exercises. The core aspects of modern complex system sciences are presented in the first chapters, covering network theory, dynamical systems, bifurcation and catastrophe theory, chaos and adaptive processes, together with the principle of self-organization in reaction-diffusion systems and social animals. Modern information theoretical principles are treated in further chapters, together with the concept of self-organized criticality, gene regulation networks, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase transitions and the cognitive system approach to the brain. Technical course prerequisites are the standard ...

  17. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2013-01-01

    Complex system theory is rapidly developing and gaining importance, providing tools and concepts central to our modern understanding of emergent phenomena. This primer offers an introduction to this area together with detailed coverage of the mathematics involved. All calculations are presented step by step and are straightforward to follow. This new third edition comes with new material, figures and exercises. Network theory, dynamical systems and information theory, the core of modern complex system sciences, are developed in the first three chapters, covering basic concepts and phenomena like small-world networks, bifurcation theory and information entropy. Further chapters use a modular approach to address the most important concepts in complex system sciences, with the emergence and self-organization playing a central role. Prominent examples are self-organized criticality in adaptive systems, life at the edge of chaos, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase...

  18. Method and system for training dynamic nonlinear adaptive filters which have embedded memory

    Science.gov (United States)

    Rabinowitz, Matthew (Inventor)

    2002-01-01

    Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.

  19. A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

    Science.gov (United States)

    Ingram, James N; Howard, Ian S; Flanagan, J Randall; Wolpert, Daniel M

    2011-09-01

    Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics

  20. A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

    Directory of Open Access Journals (Sweden)

    James N Ingram

    2011-09-01

    Full Text Available Motor learning has been extensively studied using dynamic (force-field perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar

  1. Neural basis for dynamic updating of object representation in visual working memory.

    Science.gov (United States)

    Takahama, Sachiko; Miyauchi, Satoru; Saiki, Jun

    2010-02-15

    In real world, objects have multiple features and change dynamically. Thus, object representations must satisfy dynamic updating and feature binding. Previous studies have investigated the neural activity of dynamic updating or feature binding alone, but not both simultaneously. We investigated the neural basis of feature-bound object representation in a dynamically updating situation by conducting a multiple object permanence tracking task, which required observers to simultaneously process both the maintenance and dynamic updating of feature-bound objects. Using an event-related design, we separated activities during memory maintenance and change detection. In the search for regions showing selective activation in dynamic updating of feature-bound objects, we identified a network during memory maintenance that was comprised of the inferior precentral sulcus, superior parietal lobule, and middle frontal gyrus. In the change detection period, various prefrontal regions, including the anterior prefrontal cortex, were activated. In updating object representation of dynamically moving objects, the inferior precentral sulcus closely cooperates with a so-called "frontoparietal network", and subregions of the frontoparietal network can be decomposed into those sensitive to spatial updating and feature binding. The anterior prefrontal cortex identifies changes in object representation by comparing memory and perceptual representations rather than maintaining object representations per se, as previously suggested. Copyright 2009 Elsevier Inc. All rights reserved.

  2. An Integrated Platform for Dynamic Software Updating and its Application in Self-* systems

    DEFF Research Database (Denmark)

    Gregersen, Allan Raundahl; Jørgensen, Bo Nørregaard; Hadaytullah

    2012-01-01

    Practical dynamic updating of modern Java applications requires tool support to become an integral part of the software development and maintenance lifecycle. In this paper we present Javeleon, an easy-to-use tool for dynamic updates of Java applications. To support integration with specific...... frameworks, component systems and application servers, Javeleon currently provides tight integration with the NetBeans Platform, facilitating dynamic updating for applications built on top of the NetBeans Platform in an unconstrained manner. Javeleon supports state-preserving unanticipated runtime evolution...

  3. Adapting to change: The role of the right hemisphere in mental model building and updating.

    Science.gov (United States)

    Filipowicz, Alex; Anderson, Britt; Danckert, James

    2016-09-01

    We recently proposed that the right hemisphere plays a crucial role in the processes underlying mental model building and updating. Here, we review the evidence we and others have garnered to support this novel account of right hemisphere function. We begin by presenting evidence from patient work that suggests a critical role for the right hemisphere in the ability to learn from the statistics in the environment (model building) and adapt to environmental change (model updating). We then provide a review of neuroimaging research that highlights a network of brain regions involved in mental model updating. Next, we outline specific roles for particular regions within the network such that the anterior insula is purported to maintain the current model of the environment, the medial prefrontal cortex determines when to explore new or alternative models, and the inferior parietal lobule represents salient and surprising information with respect to the current model. We conclude by proposing some future directions that address some of the outstanding questions in the field of mental model building and updating. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  4. On the number of different dynamics in Boolean networks with deterministic update schedules.

    Science.gov (United States)

    Aracena, J; Demongeot, J; Fanchon, E; Montalva, M

    2013-04-01

    Deterministic Boolean networks are a type of discrete dynamical systems widely used in the modeling of genetic networks. The dynamics of such systems is characterized by the local activation functions and the update schedule, i.e., the order in which the nodes are updated. In this paper, we address the problem of knowing the different dynamics of a Boolean network when the update schedule is changed. We begin by proving that the problem of the existence of a pair of update schedules with different dynamics is NP-complete. However, we show that certain structural properties of the interaction diagraph are sufficient for guaranteeing distinct dynamics of a network. In [1] the authors define equivalence classes which have the property that all the update schedules of a given class yield the same dynamics. In order to determine the dynamics associated to a network, we develop an algorithm to efficiently enumerate the above equivalence classes by selecting a representative update schedule for each class with a minimum number of blocks. Finally, we run this algorithm on the well known Arabidopsis thaliana network to determine the full spectrum of its different dynamics. Copyright © 2013 Elsevier Inc. All rights reserved.

  5. Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

    Science.gov (United States)

    Volyanskyy, Kostyantyn Y.

    Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance

  6. Adaptive dynamics of extortion and compliance.

    Directory of Open Access Journals (Sweden)

    Christian Hilbe

    Full Text Available Direct reciprocity is a mechanism for the evolution of cooperation. For the iterated prisoner's dilemma, a new class of strategies has recently been described, the so-called zero-determinant strategies. Using such a strategy, a player can unilaterally enforce a linear relationship between his own payoff and the co-player's payoff. In particular the player may act in such a way that it becomes optimal for the co-player to cooperate unconditionally. In this way, a player can manipulate and extort his co-player, thereby ensuring that the own payoff never falls below the co-player's payoff. However, using a compliant strategy instead, a player can also ensure that his own payoff never exceeds the co-player's payoff. Here, we use adaptive dynamics to study when evolution leads to extortion and when it leads to compliance. We find a remarkable cyclic dynamics: in sufficiently large populations, extortioners play a transient role, helping the population to move from selfish strategies to compliance. Compliant strategies, however, can be subverted by altruists, which in turn give rise to selfish strategies. Whether cooperative strategies are favored in the long run critically depends on the size of the population; we show that cooperation is most abundant in large populations, in which case average payoffs approach the social optimum. Our results are not restricted to the case of the prisoners dilemma, but can be extended to other social dilemmas, such as the snowdrift game. Iterated social dilemmas in large populations do not lead to the evolution of strategies that aim to dominate their co-player. Instead, generosity succeeds.

  7. Adaptive pseudolinear compensators of dynamic characteristics of automatic control systems

    Science.gov (United States)

    Skorospeshkin, M. V.; Sukhodoev, M. S.; Timoshenko, E. A.; Lenskiy, F. V.

    2016-04-01

    Adaptive pseudolinear gain and phase compensators of dynamic characteristics of automatic control systems are suggested. The automatic control system performance with adaptive compensators has been explored. The efficiency of pseudolinear adaptive compensators in the automatic control systems with time-varying parameters has been demonstrated.

  8. Role of update dynamics in the collective cooperation on the spatial snowdrift games: Beyond unconditional imitation and replicator dynamics

    International Nuclear Information System (INIS)

    Xia Chengyi; Wang Juan; Wang Li; Sun Shiwen; Sun Junqing; Wang Jinsong

    2012-01-01

    Highlights: ► We investigate the role of update rules in the spatial snowdrift game on regular lattices. ► Compared with UI and replicator rules, the cooperation can be further promoted by the Moran rule. ► f c and the cluster formation pattern for these three update rules are carefully explored. ► The frequency of cooperators is insensitive to the random initial set of players. - Abstract: In this paper, we investigate the role of update or imitation rules in the spatial snowdrift game on regular lattices. Three different update rules, including unconditional imitation (UI), replicator dynamics (RD) and the Moran process, are utilized to update the strategies of focal players during the game process in the spatial snowdrift on the lattice. We observe that the aggregate cooperation level between players is largely elevated by using the Moran process in the spatial snowdrift game, when compared to the UI or replicator dynamics. Meanwhile, we carefully explore the dynamical evolution of frequency of cooperators and the cluster formation pattern for these three update rules. Moreover, it is also shown that the evolutionary behavior under the Moran update is independent of and insensitive to the randomly initial configurations of cooperators and defectors. The current results clearly indicate that the introduction of moderate randomness in the strategy update will highly promote the maintenance and persistence of cooperation among selfish individuals, which will be greatly instrumental to deeply understand the evolution of cooperation within many natural, biological and social systems.

  9. Time course of dynamic range adaptation in the auditory nerve

    Science.gov (United States)

    Wang, Grace I.; Dean, Isabel; Delgutte, Bertrand

    2012-01-01

    Auditory adaptation to sound-level statistics occurs as early as in the auditory nerve (AN), the first stage of neural auditory processing. In addition to firing rate adaptation characterized by a rate decrement dependent on previous spike activity, AN fibers show dynamic range adaptation, which is characterized by a shift of the rate-level function or dynamic range toward the most frequently occurring levels in a dynamic stimulus, thereby improving the precision of coding of the most common sound levels (Wen B, Wang GI, Dean I, Delgutte B. J Neurosci 29: 13797–13808, 2009). We investigated the time course of dynamic range adaptation by recording from AN fibers with a stimulus in which the sound levels periodically switch from one nonuniform level distribution to another (Dean I, Robinson BL, Harper NS, McAlpine D. J Neurosci 28: 6430–6438, 2008). Dynamic range adaptation occurred rapidly, but its exact time course was difficult to determine directly from the data because of the concomitant firing rate adaptation. To characterize the time course of dynamic range adaptation without the confound of firing rate adaptation, we developed a phenomenological “dual adaptation” model that accounts for both forms of AN adaptation. When fitted to the data, the model predicts that dynamic range adaptation occurs as rapidly as firing rate adaptation, over 100–400 ms, and the time constants of the two forms of adaptation are correlated. These findings suggest that adaptive processing in the auditory periphery in response to changes in mean sound level occurs rapidly enough to have significant impact on the coding of natural sounds. PMID:22457465

  10. Efficient Dynamic Adaptation Strategies for Object Tracking Tree in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    CHEN, M.

    2012-12-01

    Full Text Available Most object tracking trees are established using the predefined mobility profile. However, when the real object's movement behaviors and query rates are different from the predefined mobility profile and query rates, the update cost and query cost of object tracking tree may increase. To upgrade the object tracking tree, the sink needs to send very large messages to collect the real movement information from the network, introducing a very large message overhead, which is referred to as adaptation cost. The Sub Root Message-Tree Adaptive procedure was proposed to dynamically collect the real movement information under the sub-tree and reconstruct the sub-tree to provide good performance based on the collected information. The simulation results indicates that the Sub Root Message-Tree Adaptive procedure is sufficient to achieve good total cost and lower adaptation cost.

  11. The Hitchhiker’s Guide to Adaptive Dynamics

    Directory of Open Access Journals (Sweden)

    Jacob Johansson

    2013-06-01

    Full Text Available Adaptive dynamics is a mathematical framework for studying evolution. It extends evolutionary game theory to account for more realistic ecological dynamics and it can incorporate both frequency- and density-dependent selection. This is a practical guide to adaptive dynamics that aims to illustrate how the methodology can be applied to the study of specific systems. The theory is presented in detail for a single, monomorphic, asexually reproducing population. We explain the necessary terminology to understand the basic arguments in models based on adaptive dynamics, including invasion fitness, the selection gradient, pairwise invasibility plots (PIP, evolutionarily singular strategies, and the canonical equation. The presentation is supported with a worked-out example of evolution of arrival times in migratory birds. We show how the adaptive dynamics methodology can be extended to study evolution in polymorphic populations using trait evolution plots (TEPs. We give an overview of literature that generalises adaptive dynamics techniques to other scenarios, such as sexual, diploid populations, and spatially-structured populations. We conclude by discussing how adaptive dynamics relates to evolutionary game theory and how adaptive-dynamics techniques can be used in speciation research.

  12. Updating beliefs and combining evidence in adaptive forest management under climate change

    DEFF Research Database (Denmark)

    Yousefpour, Rasoul; Temperli, Christian; Bugmann, Harald

    2013-01-01

    We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even...... variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation...... on when managers switch to forward-looking management schemes. Thus, robust climate adaptation policies may depend crucially on a better understanding of what factors influence managers' belief in climate change....

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

    Science.gov (United States)

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

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

  14. A review on model updating of joint structure for dynamic analysis purpose

    Directory of Open Access Journals (Sweden)

    Zahari S.N.

    2016-01-01

    Full Text Available Structural joints provide connection between structural element (beam, plate etc. in order to construct a whole assembled structure. There are many types of structural joints such as bolted joint, riveted joints and welded joints. The joints structures significantly contribute to structural stiffness and dynamic behaviour of structures hence the main objectives of this paper are to review on method of model updating on joints structure and to discuss the guidelines to perform model updating for dynamic analysis purpose. This review paper firstly will outline some of the existing finite element modelling works of joints structure. Experimental modal analysis is the next step to obtain modal parameters (natural frequency & mode shape to validate and improve the discrepancy between results obtained from experimental and the simulation counterparts. Hence model updating will be carried out to minimize the differences between the two results. There are two methods of model updating; direct method and iterative method. Sensitivity analysis employed using SOL200 in NASTRAN by selecting the suitable updating parameters to avoid ill-conditioning problem. It is best to consider both geometrical and material properties in the updating procedure rather than choosing only a number of geometrical properties alone. Iterative method was chosen as the best model updating procedure because the physical meaning of updated parameters are guaranteed although this method required computational effort compare to direct method.

  15. Robust adaptive synchronization of general dynamical networks ...

    Indian Academy of Sciences (India)

    Home; Journals; Pramana – Journal of Physics; Volume 86; Issue 6. Robust ... A robust adaptive synchronization scheme for these general complex networks with multiple delays and uncertainties is established and raised by employing the robust adaptive control principle and the Lyapunov stability theory. We choose ...

  16. Recruitment dynamics in adaptive social networks

    International Nuclear Information System (INIS)

    Shkarayev, Maxim S; Shaw, Leah B; Schwartz, Ira B

    2013-01-01

    We model recruitment in adaptive social networks in the presence of birth and death processes. Recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. Only a susceptible subset of nodes can be recruited. The recruiting individuals may adapt their connections in order to improve recruitment capabilities, thus changing the network structure adaptively. We derive a mean-field theory to predict the dependence of the growth threshold of the recruiting class on the adaptation parameter. Furthermore, we investigate the effect of adaptation on the recruitment level, as well as on network topology. The theoretical predictions are compared with direct simulations of the full system. We identify two parameter regimes with qualitatively different bifurcation diagrams depending on whether nodes become susceptible frequently (multiple times in their lifetime) or rarely (much less than once per lifetime). (paper)

  17. Recruitment dynamics in adaptive social networks

    Science.gov (United States)

    Shkarayev, Maxim S.; Schwartz, Ira B.; Shaw, Leah B.

    2013-06-01

    We model recruitment in adaptive social networks in the presence of birth and death processes. Recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. Only a susceptible subset of nodes can be recruited. The recruiting individuals may adapt their connections in order to improve recruitment capabilities, thus changing the network structure adaptively. We derive a mean-field theory to predict the dependence of the growth threshold of the recruiting class on the adaptation parameter. Furthermore, we investigate the effect of adaptation on the recruitment level, as well as on network topology. The theoretical predictions are compared with direct simulations of the full system. We identify two parameter regimes with qualitatively different bifurcation diagrams depending on whether nodes become susceptible frequently (multiple times in their lifetime) or rarely (much less than once per lifetime).

  18. Neural network based adaptive control for nonlinear dynamic regimes

    Science.gov (United States)

    Shin, Yoonghyun

    Adaptive control designs using neural networks (NNs) based on dynamic inversion are investigated for aerospace vehicles which are operated at highly nonlinear dynamic regimes. NNs play a key role as the principal element of adaptation to approximately cancel the effect of inversion error, which subsequently improves robustness to parametric uncertainty and unmodeled dynamics in nonlinear regimes. An adaptive control scheme previously named 'composite model reference adaptive control' is further developed so that it can be applied to multi-input multi-output output feedback dynamic inversion. It can have adaptive elements in both the dynamic compensator (linear controller) part and/or in the conventional adaptive controller part, also utilizing state estimation information for NN adaptation. This methodology has more flexibility and thus hopefully greater potential than conventional adaptive designs for adaptive flight control in highly nonlinear flight regimes. The stability of the control system is proved through Lyapunov theorems, and validated with simulations. The control designs in this thesis also include the use of 'pseudo-control hedging' techniques which are introduced to prevent the NNs from attempting to adapt to various actuation nonlinearities such as actuator position and rate saturations. Control allocation is introduced for the case of redundant control effectors including thrust vectoring nozzles. A thorough comparison study of conventional and NN-based adaptive designs for a system under a limit cycle, wing-rock, is included in this research, and the NN-based adaptive control designs demonstrate their performances for two highly maneuverable aerial vehicles, NASA F-15 ACTIVE and FQM-117B unmanned aerial vehicle (UAV), operated under various nonlinearities and uncertainties.

  19. The updated geodetic mean dynamic topography model – DTU15MDT

    DEFF Research Database (Denmark)

    Knudsen, Per; Andersen, Ole Baltazar; Maximenko, Nikolai

    An update to the global mean dynamic topography model DTU13MDT is presented. For DTU15MDT the newer gravity model EIGEN-6C4 has been combined with the DTU15MSS mean sea surface model to construct this global mean dynamic topography model. The EIGEN-6C4 is derived using the full series of GOCE data...

  20. Finite-element-model updating using computational intelligence techniques applications to structural dynamics

    CERN Document Server

    Marwala, Tshilidzi

    2010-01-01

    Finite element models (FEMs) are widely used to understand the dynamic behaviour of various systems. FEM updating allows FEMs to be tuned better to reflect measured data and may be conducted using two different statistical frameworks: the maximum likelihood approach and Bayesian approaches. Finite Element Model Updating Using Computational Intelligence Techniques applies both strategies to the field of structural mechanics, an area vital for aerospace, civil and mechanical engineering. Vibration data is used for the updating process. Following an introduction a number of computational intelligence techniques to facilitate the updating process are proposed; they include: • multi-layer perceptron neural networks for real-time FEM updating; • particle swarm and genetic-algorithm-based optimization methods to accommodate the demands of global versus local optimization models; • simulated annealing to put the methodologies into a sound statistical basis; and • response surface methods and expectation m...

  1. 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...

  2. DyNAvectors: dynamic constitutional vectors for adaptive DNA transfection.

    Science.gov (United States)

    Clima, Lilia; Peptanariu, Dragos; Pinteala, Mariana; Salic, Adrian; Barboiu, Mihail

    2015-12-25

    Dynamic constitutional frameworks, based on squalene, PEG and PEI components, reversibly connected to core centers, allow the efficient identification of adaptive vectors for good DNA transfection efficiency and are well tolerated by mammalian cells.

  3. Global network reorganization during dynamic adaptations of Bacillus subtilis metabolism

    DEFF Research Database (Denmark)

    Buescher, Joerg Martin; Liebermeister, Wolfram; Jules, Matthieu

    2012-01-01

    Adaptation of cells to environmental changes requires dynamic interactions between metabolic and regulatory networks, but studies typically address only one or a few layers of regulation. For nutritional shifts between two preferred carbon sources of Bacillus subtilis, we combined statistical...

  4. Chemotactic response and adaptation dynamics in Escherichia coli.

    Directory of Open Access Journals (Sweden)

    Diana Clausznitzer

    2010-05-01

    Full Text Available Adaptation of the chemotaxis sensory pathway of the bacterium Escherichia coli is integral for detecting chemicals over a wide range of background concentrations, ultimately allowing cells to swim towards sources of attractant and away from repellents. Its biochemical mechanism based on methylation and demethylation of chemoreceptors has long been known. Despite the importance of adaptation for cell memory and behavior, the dynamics of adaptation are difficult to reconcile with current models of precise adaptation. Here, we follow time courses of signaling in response to concentration step changes of attractant using in vivo fluorescence resonance energy transfer measurements. Specifically, we use a condensed representation of adaptation time courses for efficient evaluation of different adaptation models. To quantitatively explain the data, we finally develop a dynamic model for signaling and adaptation based on the attractant flow in the experiment, signaling by cooperative receptor complexes, and multiple layers of feedback regulation for adaptation. We experimentally confirm the predicted effects of changing the enzyme-expression level and bypassing the negative feedback for demethylation. Our data analysis suggests significant imprecision in adaptation for large additions. Furthermore, our model predicts highly regulated, ultrafast adaptation in response to removal of attractant, which may be useful for fast reorientation of the cell and noise reduction in adaptation.

  5. Complexity and network dynamics in physiological adaptation: An integrated view

    OpenAIRE

    Baffy, Gyorgy; Loscalzo, Joseph

    2014-01-01

    Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of t...

  6. 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.…

  7. Update schemes of multi-velocity floor field cellular automaton for pedestrian dynamics

    Science.gov (United States)

    Luo, Lin; Fu, Zhijian; Cheng, Han; Yang, Lizhong

    2018-02-01

    Modeling pedestrian movement is an interesting problem both in statistical physics and in computational physics. Update schemes of cellular automaton (CA) models for pedestrian dynamics govern the schedule of pedestrian movement. Usually, different update schemes make the models behave in different ways, which should be carefully recalibrated. Thus, in this paper, we investigated the influence of four different update schemes, namely parallel/synchronous scheme, random scheme, order-sequential scheme and shuffled scheme, on pedestrian dynamics. The multi-velocity floor field cellular automaton (FFCA) considering the changes of pedestrians' moving properties along walking paths and heterogeneity of pedestrians' walking abilities was used. As for parallel scheme only, the collisions detection and resolution should be considered, resulting in a great difference from any other update schemes. For pedestrian evacuation, the evacuation time is enlarged, and the difference in pedestrians' walking abilities is better reflected, under parallel scheme. In face of a bottleneck, for example a exit, using a parallel scheme leads to a longer congestion period and a more dispersive density distribution. The exit flow and the space-time distribution of density and velocity have significant discrepancies under four different update schemes when we simulate pedestrian flow with high desired velocity. Update schemes may have no influence on pedestrians in simulation to create tendency to follow others, but sequential and shuffled update scheme may enhance the effect of pedestrians' familiarity with environments.

  8. Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure.

    Science.gov (United States)

    Fei, Juntao; Lu, Cheng

    2018-04-01

    In this paper, an adaptive sliding mode control system using a double loop recurrent neural network (DLRNN) structure is proposed for a class of nonlinear dynamic systems. A new three-layer RNN is proposed to approximate unknown dynamics with two different kinds of feedback loops where the firing weights and output signal calculated in the last step are stored and used as the feedback signals in each feedback loop. Since the new structure has combined the advantages of internal feedback NN and external feedback NN, it can acquire the internal state information while the output signal is also captured, thus the new designed DLRNN can achieve better approximation performance compared with the regular NNs without feedback loops or the regular RNNs with a single feedback loop. The new proposed DLRNN structure is employed in an equivalent controller to approximate the unknown nonlinear system dynamics, and the parameters of the DLRNN are updated online by adaptive laws to get favorable approximation performance. To investigate the effectiveness of the proposed controller, the designed adaptive sliding mode controller with the DLRNN is applied to a -axis microelectromechanical system gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed methodology can achieve good tracking property, and the comparisons of the approximation performance between radial basis function NN, RNN, and DLRNN show that the DLRNN can accurately estimate the unknown dynamics with a fast speed while the internal states of DLRNN are more stable.

  9. Adaptive game AI with dynamic scripting

    NARCIS (Netherlands)

    Spronck, P.; Ponsen, M.J.V.; Sprinkhuizen-Kuyper, I.G.; Postma, E.O.

    2006-01-01

    Online learning in commercial computer games allows computer-controlled opponents to adapt to the way the game is being played. As such it provides a mechanism to deal with weaknesses in the game AI, and to respond to changes in human player tactics.We argue that online learning of game AI should

  10. Exploring dynamics of embedded ADC through adapted digital input stimuli

    NARCIS (Netherlands)

    Sheng, Xiaoqin; Kerkhoff, Hans G.; Zjajo, A.; Gronthoud, G.

    2008-01-01

    This paper reports an evaluation of adapted digital signals as a test stimulus to test dynamic parameters of analog-to-digital converters (ADC). In the first instance, the simplest digital waveform, a pulse signal, is taken as the test stimulus. The dynamics of the device under test while applying

  11. Online adaptive optimal control for continuous-time nonlinear systems with completely unknown dynamics

    Science.gov (United States)

    Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu

    2016-01-01

    An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.

  12. Adaptive game AI with dynamic scripting

    OpenAIRE

    Spronck, P.; Ponsen, M.J.V.; Sprinkhuizen-Kuyper, I.G.; Postma, E.O.

    2006-01-01

    Online learning in commercial computer games allows computer-controlled opponents to adapt to the way the game is being played. As such it provides a mechanism to deal with weaknesses in the game AI, and to respond to changes in human player tactics.We argue that online learning of game AI should meet four computational and four functional requirements. The computational requirements are speed, effectiveness, robustness and ef- ficiency. The functional requirements are clarity, variety, consi...

  13. Analog forecasting with dynamics-adapted kernels

    Science.gov (United States)

    Zhao, Zhizhen; Giannakis, Dimitrios

    2016-09-01

    Analog forecasting is a nonparametric technique introduced by Lorenz in 1969 which predicts the evolution of states of a dynamical system (or observables defined on the states) by following the evolution of the sample in a historical record of observations which most closely resembles the current initial data. Here, we introduce a suite of forecasting methods which improve traditional analog forecasting by combining ideas from kernel methods developed in harmonic analysis and machine learning and state-space reconstruction for dynamical systems. A key ingredient of our approach is to replace single-analog forecasting with weighted ensembles of analogs constructed using local similarity kernels. The kernels used here employ a number of dynamics-dependent features designed to improve forecast skill, including Takens’ delay-coordinate maps (to recover information in the initial data lost through partial observations) and a directional dependence on the dynamical vector field generating the data. Mathematically, our approach is closely related to kernel methods for out-of-sample extension of functions, and we discuss alternative strategies based on the Nyström method and the multiscale Laplacian pyramids technique. We illustrate these techniques in applications to forecasting in a low-order deterministic model for atmospheric dynamics with chaotic metastability, and interannual-scale forecasting in the North Pacific sector of a comprehensive climate model. We find that forecasts based on kernel-weighted ensembles have significantly higher skill than the conventional approach following a single analog.

  14. Complexity and network dynamics in physiological adaptation: an integrated view.

    Science.gov (United States)

    Baffy, György; Loscalzo, Joseph

    2014-05-28

    Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of the operational characteristics, allowing us to propose an integrated framework of physiological adaptation from a complex network perspective. Applicability of this concept is illustrated by analyzing molecular and cellular mechanisms of adaptation in response to the pervasive challenge of obesity, a chronic condition resulting from sustained nutrient excess that prompts chaotic exploration for system stability associated with tradeoffs and a risk of adverse outcomes such as diabetes, cardiovascular disease, and cancer. Deconstruction of this complexity holds the promise of gaining novel insights into physiological adaptation in health and disease. Published by Elsevier Inc.

  15. Using Microsoft Dynamics AX 2012 updated for version R2

    CERN Document Server

    Luszczak, Andreas

    2013-01-01

    Precise descriptions and instructions enable users, students and consultants to easily understand Microsoft Dynamics AX 2012. Microsoft offers Dynamics AX as its premium ERP solution to support large and mid-sized organizations with a complete business management solution which is easy to use. Going through a simple but comprehensive case study - the sample company 'Anso Technologies Inc.' - this book provides the required knowledge to handle all basic business processes in Dynamics AX. Exercises are there to train the processes and functionality, also making this book a good choice for self-s

  16. Using Microsoft Dynamics AX 2012 updated for version R3

    CERN Document Server

    Luszczak, Andreas

    2015-01-01

    Precise descriptions and instructions enable users, students and consultants to understand MS Dynamics AX 2012 rapidly. Microsoft offers Dynamics AX as its premium ERP solution, supporting large and mid-sized organizations with a complete business management solution which is easy to use. Going through a simple but comprehensive case study - the sample company 'Anso Technologies Inc.' - this book provides the required knowledge to handle all basic business processes in Dynamics AX. Exercises are there to train the processes and functionality, also making this book a good choice for self-study.

  17. Adaptive Strategies for Dynamic Pricing Agents

    NARCIS (Netherlands)

    S. Ramezani (Sara); P.A.N. Bosman (Peter); J.A. La Poutré (Han)

    2011-01-01

    htmlabstractDynamic Pricing (DyP) is a form of Revenue Management in which the price of a (usually) perishable good is changed over time to increase revenue. It is an effective method that has become even more relevant and useful with the emergence of Internet firms and the possibility of readily

  18. Brain-wide neuronal dynamics during motor adaptation in zebrafish.

    Science.gov (United States)

    Ahrens, Misha B; Li, Jennifer M; Orger, Michael B; Robson, Drew N; Schier, Alexander F; Engert, Florian; Portugues, Ruben

    2012-05-09

    A fundamental question in neuroscience is how entire neural circuits generate behaviour and adapt it to changes in sensory feedback. Here we use two-photon calcium imaging to record the activity of large populations of neurons at the cellular level, throughout the brain of larval zebrafish expressing a genetically encoded calcium sensor, while the paralysed animals interact fictively with a virtual environment and rapidly adapt their motor output to changes in visual feedback. We decompose the network dynamics involved in adaptive locomotion into four types of neuronal response properties, and provide anatomical maps of the corresponding sites. A subset of these signals occurred during behavioural adjustments and are candidates for the functional elements that drive motor learning. Lesions to the inferior olive indicate a specific functional role for olivocerebellar circuitry in adaptive locomotion. This study enables the analysis of brain-wide dynamics at single-cell resolution during behaviour.

  19. On Sustaining Dynamic Adaptation of Context-Aware Services

    Directory of Open Access Journals (Sweden)

    Boudjemaa Boudaa

    2015-03-01

    Full Text Available The modern human is getting more and more mobile having access to online services by using mobile cutting-edge computational devices. In the last decade, the field of context-aware services had led to emerge several works. However, most of the proposed approaches have not provided clear adaptation strategies in case of unforeseen contexts. Dealing with this last at runtime is also another crucial need that has been ignored in their proposals. This paper aims to propose a generic dynamic adaptation process as a phase in a model-driven development life-cycle for context-aware services using the MAPE-K control loop to meet the runtime adaptation. This process is validated by implementing an illustrative application on FraSCAti platform. The main benefit of the proposed process is to sustain the self-reconfiguration of such services at model and code levels by enabling successive dynamic adaptations depending on the changing context.

  20. Sharp asymptotics for stochastic dynamics with parallel updating rule with self-interaction

    NARCIS (Netherlands)

    Bovier, A.; Nardi, F.R.; Spitoni, C.

    2011-01-01

    In this paper we study metastability for a stochastic dynamics with a parallel updating rule in particular for a probabilistic cellular automata. The problem is addressed in the Freidlin Wentzel regime, i.e., finite volume, small magnetic field, and in the limit when temperature tends to zero. We

  1. Due date assignment procedures with dynamically updated coefficients for multi-level assembly job shops

    NARCIS (Netherlands)

    Adam, N.R.; Bertrand, J.W.M.; Morehead, D.C.; Surkis, J.

    1993-01-01

    This paper presents a study of due date assignment procedures in job shop environments where multi-level assembly jobs are processed and due dates are internally assigned. Most of the reported studies in the literature have focused on string type jobs. We propose a dynamic update approach (which

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

    International Nuclear Information System (INIS)

    Ma Huanfei; Lin Wei

    2009-01-01

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

  3. The Dynamics of Memory: Context-Dependent Updating

    Science.gov (United States)

    Hupbach, Almut; Hardt, Oliver; Gomez, Rebecca; Nadel, Lynn

    2008-01-01

    Understanding the dynamics of memory change is one of the current challenges facing cognitive neuroscience. Recent animal work on memory reconsolidation shows that memories can be altered long after acquisition. When reactivated, memories can be modified and require a restabilization (reconsolidation) process. We recently extended this finding to…

  4. Voter dynamics on an adaptive network with finite average connectivity

    Science.gov (United States)

    Mukhopadhyay, Abhishek; Schmittmann, Beate

    2009-03-01

    We study a simple model for voter dynamics in a two-party system. The opinion formation process is implemented in a random network of agents in which interactions are not restricted by geographical distance. In addition, we incorporate the rapidly changing nature of the interpersonal relations in the model. At each time step, agents can update their relationships, so that there is no history dependence in the model. This update is determined by their own opinion, and by their preference to make connections with individuals sharing the same opinion and with opponents. Using simulations and analytic arguments, we determine the final steady states and the relaxation into these states for different system sizes. In contrast to earlier studies, the average connectivity (``degree'') of each agent is constant here, independent of the system size. This has significant consequences for the long-time behavior of the model.

  5. Adaptive dynamic capacity borrowing in road-covering mobile networks

    NARCIS (Netherlands)

    Ule, A.; Boucherie, Richardus J.; Li, W.; Pan, Y.

    2006-01-01

    This paper introduces adaptive dynamic capacity borrowing strategies for wireless networks covering a road. In a F/TDMA-based model, road traffic prediction models are used to characterise the movement of hot spots, such as traffic jams, and subsequently to predict the teletraffic load offered to

  6. Dynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture

    Energy Technology Data Exchange (ETDEWEB)

    Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT)

    2015-01-01

    Dynamic Adaptive Neural Network Array (DANNA) is a neuromorphic hardware implementation. It differs from most other neuromorphic projects in that it allows for programmability of structure, and it is trained or designed using evolutionary optimization. This paper describes the DANNA structure, how DANNA is trained using evolutionary optimization, and an application of DANNA to a very simple classification task.

  7. Sex speeds adaptation by altering the dynamics of molecular evolution.

    Science.gov (United States)

    McDonald, Michael J; Rice, Daniel P; Desai, Michael M

    2016-03-10

    Sex and recombination are pervasive throughout nature despite their substantial costs. Understanding the evolutionary forces that maintain these phenomena is a central challenge in biology. One longstanding hypothesis argues that sex is beneficial because recombination speeds adaptation. Theory has proposed several distinct population genetic mechanisms that could underlie this advantage. For example, sex can promote the fixation of beneficial mutations either by alleviating interference competition (the Fisher-Muller effect) or by separating them from deleterious load (the ruby in the rubbish effect). Previous experiments confirm that sex can increase the rate of adaptation, but these studies did not observe the evolutionary dynamics that drive this effect at the genomic level. Here we present the first, to our knowledge, comparison between the sequence-level dynamics of adaptation in experimental sexual and asexual Saccharomyces cerevisiae populations, which allows us to identify the specific mechanisms by which sex speeds adaptation. We find that sex alters the molecular signatures of evolution by changing the spectrum of mutations that fix, and confirm theoretical predictions that it does so by alleviating clonal interference. We also show that substantially deleterious mutations hitchhike to fixation in adapting asexual populations. In contrast, recombination prevents such mutations from fixing. Our results demonstrate that sex both speeds adaptation and alters its molecular signature by allowing natural selection to more efficiently sort beneficial from deleterious mutations.

  8. 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.

  9. Jovian atmospheric dynamics: an update after Galileo and Cassini

    International Nuclear Information System (INIS)

    Vasavada, Ashwin R; Showman, Adam P

    2005-01-01

    The Galileo and Cassini spacecrafts have greatly enhanced the observational record of Jupiter's tropospheric dynamics, particularly through returning high spatial resolution, multi-spectral and global imaging data with episodic coverage over periods of months to years. These data, along with those from Earth-based telescopes, have revealed the stability of Jupiter's zonal jets, captured the evolution of vortices and equatorial waves, and mapped the distributions of lightning and moist convection. Because no observations of Jupiter's interior exist, a forward modelling approach has been used to relate observations at cloud level to models of shallow or deep jet structure, shallow or deep jet forcing and energy transfer between turbulence, vortices and jets. A range of observed phenomena can be reproduced in shallow models, though the Galileo probe winds and jet stability arguments hint at the presence of deep jets. Many deep models, however, fail to reproduce Jupiter-like non-zonal features (e.g. vortices). Jupiter's dynamics likely include both deep and shallow processes, requiring an integrated approach to future modelling-an important goal for the post-Galileo and Cassini era

  10. Gating based on internal/external signals with dynamic correlation updates

    International Nuclear Information System (INIS)

    Wu Huanmei; Zhao Qingya; Berbeco, Ross I; Nishioka, Seiko; Shirato, Hiroki; Jiang, Steve B

    2008-01-01

    Precise localization of mobile tumor positions in real time is critical to the success of gated radiotherapy. Tumor positions are usually derived from either internal or external surrogates. Fluoroscopic gating based on internal surrogates, such as implanted fiducial markers, is accurate however requiring a large amount of imaging dose. Gating based on external surrogates, such as patient abdominal surface motion, is non-invasive however less accurate due to the uncertainty in the correlation between tumor location and external surrogates. To address these complications, we propose to investigate an approach based on hybrid gating with dynamic internal/external correlation updates. In this approach, the external signal is acquired at high frequency (such as 30 Hz) while the internal signal is sparsely acquired (such as 0.5 Hz or less). The internal signal is used to validate and update the internal/external correlation during treatment. Tumor positions are derived from the external signal based on the newly updated correlation. Two dynamic correlation updating algorithms are introduced. One is based on the motion amplitude and the other is based on the motion phase. Nine patients with synchronized internal/external motion signals are simulated retrospectively to evaluate the effectiveness of hybrid gating. The influences of different clinical conditions on hybrid gating, such as the size of gating windows, the optimal timing for internal signal acquisition and the acquisition frequency are investigated. The results demonstrate that dynamically updating the internal/external correlation in or around the gating window will reduce false positive with relatively diminished treatment efficiency. This improvement will benefit patients with mobile tumors, especially greater for early stage lung cancers, for which the tumors are less attached or freely floating in the lung.

  11. Gating based on internal/external signals with dynamic correlation updates

    Energy Technology Data Exchange (ETDEWEB)

    Wu Huanmei [Purdue School of Engineering and Technology, Indiana University School of Informatics, IUPUI, Indianapolis, IN (United States); Zhao Qingya [School of Health Sciences, Purdue University, West Lafayette, IN (United States); Berbeco, Ross I [Department of Radiation Oncology, Dana-Farber/Brigham and Womens Cancer Center and Harvard Medical School, Boston, MA (United States); Nishioka, Seiko [NTT East-Japan Sapporo Hospital, Sapporo (Japan); Shirato, Hiroki [Hokkaido University Graduate School of Medicine, Sapporo (Japan); Jiang, Steve B [Department of Radiation Oncology, School of Medicine, University of California, San Diego, CA (United States)], E-mail: hw9@iupui.edu, E-mail: sbjiang@ucsd.edu

    2008-12-21

    Precise localization of mobile tumor positions in real time is critical to the success of gated radiotherapy. Tumor positions are usually derived from either internal or external surrogates. Fluoroscopic gating based on internal surrogates, such as implanted fiducial markers, is accurate however requiring a large amount of imaging dose. Gating based on external surrogates, such as patient abdominal surface motion, is non-invasive however less accurate due to the uncertainty in the correlation between tumor location and external surrogates. To address these complications, we propose to investigate an approach based on hybrid gating with dynamic internal/external correlation updates. In this approach, the external signal is acquired at high frequency (such as 30 Hz) while the internal signal is sparsely acquired (such as 0.5 Hz or less). The internal signal is used to validate and update the internal/external correlation during treatment. Tumor positions are derived from the external signal based on the newly updated correlation. Two dynamic correlation updating algorithms are introduced. One is based on the motion amplitude and the other is based on the motion phase. Nine patients with synchronized internal/external motion signals are simulated retrospectively to evaluate the effectiveness of hybrid gating. The influences of different clinical conditions on hybrid gating, such as the size of gating windows, the optimal timing for internal signal acquisition and the acquisition frequency are investigated. The results demonstrate that dynamically updating the internal/external correlation in or around the gating window will reduce false positive with relatively diminished treatment efficiency. This improvement will benefit patients with mobile tumors, especially greater for early stage lung cancers, for which the tumors are less attached or freely floating in the lung.

  12. Adaptive Dynamic Process Scheduling on Distributed Memory Parallel Computers

    Directory of Open Access Journals (Sweden)

    Wei Shu

    1994-01-01

    Full Text Available One of the challenges in programming distributed memory parallel machines is deciding how to allocate work to processors. This problem is particularly important for computations with unpredictable dynamic behaviors or irregular structures. We present a scheme for dynamic scheduling of medium-grained processes that is useful in this context. The adaptive contracting within neighborhood (ACWN is a dynamic, distributed, load-dependent, and scalable scheme. It deals with dynamic and unpredictable creation of processes and adapts to different systems. The scheme is described and contrasted with two other schemes that have been proposed in this context, namely the randomized allocation and the gradient model. The performance of the three schemes on an Intel iPSC/2 hypercube is presented and analyzed. The experimental results show that even though the ACWN algorithm incurs somewhat larger overhead than the randomized allocation, it achieves better performance in most cases due to its adaptiveness. Its feature of quickly spreading the work helps it outperform the gradient model in performance and scalability.

  13. Vehicle Sliding Mode Control with Adaptive Upper Bounds: Static versus Dynamic Allocation to Saturated Tire Forces

    Directory of Open Access Journals (Sweden)

    Ali Tavasoli

    2012-01-01

    Full Text Available Nonlinear vehicle control allocation is achieved through distributing the task of vehicle control among individual tire forces, which are constrained to nonlinear saturation conditions. A high-level sliding mode control with adaptive upper bounds is considered to assess the body yaw moment and lateral force for the vehicle motion. The proposed controller only requires the online adaptation of control gains without acquiring the knowledge of upper bounds on system uncertainties. Static and dynamic control allocation approaches have been formulated to distribute high-level control objectives among the system inputs. For static control allocation, the interior-point method is applied to solve the formulated nonlinear optimization problem. Based on the dynamic control allocation method, a dynamic update law is derived to allocate vehicle control to tire forces. The allocated tire forces are fed into a low-level control module, where the applied torque and active steering angle at each wheel are determined through a slip-ratio controller and an inverse tire model. Computer simulations are used to prove the significant effects of the proposed control allocation methods on improving the stability and handling performance. The advantages and limitations of each method have been discussed, and conclusions have been derived.

  14. Dynamic Minimum Spanning Forest with Subpolynomial Worst-case Update Time

    DEFF Research Database (Denmark)

    Nanongkai, Danupon; Saranurak, Thatchaphol; Wulff-Nilsen, Christian

    2017-01-01

    Abstract: We present a Las Vegas algorithm for dynamically maintaining a minimum spanning forest of an nnode graph undergoing edge insertions and deletions. Our algorithm guarantees an O(no(1)) worst-case update time with high probability. This significantly improves the two recent Las Vegas algo...... the previous approach in [2], [3] which is based on Frederickson's 2-dimensional topology tree [6] and illustrates a new application to this old technique....

  15. Spontaneous formation of dynamical groups in an adaptive networked system

    International Nuclear Information System (INIS)

    Li Menghui; Guan Shuguang; Lai, C-H

    2010-01-01

    In this work, we investigate a model of an adaptive networked dynamical system, where the coupling strengths among phase oscillators coevolve with the phase states. It is shown that in this model the oscillators can spontaneously differentiate into two dynamical groups after a long time evolution. Within each group, the oscillators have similar phases, while oscillators in different groups have approximately opposite phases. The network gradually converts from the initial random structure with a uniform distribution of connection strengths into a modular structure that is characterized by strong intra-connections and weak inter-connections. Furthermore, the connection strengths follow a power-law distribution, which is a natural consequence of the coevolution of the network and the dynamics. Interestingly, it is found that if the inter-connections are weaker than a certain threshold, the two dynamical groups will almost decouple and evolve independently. These results are helpful in further understanding the empirical observations in many social and biological networks.

  16. Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

    Science.gov (United States)

    Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

    2018-04-24

    Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

  17. Adaptive dynamic programming with applications in optimal control

    CERN Document Server

    Liu, Derong; Wang, Ding; Yang, Xiong; Li, Hongliang

    2017-01-01

    This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP app...

  18. Market mood, adaptive beliefs and asset price dynamics

    International Nuclear Information System (INIS)

    Dieci, Roberto; Foroni, Ilaria; Gardini, Laura; He Xuezhong

    2006-01-01

    Empirical evidence has suggested that, facing different trading strategies and complicated decision, the proportions of agents relying on particular strategies may stay at constant level or vary over time. This paper presents a simple 'dynamic market fraction' model of two groups of traders, fundamentalists and trend followers, under a market maker scenario. Market mood and evolutionary adaption are characterized by fixed and adaptive switching fraction among two groups, respectively. Using local stability and bifurcation analysis, as well as numerical simulation, the role played by the key parameters in the market behaviour is examined. Particular attention is paid to the impact of the market fraction, determined by the fixed proportions of confident fundamentalists and trend followers, and by the proportion of adaptively rational agents, who adopt different strategies over time depending on realized profits

  19. Updating of a dynamic finite element model from the Hualien scale model reactor building

    International Nuclear Information System (INIS)

    Billet, L.; Moine, P.; Lebailly, P.

    1996-08-01

    The forces occurring at the soil-structure interface of a building have generally a large influence on the way the building reacts to an earthquake. One can be tempted to characterise these forces more accurately bu updating a model from the structure. However, this procedure requires an updating method suitable for dissipative models, since significant damping can be observed at the soil-structure interface of buildings. Such a method is presented here. It is based on the minimization of a mechanical energy built from the difference between Eigen data calculated bu the model and Eigen data issued from experimental tests on the real structure. An experimental validation of this method is then proposed on a model from the HUALIEN scale-model reactor building. This scale-model, built on the HUALIEN site of TAIWAN, is devoted to the study of soil-structure interaction. The updating concerned the soil impedances, modelled by a layer of springs and viscous dampers attached to the building foundation. A good agreement was found between the Eigen modes and dynamic responses calculated bu the updated model and the corresponding experimental data. (authors). 12 refs., 3 figs., 4 tabs

  20. Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Admissibility and Termination Analysis.

    Science.gov (United States)

    Wei, Qinglai; Liu, Derong; Lin, Qiao

    In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.

  1. Generalization in adaptation to stable and unstable dynamics.

    Directory of Open Access Journals (Sweden)

    Abdelhamid Kadiallah

    Full Text Available Humans skillfully manipulate objects and tools despite the inherent instability. In order to succeed at these tasks, the sensorimotor control system must build an internal representation of both the force and mechanical impedance. As it is not practical to either learn or store motor commands for every possible future action, the sensorimotor control system generalizes a control strategy for a range of movements based on learning performed over a set of movements. Here, we introduce a computational model for this learning and generalization, which specifies how to learn feedforward muscle activity in a function of the state space. Specifically, by incorporating co-activation as a function of error into the feedback command, we are able to derive an algorithm from a gradient descent minimization of motion error and effort, subject to maintaining a stability margin. This algorithm can be used to learn to coordinate any of a variety of motor primitives such as force fields, muscle synergies, physical models or artificial neural networks. This model for human learning and generalization is able to adapt to both stable and unstable dynamics, and provides a controller for generating efficient adaptive motor behavior in robots. Simulation results exhibit predictions consistent with all experiments on learning of novel dynamics requiring adaptation of force and impedance, and enable us to re-examine some of the previous interpretations of experiments on generalization.

  2. Adaptive optics scanning laser ophthalmoscopy in fundus imaging, a review and update

    OpenAIRE

    Zhang, Bing; Li, Ni; Kang, Jie; He, Yi; Chen, Xiao-Ming

    2017-01-01

    Adaptive optics scanning laser ophthalmoscopy (AO-SLO) has been a promising technique in funds imaging with growing popularity. This review firstly gives a brief history of adaptive optics (AO) and AO-SLO. Then it compares AO-SLO with conventional imaging methods (fundus fluorescein angiography, fundus autofluorescence, indocyanine green angiography and optical coherence tomography) and other AO techniques (adaptive optics flood-illumination ophthalmoscopy and adaptive optics optical coherenc...

  3. A Multi-Pathfinder for Developing Adaptive Robust Policies in System Dynamics

    NARCIS (Netherlands)

    Hamarat, C.; Pruyt, E.; Loonen, E.T.

    2013-01-01

    Adaptivity is essential for dynamically complex and uncertain systems. Adaptive policymaking is an approach to design policies that can be adapted over time to how the future unfolds. It is crucial for adaptive policymaking to specify under what conditions and how to adapt the policy. The

  4. Constitutional dynamic chemistry: bridge from supramolecular chemistry to adaptive chemistry.

    Science.gov (United States)

    Lehn, Jean-Marie

    2012-01-01

    Supramolecular chemistry aims at implementing highly complex chemical systems from molecular components held together by non-covalent intermolecular forces and effecting molecular recognition, catalysis and transport processes. A further step consists in the investigation of chemical systems undergoing self-organization, i.e. systems capable of spontaneously generating well-defined functional supramolecular architectures by self-assembly from their components, thus behaving as programmed chemical systems. Supramolecular chemistry is intrinsically a dynamic chemistry in view of the lability of the interactions connecting the molecular components of a supramolecular entity and the resulting ability of supramolecular species to exchange their constituents. The same holds for molecular chemistry when the molecular entity contains covalent bonds that may form and break reversibility, so as to allow a continuous change in constitution by reorganization and exchange of building blocks. These features define a Constitutional Dynamic Chemistry (CDC) on both the molecular and supramolecular levels.CDC introduces a paradigm shift with respect to constitutionally static chemistry. The latter relies on design for the generation of a target entity, whereas CDC takes advantage of dynamic diversity to allow variation and selection. The implementation of selection in chemistry introduces a fundamental change in outlook. Whereas self-organization by design strives to achieve full control over the output molecular or supramolecular entity by explicit programming, self-organization with selection operates on dynamic constitutional diversity in response to either internal or external factors to achieve adaptation.The merging of the features: -information and programmability, -dynamics and reversibility, -constitution and structural diversity, points to the emergence of adaptive and evolutive chemistry, towards a chemistry of complex matter.

  5. Use of dynamic grid adaption in the ASWR-method

    International Nuclear Information System (INIS)

    Graf, U.; Romstedt, P.; Werner, W.

    1985-01-01

    A dynamic grid adaption method has been developed for use with the ASWR-method. The method automatically adapts the number and position of the spatial meshpoints as the solution of hyperbolic or parabolic vector partial differential equations progresses in time. The mesh selection algorithm is based on the minimization of the L 2 -norm of the spatial discretization error. The method permits accurate calculation of the evolution of inhomogenities like wave fronts, shock layers and other sharp transitions, while generally using a coarse computational grid. The number of required mesh points is significantly reduced, relative to a fixed Eulerian grid. Since the mesh selection algorithm is computationally inexpensive, a corresponding reduction of computing time results

  6. Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

    Science.gov (United States)

    Jorgensen, Charles C.

    1997-01-01

    A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.

  7. Adaptive learning by extremal dynamics and negative feedback

    International Nuclear Information System (INIS)

    Bak, Per; Chialvo, Dante R.

    2001-01-01

    We describe a mechanism for biological learning and adaptation based on two simple principles: (i) Neuronal activity propagates only through the network's strongest synaptic connections (extremal dynamics), and (ii) the strengths of active synapses are reduced if mistakes are made, otherwise no changes occur (negative feedback). The balancing of those two tendencies typically shapes a synaptic landscape with configurations which are barely stable, and therefore highly flexible. This allows for swift adaptation to new situations. Recollection of past successes is achieved by punishing synapses which have once participated in activity associated with successful outputs much less than neurons that have never been successful. Despite its simplicity, the model can readily learn to solve complicated nonlinear tasks, even in the presence of noise. In particular, the learning time for the benchmark parity problem scales algebraically with the problem size N, with an exponent k∼1.4

  8. Elucidating Microbial Adaptation Dynamics via Autonomous Exposure and Sampling

    Science.gov (United States)

    Grace, Joseph M.; Verseux, Cyprien; Gentry, Diana; Moffet, Amy; Thayabaran, Ramanen; Wong, Nathan; Rothschild, Lynn

    2013-01-01

    The adaptation of micro-organisms to their environments is a complex process of interaction between the pressures of the environment and of competition. Reducing this multifactorial process to environmental exposure in the laboratory is a common tool for elucidating individual mechanisms of evolution, such as mutation rates. Although such studies inform fundamental questions about the way adaptation and even speciation occur, they are often limited by labor-intensive manual techniques. Current methods for controlled study of microbial adaptation limit the length of time, the depth of collected data, and the breadth of applied environmental conditions. Small idiosyncrasies in manual techniques can have large effects on outcomes; for example, there are significant variations in induced radiation resistances following similar repeated exposure protocols. We describe here a project under development to allow rapid cycling of multiple types of microbial environmental exposure. The system allows continuous autonomous monitoring and data collection of both single species and sampled communities, independently and concurrently providing multiple types of controlled environmental pressure (temperature, radiation, chemical presence or absence, and so on) to a microbial community in dynamic response to the ecosystem's current status. When combined with DNA sequencing and extraction, such a controlled environment can cast light on microbial functional development, population dynamics, inter- and intra-species competition, and microbe-environment interaction. The project's goal is to allow rapid, repeatable iteration of studies of both natural and artificial microbial adaptation. As an example, the same system can be used both to increase the pH of a wet soil aliquot over time while periodically sampling it for genetic activity analysis, or to repeatedly expose a culture of bacteria to the presence of a toxic metal, automatically adjusting the level of toxicity based on the

  9. Dynamic and adaptive data-management in ATLAS

    CERN Document Server

    Lassnig, M; Branco, M; Molfetas, A

    2010-01-01

    Distributed data-management on the grid is subject to huge uncertainties yet static policies govern its usage. Due to the unpredictability of user behaviour, the high-latency and the heterogeneous nature of the environment, distributed data-management on the grid is challenging. In this paper we present the first steps towards a future dynamic data-management system that adapts to the changing conditions and environment. Such a system would eliminate the number of manual interventions and remove unnecessary software layers, thereby providing a higher quality of service to the collaboration.

  10. Adaptive synchronization between two different order and topology dynamical systems

    International Nuclear Information System (INIS)

    Bowong, S.; Moukam Kakmeni, F.M.; Yamapi, R.

    2006-07-01

    This contribution studies adaptive synchronization between two dynamical systems of different order whose topological structure is also different. By order we mean the number of first order differential equations. The problem is closely related to the synchronization of strictly different systems. The master system is given by a sixth order equation with chaotic behavior whereas the slave system is a fourth-order nonautonomous with rational nonlinear terms. Based on the Lyapunov stability theory, sufficient conditions for the synchronization have been analyzed theoretically and numerically. (author)

  11. Dynamic Software Updating with Gosh! Current Status and the Road Ahead

    DEFF Research Database (Denmark)

    Gregersen, Allan Raundahl; Rasmussen, Michael; Jørgensen, Bo Nørregaard

    2013-01-01

    Any non-trivial software system has to be upgraded regularly to incorporate bug fixes and security patches or simply to keep up with the inevitable evolution in end-user requirements. Software upgrading is challenging, especially when it comes to online upgrading of running systems. In this paper......, we present the current status of Gosh!, a dynamic-software-updating system for Java, which provides comprehensive support for changing class definitions of live objects, including adding, removing and moving fields, methods, classes and interfaces anywhere in the inheritance hierarchy. Prior...

  12. Hydrodynamics in adaptive resolution particle simulations: Multiparticle collision dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Alekseeva, Uliana, E-mail: Alekseeva@itc.rwth-aachen.de [Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation (IAS), Forschungszentrum Jülich, D-52425 Jülich (Germany); German Research School for Simulation Sciences (GRS), Forschungszentrum Jülich, D-52425 Jülich (Germany); Winkler, Roland G., E-mail: r.winkler@fz-juelich.de [Theoretical Soft Matter and Biophysics, Institute for Advanced Simulation (IAS), Forschungszentrum Jülich, D-52425 Jülich (Germany); Sutmann, Godehard, E-mail: g.sutmann@fz-juelich.de [Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation (IAS), Forschungszentrum Jülich, D-52425 Jülich (Germany); ICAMS, Ruhr-University Bochum, D-44801 Bochum (Germany)

    2016-06-01

    A new adaptive resolution technique for particle-based multi-level simulations of fluids is presented. In the approach, the representation of fluid and solvent particles is changed on the fly between an atomistic and a coarse-grained description. The present approach is based on a hybrid coupling of the multiparticle collision dynamics (MPC) method and molecular dynamics (MD), thereby coupling stochastic and deterministic particle-based methods. Hydrodynamics is examined by calculating velocity and current correlation functions for various mixed and coupled systems. We demonstrate that hydrodynamic properties of the mixed fluid are conserved by a suitable coupling of the two particle methods, and that the simulation results agree well with theoretical expectations.

  13. Dynamics of epidemic diseases on a growing adaptive network.

    Science.gov (United States)

    Demirel, Güven; Barter, Edmund; Gross, Thilo

    2017-02-10

    The study of epidemics on static networks has revealed important effects on disease prevalence of network topological features such as the variance of the degree distribution, i.e. the distribution of the number of neighbors of nodes, and the maximum degree. Here, we analyze an adaptive network where the degree distribution is not independent of epidemics but is shaped through disease-induced dynamics and mortality in a complex interplay. We study the dynamics of a network that grows according to a preferential attachment rule, while nodes are simultaneously removed from the network due to disease-induced mortality. We investigate the prevalence of the disease using individual-based simulations and a heterogeneous node approximation. Our results suggest that in this system in the thermodynamic limit no epidemic thresholds exist, while the interplay between network growth and epidemic spreading leads to exponential networks for any finite rate of infectiousness when the disease persists.

  14. When do mixotrophs specialize? Adaptive dynamics theory applied to a dynamic energy budget model.

    NARCIS (Netherlands)

    Troost, T.A.; Kooi, B.W.; Kooijman, S.A.L.M.

    2005-01-01

    In evolutionary history, several events have occurred at which mixotrophs specialized into pure autotrophs and heterotrophs. We studied the conditions under which such events take place, using the Dynamic Energy Budget (DEB) theory for physiological rules of the organisms' metabolism and Adaptive

  15. Selective host molecules obtained by dynamic adaptive chemistry.

    Science.gov (United States)

    Matache, Mihaela; Bogdan, Elena; Hădade, Niculina D

    2014-02-17

    Up till 20 years ago, in order to endow molecules with function there were two mainstream lines of thought. One was to rationally design the positioning of chemical functionalities within candidate molecules, followed by an iterative synthesis-optimization process. The second was the use of a "brutal force" approach of combinatorial chemistry coupled with advanced screening for function. Although both methods provided important results, "rational design" often resulted in time-consuming efforts of modeling and synthesis only to find that the candidate molecule was not performing the designed job. "Combinatorial chemistry" suffered from a fundamental limitation related to the focusing of the libraries employed, often using lead compounds that limit its scope. Dynamic constitutional chemistry has developed as a combination of the two approaches above. Through the rational use of reversible chemical bonds together with a large plethora of precursor libraries, one is now able to build functional structures, ranging from quite simple molecules up to large polymeric structures. Thus, by introduction of the dynamic component within the molecular recognition processes, a new perspective of deciphering the world of the molecular events has aroused together with a new field of chemistry. Since its birth dynamic constitutional chemistry has continuously gained attention, in particular due to its ability to easily create from scratch outstanding molecular structures as well as the addition of adaptive features. The fundamental concepts defining the dynamic constitutional chemistry have been continuously extended to currently place it at the intersection between the supramolecular chemistry and newly defined adaptive chemistry, a pivotal feature towards evolutive chemistry. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. A dynamical system that describes vein graft adaptation and failure.

    Science.gov (United States)

    Garbey, Marc; Berceli, Scott A

    2013-11-07

    Adaptation of vein bypass grafts to the mechanical stresses imposed by the arterial circulation is thought to be the primary determinant for lesion development, yet an understanding of how the various forces dictate local wall remodeling is lacking. We develop a dynamical system that summarizes the complex interplay between the mechanical environment and cell/matrix kinetics, ultimately dictating changes in the vein graft architecture. Based on a systematic mapping of the parameter space, three general remodeling response patterns are observed: (1) shear stabilized intimal thickening, (2) tension induced wall thinning and lumen expansion, and (3) tension stabilized wall thickening. Notable is our observation that the integration of multiple feedback mechanisms leads to a variety of non-linear responses that would be unanticipated by an analysis of each system component independently. This dynamic analysis supports the clinical observation that the majority of vein grafts proceed along an adaptive trajectory, where grafts dilate and mildly thicken in response to the increased tension and shear, but a small portion of the grafts demonstrate a maladaptive phenotype, where progressive inward remodeling and accentuated wall thickening lead to graft failure. © 2013 The Authors. Published by Elsevier Ltd. All rights reserved.

  17. Adaptive sampling strategies with high-throughput molecular dynamics

    Science.gov (United States)

    Clementi, Cecilia

    Despite recent significant hardware and software developments, the complete thermodynamic and kinetic characterization of large macromolecular complexes by molecular simulations still presents significant challenges. The high dimensionality of these systems and the complexity of the associated potential energy surfaces (creating multiple metastable regions connected by high free energy barriers) does not usually allow to adequately sample the relevant regions of their configurational space by means of a single, long Molecular Dynamics (MD) trajectory. Several different approaches have been proposed to tackle this sampling problem. We focus on the development of ensemble simulation strategies, where data from a large number of weakly coupled simulations are integrated to explore the configurational landscape of a complex system more efficiently. Ensemble methods are of increasing interest as the hardware roadmap is now mostly based on increasing core counts, rather than clock speeds. The main challenge in the development of an ensemble approach for efficient sampling is in the design of strategies to adaptively distribute the trajectories over the relevant regions of the systems' configurational space, without using any a priori information on the system global properties. We will discuss the definition of smart adaptive sampling approaches that can redirect computational resources towards unexplored yet relevant regions. Our approaches are based on new developments in dimensionality reduction for high dimensional dynamical systems, and optimal redistribution of resources. NSF CHE-1152344, NSF CHE-1265929, Welch Foundation C-1570.

  18. Optimal spectral tracking--adapting to dynamic regime change.

    Science.gov (United States)

    Brittain, John-Stuart; Halliday, David M

    2011-01-30

    Real world data do not always obey the statistical restraints imposed upon them by sophisticated analysis techniques. In spectral analysis for instance, an ergodic process--the interchangeability of temporal for spatial averaging--is assumed for a repeat-trial design. Many evolutionary scenarios, such as learning and motor consolidation, do not conform to such linear behaviour and should be approached from a more flexible perspective. To this end we previously introduced the method of optimal spectral tracking (OST) in the study of trial-varying parameters. In this extension to our work we modify the OST routines to provide an adaptive implementation capable of reacting to dynamic transitions in the underlying system state. In so doing, we generalise our approach to characterise both slow-varying and rapid fluctuations in time-series, simultaneously providing a metric of system stability. The approach is first applied to a surrogate dataset and compared to both our original non-adaptive solution and spectrogram approaches. The adaptive OST is seen to display fast convergence and desirable statistical properties. All three approaches are then applied to a neurophysiological recording obtained during a study on anaesthetic monitoring. Local field potentials acquired from the posterior hypothalamic region of a deep brain stimulation patient undergoing anaesthesia were analysed. The characterisation of features such as response delay, time-to-peak and modulation brevity are considered. Copyright © 2010 Elsevier B.V. All rights reserved.

  19. Dynamics of random Boolean networks under fully asynchronous stochastic update based on linear representation.

    Directory of Open Access Journals (Sweden)

    Chao Luo

    Full Text Available A novel algebraic approach is proposed to study dynamics of asynchronous random Boolean networks where a random number of nodes can be updated at each time step (ARBNs. In this article, the logical equations of ARBNs are converted into the discrete-time linear representation and dynamical behaviors of systems are investigated. We provide a general formula of network transition matrices of ARBNs as well as a necessary and sufficient algebraic criterion to determine whether a group of given states compose an attractor of length[Formula: see text] in ARBNs. Consequently, algorithms are achieved to find all of the attractors and basins in ARBNs. Examples are showed to demonstrate the feasibility of the proposed scheme.

  20. Flatness-based adaptive fuzzy control of chaotic finance dynamics

    Science.gov (United States)

    Rigatos, G.; Siano, P.; Loia, V.; Tommasetti, A.; Troisi, O.

    2017-11-01

    A flatness-based adaptive fuzzy control is applied to the problem of stabilization of the dynamics of a chaotic finance system, describing interaction between the interest rate, the investment demand and the price exponent. By proving that the system is differentially flat and by applying differential flatness diffeomorphisms, its transformation to the linear canonical (Brunovsky) is performed. For the latter description of the system, the design of a stabilizing state feedback controller becomes possible. A first problem in the design of such a controller is that the dynamic model of the finance system is unknown and thus it has to be identified with the use neurofuzzy approximators. The estimated dynamics provided by the approximators is used in the computation of the control input, thus establishing an indirect adaptive control scheme. The learning rate of the approximators is chosen from the requirement the system's Lyapunov function to have always a negative first-order derivative. Another problem that has to be dealt with is that the control loop is implemented only with the use of output feedback. To estimate the non-measurable state vector elements of the finance system, a state observer is implemented in the control loop. The computation of the feedback control signal requires the solution of two algebraic Riccati equations at each iteration of the control algorithm. Lyapunov stability analysis demonstrates first that an H-infinity tracking performance criterion is satisfied. This signifies elevated robustness against modelling errors and external perturbations. Moreover, the global asymptotic stability is proven for the control loop.

  1. Strategic tradeoffs in competitor dynamics on adaptive networks.

    Science.gov (United States)

    Hébert-Dufresne, Laurent; Allard, Antoine; Noël, Pierre-André; Young, Jean-Gabriel; Libby, Eric

    2017-08-08

    Recent empirical work highlights the heterogeneity of social competitions such as political campaigns: proponents of some ideologies seek debate and conversation, others create echo chambers. While symmetric and static network structure is typically used as a substrate to study such competitor dynamics, network structure can instead be interpreted as a signature of the competitor strategies, yielding competition dynamics on adaptive networks. Here we demonstrate that tradeoffs between aggressiveness and defensiveness (i.e., targeting adversaries vs. targeting like-minded individuals) creates paradoxical behaviour such as non-transitive dynamics. And while there is an optimal strategy in a two competitor system, three competitor systems have no such solution; the introduction of extreme strategies can easily affect the outcome of a competition, even if the extreme strategies have no chance of winning. Not only are these results reminiscent of classic paradoxical results from evolutionary game theory, but the structure of social networks created by our model can be mapped to particular forms of payoff matrices. Consequently, social structure can act as a measurable metric for social games which in turn allows us to provide a game theoretical perspective on online political debates.

  2. Nonlinear attractor dynamics in the fundamental and extended prism adaptation paradigm

    International Nuclear Information System (INIS)

    Frank, T.D.; Blau, Julia J.C.; Turvey, M.T.

    2009-01-01

    Adaptation and re-adaptation processes are studied in terms of dynamic attractors that evolve and devolve. In doing so, a theoretical account is given for the fundamental observation that adaptation and re-adaptation processes do not exhibit one-trial learning. Moreover, the emergence of the latent aftereffect in the extended prism paradigm is addressed

  3. Diagonal recurrent neural network based adaptive control of nonlinear dynamical systems using lyapunov stability criterion.

    Science.gov (United States)

    Kumar, Rajesh; Srivastava, Smriti; Gupta, J R P

    2017-03-01

    In this paper adaptive control of nonlinear dynamical systems using diagonal recurrent neural network (DRNN) is proposed. The structure of DRNN is a modification of fully connected recurrent neural network (FCRNN). Presence of self-recurrent neurons in the hidden layer of DRNN gives it an ability to capture the dynamic behaviour of the nonlinear plant under consideration (to be controlled). To ensure stability, update rules are developed using lyapunov stability criterion. These rules are then used for adjusting the various parameters of DRNN. The responses of plants obtained with DRNN are compared with those obtained when multi-layer feed forward neural network (MLFFNN) is used as a controller. Also, in example 4, FCRNN is also investigated and compared with DRNN and MLFFNN. Robustness of the proposed control scheme is also tested against parameter variations and disturbance signals. Four simulation examples including one-link robotic manipulator and inverted pendulum are considered on which the proposed controller is applied. The results so obtained show the superiority of DRNN over MLFFNN as a controller. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  4. An approximately Bayesian delta-rule model explains the dynamics of belief updating in a changing environment.

    Science.gov (United States)

    Nassar, Matthew R; Wilson, Robert C; Heasly, Benjamin; Gold, Joshua I

    2010-09-15

    Maintaining appropriate beliefs about variables needed for effective decision making can be difficult in a dynamic environment. One key issue is the amount of influence that unexpected outcomes should have on existing beliefs. In general, outcomes that are unexpected because of a fundamental change in the environment should carry more influence than outcomes that are unexpected because of persistent environmental stochasticity. Here we use a novel task to characterize how well human subjects follow these principles under a range of conditions. We show that the influence of an outcome depends on both the error made in predicting that outcome and the number of similar outcomes experienced previously. We also show that the exact nature of these tendencies varies considerably across subjects. Finally, we show that these patterns of behavior are consistent with a computationally simple reduction of an ideal-observer model. The model adjusts the influence of newly experienced outcomes according to ongoing estimates of uncertainty and the probability of a fundamental change in the process by which outcomes are generated. A prior that quantifies the expected frequency of such environmental changes accounts for individual variability, including a positive relationship between subjective certainty and the degree to which new information influences existing beliefs. The results suggest that the brain adaptively regulates the influence of decision outcomes on existing beliefs using straightforward updating rules that take into account both recent outcomes and prior expectations about higher-order environmental structure.

  5. Adaptive contact networks change effective disease infectiousness and dynamics.

    Science.gov (United States)

    Van Segbroeck, Sven; Santos, Francisco C; Pacheco, Jorge M

    2010-08-19

    Human societies are organized in complex webs that are constantly reshaped by a social dynamic which is influenced by the information individuals have about others. Similarly, epidemic spreading may be affected by local information that makes individuals aware of the health status of their social contacts, allowing them to avoid contact with those infected and to remain in touch with the healthy. Here we study disease dynamics in finite populations in which infection occurs along the links of a dynamical contact network whose reshaping may be biased based on each individual's health status. We adopt some of the most widely used epidemiological models, investigating the impact of the reshaping of the contact network on the disease dynamics. We derive analytical results in the limit where network reshaping occurs much faster than disease spreading and demonstrate numerically that this limit extends to a much wider range of time scales than one might anticipate. Specifically, we show that from a population-level description, disease propagation in a quickly adapting network can be formulated equivalently as disease spreading on a well-mixed population but with a rescaled infectiousness. We find that for all models studied here--SI, SIS and SIR--the effective infectiousness of a disease depends on the population size, the number of infected in the population, and the capacity of healthy individuals to sever contacts with the infected. Importantly, we indicate how the use of available information hinders disease progression, either by reducing the average time required to eradicate a disease (in case recovery is possible), or by increasing the average time needed for a disease to spread to the entire population (in case recovery or immunity is impossible).

  6. Adaptive Dynamic Surface Control for Generator Excitation Control System

    Directory of Open Access Journals (Sweden)

    Zhang Xiu-yu

    2014-01-01

    Full Text Available For the generator excitation control system which is equipped with static var compensator (SVC and unknown parameters, a novel adaptive dynamic surface control scheme is proposed based on neural network and tracking error transformed function with the following features: (1 the transformation of the excitation generator model to the linear systems is omitted; (2 the prespecified performance of the tracking error can be guaranteed by combining with the tracking error transformed function; (3 the computational burden is greatly reduced by estimating the norm of the weighted vector of neural network instead of the weighted vector itself; therefore, it is more suitable for the real time control; and (4 the explosion of complicity problem inherent in the backstepping control can be eliminated. It is proved that the new scheme can make the system semiglobally uniformly ultimately bounded. Simulation results show the effectiveness of this control scheme.

  7. Adaptation and learning: characteristic time scales of performance dynamics.

    Science.gov (United States)

    Newell, Karl M; Mayer-Kress, Gottfried; Hong, S Lee; Liu, Yeou-Teh

    2009-12-01

    A multiple time scales landscape model is presented that reveals structures of performance dynamics that were not resolved in the traditional power law analysis of motor learning. It shows the co-existence of separate processes during and between practice sessions that evolve in two independent dimensions characterized by time scales that differ by about an order of magnitude. Performance along the slow persistent dimension of learning improves often as much and sometimes more during rest (memory consolidation and/or insight generation processes) than during a practice session itself. In contrast, the process characterized by the fast, transient dimension of adaptation reverses direction between practice sessions, thereby significantly degrading performance at the beginning of the next practice session (warm-up decrement). The theoretical model fits qualitatively and quantitatively the data from Snoddy's [Snoddy, G. S. (1926). Learning and stability. Journal of Applied Psychology, 10, 1-36] classic learning study of mirror tracing and other averaged and individual data sets, and provides a new account of the processes of change in adaptation and learning. 2009 Elsevier B.V. All rights reserved.

  8. Dynamic changes in brain activity during prism adaptation.

    Science.gov (United States)

    Luauté, Jacques; Schwartz, Sophie; Rossetti, Yves; Spiridon, Mona; Rode, Gilles; Boisson, Dominique; Vuilleumier, Patrik

    2009-01-07

    Prism adaptation does not only induce short-term sensorimotor plasticity, but also longer-term reorganization in the neural representation of space. We used event-related fMRI to study dynamic changes in brain activity during both early and prolonged exposure to visual prisms. Participants performed a pointing task before, during, and after prism exposure. Measures of trial-by-trial pointing errors and corrections allowed parametric analyses of brain activity as a function of performance. We show that during the earliest phase of prism exposure, anterior intraparietal sulcus was primarily implicated in error detection, whereas parieto-occipital sulcus was implicated in error correction. Cerebellum activity showed progressive increases during prism exposure, in accordance with a key role for spatial realignment. This time course further suggests that the cerebellum might promote neural changes in superior temporal cortex, which was selectively activated during the later phase of prism exposure and could mediate the effects of prism adaptation on cognitive spatial representations.

  9. 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....

  10. Modeling update for the Thirty Meter Telescope laser guide star dual-conjugate adaptive optics system

    Science.gov (United States)

    Gilles, Luc; Wang, Lianqi; Ellerbroek, Brent

    2010-07-01

    This paper describes the modeling efforts undertaken in the past couple of years to derive wavefront error (WFE) performance estimates for the Narrow Field Infrared Adaptive Optics System (NFIRAOS), which is the facility laser guide star (LGS) dual-conjugate adaptive optics (AO) system for the Thirty Meter Telescope (TMT). The estimates describe the expected performance of NFIRAOS as a function of seeing on Mauna Kea, zenith angle, and galactic latitude (GL). They have been developed through a combination of integrated AO simulations, side analyses, allocations, lab and lidar experiments.

  11. Predicting Depression From Language-Based Emotion Dynamics: Longitudinal Analysis of Facebook and Twitter Status Updates

    Science.gov (United States)

    Kern, Margaret L; Fulcher, Ben D; Rickard, Nikki S

    2018-01-01

    Background Frequent expression of negative emotion words on social media has been linked to depression. However, metrics have relied on average values, not dynamic measures of emotional volatility. Objective The aim of this study was to report on the associations between depression severity and the variability (time-unstructured) and instability (time-structured) in emotion word expression on Facebook and Twitter across status updates. Methods Status updates and depression severity ratings of 29 Facebook users and 49 Twitter users were collected through the app MoodPrism. The average proportion of positive and negative emotion words used, within-person variability, and instability were computed. Results Negative emotion word instability was a significant predictor of greater depression severity on Facebook (rs(29)=.44, P=.02, 95% CI 0.09-0.69), even after controlling for the average proportion of negative emotion words used (partial rs(26)=.51, P=.006) and within-person variability (partial rs(26)=.49, P=.009). A different pattern emerged on Twitter where greater negative emotion word variability indicated lower depression severity (rs(49)=−.34, P=.01, 95% CI −0.58 to 0.09). Differences between Facebook and Twitter users in their emotion word patterns and psychological characteristics were also explored. Conclusions The findings suggest that negative emotion word instability may be a simple yet sensitive measure of time-structured variability, useful when screening for depression through social media, though its usefulness may depend on the social media platform. PMID:29739736

  12. An Update on the Scholarly Networks on Resilience, Vulnerability, and Adaptation within the Human Dimensions of Global Environmental Change

    Directory of Open Access Journals (Sweden)

    Marco A. Janssen

    2007-12-01

    Full Text Available In Janssen et al. (2006, we presented a bibliometric analysis of the resilience, vulnerability, and adaptation knowledge domains within the research activities on human dimensions of global environmental change. We have updated the analysis because 2 years have gone by since the original analysis, and 1113 more publications can now be added to the database. We analyzed how the resulting 3399 publications between 1967 and 2007 are related in terms of co-authorship and citations. The rapid increase in the number of publications in the three knowledge domains continued over the last 2 years, and we still see an overlap between the knowledge domains. We were also able to identify the "hot" publications of the last 2 years.

  13. Adapt

    Science.gov (United States)

    Bargatze, L. F.

    2015-12-01

    files, or the addition of new or the deletion of old data products. Next, ADAPT routines analyzed the query results and issued updates to the metadata stored in the UCLA CDAWEB and SPDF metadata registries. In this way, the SPASE metadata registries generated by ADAPT can be relied on to provide up to date and complete access to Heliophysics CDF data resources on a daily basis.

  14. Cluster Optimization and Parallelization of Simulations with Dynamically Adaptive Grids

    KAUST Repository

    Schreiber, Martin; Weinzierl, Tobias; Bungartz, Hans-Joachim

    2013-01-01

    The present paper studies solvers for partial differential equations that work on dynamically adaptive grids stemming from spacetrees. Due to the underlying tree formalism, such grids efficiently can be decomposed into connected grid regions (clusters) on-the-fly. A graph on those clusters classified according to their grid invariancy, workload, multi-core affinity, and further meta data represents the inter-cluster communication. While stationary clusters already can be handled more efficiently than their dynamic counterparts, we propose to treat them as atomic grid entities and introduce a skip mechanism that allows the grid traversal to omit those regions completely. The communication graph ensures that the cluster data nevertheless are kept consistent, and several shared memory parallelization strategies are feasible. A hyperbolic benchmark that has to remesh selected mesh regions iteratively to preserve conforming tessellations acts as benchmark for the present work. We discuss runtime improvements resulting from the skip mechanism and the implications on shared memory performance and load balancing. © 2013 Springer-Verlag.

  15. Loss Aversion, Adaptive Beliefs, and Asset Pricing Dynamics

    Directory of Open Access Journals (Sweden)

    Kamal Samy Selim

    2015-01-01

    Full Text Available We study asset pricing dynamics in artificial financial markets model. The financial market is populated with agents following two heterogeneous trading beliefs, the technical and the fundamental prediction rules. Agents switch between trading rules with respect to their past performance. The agents are loss averse over asset price fluctuations. Loss aversion behaviour depends on the past performance of the trading strategies in terms of an evolutionary fitness measure. We propose a novel application of the prospect theory to agent-based modelling, and by simulation, the effect of evolutionary fitness measure on adaptive belief system is investigated. For comparison, we study pricing dynamics of a financial market populated with chartists perceive losses and gains symmetrically. One of our contributions is validating the agent-based models using real financial data of the Egyptian Stock Exchange. We find that our framework can explain important stylized facts in financial time series, such as random walk price behaviour, bubbles and crashes, fat-tailed return distributions, power-law tails in the distribution of returns, excess volatility, volatility clustering, the absence of autocorrelation in raw returns, and the power-law autocorrelations in absolute returns. In addition to this, we find that loss aversion improves market quality and market stability.

  16. Adaptive fuzzy dynamic surface control of nonlinear systems with input saturation and time-varying output constraints

    Science.gov (United States)

    Edalati, L.; Khaki Sedigh, A.; Aliyari Shooredeli, M.; Moarefianpour, A.

    2018-02-01

    This paper deals with the design of adaptive fuzzy dynamic surface control for uncertain strict-feedback nonlinear systems with asymmetric time-varying output constraints in the presence of input saturation. To approximate the unknown nonlinear functions and overcome the problem of explosion of complexity, a Fuzzy logic system is combined with the dynamic surface control in the backstepping design technique. To ensure the output constraints satisfaction, an asymmetric time-varying Barrier Lyapunov Function (BLF) is used. Moreover, by applying the minimal learning parameter technique, the number of the online parameters update for each subsystem is reduced to 2. Hence, the semi-globally uniformly ultimately boundedness (SGUUB) of all the closed-loop signals with appropriate tracking error convergence is guaranteed. The effectiveness of the proposed control is demonstrated by two simulation examples.

  17. Molecular Dynamics Simulations with Quantum Mechanics/Molecular Mechanics and Adaptive Neural Networks.

    Science.gov (United States)

    Shen, Lin; Yang, Weitao

    2018-03-13

    Direct molecular dynamics (MD) simulation with ab initio quantum mechanical and molecular mechanical (QM/MM) methods is very powerful for studying the mechanism of chemical reactions in a complex environment but also very time-consuming. The computational cost of QM/MM calculations during MD simulations can be reduced significantly using semiempirical QM/MM methods with lower accuracy. To achieve higher accuracy at the ab initio QM/MM level, a correction on the existing semiempirical QM/MM model is an attractive idea. Recently, we reported a neural network (NN) method as QM/MM-NN to predict the potential energy difference between semiempirical and ab initio QM/MM approaches. The high-level results can be obtained using neural network based on semiempirical QM/MM MD simulations, but the lack of direct MD samplings at the ab initio QM/MM level is still a deficiency that limits the applications of QM/MM-NN. In the present paper, we developed a dynamic scheme of QM/MM-NN for direct MD simulations on the NN-predicted potential energy surface to approximate ab initio QM/MM MD. Since some configurations excluded from the database for NN training were encountered during simulations, which may cause some difficulties on MD samplings, an adaptive procedure inspired by the selection scheme reported by Behler [ Behler Int. J. Quantum Chem. 2015 , 115 , 1032 ; Behler Angew. Chem., Int. Ed. 2017 , 56 , 12828 ] was employed with some adaptions to update NN and carry out MD iteratively. We further applied the adaptive QM/MM-NN MD method to the free energy calculation and transition path optimization on chemical reactions in water. The results at the ab initio QM/MM level can be well reproduced using this method after 2-4 iteration cycles. The saving in computational cost is about 2 orders of magnitude. It demonstrates that the QM/MM-NN with direct MD simulations has great potentials not only for the calculation of thermodynamic properties but also for the characterization of

  18. Significant improvements of electrical discharge machining performance by step-by-step updated adaptive control laws

    Science.gov (United States)

    Zhou, Ming; Wu, Jianyang; Xu, Xiaoyi; Mu, Xin; Dou, Yunping

    2018-02-01

    In order to obtain improved electrical discharge machining (EDM) performance, we have dedicated more than a decade to correcting one essential EDM defect, the weak stability of the machining, by developing adaptive control systems. The instabilities of machining are mainly caused by complicated disturbances in discharging. To counteract the effects from the disturbances on machining, we theoretically developed three control laws from minimum variance (MV) control law to minimum variance and pole placements coupled (MVPPC) control law and then to a two-step-ahead prediction (TP) control law. Based on real-time estimation of EDM process model parameters and measured ratio of arcing pulses which is also called gap state, electrode discharging cycle was directly and adaptively tuned so that a stable machining could be achieved. To this end, we not only theoretically provide three proved control laws for a developed EDM adaptive control system, but also practically proved the TP control law to be the best in dealing with machining instability and machining efficiency though the MVPPC control law provided much better EDM performance than the MV control law. It was also shown that the TP control law also provided a burn free machining.

  19. Adaptive Equalizer Using Selective Partial Update Algorithm and Selective Regressor Affine Projection Algorithm over Shallow Water Acoustic Channels

    Directory of Open Access Journals (Sweden)

    Masoumeh Soflaei

    2014-01-01

    Full Text Available One of the most important problems of reliable communications in shallow water channels is intersymbol interference (ISI which is due to scattering from surface and reflecting from bottom. Using adaptive equalizers in receiver is one of the best suggested ways for overcoming this problem. In this paper, we apply the family of selective regressor affine projection algorithms (SR-APA and the family of selective partial update APA (SPU-APA which have low computational complexity that is one of the important factors that influences adaptive equalizer performance. We apply experimental data from Strait of Hormuz for examining the efficiency of the proposed methods over shallow water channel. We observe that the values of the steady-state mean square error (MSE of SR-APA and SPU-APA decrease by 5.8 (dB and 5.5 (dB, respectively, in comparison with least mean square (LMS algorithm. Also the families of SPU-APA and SR-APA have better convergence speed than LMS type algorithm.

  20. Adaptive control of dynamic balance in human gait on a split-belt treadmill.

    Science.gov (United States)

    Buurke, Tom J W; Lamoth, Claudine J C; Vervoort, Danique; van der Woude, Lucas H V; den Otter, Rob

    2018-05-17

    Human bipedal gait is inherently unstable and staying upright requires adaptive control of dynamic balance. Little is known about adaptive control of dynamic balance in reaction to long-term, continuous perturbations. We examined how dynamic balance control adapts to a continuous perturbation in gait, by letting people walk faster with one leg than the other on a treadmill with two belts (i.e. split-belt walking). In addition, we assessed whether changes in mediolateral dynamic balance control coincide with changes in energy use during split-belt adaptation. In nine minutes of split-belt gait, mediolateral margins of stability and mediolateral foot roll-off changed during adaptation to the imposed gait asymmetry, especially on the fast side, and returned to baseline during washout. Interestingly, no changes in mediolateral foot placement (i.e. step width) were found during split-belt adaptation. Furthermore, the initial margin of stability and subsequent mediolateral foot roll-off were strongly coupled to maintain mediolateral dynamic balance throughout the gait cycle. Consistent with previous results net metabolic power was reduced during split-belt adaptation, but changes in mediolateral dynamic balance control were not correlated with the reduction of net metabolic power during split-belt adaptation. Overall, this study has shown that a complementary mechanism of relative foot positioning and mediolateral foot roll-off adapts to continuously imposed gait asymmetry to maintain dynamic balance in human bipedal gait. © 2018. Published by The Company of Biologists Ltd.

  1. Plant toxicity, adaptive herbivory, and plant community dynamics

    Science.gov (United States)

    Feng, Z.; Liu, R.; DeAngelis, D.L.; Bryant, J.P.; Kielland, K.; Stuart, Chapin F.; Swihart, R.K.

    2009-01-01

    We model effects of interspecific plant competition, herbivory, and a plant's toxic defenses against herbivores on vegetation dynamics. The model predicts that, when a generalist herbivore feeds in the absence of plant toxins, adaptive foraging generally increases the probability of coexistence of plant species populations, because the herbivore switches more of its effort to whichever plant species is more common and accessible. In contrast, toxin-determined selective herbivory can drive plant succession toward dominance by the more toxic species, as previously documented in boreal forests and prairies. When the toxin concentrations in different plant species are similar, but species have different toxins with nonadditive effects, herbivores tend to diversify foraging efforts to avoid high intakes of any one toxin. This diversification leads the herbivore to focus more feeding on the less common plant species. Thus, uncommon plants may experience depensatory mortality from herbivory, reducing local species diversity. The depensatory effect of herbivory may inhibit the invasion of other plant species that are more palatable or have different toxins. These predictions were tested and confirmed in the Alaskan boreal forest. ?? 2009 Springer Science+Business Media, LLC.

  2. Predicting Depression From Language-Based Emotion Dynamics: Longitudinal Analysis of Facebook and Twitter Status Updates.

    Science.gov (United States)

    Seabrook, Elizabeth M; Kern, Margaret L; Fulcher, Ben D; Rickard, Nikki S

    2018-05-08

    Frequent expression of negative emotion words on social media has been linked to depression. However, metrics have relied on average values, not dynamic measures of emotional volatility. The aim of this study was to report on the associations between depression severity and the variability (time-unstructured) and instability (time-structured) in emotion word expression on Facebook and Twitter across status updates. Status updates and depression severity ratings of 29 Facebook users and 49 Twitter users were collected through the app MoodPrism. The average proportion of positive and negative emotion words used, within-person variability, and instability were computed. Negative emotion word instability was a significant predictor of greater depression severity on Facebook (r s (29)=.44, P=.02, 95% CI 0.09-0.69), even after controlling for the average proportion of negative emotion words used (partial r s (26)=.51, P=.006) and within-person variability (partial r s (26)=.49, P=.009). A different pattern emerged on Twitter where greater negative emotion word variability indicated lower depression severity (r s (49)=-.34, P=.01, 95% CI -0.58 to 0.09). Differences between Facebook and Twitter users in their emotion word patterns and psychological characteristics were also explored. The findings suggest that negative emotion word instability may be a simple yet sensitive measure of time-structured variability, useful when screening for depression through social media, though its usefulness may depend on the social media platform. ©Elizabeth M Seabrook, Margaret L Kern, Ben D Fulcher, Nikki S Rickard. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 08.05.2018.

  3. Hamiltonian-Driven Adaptive Dynamic Programming for Continuous Nonlinear Dynamical Systems.

    Science.gov (United States)

    Yang, Yongliang; Wunsch, Donald; Yin, Yixin

    2017-08-01

    This paper presents a Hamiltonian-driven framework of adaptive dynamic programming (ADP) for continuous time nonlinear systems, which consists of evaluation of an admissible control, comparison between two different admissible policies with respect to the corresponding the performance function, and the performance improvement of an admissible control. It is showed that the Hamiltonian can serve as the temporal difference for continuous-time systems. In the Hamiltonian-driven ADP, the critic network is trained to output the value gradient. Then, the inner product between the critic and the system dynamics produces the value derivative. Under some conditions, the minimization of the Hamiltonian functional is equivalent to the value function approximation. An iterative algorithm starting from an arbitrary admissible control is presented for the optimal control approximation with its convergence proof. The implementation is accomplished by a neural network approximation. Two simulation studies demonstrate the effectiveness of Hamiltonian-driven ADP.

  4. Optimal and robust control of a class of nonlinear systems using dynamically re-optimised single network adaptive critic design

    Science.gov (United States)

    Tiwari, Shivendra N.; Padhi, Radhakant

    2018-01-01

    Following the philosophy of adaptive optimal control, a neural network-based state feedback optimal control synthesis approach is presented in this paper. First, accounting for a nominal system model, a single network adaptive critic (SNAC) based multi-layered neural network (called as NN1) is synthesised offline. However, another linear-in-weight neural network (called as NN2) is trained online and augmented to NN1 in such a manner that their combined output represent the desired optimal costate for the actual plant. To do this, the nominal model needs to be updated online to adapt to the actual plant, which is done by synthesising yet another linear-in-weight neural network (called as NN3) online. Training of NN3 is done by utilising the error information between the nominal and actual states and carrying out the necessary Lyapunov stability analysis using a Sobolev norm based Lyapunov function. This helps in training NN2 successfully to capture the required optimal relationship. The overall architecture is named as 'Dynamically Re-optimised single network adaptive critic (DR-SNAC)'. Numerical results for two motivating illustrative problems are presented, including comparison studies with closed form solution for one problem, which clearly demonstrate the effectiveness and benefit of the proposed approach.

  5. Does the Effort of Processing Potential Incentives Influence the Adaption of Context Updating in Older Adults?

    Science.gov (United States)

    Schmitt, Hannah; Kray, Jutta; Ferdinand, Nicola K

    2017-01-01

    A number of aging studies suggest that older adults process positive and negative information differently. For instance, the socioemotional selectivity theory postulates that older adults preferably process positive information in service of emotional well-being (Reed and Carstensen, 2012). Moreover, recent research has started to investigate whether incentives like gains or losses can influence cognitive control in an ongoing task. In an earlier study (Schmitt et al., 2015), we examined whether incentive cues, indicating potential monetary gains, losses, or neutral outcomes for good performance in the following trial, would influence older adults' ability to exert cognitive control. Cognitive control was measured in an AX-Continuous-Performance-Task (AX-CPT) in which participants had to select their responses to probe stimuli depending on a preceding context cue. In this study, we did not find support for a positivity effect in older adults, but both gains and losses led to enhanced context processing. As the trial-wise presentation mode may be too demanding on cognitive resources for such a bias to occur, the main goal of the present study was to examine whether motivational mindsets, induced by block-wise presentation of incentives, would result in a positivity effect. For this reason, we examined 17 older participants (65-76 years) in the AX-CPT using a block-wise presentation of incentive cues and compared them to 18 older adults (69-78 years) with the trial-wise presentation mode from our earlier study (Schmitt et al., 2015). Event-related potentials were recorded to the onset of the motivational cue and during the AX-CPT. Our results show that (a) older adults initially process cues signaling potential losses more strongly, but later during the AX-CPT invest more cognitive resources in preparatory processes like context updating in conditions with potential gains, and (b) block-wise and trial-wise presentation of incentive cues differentially influenced

  6. Does the Effort of Processing Potential Incentives Influence the Adaption of Context Updating in Older Adults?

    Directory of Open Access Journals (Sweden)

    Hannah Schmitt

    2017-11-01

    Full Text Available A number of aging studies suggest that older adults process positive and negative information differently. For instance, the socioemotional selectivity theory postulates that older adults preferably process positive information in service of emotional well-being (Reed and Carstensen, 2012. Moreover, recent research has started to investigate whether incentives like gains or losses can influence cognitive control in an ongoing task. In an earlier study (Schmitt et al., 2015, we examined whether incentive cues, indicating potential monetary gains, losses, or neutral outcomes for good performance in the following trial, would influence older adults’ ability to exert cognitive control. Cognitive control was measured in an AX-Continuous-Performance-Task (AX-CPT in which participants had to select their responses to probe stimuli depending on a preceding context cue. In this study, we did not find support for a positivity effect in older adults, but both gains and losses led to enhanced context processing. As the trial-wise presentation mode may be too demanding on cognitive resources for such a bias to occur, the main goal of the present study was to examine whether motivational mindsets, induced by block-wise presentation of incentives, would result in a positivity effect. For this reason, we examined 17 older participants (65–76 years in the AX-CPT using a block-wise presentation of incentive cues and compared them to 18 older adults (69–78 years with the trial-wise presentation mode from our earlier study (Schmitt et al., 2015. Event-related potentials were recorded to the onset of the motivational cue and during the AX-CPT. Our results show that (a older adults initially process cues signaling potential losses more strongly, but later during the AX-CPT invest more cognitive resources in preparatory processes like context updating in conditions with potential gains, and (b block-wise and trial-wise presentation of incentive cues

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1999-12-01

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

  8. A rapid learning and dynamic stepwise updating algorithm for flat neural networks and the application to time-series prediction.

    Science.gov (United States)

    Chen, C P; Wan, J Z

    1999-01-01

    A fast learning algorithm is proposed to find an optimal weights of the flat neural networks (especially, the functional-link network). Although the flat networks are used for nonlinear function approximation, they can be formulated as linear systems. Thus, the weights of the networks can be solved easily using a linear least-square method. This formulation makes it easier to update the weights instantly for both a new added pattern and a new added enhancement node. A dynamic stepwise updating algorithm is proposed to update the weights of the system on-the-fly. The model is tested on several time-series data including an infrared laser data set, a chaotic time-series, a monthly flour price data set, and a nonlinear system identification problem. The simulation results are compared to existing models in which more complex architectures and more costly training are needed. The results indicate that the proposed model is very attractive to real-time processes.

  9. Quinoa - Adaptive Computational Fluid Dynamics, 0.2

    Energy Technology Data Exchange (ETDEWEB)

    2017-09-22

    Quinoa is a set of computational tools that enables research and numerical analysis in fluid dynamics. At this time it remains a test-bed to experiment with various algorithms using fully asynchronous runtime systems. Currently, Quinoa consists of the following tools: (1) Walker, a numerical integrator for systems of stochastic differential equations in time. It is a mathematical tool to analyze and design the behavior of stochastic differential equations. It allows the estimation of arbitrary coupled statistics and probability density functions and is currently used for the design of statistical moment approximations for multiple mixing materials in variable-density turbulence. (2) Inciter, an overdecomposition-aware finite element field solver for partial differential equations using 3D unstructured grids. Inciter is used to research asynchronous mesh-based algorithms and to experiment with coupling asynchronous to bulk-synchronous parallel code. Two planned new features of Inciter, compared to the previous release (LA-CC-16-015), to be implemented in 2017, are (a) a simple Navier-Stokes solver for ideal single-material compressible gases, and (b) solution-adaptive mesh refinement (AMR), which enables dynamically concentrating compute resources to regions with interesting physics. Using the NS-AMR problem we plan to explore how to scale such high-load-imbalance simulations, representative of large production multiphysics codes, to very large problems on very large computers using an asynchronous runtime system. (3) RNGTest, a test harness to subject random number generators to stringent statistical tests enabling quantitative ranking with respect to their quality and computational cost. (4) UnitTest, a unit test harness, running hundreds of tests per second, capable of testing serial, synchronous, and asynchronous functions. (5) MeshConv, a mesh file converter that can be used to convert 3D tetrahedron meshes from and to either of the following formats: Gmsh

  10. Finite element model updating in structural dynamics using design sensitivity and optimisation

    OpenAIRE

    Calvi, Adriano

    1998-01-01

    Model updating is an important issue in engineering. In fact a well-correlated model provides for accurate evaluation of the structure loads and responses. The main objectives of the study were to exploit available optimisation programs to create an error localisation and updating procedure of nite element models that minimises the "error" between experimental and analytical modal data, addressing in particular the updating of large scale nite element models with se...

  11. An LPV Adaptive Observer for Updating a Map Applied to an MAF Sensor in a Diesel Engine.

    Science.gov (United States)

    Liu, Zhiyuan; Wang, Changhui

    2015-10-23

    In this paper, a new method for mass air flow (MAF) sensor error compensation and an online updating error map (or lookup table) due to installation and aging in a diesel engine is developed. Since the MAF sensor error is dependent on the engine operating point, the error model is represented as a two-dimensional (2D) map with two inputs, fuel mass injection quantity and engine speed. Meanwhile, the 2D map representing the MAF sensor error is described as a piecewise bilinear interpolation model, which can be written as a dot product between the regression vector and parameter vector using a membership function. With the combination of the 2D map regression model and the diesel engine air path system, an LPV adaptive observer with low computational load is designed to estimate states and parameters jointly. The convergence of the proposed algorithm is proven under the conditions of persistent excitation and given inequalities. The observer is validated against the simulation data from engine software enDYNA provided by Tesis. The results demonstrate that the operating point-dependent error of the MAF sensor can be approximated acceptably by the 2D map from the proposed method.

  12. Adaptive control of structural balance for complex dynamical networks based on dynamic coupling of nodes

    Science.gov (United States)

    Gao, Zilin; Wang, Yinhe; Zhang, Lili

    2018-02-01

    In the existing research results of the complex dynamical networks controlled, the controllers are mainly used to guarantee the synchronization or stabilization of the nodes’ state, and the terms coupled with connection relationships may affect the behaviors of nodes, this obviously ignores the dynamic common behavior of the connection relationships between the nodes. In fact, from the point of view of large-scale system, a complex dynamical network can be regarded to be composed of two time-varying dynamic subsystems, which can be called the nodes subsystem and the connection relationships subsystem, respectively. Similar to the synchronization or stabilization of the nodes subsystem, some characteristic phenomena can be also emerged in the connection relationships subsystem. For example, the structural balance in the social networks and the synaptic facilitation in the biological neural networks. This paper focuses on the structural balance in dynamic complex networks. Generally speaking, the state of the connection relationships subsystem is difficult to be measured accurately in practical applications, and thus it is not easy to implant the controller directly into the connection relationships subsystem. It is noted that the nodes subsystem and the relationships subsystem are mutually coupled, which implies that the state of the connection relationships subsystem can be affected by the controllable state of nodes subsystem. Inspired by this observation, by using the structural balance theory of triad, the controller with the parameter adaptive law is proposed for the nodes subsystem in this paper, which may ensure the connection relationship matrix to approximate a given structural balance matrix in the sense of the uniformly ultimately bounded (UUB). That is, the structural balance may be obtained by employing the controlling state of the nodes subsystem. Finally, the simulations are used to show the validity of the method in this paper.

  13. Students' Adaptation in the Social and Cultural Dynamics

    Science.gov (United States)

    Sadyrin, Vladimir Vitalievich; Potapova, Marina Vladimirovna; Gnatyshina, Elena Alexandrovna; Uvarina, Nataliya Viktorovna; Danilova, Viktoriya Valerievna

    2016-01-01

    Modern scientific literature views issues on adaptation based on various aspects: biological, medical, pedagogical, sociological, cybernetic, interdisciplinary, etc. The given article is devoted to the analysis of the problem of adaptation as social and psychological phenomenon including peculiarities of its functioning in the conditions of social…

  14. Body surface adaptations to boundary-layer dynamics

    NARCIS (Netherlands)

    Videler, J.J.

    1995-01-01

    Evolutionary processes have adapted nektonic animals to interact efficiently with the water that surrounds them. Not all these adaptations serve the same purpose. This paper concentrates on reduction of drag due to friction in the boundary layer close to the body surface. Mucus, compliant skins,

  15. Adaptation strategies of airline travel agencies to the dynamics of ...

    African Journals Online (AJOL)

    The role of airline travel agencies in a changing operational environment depends on their ability to adapt and survive in the airline travel industry. This paper examines the adaptation strategies airline travel agencies adopt to remain in business. Data for this paper was obtained through multi-stage sampling system that ...

  16. Achieving Optimal Self-Adaptivity for Dynamic Tuning of Organic Semiconductors through Resonance Engineering.

    Science.gov (United States)

    Tao, Ye; Xu, Lijia; Zhang, Zhen; Chen, Runfeng; Li, Huanhuan; Xu, Hui; Zheng, Chao; Huang, Wei

    2016-08-03

    Current static-state explorations of organic semiconductors for optimal material properties and device performance are hindered by limited insights into the dynamically changed molecular states and charge transport and energy transfer processes upon device operation. Here, we propose a simple yet successful strategy, resonance variation-based dynamic adaptation (RVDA), to realize optimized self-adaptive properties in donor-resonance-acceptor molecules by engineering the resonance variation for dynamic tuning of organic semiconductors. Organic light-emitting diodes hosted by these RVDA materials exhibit remarkably high performance, with external quantum efficiencies up to 21.7% and favorable device stability. Our approach, which supports simultaneous realization of dynamically adapted and selectively enhanced properties via resonance engineering, illustrates a feasible design map for the preparation of smart organic semiconductors capable of dynamic structure and property modulations, promoting the studies of organic electronics from static to dynamic.

  17. Ready or Not: Microbial Adaptive Responses in Dynamic Symbiosis Environments.

    Science.gov (United States)

    Cao, Mengyi; Goodrich-Blair, Heidi

    2017-08-01

    In mutually beneficial and pathogenic symbiotic associations, microbes must adapt to the host environment for optimal fitness. Both within an individual host and during transmission between hosts, microbes are exposed to temporal and spatial variation in environmental conditions. The phenomenon of phenotypic variation, in which different subpopulations of cells express distinctive and potentially adaptive characteristics, can contribute to microbial adaptation to a lifestyle that includes rapidly changing environments. The environments experienced by a symbiotic microbe during its life history can be erratic or predictable, and each can impact the evolution of adaptive responses. In particular, the predictability of a rhythmic or cyclical series of environments may promote the evolution of signal transduction cascades that allow preadaptive responses to environments that are likely to be encountered in the future, a phenomenon known as adaptive prediction. In this review, we summarize environmental variations known to occur in some well-studied models of symbiosis and how these may contribute to the evolution of microbial population heterogeneity and anticipatory behavior. We provide details about the symbiosis between Xenorhabdus bacteria and Steinernema nematodes as a model to investigate the concept of environmental adaptation and adaptive prediction in a microbial symbiosis. Copyright © 2017 American Society for Microbiology.

  18. Adapting the Medium: Dynamics of Intermedial Adaptation in Contemporary Japanese Popular Visual Culture

    Directory of Open Access Journals (Sweden)

    Pusztai Beáta

    2015-08-01

    Full Text Available With respect to adaptation studies, contemporary Japanese popular culture signifies a unique case, as different types of media (be those textual, auditive, visual or audio-visual are tightly intertwined through the “recycling” of successful characters and stories. As a result, a neatly woven net of intermedial adaptations has been formed - the core of this complex system being the manga-anime-live-action film “adaptational triangle.” On the one hand, the paper addresses the interplay of the various factors by which the very existence of this network is made possible, such as the distinctive cultural attitude to “originality,” the structure of the comics, animation and film industries, and finally, the role of fictitious genealogies of both traditional and contemporary media in the negotiation of national identity. On the other hand, the essay also considers some of the most significant thematic, narrative, and stylistic effects this close interconnectedness has on the individual medium. Special attention is being paid to the nascent trend of merging the adaptive medium with that of the original story (viewing adaptation as integration, apparent in contemporary manga-based live- action comedies, as the extreme case of intermedial adaptation. That is, when the aim of the adaptational process is no longer the transposition of the story but the adaptation (i.e. the incorporation of the medium itself- elevating certain medium-specific devices into transmedial phenomena.

  19. The Dynamics of Learning and the Emergence of Distributed Adaption

    National Research Council Canada - National Science Library

    Crutchfield, James P

    2006-01-01

    .... The second goal was to adapt this single-agent learning theory and associated learning algorithms to the distributed setting in which a population of autonomous agents communicate to achieve a desired group task...

  20. Dynamic Difficulty Adaptation for Heterogeneously Skilled Player Groups in Multiplayer Collaborative Games

    OpenAIRE

    Greciano, Miguel Cristian

    2016-01-01

    This work focuses on the combination of two key concepts: Dynamic Difficulty Adjustment/Adaptation (video games adapting their difficulty according to the in-game performance of players, making themselves easier if the player performs poorly or more difficult if the player performs well) and Collaborative Multiplayer Games (video games where two or more human players work together to achieve a common goal). It considers and analyzes the challenges, potential and possibilities of Dynamic Diffi...

  1. Dynamic adaptation of tendon and muscle connective tissue to mechanical loading

    DEFF Research Database (Denmark)

    Mackey, Abigail; Heinemeier, Katja Maria; Koskinen, Satu Osmi Anneli

    2008-01-01

    The connective tissue of tendon and skeletal muscle is a crucial structure for force transmission. A dynamic adaptive capacity of these tissues in healthy individuals is evident from reports of altered gene expression and protein levels of the fibrillar and network-forming collagens, when subjected...... in this article provide strong evidence for the highly adaptable nature of connective tissue in muscle and tendon....

  2. The self-adaptation to dynamic failures for efficient virtual organization formations in grid computing context

    International Nuclear Information System (INIS)

    Han Liangxiu

    2009-01-01

    Grid computing aims to enable 'resource sharing and coordinated problem solving in dynamic, multi-institutional virtual organizations (VOs)'. However, due to the nature of heterogeneous and dynamic resources, dynamic failures in the distributed grid environment usually occur more than in traditional computation platforms, which cause failed VO formations. In this paper, we develop a novel self-adaptive mechanism to dynamic failures during VO formations. Such a self-adaptive scheme allows an individual and member of VOs to automatically find other available or replaceable one once a failure happens and therefore makes systems automatically recover from dynamic failures. We define dynamic failure situations of a system by using two standard indicators: mean time between failures (MTBF) and mean time to recover (MTTR). We model both MTBF and MTTR as Poisson distributions. We investigate and analyze the efficiency of the proposed self-adaptation mechanism to dynamic failures by comparing the success probability of VO formations before and after adopting it in three different cases: (1) different failure situations; (2) different organizational structures and scales; (3) different task complexities. The experimental results show that the proposed scheme can automatically adapt to dynamic failures and effectively improve the dynamic VO formation performance in the event of node failures, which provide a valuable addition to the field.

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

    NARCIS (Netherlands)

    Treur, J.; Umair, M.

    2011-01-01

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

  4. Techniques for grid manipulation and adaptation. [computational fluid dynamics

    Science.gov (United States)

    Choo, Yung K.; Eisemann, Peter R.; Lee, Ki D.

    1992-01-01

    Two approaches have been taken to provide systematic grid manipulation for improved grid quality. One is the control point form (CPF) of algebraic grid generation. It provides explicit control of the physical grid shape and grid spacing through the movement of the control points. It works well in the interactive computer graphics environment and hence can be a good candidate for integration with other emerging technologies. The other approach is grid adaptation using a numerical mapping between the physical space and a parametric space. Grid adaptation is achieved by modifying the mapping functions through the effects of grid control sources. The adaptation process can be repeated in a cyclic manner if satisfactory results are not achieved after a single application.

  5. A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy

    Directory of Open Access Journals (Sweden)

    Ge Jianjun

    2017-12-01

    Full Text Available Nowadays, the battlefield environment has become much more complex and variable. This paper presents a quantitative method and lower bound for the amount of target information acquired from multiple radar observations to adaptively and dynamically organize the detection of battlefield resources based on the principle of information entropy. Furthermore, for minimizing the given information entropy’s lower bound for target measurement at every moment, a method to dynamically and adaptively select radars with a high amount of information for target tracking is proposed. The simulation results indicate that the proposed method has higher tracking accuracy than that of tracking without adaptive radar selection based on entropy.

  6. Hybrid Adaptive Flight Control with Model Inversion Adaptation

    Science.gov (United States)

    Nguyen, Nhan

    2011-01-01

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

  7. Advanced Dynamically Adaptive Algorithms for Stochastic Simulations on Extreme Scales

    Energy Technology Data Exchange (ETDEWEB)

    Xiu, Dongbin [Univ. of Utah, Salt Lake City, UT (United States)

    2017-03-03

    The focus of the project is the development of mathematical methods and high-performance computational tools for stochastic simulations, with a particular emphasis on computations on extreme scales. The core of the project revolves around the design of highly efficient and scalable numerical algorithms that can adaptively and accurately, in high dimensional spaces, resolve stochastic problems with limited smoothness, even containing discontinuities.

  8. An extension of the classification of evolutionary singular strategies in Adaptive Dynamics

    NARCIS (Netherlands)

    Boldin, Barbara; Diekmann, Odo

    2014-01-01

    The existing classification of evolutionarily singular strategies in Adaptive Dynamics (Geritz et al. in Evol Ecol 12:35–57, 1998; Metz et al. in Stochastic and spatial structures of dynamical systems, pp 183–231, 1996) assumes an invasion exponent that is differentiable twice as a function of both

  9. Quantitative adaptation analytics for assessing dynamic systems of systems: LDRD Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Gauthier, John H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). System Readiness & Sustainment Technologies (6133, M/S 1188); Miner, Nadine E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Military & Energy Systems Analysis (6114, M/S 1188); Wilson, Michael L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Resilience and Regulatory Effects (6921, M/S 1138); Le, Hai D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). System Readiness & Sustainment Technologies (6133, M/S 1188); Kao, Gio K. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Networked System Survivability & Assurance (5629, M/S 0671); Melander, Darryl J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Software Systems R& D (9525, M/S 1188); Longsine, Dennis Earl [Sandia National Laboratories, Unknown, Unknown; Vander Meer, Jr., Robert C. [SAIC, Inc., Albuquerque, NM (United States)

    2015-01-01

    Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combining the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.

  10. Strategies in edge plasma simulation using adaptive dynamic nodalization techniques

    International Nuclear Information System (INIS)

    Kainz, A.; Weimann, G.; Kamelander, G.

    2003-01-01

    A wide span of steady-state and transient edge plasma processes simulation problems require accurate discretization techniques and can then be treated with Finite Element (FE) and Finite Volume (FV) methods. The software used here to meet these meshing requirements is a 2D finite element grid generator. It allows to produce adaptive unstructured grids taking into consideration the flux surface characteristics. To comply with the common mesh handling features of FE/FV packages, some options have been added to the basic generation tool. These enhancements include quadrilateral meshes without non-regular transition elements obtained by substituting them by transition constructions consisting of regular quadrilateral elements. Furthermore triangular grids can be created with one edge parallel to the magnetic field and modified by the basic adaptation/realignment techniques. Enhanced code operation properties and processing capabilities are expected. (author)

  11. Dynamics of Individual and Collective Agricultural Adaptation to Water Scarcity

    Science.gov (United States)

    Burchfield, E. K.; Gilligan, J. M.

    2016-12-01

    Drought and water scarcity are challenging agricultural systems around the world. We draw on extensive field-work conducted with paddy farmers in rural Sri Lanka to study adaptations to water scarcity, including switching to less water-intensive crops, farming collectively on shared land, and turning to groundwater by digging wells. We explore how variability in climate affects agricultural decision-making at the community and individual levels using three decision-making heuristics, each characterized by an objective function: risk-averse expected utility, regret-adjusted expected utility, and prospect theory loss-aversion. We also assess how the introduction of individualized access to irrigation water with wells affects long-standing community-based drought mitigation practices. Results suggest that the growth of well-irrigation may produce sudden disruptions to community-based adaptations, but that this depends on the mental models farmers use to think about risk and make decisions under uncertainty.

  12. 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.

  13. Dynamic Nature of Noncoding RNA Regulation of Adaptive Immune Response

    Directory of Open Access Journals (Sweden)

    Franca Citarella

    2013-08-01

    Full Text Available Immune response plays a fundamental role in protecting the organism from infections; however, dysregulation often occurs and can be detrimental for the organism, leading to a variety of immune-mediated diseases. Recently our understanding of the molecular and cellular networks regulating the immune response, and, in particular, adaptive immunity, has improved dramatically. For many years, much of the focus has been on the study of protein regulators; nevertheless, recent evidence points to a fundamental role for specific classes of noncoding RNAs (ncRNAs in regulating development, activation and homeostasis of the immune system. Although microRNAs (miRNAs are the most comprehensive and well-studied, a number of reports suggest the exciting possibility that long ncRNAs (lncRNAs could mediate host response and immune function. Finally, evidence is also accumulating that suggests a role for miRNAs and other small ncRNAs in autocrine, paracrine and exocrine signaling events, thus highlighting an elaborate network of regulatory interactions mediated by different classes of ncRNAs during immune response. This review will explore the multifaceted roles of ncRNAs in the adaptive immune response. In particular, we will focus on the well-established role of miRNAs and on the emerging role of lncRNAs and circulating ncRNAs, which all make indispensable contributions to the understanding of the multilayered modulation of the adaptive immune response.

  14. Adaptive spectrum decision framework for heterogeneous dynamic spectrum access networks

    CSIR Research Space (South Africa)

    Masonta, M

    2015-09-01

    Full Text Available Spectrum decision is the ability of a cognitive radio (CR) system to select the best available spectrum band to satisfy dynamic spectrum access network (DSAN) users¿ quality of service (QoS) requirements without causing harmful interference...

  15. Privacy context model for dynamic privacy adaptation in ubiquitous computing

    NARCIS (Netherlands)

    Schaub, Florian; Koenings, Bastian; Dietzel, Stefan; Weber, M.; Kargl, Frank

    Ubiquitous computing is characterized by the merger of physical and virtual worlds as physical artifacts gain digital sensing, processing, and communication capabilities. Maintaining an appropriate level of privacy in the face of such complex and often highly dynamic systems is challenging. We argue

  16. What to change and what to keep? Values and dynamics of adaptation to climate change

    Directory of Open Access Journals (Sweden)

    Sebastian Wessels

    2015-04-01

    Full Text Available This paper uses a complex systems theory framework to clarify what adaptation to climate change means in practice, which is to make targeted changes to a society's functioning in order to avoid changes happening to that which is of value to the members of that society. It is shown that the question what is to be changed and what to be preserved is not prescribed by the facts of climate change and technology, but a contingent one to be made by society. Discussing four important domains of adaptation and the respective narratives found in academia and politics, it is investigated how these decisions are formed, giving special consideration to the case of Germany. This leads to the finding that the generally defensive framings that characterizes common notions of adaptation reinforce predominant cultural paradigms and social dynamics that arguably have contributed considerably to the need for adaptation to climate change in the first place and will most likely create further need for adaptation in the future. A paradoxical tendency to accelerate predominant social dynamics in attempts to keep current states of affairs unchanged is identified. It is concluded that the concept of adaptation is a regression behind the concept of sustainability which can easily accommodate adaptation needs but avoids the identified pitfalls of adaptation by its future orientation and oft-criticized openness.

  17. Sequential updating of a new dynamic pharmacokinetic model for caffeine in premature neonates.

    Science.gov (United States)

    Micallef, Sandrine; Amzal, Billy; Bach, Véronique; Chardon, Karen; Tourneux, Pierre; Bois, Frédéric Y

    2007-01-01

    Caffeine treatment is widely used in nursing care to reduce the risk of apnoea in premature neonates. To check the therapeutic efficacy of the treatment against apnoea, caffeine concentration in blood is an important indicator. The present study was aimed at building a pharmacokinetic model as a basis for a medical decision support tool. In the proposed model, time dependence of physiological parameters is introduced to describe rapid growth of neonates. To take into account the large variability in the population, the pharmacokinetic model is embedded in a population structure. The whole model is inferred within a Bayesian framework. To update caffeine concentration predictions as data of an incoming patient are collected, we propose a fast method that can be used in a medical context. This involves the sequential updating of model parameters (at individual and population levels) via a stochastic particle algorithm. Our model provides better predictions than the ones obtained with models previously published. We show, through an example, that sequential updating improves predictions of caffeine concentration in blood (reduce bias and length of credibility intervals). The update of the pharmacokinetic model using body mass and caffeine concentration data is studied. It shows how informative caffeine concentration data are in contrast to body mass data. This study provides the methodological basis to predict caffeine concentration in blood, after a given treatment if data are collected on the treated neonate.

  18. Finite element model updating of natural fibre reinforced composite structure in structural dynamics

    Directory of Open Access Journals (Sweden)

    Sani M.S.M.

    2016-01-01

    Full Text Available Model updating is a process of making adjustment of certain parameters of finite element model in order to reduce discrepancy between analytical predictions of finite element (FE and experimental results. Finite element model updating is considered as an important field of study as practical application of finite element method often shows discrepancy to the test result. The aim of this research is to perform model updating procedure on a composite structure as well as trying improving the presumed geometrical and material properties of tested composite structure in finite element prediction. The composite structure concerned in this study is a plate of reinforced kenaf fiber with epoxy. Modal properties (natural frequency, mode shapes, and damping ratio of the kenaf fiber structure will be determined using both experimental modal analysis (EMA and finite element analysis (FEA. In EMA, modal testing will be carried out using impact hammer test while normal mode analysis using FEA will be carried out using MSC. Nastran/Patran software. Correlation of the data will be carried out before optimizing the data from FEA. Several parameters will be considered and selected for the model updating procedure.

  19. Dynamically adaptive data-driven simulation of extreme hydrological flows

    Science.gov (United States)

    Kumar Jain, Pushkar; Mandli, Kyle; Hoteit, Ibrahim; Knio, Omar; Dawson, Clint

    2018-02-01

    Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.

  20. Dynamically adaptive data-driven simulation of extreme hydrological flows

    KAUST Repository

    Kumar Jain, Pushkar

    2017-12-27

    Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.

  1. A quantitative evolutionary theory of adaptive behavior dynamics.

    Science.gov (United States)

    McDowell, J J

    2013-10-01

    The idea that behavior is selected by its consequences in a process analogous to organic evolution has been discussed for over 100 years. A recently proposed theory instantiates this idea by means of a genetic algorithm that operates on a population of potential behaviors. Behaviors in the population are represented by numbers in decimal integer (phenotypic) and binary bit string (genotypic) forms. One behavior from the population is emitted at random each time tick, after which a new population of potential behaviors is constructed by recombining parent behavior bit strings. If the emitted behavior produced a benefit to the organism, then parents are chosen on the basis of their phenotypic similarity to the emitted behavior; otherwise, they are chosen at random. After parent behavior recombination, the population is subjected to a small amount of mutation by flipping random bits in the population's bit strings. The behavior generated by this process of selection, reproduction, and mutation reaches equilibrium states that conform to every empirically valid equation of matching theory, exactly and without systematic error. These equations are known to describe the behavior of many vertebrate species, including humans, in a variety of experimental, naturalistic, natural, and social environments. The evolutionary theory also generates instantaneous dynamics and patterns of preference change in constantly changing environments that are consistent with the dynamics of live-organism behavior. These findings support the assertion that the world of behavior we observe and measure is generated by evolutionary dynamics. PsycINFO Database Record (c) 2013 APA, all rights reserved

  2. Dynamic Modelling and Adaptive Traction Control for Mobile Robots

    Directory of Open Access Journals (Sweden)

    A. Albagul

    2004-09-01

    Full Text Available Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used kinematic models to develop motion control strategy for mobile robots. Their argument and assumption that these models are valid if the robot has low speed, low acceleration and light load. However, dynamic modelling of mobile robots is very important as they are designed to travel at higher speed and perform heavy duty work. This paper presents and discusses a new approach to develop a dynamic model and control strategy for wheeled mobile robot which I modelled as a rigid body that roles on two wheels and a castor. The motion control strategy consists of two levels. The first level is dealing with the dynamic of the system and denoted as ‘Low’ level controller. The second level is developed to take care of path planning and trajectory generation.

  3. Adaptive and dynamic meshing methods for numerical simulations

    Science.gov (United States)

    Acikgoz, Nazmiye

    For the numerical simulation of many problems of engineering interest, it is desirable to have an automated mesh adaption tool capable of producing high quality meshes with an affordably low number of mesh points. This is important especially for problems, which are characterized by anisotropic features of the solution and require mesh clustering in the direction of high gradients. Another significant issue in meshing emerges in the area of unsteady simulations with moving boundaries or interfaces, where the motion of the boundary has to be accommodated by deforming the computational grid. Similarly, there exist problems where current mesh needs to be adapted to get more accurate solutions because either the high gradient regions are initially predicted inaccurately or they change location throughout the simulation. To solve these problems, we propose three novel procedures. For this purpose, in the first part of this work, we present an optimization procedure for three-dimensional anisotropic tetrahedral grids based on metric-driven h-adaptation. The desired anisotropy in the grid is dictated by a metric that defines the size, shape, and orientation of the grid elements throughout the computational domain. Through the use of topological and geometrical operators, the mesh is iteratively adapted until the final mesh minimizes a given objective function. In this work, the objective function measures the distance between the metric of each simplex and a target metric, which can be either user-defined (a-priori) or the result of a-posteriori error analysis. During the adaptation process, one tries to decrease the metric-based objective function until the final mesh is compliant with the target within a given tolerance. However, in regions such as corners and complex face intersections, the compliance condition was found to be very difficult or sometimes impossible to satisfy. In order to address this issue, we propose an optimization process based on an ad

  4. Finite-horizon differential games for missile-target interception system using adaptive dynamic programming with input constraints

    Science.gov (United States)

    Sun, Jingliang; Liu, Chunsheng

    2018-01-01

    In this paper, the problem of intercepting a manoeuvring target within a fixed final time is posed in a non-linear constrained zero-sum differential game framework. The Nash equilibrium solution is found by solving the finite-horizon constrained differential game problem via adaptive dynamic programming technique. Besides, a suitable non-quadratic functional is utilised to encode the control constraints into a differential game problem. The single critic network with constant weights and time-varying activation functions is constructed to approximate the solution of associated time-varying Hamilton-Jacobi-Isaacs equation online. To properly satisfy the terminal constraint, an additional error term is incorporated in a novel weight-updating law such that the terminal constraint error is also minimised over time. By utilising Lyapunov's direct method, the closed-loop differential game system and the estimation weight error of the critic network are proved to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is demonstrated by using a simple non-linear system and a non-linear missile-target interception system, assuming first-order dynamics for the interceptor and target.

  5. Adapt or Die

    DEFF Research Database (Denmark)

    Brody, Joshua Eric; Larsen, Kasper Green

    2015-01-01

    In this paper, we study the role non-adaptivity plays in maintaining dynamic data structures. Roughly speaking, a data structure is non-adaptive if the memory locations it reads and/or writes when processing a query or update depend only on the query or update and not on the contents of previously...... read cells. We study such non-adaptive data structures in the cell probe model. This model is one of the least restrictive lower bound models and in particular, cell probe lower bounds apply to data structures developed in the popular word-RAM model. Unfortunately, this generality comes at a high cost......: the highest lower bound proved for any data structure problem is only polylogarithmic. Our main result is to demonstrate that one can in fact obtain polynomial cell probe lower bounds for non-adaptive data structures. To shed more light on the seemingly inherent polylogarithmic lower bound barrier, we study...

  6. Cortical microcircuit dynamics mediating Binocular Rivalry: The role of adaptation in inhibition

    Directory of Open Access Journals (Sweden)

    Panagiota eTheodoni

    2011-11-01

    Full Text Available Perceptual bistability arises when two conflicting interpretations of an ambiguous stimulus or images in binocular rivalry (BR compete for perceptual dominance. From a computational point of view competition models based on cross-inhibition and adaptation have shown that noise is a crucial force for rivalry and operates in balance with adaptation in order to explain the observed alternations in perception. In particular, noise-driven transitions and adaptation-driven oscillations define two dynamical regimes and the system operates near its boundary. In order to gain insights into the microcircuit dynamics mediating spontaneous perceptual alternations we used a reduced recurrent attractor-based biophysically realistic spiking network well known for working memory, attention and decision-making, where a spike-frequency adaptation mechanism is implemented to account for perceptual bistability. We, thus, derived a consistently reduced four-variable population rate model using mean-field techniques and tested it on BR data collected from human subjects. Our model accounts for experimental data parameters such as time dominance, coefficient of variation and gamma distribution. In addition, we show that our model also operates on the boundary between noise and adaptation and agrees with Levelt’s second revised and fourth propositions. These results show for the first time that a consistent reduction of a biophysically realistic spiking network of integrate and fire neurons with spike frequency adaptation could account for BR. Moreover, we demonstrate that BR can be explained only through the dynamics of the competing neuronal pools, without taking into account the adaptation of inhibitory interneurons..However, adaptation of interneurons affects the optimal parametric space of the system, by decreasing the overall adaptation necessary for the bifurcation to occur.

  7. Adaptive Process Management in Highly Dynamic and Pervasive Scenarios

    Directory of Open Access Journals (Sweden)

    Massimiliano de Leoni

    2009-06-01

    Full Text Available Process Management Systems (PMSs are currently more and more used as a supporting tool for cooperative processes in pervasive and highly dynamic situations, such as emergency situations, pervasive healthcare or domotics/home automation. But in all such situations, designed processes can be easily invalidated since the execution environment may change continuously due to frequent unforeseeable events. This paper aims at illustrating the theoretical framework and the concrete implementation of SmartPM, a PMS that features a set of sound and complete techniques to automatically cope with unplanned exceptions. PMS SmartPM is based on a general framework which adopts the Situation Calculus and Indigolog.

  8. High Speed, Low Cost Telemetry Access from Space Development Update on Programmable Ultra Lightweight System Adaptable Radio (PULSAR)

    Science.gov (United States)

    Simms, William Herbert, III; Varnavas, Kosta; Eberly, Eric

    2014-01-01

    Software Defined Radio (SDR) technology has been proven in the commercial sector since the early 1990's. Today's rapid advancement in mobile telephone reliability and power management capabilities exemplifies the effectiveness of the SDR technology for the modern communications market. In contrast, the foundations of transponder technology presently qualified for satellite applications were developed during the early space program of the 1960's. Conventional transponders are built to a specific platform and must be redesigned for every new bus while the SDR is adaptive in nature and can fit numerous applications with no hardware modifications. A SDR uses a minimum amount of analog / Radio Frequency (RF) components to up/down-convert the RF signal to/from a digital format. Once the signal is digitized, all processing is performed using hardware or software logic. Typical SDR digital processes include; filtering, modulation, up/down converting and demodulation. NASA Marshall Space Flight Center (MSFC) Programmable Ultra Lightweight System Adaptable Radio (PULSAR) leverages existing MSFC SDR designs and commercial sector enhanced capabilities to provide a path to a radiation tolerant SDR transponder. These innovations (1) reduce the cost of NASA Low Earth Orbit (LEO) and Deep Space standard transponders, (2) decrease power requirements, and (3) commensurately reduce volume. A second pay-off is the increased SDR flexibility by allowing the same hardware to implement multiple transponder types simply by altering hardware logic - no change of hardware is required - all of which will ultimately be accomplished in orbit. Development of SDR technology for space applications will provide a highly capable, low cost transponder to programs of all sizes. The MSFC PULSAR Project results in a Technology Readiness Level (TRL) 7 low-cost telemetry system available to Smallsat and CubeSat missions, as well as other platforms. This paper documents the continued development and

  9. Nanostructural self-organization and dynamic adaptation of metal-polymer tribosystems

    Science.gov (United States)

    Mashkov, Yu. K.

    2017-02-01

    The results of investigating the effect of nanosize modifiers of a polymer matrix on the nanostructural self-organization of polymer composites and dynamic adaptation of metal-polymer tribosystems, which considerably affect the wear resistance of polymer composite materials, have been analyzed. It has been shown that the physicochemical nanostructural self-organization processes are developed in metal-polymer tribosystems with the formation of thermotropic liquid-crystal structures of the polymer matrix, followed by the transition of the system to the stationary state with a negative feedback that ensures dynamic adaptation of the tribosystem to given operating conditions.

  10. Dynamic Surface Adaptive Robust Control of Unmanned Marine Vehicles with Disturbance Observer

    Directory of Open Access Journals (Sweden)

    Pengchao Zhang

    2018-01-01

    Full Text Available This paper presents a dynamic surface adaptive robust control method with disturbance observer for unmanned marine vehicles (UMV. It uses adaptive law to estimate and compensate the disturbance observer error. Dynamic surface is introduced to solve the “differential explosion” caused by the virtual control derivation in traditional backstepping method. The final controlled system is proved to be globally uniformly bounded based on Lyapunov stability theory. Simulation results illustrate the effectiveness of the proposed controller, which can realize the three-dimensional trajectory tracking for UMV with the systematic uncertainty and time-varying disturbances.

  11. Adaptive synchronization of the complex dynamical network with non-derivative and derivative coupling

    Energy Technology Data Exchange (ETDEWEB)

    Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teachers' College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Sun Wen [School of Mathematics and Information, Yangtze University, Hubei Jingzhou 434023 (China)

    2010-04-05

    This Letter investigates the synchronization of a general complex dynamical network with non-derivative and derivative coupling. Based on LaSalle's invariance principle, adaptive synchronization criteria are obtained. Analytical result shows that under the designed adaptive controllers, a general complex dynamical network with non-derivative and derivative coupling can asymptotically synchronize to a given trajectory, and several useful criteria for synchronization are given. What is more, the coupling matrix is not assumed to be symmetric or irreducible. Finally, simulations results show the method is effective.

  12. Intelligent control of non-linear dynamical system based on the adaptive neurocontroller

    Science.gov (United States)

    Engel, E.; Kovalev, I. V.; Kobezhicov, V.

    2015-10-01

    This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.

  13. Dynamic and adaptive policy models for coalition operations

    Science.gov (United States)

    Verma, Dinesh; Calo, Seraphin; Chakraborty, Supriyo; Bertino, Elisa; Williams, Chris; Tucker, Jeremy; Rivera, Brian; de Mel, Geeth R.

    2017-05-01

    It is envisioned that the success of future military operations depends on the better integration, organizationally and operationally, among allies, coalition members, inter-agency partners, and so forth. However, this leads to a challenging and complex environment where the heterogeneity and dynamism in the operating environment intertwines with the evolving situational factors that affect the decision-making life cycle of the war fighter. Therefore, the users in such environments need secure, accessible, and resilient information infrastructures where policy-based mechanisms adopt the behaviours of the systems to meet end user goals. By specifying and enforcing a policy based model and framework for operations and security which accommodates heterogeneous coalitions, high levels of agility can be enabled to allow rapid assembly and restructuring of system and information resources. However, current prevalent policy models (e.g., rule based event-condition-action model and its variants) are not sufficient to deal with the highly dynamic and plausibly non-deterministic nature of these environments. Therefore, to address the above challenges, in this paper, we present a new approach for policies which enables managed systems to take more autonomic decisions regarding their operations.

  14. Methodology for Simulation and Analysis of Complex Adaptive Supply Network Structure and Dynamics Using Information Theory

    Directory of Open Access Journals (Sweden)

    Joshua Rodewald

    2016-10-01

    Full Text Available Supply networks existing today in many industries can behave as complex adaptive systems making them more difficult to analyze and assess. Being able to fully understand both the complex static and dynamic structures of a complex adaptive supply network (CASN are key to being able to make more informed management decisions and prioritize resources and production throughout the network. Previous efforts to model and analyze CASN have been impeded by the complex, dynamic nature of the systems. However, drawing from other complex adaptive systems sciences, information theory provides a model-free methodology removing many of those barriers, especially concerning complex network structure and dynamics. With minimal information about the network nodes, transfer entropy can be used to reverse engineer the network structure while local transfer entropy can be used to analyze the network structure’s dynamics. Both simulated and real-world networks were analyzed using this methodology. Applying the methodology to CASNs allows the practitioner to capitalize on observations from the highly multidisciplinary field of information theory which provides insights into CASN’s self-organization, emergence, stability/instability, and distributed computation. This not only provides managers with a more thorough understanding of a system’s structure and dynamics for management purposes, but also opens up research opportunities into eventual strategies to monitor and manage emergence and adaption within the environment.

  15. Dynamic game balancing implementation using adaptive algorithm in mobile-based Safari Indonesia game

    Science.gov (United States)

    Yuniarti, Anny; Nata Wardanie, Novita; Kuswardayan, Imam

    2018-03-01

    In developing a game there is one method that should be applied to maintain the interest of players, namely dynamic game balancing. Dynamic game balancing is a process to match a player’s playing style with the behaviour, attributes, and game environment. This study applies dynamic game balancing using adaptive algorithm in scrolling shooter game type called Safari Indonesia which developed using Unity. The game of this type is portrayed by a fighter aircraft character trying to defend itself from insistent enemy attacks. This classic game is chosen to implement adaptive algorithms because it has quite complex attributes to be developed using dynamic game balancing. Tests conducted by distributing questionnaires to a number of players indicate that this method managed to reduce frustration and increase the pleasure factor in playing.

  16. Dynamic adaptation of myocardial proteome during heart failure development

    Science.gov (United States)

    Poesch, Axel; Dörr, Marcus; Völker, Uwe; Grube, Karina; Hammer, Elke; Felix, Stephan B.

    2017-01-01

    Heart failure (HF) development is characterized by huge structural changes that are crucial for disease progression. Analysis of time dependent global proteomic adaptations during HF progression offers the potential to gain deeper insights in the disease development and identify new biomarker candidates. Therefore, hearts of TAC (transverse aortic constriction) and sham mice were examined by cardiac MRI on either day 4, 14, 21, 28, 42, and 56 after surgery (n = 6 per group/time point). At each time point, proteomes of the left (LV) and right ventricles (RV) of TAC and sham mice were analyzed by mass spectrometry (MS). In TAC mice, systolic LV heart function worsened from day 4 to day 14, remained on a stable level from day 14 to day 42, and showed a further pronounced decline at day 56. MS analysis identified in the LV 330 and in RV 246 proteins with altered abundance over time (TAC vs. sham, fc≥±2). Functional categorization of proteins disclosed the time-dependent alteration of different pathways. Heat shock protein beta-7 (HSPB7) displayed differences in abundance in tissue and serum at an early stage of HF. This study not only provides an overview of the time dependent molecular alterations during transition to HF, but also identified HSPB7 as a novel blood biomarker candidate for the onset of cardiac remodeling. PMID:28973020

  17. 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.

  18. 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

  19. Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations.

    Directory of Open Access Journals (Sweden)

    Jian Liu

    Full Text Available In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic systems (CVCSs in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.

  20. Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations.

    Science.gov (United States)

    Liu, Jian; Liu, Kexin; Liu, Shutang

    2017-01-01

    In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.

  1. Normalized value coding explains dynamic adaptation in the human valuation process.

    Science.gov (United States)

    Khaw, Mel W; Glimcher, Paul W; Louie, Kenway

    2017-11-28

    The notion of subjective value is central to choice theories in ecology, economics, and psychology, serving as an integrated decision variable by which options are compared. Subjective value is often assumed to be an absolute quantity, determined in a static manner by the properties of an individual option. Recent neurobiological studies, however, have shown that neural value coding dynamically adapts to the statistics of the recent reward environment, introducing an intrinsic temporal context dependence into the neural representation of value. Whether valuation exhibits this kind of dynamic adaptation at the behavioral level is unknown. Here, we show that the valuation process in human subjects adapts to the history of previous values, with current valuations varying inversely with the average value of recently observed items. The dynamics of this adaptive valuation are captured by divisive normalization, linking these temporal context effects to spatial context effects in decision making as well as spatial and temporal context effects in perception. These findings suggest that adaptation is a universal feature of neural information processing and offer a unifying explanation for contextual phenomena in fields ranging from visual psychophysics to economic choice.

  2. 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.

  3. Supporting Dynamic Adaptive Streaming over HTTP in Wireless Meshed Networks using Random Linear Network Coding

    DEFF Research Database (Denmark)

    Hundebøll, Martin; Pedersen, Morten Videbæk; Roetter, Daniel Enrique Lucani

    2014-01-01

    This work studies the potential and impact of the FRANC network coding protocol for delivering high quality Dynamic Adaptive Streaming over HTTP (DASH) in wireless networks. Although DASH aims to tailor the video quality rate based on the available throughput to the destination, it relies...

  4. Adaptive dynamics on an environmental gradient that changes over a geological time-scale.

    Science.gov (United States)

    Fortelius, Mikael; Geritz, Stefan; Gyllenberg, Mats; Toivonen, Jaakko

    2015-07-07

    The standard adaptive dynamics framework assumes two timescales, i.e. fast population dynamics and slow evolutionary dynamics. We further assume a third timescale, which is even slower than the evolutionary timescale. We call this the geological timescale and we assume that slow climatic change occurs within this timescale. We study the evolution of our model population over this very slow geological timescale with bifurcation plots of the standard adaptive dynamics framework. The bifurcation parameter being varied describes the abiotic environment that changes over the geological timescale. We construct evolutionary trees over the geological timescale and observe both gradual phenotypic evolution and punctuated branching events. We concur with the established notion that branching of a monomorphic population on an environmental gradient only happens when the gradient is not too shallow and not too steep. However, we show that evolution within the habitat can produce polymorphic populations that inhabit steep gradients. What is necessary is that the environmental gradient at some point in time is such that the initial branching of the monomorphic population can occur. We also find that phenotypes adapted to environments in the middle of the existing environmental range are more likely to branch than phenotypes adapted to extreme environments. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. A Self-adaptive Scope Allocation Scheme for Labeling Dynamic XML Documents

    NARCIS (Netherlands)

    Shen, Y.; Feng, L.; Shen, T.; Wang, B.

    This paper proposes a self-adaptive scope allocation scheme for labeling dynamic XML documents. It is general, light-weight and can be built upon existing data retrieval mechanisms. Bayesian inference is used to compute the actual scope allocated for labeling a certain node based on both the prior

  6. High Dynamic Range adaptive ΔΣ-based Focal Plane Array architecture

    KAUST Repository

    Yao, Shun; Kavusi, Sam; Salama, Khaled N.

    2012-01-01

    In this paper, an Adaptive Delta-Sigma based architecture for High Dynamic Range (HDR) Focal Plane Arrays is presented. The noise shaping effect of the Delta-Sigma modulation in the low end, and the distortion noise induced in the high end of Photo

  7. Adaptive fuzzy wavelet network control of second order multi-agent systems with unknown nonlinear dynamics.

    Science.gov (United States)

    Taheri, Mehdi; Sheikholeslam, Farid; Najafi, Majddedin; Zekri, Maryam

    2017-07-01

    In this paper, consensus problem is considered for second order multi-agent systems with unknown nonlinear dynamics under undirected graphs. A novel distributed control strategy is suggested for leaderless systems based on adaptive fuzzy wavelet networks. Adaptive fuzzy wavelet networks are employed to compensate for the effect of unknown nonlinear dynamics. Moreover, the proposed method is developed for leader following systems and leader following systems with state time delays. Lyapunov functions are applied to prove uniformly ultimately bounded stability of closed loop systems and to obtain adaptive laws. Three simulation examples are presented to illustrate the effectiveness of the proposed control algorithms. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  8. HOLD MODE BASED DYNAMIC PRIORITY LOAD ADAPTIVE INTERPICONET SCHEDULING FOR BLUETOOTH SCATTERNETS

    Directory of Open Access Journals (Sweden)

    G.S. Mahalakshmi

    2011-09-01

    Full Text Available Scheduling in piconets has emerged as a challenging research area. Interpiconet scheduling focuses on when a bridge is switched among various piconets and how a bridge node communicates with the masters in different piconets. This paper proposes an interpiconet scheduling algorithm named, hold mode based dynamic traffic priority load adaptive scheduling. The bridges are adaptively switched between the piconets according to various traffic loads. The main goal is to maximize the utilization of the bridge by reducing the bridge switch wastes, utilize intelligent decision making algorithm, resolve conflict between the masters, and allow negotiation for bridge utilization in HDPLIS using bridge failure-bridge repair procedure . The Hold mode - dynamic traffic - priority based - load adaptive scheduling reduces the number of bridge switch wastes and hence increases the efficiency of the bridge which results in increased performance of the system.

  9. Wavelet and adaptive methods for time dependent problems and applications in aerosol dynamics

    Science.gov (United States)

    Guo, Qiang

    Time dependent partial differential equations (PDEs) are widely used as mathematical models of environmental problems. Aerosols are now clearly identified as an important factor in many environmental aspects of climate and radiative forcing processes, as well as in the health effects of air quality. The mathematical models for the aerosol dynamics with respect to size distribution are nonlinear partial differential and integral equations, which describe processes of condensation, coagulation and deposition. Simulating the general aerosol dynamic equations on time, particle size and space exhibits serious difficulties because the size dimension ranges from a few nanometer to several micrometer while the spatial dimension is usually described with kilometers. Therefore, it is an important and challenging task to develop efficient techniques for solving time dependent dynamic equations. In this thesis, we develop and analyze efficient wavelet and adaptive methods for the time dependent dynamic equations on particle size and further apply them to the spatial aerosol dynamic systems. Wavelet Galerkin method is proposed to solve the aerosol dynamic equations on time and particle size due to the fact that aerosol distribution changes strongly along size direction and the wavelet technique can solve it very efficiently. Daubechies' wavelets are considered in the study due to the fact that they possess useful properties like orthogonality, compact support, exact representation of polynomials to a certain degree. Another problem encountered in the solution of the aerosol dynamic equations results from the hyperbolic form due to the condensation growth term. We propose a new characteristic-based fully adaptive multiresolution numerical scheme for solving the aerosol dynamic equation, which combines the attractive advantages of adaptive multiresolution technique and the characteristics method. On the aspect of theoretical analysis, the global existence and uniqueness of

  10. The Dynamics of Vulnerability and Implications for Climate Change Adaptation: Lessons from Urban Water Management

    Science.gov (United States)

    Dilling, L.; Daly, M.; Travis, W.; Wilhelmi, O.; Klein, R.; Kenney, D.; Ray, A. J.; Miller, K.

    2013-12-01

    Recent reports and scholarship have suggested that adapting to current climate variability may represent a "no regrets" strategy for adapting to climate change. Filling "adaptation deficits" and other approaches that rely on addressing current vulnerabilities are of course helpful for responding to current climate variability, but we find here that they are not sufficient for adapting to climate change. First, following a comprehensive review and unique synthesis of the natural hazards and climate adaptation literatures, we advance six reasons why adapting to climate variability is not sufficient for adapting to climate change: 1) Vulnerability is different at different levels of exposure; 2) Coping with climate variability is not equivalent to adaptation to longer term change; 3) The socioeconomic context for vulnerability is constantly changing; 4) The perception of risk associated with climate variability does not necessarily promote adaptive behavior in the face of climate change; 5) Adaptations made to short term climate variability may reduce the flexibility of the system in the long term; and 6) Adaptive actions may shift vulnerabilities to other parts of the system or to other people. Instead we suggest that decision makers faced with choices to adapt to climate change must consider the dynamics of vulnerability in a connected system-- how choices made in one part of the system might impact other valued outcomes or even create new vulnerabilities. Furthermore we suggest that rather than expressing climate change adaptation as an extension of adaptation to climate variability, the research and practice communities would do well to articulate adaptation as an imperfect policy, with tradeoffs and consequences and that decisions be prioritized to preserve flexibility be revisited often as climate change unfolds. We then present the results of a number of empirical studies of decision making for drought in urban water systems in the United States to understand

  11. Adaptive Control Based Harvesting Strategy for a Predator-Prey Dynamical System.

    Science.gov (United States)

    Sen, Moitri; Simha, Ashutosh; Raha, Soumyendu

    2018-04-23

    This paper deals with designing a harvesting control strategy for a predator-prey dynamical system, with parametric uncertainties and exogenous disturbances. A feedback control law for the harvesting rate of the predator is formulated such that the population dynamics is asymptotically stabilized at a positive operating point, while maintaining a positive, steady state harvesting rate. The hierarchical block strict feedback structure of the dynamics is exploited in designing a backstepping control law, based on Lyapunov theory. In order to account for unknown parameters, an adaptive control strategy has been proposed in which the control law depends on an adaptive variable which tracks the unknown parameter. Further, a switching component has been incorporated to robustify the control performance against bounded disturbances. Proofs have been provided to show that the proposed adaptive control strategy ensures asymptotic stability of the dynamics at a desired operating point, as well as exact parameter learning in the disturbance-free case and learning with bounded error in the disturbance prone case. The dynamics, with uncertainty in the death rate of the predator, subjected to a bounded disturbance has been simulated with the proposed control strategy.

  12. Neural network-based adaptive dynamic surface control for permanent magnet synchronous motors.

    Science.gov (United States)

    Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Chen, Bing; Lin, Chong

    2015-03-01

    This brief considers the problem of neural networks (NNs)-based adaptive dynamic surface control (DSC) for permanent magnet synchronous motors (PMSMs) with parameter uncertainties and load torque disturbance. First, NNs are used to approximate the unknown and nonlinear functions of PMSM drive system and a novel adaptive DSC is constructed to avoid the explosion of complexity in the backstepping design. Next, under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced to only one, and the designed neural controllers structure is much simpler than some existing results in literature, which can guarantee that the tracking error converges to a small neighborhood of the origin. Then, simulations are given to illustrate the effectiveness and potential of the new design technique.

  13. Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.

    Science.gov (United States)

    Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L

    2017-10-01

    The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.

  14. Adaptation.

    Science.gov (United States)

    Broom, Donald M

    2006-01-01

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

  15. We be jammin’: an update on pectin biosynthesis, trafficking and dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Charles T.

    2015-11-20

    Pectins are complex polysaccharides that contain acidic sugars and are major determinants of the cohesion, adhesion, extensibility, porosity and electrostatic potential of plant cell walls. Recent evidence has solidified their positions as key regulators of cellular growth and tissue morphogenesis, although important details of how they achieve this regulation are still missing. Pectins are also hypothesized to function as ligands for wall integrity sensors that enable plant cells to respond to intrinsic defects in wall biomechanics and to wall degradation by attacking pathogens. This update highlights recent advances in our understanding of the biosynthesis of pectins, how they are delivered to the cell surface and become incorporated into the cell wall matrix and how pectins are modified over time in the apoplast. It also poses unanswered questions for further research into this enigmatic but essential class of carbohydrate polymers.

  16. Update on Small Modular Reactors Dynamic System Modeling Tool: Web Application

    International Nuclear Information System (INIS)

    Hale, Richard Edward; Cetiner, Sacit M.; Fugate, David L.; Batteh, John J; Tiller, Michael M.

    2015-01-01

    Previous reports focused on the development of component and system models as well as end-to-end system models using Modelica and Dymola for two advanced reactor architectures: (1) Advanced Liquid Metal Reactor and (2) fluoride high-temperature reactor (FHR). The focus of this report is the release of the first beta version of the web-based application for model use and collaboration, as well as an update on the FHR model. The web-based application allows novice users to configure end-to-end system models from preconfigured choices to investigate the instrumentation and controls implications of these designs and allows for the collaborative development of individual component models that can be benchmarked against test systems for potential inclusion in the model library. A description of this application is provided along with examples of its use and a listing and discussion of all the models that currently exist in the library.

  17. Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making

    Science.gov (United States)

    Kwakkel, Jan; Haasnoot, Marjolijn

    2017-04-01

    Dealing with climate risks in water management requires confronting a wide variety of deeply uncertain factors, while navigating a many dimensional space of trade-offs amongst objectives. There is an emerging body of literature on supporting this type of decision problem, under the label of decision making under deep uncertainty. Two approaches within this literature are Many-Objective Robust Decision Making, and Dynamic Adaptive Policy Pathways. In recent work, these approaches have been compared. One of the main conclusions of this comparison was that they are highly complementary. Many-Objective Robust Decision Making is a model based decision support approach, while Dynamic Adaptive Policy Pathways is primarily a conceptual framework for the design of flexible strategies that can be adapted over time in response to how the future is actually unfolding. In this research we explore this complementarity in more detail. Specifically, we demonstrate how Many-Objective Robust Decision Making can be used to design adaptation pathways. We demonstrate this combined approach using a water management problem, in the Netherlands. The water level of Lake IJselmeer, the main fresh water resource of the Netherlands, is currently managed through discharge by gravity. Due to climate change, this won't be possible in the future, unless water levels are changed. Changing the water level has undesirable flood risk and spatial planning consequences. The challenge is to find promising adaptation pathways that balance objectives related to fresh water supply, flood risk, and spatial issues, while accounting for uncertain climatic and land use change. We conclude that the combination of Many-Objective Robust Decision Making and Dynamic Adaptive Policy Pathways is particularly suited for dealing with deeply uncertain climate risks.

  18. Dynamic balance during walking adaptability tasks in individuals post-stroke.

    Science.gov (United States)

    Vistamehr, Arian; Balasubramanian, Chitralakshmi K; Clark, David J; Neptune, Richard R; Fox, Emily J

    2018-04-24

    Maintaining dynamic balance during community ambulation is a major challenge post-stroke. Community ambulation requires performance of steady-state level walking as well as tasks that require walking adaptability. Prior studies on balance control post-stroke have mainly focused on steady-state walking, but walking adaptability tasks have received little attention. The purpose of this study was to quantify and compare dynamic balance requirements during common walking adaptability tasks post-stroke and in healthy adults and identify differences in underlying mechanisms used for maintaining dynamic balance. Kinematic data were collected from fifteen individuals with post-stroke hemiparesis during steady-state forward and backward walking, obstacle negotiation, and step-up tasks. In addition, data from ten healthy adults provided the basis for comparison. Dynamic balance was quantified using the peak-to-peak range of whole-body angular-momentum in each anatomical plane during the paretic, nonparetic and healthy control single-leg-stance phase of the gait cycle. To understand differences in some of the key underlying mechanisms for maintaining dynamic balance, foot placement and plantarflexor muscle activation were examined. Individuals post-stroke had significant dynamic balance deficits in the frontal plane across most tasks, particularly during the paretic single-leg-stance. Frontal plane balance deficits were associated with wider paretic foot placement, elevated body center-of-mass, and lower soleus activity. Further, the obstacle negotiation task imposed a higher balance requirement, particularly during the trailing leg single-stance. Thus, improving paretic foot placement and ankle plantarflexor activity, particularly during obstacle negotiation, may be important rehabilitation targets to enhance dynamic balance during post-stroke community ambulation. Copyright © 2018. Published by Elsevier Ltd.

  19. Adaptation

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

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

  20. Facial Expression Aftereffect Revealed by Adaption to Emotion-Invisible Dynamic Bubbled Faces

    Science.gov (United States)

    Luo, Chengwen; Wang, Qingyun; Schyns, Philippe G.; Kingdom, Frederick A. A.; Xu, Hong

    2015-01-01

    Visual adaptation is a powerful tool to probe the short-term plasticity of the visual system. Adapting to local features such as the oriented lines can distort our judgment of subsequently presented lines, the tilt aftereffect. The tilt aftereffect is believed to be processed at the low-level of the visual cortex, such as V1. Adaptation to faces, on the other hand, can produce significant aftereffects in high-level traits such as identity, expression, and ethnicity. However, whether face adaptation necessitate awareness of face features is debatable. In the current study, we investigated whether facial expression aftereffects (FEAE) can be generated by partially visible faces. We first generated partially visible faces using the bubbles technique, in which the face was seen through randomly positioned circular apertures, and selected the bubbled faces for which the subjects were unable to identify happy or sad expressions. When the subjects adapted to static displays of these partial faces, no significant FEAE was found. However, when the subjects adapted to a dynamic video display of a series of different partial faces, a significant FEAE was observed. In both conditions, subjects could not identify facial expression in the individual adapting faces. These results suggest that our visual system is able to integrate unrecognizable partial faces over a short period of time and that the integrated percept affects our judgment on subsequently presented faces. We conclude that FEAE can be generated by partial face with little facial expression cues, implying that our cognitive system fills-in the missing parts during adaptation, or the subcortical structures are activated by the bubbled faces without conscious recognition of emotion during adaptation. PMID:26717572

  1. Macroscopic description of complex adaptive networks coevolving with dynamic node states

    Science.gov (United States)

    Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

    2015-05-01

    In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

  2. Adaptive Synchronization of Fractional Order Complex-Variable Dynamical Networks via Pinning Control

    Science.gov (United States)

    Ding, Da-Wei; Yan, Jie; Wang, Nian; Liang, Dong

    2017-09-01

    In this paper, the synchronization of fractional order complex-variable dynamical networks is studied using an adaptive pinning control strategy based on close center degree. Some effective criteria for global synchronization of fractional order complex-variable dynamical networks are derived based on the Lyapunov stability theory. From the theoretical analysis, one concludes that under appropriate conditions, the complex-variable dynamical networks can realize the global synchronization by using the proper adaptive pinning control method. Meanwhile, we succeed in solving the problem about how much coupling strength should be applied to ensure the synchronization of the fractional order complex networks. Therefore, compared with the existing results, the synchronization method in this paper is more general and convenient. This result extends the synchronization condition of the real-variable dynamical networks to the complex-valued field, which makes our research more practical. Finally, two simulation examples show that the derived theoretical results are valid and the proposed adaptive pinning method is effective. Supported by National Natural Science Foundation of China under Grant No. 61201227, National Natural Science Foundation of China Guangdong Joint Fund under Grant No. U1201255, the Natural Science Foundation of Anhui Province under Grant No. 1208085MF93, 211 Innovation Team of Anhui University under Grant Nos. KJTD007A and KJTD001B, and also supported by Chinese Scholarship Council

  3. The absence or temporal offset of visual feedback does not influence adaptation to novel movement dynamics.

    Science.gov (United States)

    McKenna, Erin; Bray, Laurence C Jayet; Zhou, Weiwei; Joiner, Wilsaan M

    2017-10-01

    Delays in transmitting and processing sensory information require correctly associating delayed feedback to issued motor commands for accurate error compensation. The flexibility of this alignment between motor signals and feedback has been demonstrated for movement recalibration to visual manipulations, but the alignment dependence for adapting movement dynamics is largely unknown. Here we examined the effect of visual feedback manipulations on force-field adaptation. Three subject groups used a manipulandum while experiencing a lag in the corresponding cursor motion (0, 75, or 150 ms). When the offset was applied at the start of the session (continuous condition), adaptation was not significantly different between groups. However, these similarities may be due to acclimation to the offset before motor adaptation. We tested additional subjects who experienced the same delays concurrent with the introduction of the perturbation (abrupt condition). In this case adaptation was statistically indistinguishable from the continuous condition, indicating that acclimation to feedback delay was not a factor. In addition, end-point errors were not significantly different across the delay or onset conditions, but end-point correction (e.g., deceleration duration) was influenced by the temporal offset. As an additional control, we tested a group of subjects who performed without visual feedback and found comparable movement adaptation results. These results suggest that visual feedback manipulation (absence or temporal misalignment) does not affect adaptation to novel dynamics, independent of both acclimation and perceptual awareness. These findings could have implications for modeling how the motor system adjusts to errors despite concurrent delays in sensory feedback information. NEW & NOTEWORTHY A temporal offset between movement and distorted visual feedback (e.g., visuomotor rotation) influences the subsequent motor recalibration, but the effects of this offset for

  4. 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).

  5. Distributed Consensus-Based Robust Adaptive Formation Control for Nonholonomic Mobile Robots with Partial Known Dynamics

    Directory of Open Access Journals (Sweden)

    Zhaoxia Peng

    2014-01-01

    Full Text Available This paper investigates the distributed consensus-based robust adaptive formation control for nonholonomic mobile robots with partially known dynamics. Firstly, multirobot formation control problem has been converted into a state consensus problem. Secondly, the practical control strategies, which incorporate the distributed kinematic controllers and the robust adaptive torque controllers, are designed for solving the formation control problem. Thirdly, the specified reference trajectory for the geometric centroid of the formation is assumed as the trajectory of a virtual leader, whose information is available to only a subset of the followers. Finally, numerical results are provided to illustrate the effectiveness of the proposed control approaches.

  6. A mobile communication device adapted to provide a dynamic display arrangement

    DEFF Research Database (Denmark)

    2011-01-01

    The invention relates to a mobile communication device comprising a light projector adapted to project a multi-coloured image onto a surface; a hinged mirror comprising a first mirror part adapted to be tilted around the hinge into the light path of the light projector; wherein the first mirror...... part comprises means for correcting a skew angle in the multi-coloured image projected onto a surface. Thereby is achieved that the mobile communication device is able to provide RGB full colour dynamic image projection which is preferred over monochromatic laser projection because it is a speckle free...... and eye-friendly projection....

  7. 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

  8. Force adaptation transfers to untrained workspace regions in children: evidence for developing inverse dynamic motor models.

    Science.gov (United States)

    Jansen-Osmann, Petra; Richter, Stefanie; Konczak, Jürgen; Kalveram, Karl-Theodor

    2002-03-01

    When humans perform goal-directed arm movements under the influence of an external damping force, they learn to adapt to these external dynamics. After removal of the external force field, they reveal kinematic aftereffects that are indicative of a neural controller that still compensates the no longer existing force. Such behavior suggests that the adult human nervous system uses a neural representation of inverse arm dynamics to control upper-extremity motion. Central to the notion of an inverse dynamic model (IDM) is that learning generalizes. Consequently, aftereffects should be observable even in untrained workspace regions. Adults have shown such behavior, but the ontogenetic development of this process remains unclear. This study examines the adaptive behavior of children and investigates whether learning a force field in one hemifield of the right arm workspace has an effect on force adaptation in the other hemifield. Thirty children (aged 6-10 years) and ten adults performed 30 degrees elbow flexion movements under two conditions of external damping (negative and null). We found that learning to compensate an external damping force transferred to the opposite hemifield, which indicates that a model of the limb dynamics rather than an association of visited space and experienced force was acquired. Aftereffects were more pronounced in the younger children and readaptation to a null-force condition was prolonged. This finding is consistent with the view that IDMs in children are imprecise neural representations of the actual arm dynamics. It indicates that the acquisition of IDMs is a developmental achievement and that the human motor system is inherently flexible enough to adapt to any novel force within the limits of the organism's biomechanics.

  9. Parallel Adaptive Mesh Refinement for High-Order Finite-Volume Schemes in Computational Fluid Dynamics

    Science.gov (United States)

    Schwing, Alan Michael

    For computational fluid dynamics, the governing equations are solved on a discretized domain of nodes, faces, and cells. The quality of the grid or mesh can be a driving source for error in the results. While refinement studies can help guide the creation of a mesh, grid quality is largely determined by user expertise and understanding of the flow physics. Adaptive mesh refinement is a technique for enriching the mesh during a simulation based on metrics for error, impact on important parameters, or location of important flow features. This can offload from the user some of the difficult and ambiguous decisions necessary when discretizing the domain. This work explores the implementation of adaptive mesh refinement in an implicit, unstructured, finite-volume solver. Consideration is made for applying modern computational techniques in the presence of hanging nodes and refined cells. The approach is developed to be independent of the flow solver in order to provide a path for augmenting existing codes. It is designed to be applicable for unsteady simulations and refinement and coarsening of the grid does not impact the conservatism of the underlying numerics. The effect on high-order numerical fluxes of fourth- and sixth-order are explored. Provided the criteria for refinement is appropriately selected, solutions obtained using adapted meshes have no additional error when compared to results obtained on traditional, unadapted meshes. In order to leverage large-scale computational resources common today, the methods are parallelized using MPI. Parallel performance is considered for several test problems in order to assess scalability of both adapted and unadapted grids. Dynamic repartitioning of the mesh during refinement is crucial for load balancing an evolving grid. Development of the methods outlined here depend on a dual-memory approach that is described in detail. Validation of the solver developed here against a number of motivating problems shows favorable

  10. Improving the adaptability of simulated evolutionary swarm robots in dynamically changing environments.

    Directory of Open Access Journals (Sweden)

    Yao Yao

    Full Text Available One of the important challenges in the field of evolutionary robotics is the development of systems that can adapt to a changing environment. However, the ability to adapt to unknown and fluctuating environments is not straightforward. Here, we explore the adaptive potential of simulated swarm robots that contain a genomic encoding of a bio-inspired gene regulatory network (GRN. An artificial genome is combined with a flexible agent-based system, representing the activated part of the regulatory network that transduces environmental cues into phenotypic behaviour. Using an artificial life simulation framework that mimics a dynamically changing environment, we show that separating the static from the conditionally active part of the network contributes to a better adaptive behaviour. Furthermore, in contrast with most hitherto developed ANN-based systems that need to re-optimize their complete controller network from scratch each time they are subjected to novel conditions, our system uses its genome to store GRNs whose performance was optimized under a particular environmental condition for a sufficiently long time. When subjected to a new environment, the previous condition-specific GRN might become inactivated, but remains present. This ability to store 'good behaviour' and to disconnect it from the novel rewiring that is essential under a new condition allows faster re-adaptation if any of the previously observed environmental conditions is reencountered. As we show here, applying these evolutionary-based principles leads to accelerated and improved adaptive evolution in a non-stable environment.

  11. Improving the Adaptability of Simulated Evolutionary Swarm Robots in Dynamically Changing Environments

    Science.gov (United States)

    Yao, Yao; Marchal, Kathleen; Van de Peer, Yves

    2014-01-01

    One of the important challenges in the field of evolutionary robotics is the development of systems that can adapt to a changing environment. However, the ability to adapt to unknown and fluctuating environments is not straightforward. Here, we explore the adaptive potential of simulated swarm robots that contain a genomic encoding of a bio-inspired gene regulatory network (GRN). An artificial genome is combined with a flexible agent-based system, representing the activated part of the regulatory network that transduces environmental cues into phenotypic behaviour. Using an artificial life simulation framework that mimics a dynamically changing environment, we show that separating the static from the conditionally active part of the network contributes to a better adaptive behaviour. Furthermore, in contrast with most hitherto developed ANN-based systems that need to re-optimize their complete controller network from scratch each time they are subjected to novel conditions, our system uses its genome to store GRNs whose performance was optimized under a particular environmental condition for a sufficiently long time. When subjected to a new environment, the previous condition-specific GRN might become inactivated, but remains present. This ability to store ‘good behaviour’ and to disconnect it from the novel rewiring that is essential under a new condition allows faster re-adaptation if any of the previously observed environmental conditions is reencountered. As we show here, applying these evolutionary-based principles leads to accelerated and improved adaptive evolution in a non-stable environment. PMID:24599485

  12. Weather and Climate Manipulation as an Optimal Control for Adaptive Dynamical Systems

    Directory of Open Access Journals (Sweden)

    Sergei A. Soldatenko

    2017-01-01

    Full Text Available The weather and climate manipulation is examined as an optimal control problem for the earth climate system, which is considered as a complex adaptive dynamical system. Weather and climate manipulations are actually amorphous operations. Since their objectives are usually formulated vaguely, the expected results are fairly unpredictable and uncertain. However, weather and climate modification is a purposeful process and, therefore, we can formulate operations to manipulate weather and climate as the optimization problem within the framework of the optimal control theory. The complexity of the earth’s climate system is discussed and illustrated using the simplified low-order coupled chaotic dynamical system. The necessary conditions of optimality are derived for the large-scale atmospheric dynamics. This confirms that even a relatively simplified control problem for the atmospheric dynamics requires significant efforts to obtain the solution.

  13. High protein flexibility and reduced hydration water dynamics are key pressure adaptive strategies in prokaryotes

    KAUST Repository

    Martinez, N.

    2016-09-06

    Water and protein dynamics on a nanometer scale were measured by quasi-elastic neutron scattering in the piezophile archaeon Thermococcus barophilus and the closely related pressure-sensitive Thermococcus kodakarensis, at 0.1 and 40 MPa. We show that cells of the pressure sensitive organism exhibit higher intrinsic stability. Both the hydration water dynamics and the fast protein and lipid dynamics are reduced under pressure. In contrast, the proteome of T. barophilus is more pressure sensitive than that of T. kodakarensis. The diffusion coefficient of hydration water is reduced, while the fast protein and lipid dynamics are slightly enhanced with increasing pressure. These findings show that the coupling between hydration water and cellular constituents might not be simply a master-slave relationship. We propose that the high flexibility of the T. barophilus proteome associated with reduced hydration water may be the keys to the molecular adaptation of the cells to high hydrostatic pressure.

  14. High protein flexibility and reduced hydration water dynamics are key pressure adaptive strategies in prokaryotes

    KAUST Repository

    Martinez, N.; Michoud, Gregoire; Cario, A.; Ollivier, J.; Franzetti, B.; Jebbar, M.; Oger, P.; Peters, J.

    2016-01-01

    Water and protein dynamics on a nanometer scale were measured by quasi-elastic neutron scattering in the piezophile archaeon Thermococcus barophilus and the closely related pressure-sensitive Thermococcus kodakarensis, at 0.1 and 40 MPa. We show that cells of the pressure sensitive organism exhibit higher intrinsic stability. Both the hydration water dynamics and the fast protein and lipid dynamics are reduced under pressure. In contrast, the proteome of T. barophilus is more pressure sensitive than that of T. kodakarensis. The diffusion coefficient of hydration water is reduced, while the fast protein and lipid dynamics are slightly enhanced with increasing pressure. These findings show that the coupling between hydration water and cellular constituents might not be simply a master-slave relationship. We propose that the high flexibility of the T. barophilus proteome associated with reduced hydration water may be the keys to the molecular adaptation of the cells to high hydrostatic pressure.

  15. Self adaptive internal combustion engine control for hydrogen mixtures based on piezoelectric dynamic cylinder pressure transducers

    Energy Technology Data Exchange (ETDEWEB)

    Courteau, R.; Bose, T. K. [Universite du Quebec a Trois-Rivieres, Hydrogen Research Institute, Trois-Rivieres, PQ (Canada)

    2004-07-01

    An algorithm for self-adaptive tuning of an internal combustion engine is proposed, based on a Kalman filter operating on a few selected metrics of the dynamic pressure curve. Piezoelectric transducers are devices to monitor dynamic cylinder pressure; spark plugs with embedded piezo elements are now available to provide diagnostic engine functions. Such transducers are also capable of providing signals to the engine controller to perform auto tuning, a function that is considered very useful particularly in vehicles using alternative fuels whose characteristics frequently show variations between fill-ups. 2 refs., 2 figs.

  16. Chaos Synchronization Using Adaptive Dynamic Neural Network Controller with Variable Learning Rates

    Directory of Open Access Journals (Sweden)

    Chih-Hong Kao

    2011-01-01

    Full Text Available This paper addresses the synchronization of chaotic gyros with unknown parameters and external disturbance via an adaptive dynamic neural network control (ADNNC system. The proposed ADNNC system is composed of a neural controller and a smooth compensator. The neural controller uses a dynamic RBF (DRBF network to online approximate an ideal controller. The DRBF network can create new hidden neurons online if the input data falls outside the hidden layer and prune the insignificant hidden neurons online if the hidden neuron is inappropriate. The smooth compensator is designed to compensate for the approximation error between the neural controller and the ideal controller. Moreover, the variable learning rates of the parameter adaptation laws are derived based on a discrete-type Lyapunov function to speed up the convergence rate of the tracking error. Finally, the simulation results which verified the chaotic behavior of two nonlinear identical chaotic gyros can be synchronized using the proposed ADNNC scheme.

  17. Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network

    International Nuclear Information System (INIS)

    Mai, Huanhuan; Liao, Xiaofeng; Song, Gangbing

    2013-01-01

    Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller. (paper)

  18. Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network

    Science.gov (United States)

    Mai, Huanhuan; Song, Gangbing; Liao, Xiaofeng

    2013-01-01

    Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller.

  19. Behavioral and neural Darwinism: selectionist function and mechanism in adaptive behavior dynamics.

    Science.gov (United States)

    McDowell, J J

    2010-05-01

    An evolutionary theory of behavior dynamics and a theory of neuronal group selection share a common selectionist framework. The theory of behavior dynamics instantiates abstractly the idea that behavior is selected by its consequences. It implements Darwinian principles of selection, reproduction, and mutation to generate adaptive behavior in virtual organisms. The behavior generated by the theory has been shown to be quantitatively indistinguishable from that of live organisms. The theory of neuronal group selection suggests a mechanism whereby the abstract principles of the evolutionary theory may be implemented in the nervous systems of biological organisms. According to this theory, groups of neurons subserving behavior may be selected by synaptic modifications that occur when the consequences of behavior activate value systems in the brain. Together, these theories constitute a framework for a comprehensive account of adaptive behavior that extends from brain function to the behavior of whole organisms in quantitative detail. Copyright (c) 2009 Elsevier B.V. All rights reserved.

  20. Understanding role of genome dynamics in host adaptation of gut commensal, L. reuteri

    Directory of Open Access Journals (Sweden)

    Shikha Sharma

    2017-10-01

    Full Text Available Lactobacillus reuteri is a gram-positive gut commensal and exhibits noteworthy adaptation to its vertebrate hosts. Host adaptation is often driven by inter-strain genome dynamics like expansion of insertion sequences that lead to acquisition and loss of gene(s and creation of large dynamic regions. In this regard we carried in-house genome sequencing of large number of L. reuteri strains origination from human, chicken, pig and rodents. We further next generation sequence data in understanding invasion and expansion of an IS element in shaping genome of strains belonging to human associated lineage. Finally, we share our experience in high-throughput genomic library preparation and generating high quality sequence data of a very low GC bacterium like L. reuteri.

  1. Inversion for Refractivity Parameters Using a Dynamic Adaptive Cuckoo Search with Crossover Operator Algorithm

    Directory of Open Access Journals (Sweden)

    Zhihua Zhang

    2016-01-01

    Full Text Available Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO. Rechenberg’s 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter.

  2. Inversion for Refractivity Parameters Using a Dynamic Adaptive Cuckoo Search with Crossover Operator Algorithm.

    Science.gov (United States)

    Zhang, Zhihua; Sheng, Zheng; Shi, Hanqing; Fan, Zhiqiang

    2016-01-01

    Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg's 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter.

  3. Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors.

    Science.gov (United States)

    Zhu, Dongchen; Li, Jiamao; Wang, Xianshun; Peng, Jingquan; Shi, Wenjun; Zhang, Xiaolin

    2018-04-03

    Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison.

  4. Online Adaptive Optimal Control of Vehicle Active Suspension Systems Using Single-Network Approximate Dynamic Programming

    Directory of Open Access Journals (Sweden)

    Zhi-Jun Fu

    2017-01-01

    Full Text Available In view of the performance requirements (e.g., ride comfort, road holding, and suspension space limitation for vehicle suspension systems, this paper proposes an adaptive optimal control method for quarter-car active suspension system by using the approximate dynamic programming approach (ADP. Online optimal control law is obtained by using a single adaptive critic NN to approximate the solution of the Hamilton-Jacobi-Bellman (HJB equation. Stability of the closed-loop system is proved by Lyapunov theory. Compared with the classic linear quadratic regulator (LQR approach, the proposed ADP-based adaptive optimal control method demonstrates improved performance in the presence of parametric uncertainties (e.g., sprung mass and unknown road displacement. Numerical simulation results of a sedan suspension system are presented to verify the effectiveness of the proposed control strategy.

  5. Quantum Information Biology: From Theory of Open Quantum Systems to Adaptive Dynamics

    Science.gov (United States)

    Asano, Masanari; Basieva, Irina; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

    This chapter reviews quantum(-like) information biology (QIB). Here biology is treated widely as even covering cognition and its derivatives: psychology and decision making, sociology, and behavioral economics and finances. QIB provides an integrative description of information processing by bio-systems at all scales of life: from proteins and cells to cognition, ecological and social systems. Mathematically QIB is based on the theory of adaptive quantum systems (which covers also open quantum systems). Ideologically QIB is based on the quantum-like (QL) paradigm: complex bio-systems process information in accordance with the laws of quantum information and probability. This paradigm is supported by plenty of statistical bio-data collected at all bio-scales. QIB re ects the two fundamental principles: a) adaptivity; and, b) openness (bio-systems are fundamentally open). In addition, quantum adaptive dynamics provides the most generally possible mathematical representation of these principles.

  6. Structure identification and adaptive synchronization of uncertain general complex dynamical networks

    Energy Technology Data Exchange (ETDEWEB)

    Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teacher' s College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Lu Hongqian [Shandong Institute of Light Industry, Shandong Jinan 250353 (China)

    2009-12-28

    This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.

  7. Calculation Method for Equilibrium Points in Dynamical Systems Based on Adaptive Sinchronization

    Directory of Open Access Journals (Sweden)

    Manuel Prian Rodríguez

    2017-12-01

    Full Text Available In this work, a control system is proposed as an equivalent numerical procedure whose aim is to obtain the natural equilibrium points of a dynamical system. These equilibrium points may be employed later as setpoint signal for different control techniques. The proposed procedure is based on the adaptive synchronization between an oscillator and a reference model driven by the oscillator state variables. A stability analysis is carried out and a simplified algorithm is proposed. Finally, satisfactory simulation results are shown.

  8. Structure identification and adaptive synchronization of uncertain general complex dynamical networks

    International Nuclear Information System (INIS)

    Xu Yuhua; Zhou Wuneng; Fang Jian'an; Lu Hongqian

    2009-01-01

    This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.

  9. Dynamically adaptive Lattice Boltzmann simulation of shallow water flows with the Peano framework

    KAUST Repository

    Neumann, Philipp

    2015-09-01

    © 2014 Elsevier Inc. All rights reserved. We present a dynamically adaptive Lattice Boltzmann (LB) implementation for solving the shallow water equations (SWEs). Our implementation extends an existing LB component of the Peano framework. We revise the modular design with respect to the incorporation of new simulation aspects and LB models. The basic SWE-LB implementation is validated in different breaking dam scenarios. We further provide a numerical study on stability of the MRT collision operator used in our simulations.

  10. An Adaptive Genetic Algorithm with Dynamic Population Size for Optimizing Join Queries

    OpenAIRE

    Vellev, Stoyan

    2008-01-01

    The problem of finding the optimal join ordering executing a query to a relational database management system is a combinatorial optimization problem, which makes deterministic exhaustive solution search unacceptable for queries with a great number of joined relations. In this work an adaptive genetic algorithm with dynamic population size is proposed for optimizing large join queries. The performance of the algorithm is compared with that of several classical non-determinis...

  11. The dynamics of diverse segmental amplifications in populations of Saccharomyces cerevisiae adapting to strong selection.

    Science.gov (United States)

    Payen, Celia; Di Rienzi, Sara C; Ong, Giang T; Pogachar, Jamie L; Sanchez, Joseph C; Sunshine, Anna B; Raghuraman, M K; Brewer, Bonita J; Dunham, Maitreya J

    2014-03-20

    Population adaptation to strong selection can occur through the sequential or parallel accumulation of competing beneficial mutations. The dynamics, diversity, and rate of fixation of beneficial mutations within and between populations are still poorly understood. To study how the mutational landscape varies across populations during adaptation, we performed experimental evolution on seven parallel populations of Saccharomyces cerevisiae continuously cultured in limiting sulfate medium. By combining quantitative polymerase chain reaction, array comparative genomic hybridization, restriction digestion and contour-clamped homogeneous electric field gel electrophoresis, and whole-genome sequencing, we followed the trajectory of evolution to determine the identity and fate of beneficial mutations. During a period of 200 generations, the yeast populations displayed parallel evolutionary dynamics that were driven by the coexistence of independent beneficial mutations. Selective amplifications rapidly evolved under this selection pressure, in particular common inverted amplifications containing the sulfate transporter gene SUL1. Compared with single clones, detailed analysis of the populations uncovers a greater complexity whereby multiple subpopulations arise and compete despite a strong selection. The most common evolutionary adaptation to strong selection in these populations grown in sulfate limitation is determined by clonal interference, with adaptive variants both persisting and replacing one another.

  12. Dynamic adjustments of cognitive control: oscillatory correlates of the conflict adaptation effect.

    Science.gov (United States)

    Pastötter, Bernhard; Dreisbach, Gesine; Bäuml, Karl-Heinz T

    2013-12-01

    It is a prominent idea that cognitive control mediates conflict adaptation, in that response conflict in a previous trial triggers control adjustments that reduce conflict in a current trial. In the present EEG study, we investigated the dynamics of cognitive control in a response-priming task by examining the effects of previous trial conflict on intertrial and current trial oscillatory brain activities, both on the electrode and the source level. Behavioral results showed conflict adaptation effects for RTs and response accuracy. Physiological results showed sustained intertrial effects in left parietal theta power, originating in the left inferior parietal cortex, and midcentral beta power, originating in the left and right (pre)motor cortex. Moreover, physiological analysis revealed a current trial conflict adaptation effect in midfrontal theta power, originating in the ACC. Correlational analyses showed that intertrial effects predicted conflict-induced midfrontal theta power in currently incongruent trials. In addition, conflict adaptation effects in midfrontal theta power and RTs were positively related. Together, these findings point to a dynamic cognitive control system that, as a function of previous trial type, up- and down-regulates attention and preparatory motor activities in anticipation of the next trial.

  13. 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.

  14. Block Fusion on Dynamically Adaptive Spacetree Grids for Shallow Water Waves

    KAUST Repository

    Weinzierl, Tobias

    2014-09-01

    © 2014 World Scientific Publishing Company. Spacetrees are a popular formalism to describe dynamically adaptive Cartesian grids. Even though they directly yield a mesh, it is often computationally reasonable to embed regular Cartesian blocks into their leaves. This promotes stencils working on homogeneous data chunks. The choice of a proper block size is sensitive. While large block sizes foster loop parallelism and vectorisation, they restrict the adaptivity\\'s granularity and hence increase the memory footprint and lower the numerical accuracy per byte. In the present paper, we therefore use a multiscale spacetree-block coupling admitting blocks on all spacetree nodes. We propose to find sets of blocks on the finest scale throughout the simulation and to replace them by fused big blocks. Such a replacement strategy can pick up hardware characteristics, i.e. which block size yields the highest throughput, while the dynamic adaptivity of the fine grid mesh is not constrained - applications can work with fine granular blocks. We study the fusion with a state-of-the-art shallow water solver at hands of an Intel Sandy Bridge and a Xeon Phi processor where we anticipate their reaction to selected block optimisation and vectorisation.

  15. Evolution dynamics of a model for gene duplication under adaptive conflict

    Science.gov (United States)

    Ancliff, Mark; Park, Jeong-Man

    2014-06-01

    We present and solve the dynamics of a model for gene duplication showing escape from adaptive conflict. We use a Crow-Kimura quasispecies model of evolution where the fitness landscape is a function of Hamming distances from two reference sequences, which are assumed to optimize two different gene functions, to describe the dynamics of a mixed population of individuals with single and double copies of a pleiotropic gene. The evolution equations are solved through a spin coherent state path integral, and we find two phases: one is an escape from an adaptive conflict phase, where each copy of a duplicated gene evolves toward subfunctionalization, and the other is a duplication loss of function phase, where one copy maintains its pleiotropic form and the other copy undergoes neutral mutation. The phase is determined by a competition between the fitness benefits of subfunctionalization and the greater mutational load associated with maintaining two gene copies. In the escape phase, we find a dynamics of an initial population of single gene sequences only which escape adaptive conflict through gene duplication and find that there are two time regimes: until a time t* single gene sequences dominate, and after t* double gene sequences outgrow single gene sequences. The time t* is identified as the time necessary for subfunctionalization to evolve and spread throughout the double gene sequences, and we show that there is an optimum mutation rate which minimizes this time scale.

  16. Molecular Mechanisms That Underlie the Dynamic Adaptation of Innate Monocyte Memory to Varying Stimulant Strength of TLR Ligands.

    Science.gov (United States)

    Yuan, Ruoxi; Geng, Shuo; Li, Liwu

    2016-01-01

    In adaptation to rising stimulant strength, innate monocytes can be dynamically programed to preferentially express either pro- or anti-inflammatory mediators. Such dynamic innate adaptation or programing may bear profound relevance in host health and disease. However, molecular mechanisms that govern innate adaptation to varying strength of stimulants are not well understood. Using lipopolysaccharide (LPS), the model stimulant of toll-like-receptor 4 (TLR4), we reported that the expressions of pro-inflammatory mediators are preferentially sustained in monocytes adapted by lower doses of LPS, and suppressed/tolerized in monocytes adapted by higher doses of LPS. Mechanistically, monocytes adapted by super-low dose LPS exhibited higher levels of transcription factor, interferon regulatory factor 5 (IRF5), and reduced levels of transcriptional modulator B lymphocyte-induced maturation protein-1 (Blimp-1). Intriguingly, the inflammatory monocyte adaptation by super-low dose LPS is dependent upon TRAM/TRIF but not MyD88. Similar to LPS, we also observed biphasic inflammatory adaptation and tolerance in monocytes challenged with varying dosages of TLR7 agonist. In sharp contrast, rising doses of TLR3 agonist preferentially caused inflammatory adaptation without inducing tolerance. At the molecular level, the differential regulation of IRF5 and Blimp-1 coincides with unique monocyte adaptation dynamics by TLR4/7 and TLR3 agonists. Our study provides novel clue toward the understanding of monocyte adaptation and memory toward distinct TLR ligands.

  17. Molecular mechanisms that underlie the dynamic adaptation of innate monocyte memory to varying stimulant strength of TLR ligands

    Directory of Open Access Journals (Sweden)

    Ruoxi Yuan

    2016-11-01

    Full Text Available In adaptation to rising stimulant strength, innate monocytes can be dynamically programmed to preferentially express either pro- or anti-inflammatory mediators. Such dynamic innate adaptation or programming may bear profound relevance in host health and disease. However, molecular mechanisms that govern innate adaptation to varying strength of stimulants are not well understood. Using lipopolysaccharide (LPS, the model stimulant of Toll-Like-Receptor 4 (TLR4, we reported that the expressions of pro-inflammatory mediators are preferentially sustained in monocytes adapted by lower doses of LPS, and suppressed/tolerized in monocytes adapted by higher doses of LPS. Mechanistically, monocytes adapted by super-low dose LPS exhibited higher levels of transcription factor IRF5 and reduced levels of transcriptional modulator BLIMP-1. Intriguingly, the inflammatory monocyte adaptation by super-low dose LPS is dependent upon TRAM/TRIF but not MyD88. Similar to LPS, we also observed biphasic inflammatory adaptation and tolerance in monocytes challenged with varying dosages of TLR7 agonist. In sharp contrast, rising doses of TLR3 agonist preferentially caused inflammatory adaptation without inducing tolerance. At the molecular level, the differential regulation of IRF5 and Blimp-1 coincides with unique monocyte adaptation dynamics by TLR4/7 and TLR3 agonists. Our study provides novel clue toward the understanding of monocyte adaptation and memory toward distinct TLR ligands.

  18. What's in a Name? Interlocutors Dynamically Update Expectations about Shared Names.

    Science.gov (United States)

    Gegg-Harrison, Whitney M; Tanenhaus, Michael K

    2016-01-01

    In order to refer using a name, speakers must believe that their addressee knows about the link between the name and the intended referent. In cases where speakers and addressees learned a subset of names together, speakers are adept at using only the names their partner knows. But speakers do not always share such learning experience with their conversational partners. In these situations, what information guides speakers' choice of referring expression? A speaker who is uncertain about a names' common ground (CG) status often uses a name and description together. This N+D form allows speakers to demonstrate knowledge of a name, and could provide, even in the absence of miscommunication, useful evidence to the addressee regarding the speaker's knowledge. In cases where knowledge of one name is associated with knowledge of other names, this could provide indirect evidence regarding knowledge of other names that could support generalizations used to update beliefs about CG. Using Bayesian approaches to language processing as a guiding framework, we predict that interlocutors can use their partner's choice of referring expression, in particular their use of an N+D form, to generate more accurate beliefs regarding their partner's knowledge of other names. In Experiment 1, we find that domain experts are able to use their partner's referring expression choices to generate more accurate estimates of CG. In Experiment 2, we find that interlocutors are able to infer from a partner's use of an N+D form which other names that partner is likely to know or not know. Our results suggest that interlocutors can use the information conveyed in their partner's choice of referring expression to make generalizations that contribute to more accurate beliefs about what is shared with their partner, and further, that models of CG for reference need to account not just for the status of referents, but the status of means of referring to those referents.

  19. What's in a Name? Interlocutors dynamically update expectations about shared names

    Directory of Open Access Journals (Sweden)

    Whitney Marie Gegg-Harrison

    2016-02-01

    Full Text Available In order to refer using a name, speakers must know that their addressee knows about the link between the name and the intended referent. In cases where speakers and addressees learned names together, speakers are adept at using names only when their addressee knows them. But speakers do not always share such learning experience with their conversational partners. In these situations, what information guides speakers’ choice of referring expression? A speaker who is uncertain about a names’ common ground (CG status often uses a name and description together. This N+D form allows speakers to demonstrate knowledge of a name, and could provide, even in the absence of miscommunication, useful evidence to the addressee regarding the speaker’s knowledge. In cases where knowledge of one name is associated with knowledge of other names, could provide indirect evidence regarding knowledge of other names that could support generalizations used to update beliefs about CG. Using data explanation approaches to language processing as a guiding framework, we predict that interlocutors can use their partner’s choice of referring expression, in particular their use of an N+D form, to generate more accurate beliefs regarding their partner’s knowledge of other names. In Experiment 1, we find that domain experts are able to use their partner’s referring expression choices to generate more accurate estimates of CG. In Experiment 2, we find that interlocutors are able to infer from a partner’s use of an N+D form which other names that partner is likely to know or not know. Our results suggest that interlocutors can use the information conveyed in their partner’s choice of referring expression to make generalizations that contribute to more accurate beliefs about what is shared with their partner, and further, that models of CG for reference need to account not just for the status of referents, but the status of means of referring to those referents.

  20. Update on Small Modular Reactors Dynamics System Modeling Tool -- Molten Salt Cooled Architecture

    Energy Technology Data Exchange (ETDEWEB)

    Hale, Richard Edward [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cetiner, Sacit M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Qualls, A L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Borum, Robert C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Chaleff, Ethan S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Rogerson, Doug W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Batteh, John J. [Modelon Corporation (Sweden); Tiller, Michael M. [Xogeny Corporation, Canton, MI (United States)

    2014-08-01

    The Small Modular Reactor (SMR) Dynamic System Modeling Tool project is in the third year of development. The project is designed to support collaborative modeling and study of various advanced SMR (non-light water cooled) concepts, including the use of multiple coupled reactors at a single site. The objective of the project is to provide a common simulation environment and baseline modeling resources to facilitate rapid development of dynamic advanced reactor SMR models, ensure consistency among research products within the Instrumentation, Controls, and Human-Machine Interface (ICHMI) technical area, and leverage cross-cutting capabilities while minimizing duplication of effort. The combined simulation environment and suite of models are identified as the Modular Dynamic SIMulation (MoDSIM) tool. The critical elements of this effort include (1) defining a standardized, common simulation environment that can be applied throughout the program, (2) developing a library of baseline component modules that can be assembled into full plant models using existing geometry and thermal-hydraulic data, (3) defining modeling conventions for interconnecting component models, and (4) establishing user interfaces and support tools to facilitate simulation development (i.e., configuration and parameterization), execution, and results display and capture.

  1. Reinforcement learning for partially observable dynamic processes: adaptive dynamic programming using measured output data.

    Science.gov (United States)

    Lewis, F L; Vamvoudakis, Kyriakos G

    2011-02-01

    Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured input/output data from the system. Linear dynamical systems with deterministic behavior are considered herein, which are systems of great interest in the control system community. In control system theory, these types of methods are referred to as output feedback (OPFB). The stochastic equivalent of the systems dealt with in this paper is a class of partially observable Markov decision processes. We develop both policy iteration and value iteration algorithms that converge to an optimal controller that requires only OPFB. It is shown that, similar to Q -learning, the new methods have the important advantage that knowledge of the system dynamics is not needed for the implementation of these learning algorithms or for the OPFB control. Only the order of the system, as well as an upper bound on its "observability index," must be known. The learned OPFB controller is in the form of a polynomial autoregressive moving-average controller that has equivalent performance with the optimal state variable feedback gain.

  2. Patient-adapted reconstruction and acquisition dynamic imaging method (PARADIGM) for MRI

    International Nuclear Information System (INIS)

    Aggarwal, Nitin; Bresler, Yoram

    2008-01-01

    Dynamic magnetic resonance imaging (MRI) is a challenging problem because the MR data acquisition is often not fast enough to meet the combined spatial and temporal Nyquist sampling rate requirements. Current approaches to this problem include hardware-based acceleration of the acquisition, and model-based image reconstruction techniques. In this paper we propose an alternative approach, called PARADIGM, which adapts both the acquisition and reconstruction to the spatio-temporal characteristics of the imaged object. The approach is based on time-sequential sampling theory, addressing the problem of acquiring a spatio-temporal signal under the constraint that only a limited amount of data can be acquired at a time instant. PARADIGM identifies a model class for the particular imaged object using a scout MR scan or auxiliary data. This object-adapted model is then used to optimize MR data acquisition, such that the imaging constraints are met, acquisition speed requirements are minimized, essentially perfect reconstruction of any object in the model class is guaranteed, and the inverse problem of reconstructing the dynamic object has a condition number of one. We describe spatio-temporal object models for various dynamic imaging applications including cardiac imaging. We present the theory underlying PARADIGM and analyze its performance theoretically and numerically. We also propose a practical MR imaging scheme for 2D dynamic cardiac imaging based on the theory. For this application, PARADIGM is predicted to provide a 10–25 × acceleration compared to the optimal non-adaptive scheme. Finally we present generalized optimality criteria and extend the scheme to dynamic imaging with three spatial dimensions

  3. Demographic source-sink dynamics restrict local adaptation in Elliott's blueberry (Vaccinium elliottii).

    Science.gov (United States)

    Anderson, Jill T; Geber, Monica A

    2010-02-01

    In heterogeneous landscapes, divergent selection can favor the evolution of locally adapted ecotypes, especially when interhabitat gene flow is minimal. However, if habitats differ in size or quality, source-sink dynamics can shape evolutionary trajectories. Upland and bottomland forests of the southeastern USA differ in water table depth, light availability, edaphic conditions, and plant community. We conducted a multiyear reciprocal transplant experiment to test whether Elliott's blueberry (Vaccinium elliottii) is locally adapted to these contrasting environments. Additionally, we exposed seedlings and cuttings to prolonged drought and flooding in the greenhouse to assess fitness responses to abiotic stress. Contrary to predictions of local adaptation, V. elliottii families exhibited significantly higher survivorship and growth in upland than in bottomland forests and under drought than flooded conditions, regardless of habitat of origin. Neutral population differentiation was minimal, suggesting widespread interhabitat migration. Population density, reproductive output, and genetic diversity were all significantly greater in uplands than in bottomlands. These disparities likely result in asymmetric gene flow from uplands to bottomlands. Thus, adaptation to a marginal habitat can be constrained by small populations, limited fitness, and immigration from a benign habitat. Our study highlights the importance of demography and genetic diversity in the evolution of local (mal)adaptation.

  4. Spike-threshold adaptation predicted by membrane potential dynamics in vivo.

    Directory of Open Access Journals (Sweden)

    Bertrand Fontaine

    2014-04-01

    Full Text Available Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo.

  5. Self adaptive internal combustion engine control for hydrogen mixtures based on piezoelectric dynamic cylinder pressure transducers

    International Nuclear Information System (INIS)

    Courteau, R.; Bose, T.K.

    2004-01-01

    Piezoelectric transducers offer an effective, non-intrusive way to monitor dynamic cylinder pressure in internal combustion engines. Devices dedicated to this purpose are appearing on the market, often in the form of spark plugs with embedded piezo elements. Dynamic cylinder pressure is typically used to provide diagnostic functions, or to help map an engine after it is designed. With the advent of powerful signal processor chips, it is now possible to embed enough computing power in the engine controller to perform auto tuning based on the signals provided by such transducers. Such functionality is very useful if the fuel characteristics vary between fill ups, as is often the case with alternative fuels. We propose here an algorithm for self-adaptive tuning based on a Kalman filter operating on a few selected metrics of the dynamic pressure curve. (author)

  6. 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.

  7. Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters.

    Science.gov (United States)

    Chiang, Austin W T; Liu, Wei-Chung; Charusanti, Pep; Hwang, Ming-Jing

    2014-01-15

    A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system's dynamics. We demonstrate our methodology on a prototype biological system of perfect adaptation dynamics, namely the chemotaxis model for Escherichia coli. Our results agreed well with those derived from experimental data and theoretical studies in the literature. Using this model system, we showed that there are motifs in kinetic parameters and that these motifs are governed by constraints of the specified system dynamics. A systematic approach based on enrichment statistical tests has been developed to elucidate the relationships between model parameters and the roles they play in affecting system dynamics of a prototype biological network. The proposed approach is generally applicable and therefore can find wide use in systems biology modeling research.

  8. Robust Adaptive Stabilization of Linear Time-Invariant Dynamic Systems by Using Fractional-Order Holds and Multirate Sampling Controls

    Directory of Open Access Journals (Sweden)

    S. Alonso-Quesada

    2010-01-01

    Full Text Available This paper presents a strategy for designing a robust discrete-time adaptive controller for stabilizing linear time-invariant (LTI continuous-time dynamic systems. Such systems may be unstable and noninversely stable in the worst case. A reduced-order model is considered to design the adaptive controller. The control design is based on the discretization of the system with the use of a multirate sampling device with fast-sampled control signal. A suitable on-line adaptation of the multirate gains guarantees the stability of the inverse of the discretized estimated model, which is used to parameterize the adaptive controller. A dead zone is included in the parameters estimation algorithm for robustness purposes under the presence of unmodeled dynamics in the controlled dynamic system. The adaptive controller guarantees the boundedness of the system measured signal for all time. Some examples illustrate the efficacy of this control strategy.

  9. Research Update: Utilizing magnetization dynamics in solid-state thermal energy conversion

    Directory of Open Access Journals (Sweden)

    Stephen R. Boona

    2016-10-01

    Full Text Available We review the spin-Seebeck and magnon-electron drag effects in the context of solid-state energy conversion. These phenomena are driven by advective magnon-electron interactions. Heat flow through magnetic materials generates magnetization dynamics, which can strongly affect free electrons within or adjacent to the magnetic material, thereby producing magnetization-dependent (e.g., remnant electric fields. The relative strength of spin-dependent interactions means that magnon-driven effects can generate significantly larger thermoelectric power factors as compared to classical thermoelectric phenomena. This is a surprising situation in which spin-based effects are larger than purely charge-based effects, potentially enabling new approaches to thermal energy conversion.

  10. Innate and adaptive immunity in the development of depression: An update on current knowledge and technological advances.

    Science.gov (United States)

    Haapakoski, Rita; Ebmeier, Klaus P; Alenius, Harri; Kivimäki, Mika

    2016-04-03

    The inflammation theory of depression, proposed over 20years ago, was influenced by early studies on T cell responses and since then has been a stimulus for numerous research projects aimed at understanding the relationship between immune function and depression. Observational studies have shown that indicators of immunity, especially C reactive protein and proinflammatory cytokines, such as interleukin 6, are associated with an increased risk of depressive disorders, although the evidence from randomized trials remains limited and only few studies have assessed the interplay between innate and adaptive immunity in depression. In this paper, we review current knowledge on the interactions between central and peripheral innate and adaptive immune molecules and the potential role of immune-related activation of microglia, inflammasomes and indoleamine-2,3-dioxygenase in the development of depressive symptoms. We highlight how combining basic immune methods with more advanced 'omics' technologies would help us to make progress in unravelling the complex associations between altered immune function and depressive disorders, in the identification of depression-specific biomarkers and in developing immunotherapeutic treatment strategies that take individual variability into account. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  11. Dynamic Post-Earthquake Image Segmentation with an Adaptive Spectral-Spatial Descriptor

    Directory of Open Access Journals (Sweden)

    Genyun Sun

    2017-08-01

    Full Text Available The region merging algorithm is a widely used segmentation technique for very high resolution (VHR remote sensing images. However, the segmentation of post-earthquake VHR images is more difficult due to the complexity of these images, especially high intra-class and low inter-class variability among damage objects. Herein two key issues must be resolved: the first is to find an appropriate descriptor to measure the similarity of two adjacent regions since they exhibit high complexity among the diverse damage objects, such as landslides, debris flow, and collapsed buildings. The other is how to solve over-segmentation and under-segmentation problems, which are commonly encountered with conventional merging strategies due to their strong dependence on local information. To tackle these two issues, an adaptive dynamic region merging approach (ADRM is introduced, which combines an adaptive spectral-spatial descriptor and a dynamic merging strategy to adapt to the changes of merging regions for successfully detecting objects scattered globally in a post-earthquake image. In the new descriptor, the spectral similarity and spatial similarity of any two adjacent regions are automatically combined to measure their similarity. Accordingly, the new descriptor offers adaptive semantic descriptions for geo-objects and thus is capable of characterizing different damage objects. Besides, in the dynamic region merging strategy, the adaptive spectral-spatial descriptor is embedded in the defined testing order and combined with graph models to construct a dynamic merging strategy. The new strategy can find the global optimal merging order and ensures that the most similar regions are merged at first. With combination of the two strategies, ADRM can identify spatially scattered objects and alleviates the phenomenon of over-segmentation and under-segmentation. The performance of ADRM has been evaluated by comparing with four state-of-the-art segmentation methods

  12. Adaptive control of dynamical synchronization on evolving networks with noise disturbances

    Science.gov (United States)

    Yuan, Wu-Jie; Zhou, Jian-Fang; Sendiña-Nadal, Irene; Boccaletti, Stefano; Wang, Zhen

    2018-02-01

    In real-world networked systems, the underlying structure is often affected by external and internal unforeseen factors, making its evolution typically inaccessible. An adaptive strategy was introduced for maintaining synchronization on unpredictably evolving networks [Sorrentino and Ott, Phys. Rev. Lett. 100, 114101 (2008), 10.1103/PhysRevLett.100.114101], which yet does not consider the noise disturbances widely existing in networks' environments. We provide here strategies to control dynamical synchronization on slowly and unpredictably evolving networks subjected to noise disturbances which are observed at the node and at the communication channel level. With our strategy, the nodes' coupling strength is adaptively adjusted with the aim of controlling synchronization, and according only to their received signal and noise disturbances. We first provide a theoretical analysis of the control scheme by introducing an error potential function to seek for the minimization of the synchronization error. Then, we show numerical experiments which verify our theoretical results. In particular, it is found that our adaptive strategy is effective even for the case in which the dynamics of the uncontrolled network would be explosive (i.e., the states of all the nodes would diverge to infinity).

  13. Online Dynamic Balance Technology for High Speed Spindle Based on Gain Parameter Adaption and Scheduling Control

    Directory of Open Access Journals (Sweden)

    Shihai Zhang

    2018-06-01

    Full Text Available Unbalance vibration is one of the main vibration forms of a high speed machine tool spindle. The overlarge unbalance vibration will have some adverse effects on the working life of the spindle system and the surface quality of the work-piece. In order to reduce the unbalance of a high speed spindle system, a pneumatic online dynamic balance device and its control system are presented in the paper. To improve the balance accuracy and adaptation of the balance system, the gain parameter adaption and scheduling control method are proposed first, and then the different balance effects of the influence coefficient method and the gain scheduling control method are compared through many dynamic balance experiments of the high speed spindle. The experimental results indicate that the gain parameters can be changed timely according to the transformation of the speed and kinetic parameters of the spindle system. The balance accuracy can be improved for a high speed spindle with time-varying characteristics, based on the adaptive gain scheduling control method.

  14. Adaptive SLICE method: an enhanced method to determine nonlinear dynamic respiratory system mechanics

    International Nuclear Information System (INIS)

    Zhao, Zhanqi; Möller, Knut; Guttmann, Josef

    2012-01-01

    The objective of this paper is to introduce and evaluate the adaptive SLICE method (ASM) for continuous determination of intratidal nonlinear dynamic compliance and resistance. The tidal volume is subdivided into a series of volume intervals called slices. For each slice, one compliance and one resistance are calculated by applying a least-squares-fit method. The volume window (width) covered by each slice is determined based on the confidence interval of the parameter estimation. The method was compared to the original SLICE method and evaluated using simulation and animal data. The ASM was also challenged with separate analysis of dynamic compliance during inspiration. If the signal-to-noise ratio (SNR) in the respiratory data decreased from +∞ to 10 dB, the relative errors of compliance increased from 0.1% to 22% for the ASM and from 0.2% to 227% for the SLICE method. Fewer differences were found in resistance. When the SNR was larger than 40 dB, the ASM delivered over 40 parameter estimates (42.2 ± 1.3). When analyzing the compliance during inspiration separately, the estimates calculated with the ASM were more stable. The adaptive determination of slice bounds results in consistent and reliable parameter values. Online analysis of nonlinear respiratory mechanics will profit from such an adaptive selection of interval size. (paper)

  15. Heterogeneous update mechanisms in evolutionary games: Mixing innovative and imitative dynamics

    Science.gov (United States)

    Amaral, Marco Antonio; Javarone, Marco Alberto

    2018-04-01

    Innovation and evolution are two processes of paramount relevance for social and biological systems. In general, the former allows the introduction of elements of novelty, while the latter is responsible for the motion of a system in its phase space. Often, these processes are strongly related, since an innovation can trigger the evolution, and the latter can provide the optimal conditions for the emergence of innovations. Both processes can be studied by using the framework of evolutionary game theory, where evolution constitutes an intrinsic mechanism. At the same time, the concept of innovation requires an opportune mathematical representation. Notably, innovation can be modeled as a strategy, or it can constitute the underlying mechanism that allows agents to change strategy. Here, we analyze the second case, investigating the behavior of a heterogeneous population, composed of imitative and innovative agents. Imitative agents change strategy only by imitating that of their neighbors, whereas innovative ones change strategy without the need for a copying source. The proposed model is analyzed by means of analytical calculations and numerical simulations in different topologies. Remarkably, results indicate that the mixing of mechanisms can be detrimental to cooperation near phase transitions. In those regions, the spatial reciprocity from imitative mechanisms is destroyed by innovative agents, leading to the downfall of cooperation. Our investigation sheds some light on the complex dynamics emerging from the heterogeneity of strategy revision methods, highlighting the role of innovation in evolutionary games.

  16. Design update, thermal and fluid dynamic analyses of the EU-HCPB TBM in vertical arrangement

    International Nuclear Information System (INIS)

    Cismondi, F.; Kecskes, S.; Ilic, M.; Legradi, G.; Kiss, B.; Bitz, O.; Dolensky, B.; Neuberger, H.; Boccaccini, L.V.; Ihli, T.

    2009-01-01

    In the frame of the activities of the EU Breeder Blanket Programme and of the Test Blanket Working Group of ITER, the Helium Cooled Pebble Bed Test Blanket Module (HCPB TBM) is developed in Forschungszentrum Karlsruhe (FZK) to investigate DEMO relevant concepts for blanket modules. The three main functions of a blanket module (removing heat, breeding tritium and shielding sensitive components from radiation) will be tested in ITER using a series of four TBMs, which are irradiated successively during different test campaigns. Each HCPB TBM will be installed, with a vertical orientation, into the vacuum vessel connected to one equatorial port. As the studies performed up to 2006 in FZK concerned a horizontal orientation of the HCPB TBM, a global review of the design is necessary to match with the new ITER specifications. A preliminary version of the new vertical design is proposed extrapolating the neutronic analysis performed for the horizontal HCPB TBM. An overview of the new HCPB TBM vertical designs, as well as the preliminary thermal and fluid dynamic analyses performed for the validation of the design, are presented in this paper. A critical review of the results obtained allows us, in the conclusion, to prepare a plan for the future detailed analyses of the vertical HCPB TBM.

  17. Signaling and Adaptation Modulate the Dynamics of the Photosensoric Complex of Natronomonas pharaonis.

    Directory of Open Access Journals (Sweden)

    Philipp S Orekhov

    2015-10-01

    Full Text Available Motile bacteria and archaea respond to chemical and physical stimuli seeking optimal conditions for survival. To this end transmembrane chemo- and photoreceptors organized in large arrays initiate signaling cascades and ultimately regulate the rotation of flagellar motors. To unravel the molecular mechanism of signaling in an archaeal phototaxis complex we performed coarse-grained molecular dynamics simulations of a trimer of receptor/transducer dimers, namely NpSRII/NpHtrII from Natronomonas pharaonis. Signaling is regulated by a reversible methylation mechanism called adaptation, which also influences the level of basal receptor activation. Mimicking two extreme methylation states in our simulations we found conformational changes for the transmembrane region of NpSRII/NpHtrII which resemble experimentally observed light-induced changes. Further downstream in the cytoplasmic domain of the transducer the signal propagates via distinct changes in the dynamics of HAMP1, HAMP2, the adaptation domain and the binding region for the kinase CheA, where conformational rearrangements were found to be subtle. Overall these observations suggest a signaling mechanism based on dynamic allostery resembling models previously proposed for E. coli chemoreceptors, indicating similar properties of signal transduction for archaeal photoreceptors and bacterial chemoreceptors.

  18. Dynamic Self-Adaptive Reliability Control for Electric-Hydraulic Systems

    Directory of Open Access Journals (Sweden)

    Yi Wan

    2015-02-01

    Full Text Available The high-speed electric-hydraulic proportional control is a new development of the hydraulic control technique with high reliability, low cost, efficient energy, and easy maintenance; it is widely used in industrial manufacturing and production. However, there are still some unresolved challenges, the most notable being the requirements of high stability and real-time by the classical control algorithm due to its high nonlinear characteristics. We propose a dynamic self-adaptive mixed control method based on the least squares support vector machine (LSSVM and the genetic algorithm for high-speed electric-hydraulic proportional control systems in this paper; LSSVM is used to identify and adjust online a nonlinear electric-hydraulic proportional system, and the genetic algorithm is used to optimize the control law of the controlled system and dynamic self-adaptive internal model control and predictive control are implemented by using the mixed intelligent method. The internal model and the inverse control model are online adjusted together. At the same time, a time-dependent Hankel matrix is constructed based on sample data; thus finite dimensional solution can be optimized on finite dimensional space. The results of simulation experiments show that the dynamic characteristics are greatly improved by the mixed intelligent control strategy, and good tracking and high stability are met in condition of high frequency response.

  19. Adaptive dynamics of competition for nutritionally complementary resources: character convergence, displacement, and parallelism.

    Science.gov (United States)

    Vasseur, David A; Fox, Jeremy W

    2011-10-01

    Consumers acquire essential nutrients by ingesting the tissues of resource species. When these tissues contain essential nutrients in a suboptimal ratio, consumers may benefit from ingesting a mixture of nutritionally complementary resource species. We investigate the joint ecological and evolutionary consequences of competition for complementary resources, using an adaptive dynamics model of two consumers and two resources that differ in their relative content of two essential nutrients. In the absence of competition, a nutritionally balanced diet rarely maximizes fitness because of the dynamic feedbacks between uptake rate and resource density, whereas in sympatry, nutritionally balanced diets maximize fitness because competing consumers with different nutritional requirements tend to equalize the relative abundances of the two resources. Adaptation from allopatric to sympatric fitness optima can generate character convergence, divergence, and parallel shifts, depending not on the degree of diet overlap but on the match between resource nutrient content and consumer nutrient requirements. Contrary to previous verbal arguments that suggest that character convergence leads to neutral stability, coadaptation of competing consumers always leads to stable coexistence. Furthermore, we show that incorporating costs of consuming or excreting excess nonlimiting nutrients selects for nutritionally balanced diets and so promotes character convergence. This article demonstrates that resource-use overlap has little bearing on coexistence when resources are nutritionally complementary, and it highlights the importance of using mathematical models to infer the stability of ecoevolutionary dynamics.

  20. An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks.

    Science.gov (United States)

    Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Zhang, Xuekun

    2015-12-03

    Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT), Machine-to-Machine (M2M) communications, Vehicular-to-Vehicular (V2V) communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than 95 % of the theoretical optimal throughput and 0 . 97 of fairness index especially in dynamic and dense networks.

  1. An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chunyang Lei

    2015-12-01

    Full Text Available Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT, Machine-to-Machine (M2M communications, Vehicular-to-Vehicular (V2V communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than 95 % of the theoretical optimal throughput and 0 . 97 of fairness index especially in dynamic and dense networks.

  2. Universal dynamics of complex adaptive systems: Gauge theory of things alive

    International Nuclear Information System (INIS)

    Mack, G.

    1994-04-01

    A universal dynamics of objects and their relations - a kind of ''universal chemistry'' - is discussed which satisfies general principles of locality and relativity. Einsteins theory of gravitation and the gauge theory of elementary particles are prototypes, but complex adaptive systems - anything that is alive in the widest sense - fall under the same paradigma. Frustration and gauge symmetry arise naturally in this context. Besides a nondissipative deterministic dynamics, which is thought to operate at a fundamental levle, a Thermo-Dynamics in sense of Prigogine is introduced by adding a diffusion process. It introduces irreversibility and entropy production. It equilibrates the chaotic local model of the time development (only) and is designed to be undetectable under continued observation with given finite measuring accuracy. Compositeness and the development of structure can be described in this framework. The existence of a critical equilibrium state may be postulated which is invariant under the dynamics. But it is usually not reached in a finite time from a given starting configuration, because local dynamics suffers from critical slowing down, especially in the presence of frustration. (orig.)

  3. Use of a dynamic grid adaptation in the asymmetric weighted residual method

    International Nuclear Information System (INIS)

    Graf, V.; Romstedt, P.; Werner, W.

    1986-01-01

    A dynamic grid adaptive method has been developed for use with the asymmetric weighted residual method. The method automatically adapts the number and position of the spatial mesh points as the solution of hyperbolic or parabolic vector partial differential equations progresses in time. The mesh selection algorithm is based on the minimization of the L 2 norm of the spatial discretization error. The method permits the accurate calculation of the evolution of inhomogeneities, like wave fronts, shock layers, and other sharp transitions, while generally using a coarse computational grid. The number of required mesh points is significantly reduced, relative to a fixed Eulerian grid. Since the mesh selection algorithm is computationally inexpensive, a corresponding reduction of computing time results

  4. Air-Breathing Hypersonic Vehicle Tracking Control Based on Adaptive Dynamic Programming.

    Science.gov (United States)

    Mu, Chaoxu; Ni, Zhen; Sun, Changyin; He, Haibo

    2017-03-01

    In this paper, we propose a data-driven supplementary control approach with adaptive learning capability for air-breathing hypersonic vehicle tracking control based on action-dependent heuristic dynamic programming (ADHDP). The control action is generated by the combination of sliding mode control (SMC) and the ADHDP controller to track the desired velocity and the desired altitude. In particular, the ADHDP controller observes the differences between the actual velocity/altitude and the desired velocity/altitude, and then provides a supplementary control action accordingly. The ADHDP controller does not rely on the accurate mathematical model function and is data driven. Meanwhile, it is capable to adjust its parameters online over time under various working conditions, which is very suitable for hypersonic vehicle system with parameter uncertainties and disturbances. We verify the adaptive supplementary control approach versus the traditional SMC in the cruising flight, and provide three simulation studies to illustrate the improved performance with the proposed approach.

  5. Dynamic optimization of the complex adaptive controlling by the structure of enterprise’s product range

    Directory of Open Access Journals (Sweden)

    Andrey Fyodorovich Shorikov

    2013-06-01

    Full Text Available This paper reviews a methodical approach to solve multi-step dynamic problem of optimal integrated adaptive management of a product portfolio structure of the enterprise. For the organization of optimal adaptive terminal control of the system the recurrent algorithm, which reduces an initial multistage problem to the realization of the final sequence of problems of optimal program terminal control is offered. In turn, the decision of each problem of optimal program terminal control is reduced to the realization of the final sequence only single-step operations in the form of the problems solving of linear and convex mathematical programming. Thus, the offered approach allows to develop management solutions at current information support, which consider feedback, and which create the optimal structure of an enterprise’s product lines, contributing to optimising of profits, as well as maintenance of the desired level of profit for a long period of time

  6. 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

  7. Multipoint dynamically reconfigure adaptive distributed fiber optic acoustic emission sensor (FAESense) system for condition based maintenance

    Science.gov (United States)

    Mendoza, Edgar; Prohaska, John; Kempen, Connie; Esterkin, Yan; Sun, Sunjian; Krishnaswamy, Sridhar

    2010-09-01

    This paper describes preliminary results obtained under a Navy SBIR contract by Redondo Optics Inc. (ROI), in collaboration with Northwestern University towards the development and demonstration of a next generation, stand-alone and fully integrated, dynamically reconfigurable, adaptive fiber optic acoustic emission sensor (FAESense™) system for the in-situ unattended detection and localization of shock events, impact damage, cracks, voids, and delaminations in new and aging critical infrastructures found in ships, submarines, aircraft, and in next generation weapon systems. ROI's FAESense™ system is based on the integration of proven state-of-the-art technologies: 1) distributed array of in-line fiber Bragg gratings (FBGs) sensors sensitive to strain, vibration, and acoustic emissions, 2) adaptive spectral demodulation of FBG sensor dynamic signals using two-wave mixing interferometry on photorefractive semiconductors, and 3) integration of all the sensor system passive and active optoelectronic components within a 0.5-cm x 1-cm photonic integrated circuit microchip. The adaptive TWM demodulation methodology allows the measurement of dynamic high frequnency acoustic emission events, while compensating for passive quasi-static strain and temperature drifts. It features a compact, low power, environmentally robust 1-inch x 1-inch x 4-inch small form factor (SFF) package with no moving parts. The FAESense™ interrogation system is microprocessor-controlled using high data rate signal processing electronics for the FBG sensors calibration, temperature compensation and the detection and analysis of acoustic emission signals. Its miniaturized package, low power operation, state-of-the-art data communications, and low cost makes it a very attractive solution for a large number of applications in naval and maritime industries, aerospace, civil structures, the oil and chemical industry, and for homeland security applications.

  8. The repertoire and dynamics of evolutionary adaptations to controlled nutrient-limited environments in yeast.

    Directory of Open Access Journals (Sweden)

    David Gresham

    2008-12-01

    Full Text Available The experimental evolution of laboratory populations of microbes provides an opportunity to observe the evolutionary dynamics of adaptation in real time. Until very recently, however, such studies have been limited by our inability to systematically find mutations in evolved organisms. We overcome this limitation by using a variety of DNA microarray-based techniques to characterize genetic changes -- including point mutations, structural changes, and insertion variation -- that resulted from the experimental adaptation of 24 haploid and diploid cultures of Saccharomyces cerevisiae to growth in either glucose, sulfate, or phosphate-limited chemostats for approximately 200 generations. We identified frequent genomic amplifications and rearrangements as well as novel retrotransposition events associated with adaptation. Global nucleotide variation detection in ten clonal isolates identified 32 point mutations. On the basis of mutation frequencies, we infer that these mutations and the subsequent dynamics of adaptation are determined by the batch phase of growth prior to initiation of the continuous phase in the chemostat. We relate these genotypic changes to phenotypic outcomes, namely global patterns of gene expression, and to increases in fitness by 5-50%. We found that the spectrum of available mutations in glucose- or phosphate-limited environments combined with the batch phase population dynamics early in our experiments allowed several distinct genotypic and phenotypic evolutionary pathways in response to these nutrient limitations. By contrast, sulfate-limited populations were much more constrained in both genotypic and phenotypic outcomes. Thus, the reproducibility of evolution varies with specific selective pressures, reflecting the constraints inherent in the system-level organization of metabolic processes in the cell. We were able to relate some of the observed adaptive mutations (e.g., transporter gene amplifications to known features

  9. Adaptation dynamics of laboratory populations of Drosophila Melanogaster to low dose chronic ionizing irradiation

    International Nuclear Information System (INIS)

    Zajnullin, V.G.; Yushkova, E.A.

    2008-01-01

    In genetically non-uniform populations D. melanogaster in conditions of a chronic irradiation in a doze 10-11 about sGy/generation dynamics parameters of populations was investigated. It is established, that number of individuals in irradiated populations is lower, than in control. It is revealed, that viability of populations undergone to a chronic irradiation depends on their genotype. The gradual increase in fruitfulness, viability of individuals and decrease in a level of lethal mutations in a number of generations after of an irradiation in low doses is caused by adaptable opportunities of populations. (authors)

  10. Self-organized emergence of multilayer structure and chimera states in dynamical networks with adaptive couplings

    Science.gov (United States)

    Kasatkin, D. V.; Yanchuk, S.; Schöll, E.; Nekorkin, V. I.

    2017-12-01

    We report the phenomenon of self-organized emergence of hierarchical multilayered structures and chimera states in dynamical networks with adaptive couplings. This process is characterized by a sequential formation of subnetworks (layers) of densely coupled elements, the size of which is ordered in a hierarchical way, and which are weakly coupled between each other. We show that the hierarchical structure causes the decoupling of the subnetworks. Each layer can exhibit either a two-cluster state, a periodic traveling wave, or an incoherent state, and these states can coexist on different scales of subnetwork sizes.

  11. The neural dynamics of conflict adaptation within a look-to-do transition.

    Directory of Open Access Journals (Sweden)

    Dandan Tang

    Full Text Available BACKGROUND: For optimal performance in conflict situations, conflict adaptation (conflict detection and adjustment is necessary. However, the neural dynamics of conflict adaptation is still unclear. METHODS: In the present study, behavioral and electroencephalography (EEG data were recorded from seventeen healthy participants during performance of a color-word Stroop task with a novel look-to-do transition. Within this transition, participants looked at the Stroop stimuli but no responses were required in the 'look' trials; or made manual responses to the Stroop stimuli in the 'do' trials. RESULTS: In the 'look' trials, the amplitude modulation of N450 occurred exclusively in the right-frontal region. Subsequently, the amplitude modulation of sustained potential (SP emerged in the posterior parietal and right-frontal regions. A significantly positive correlation between the modulation of reconfiguration in the 'look' trials and the behavioral conflict adaptation in the 'do' trials was observed. Specially, a stronger information flow from right-frontal region to posterior parietal region in the beta band was observed for incongruent condition than for congruent condition. In the 'do' trials, the conflict of 'look' trials enhanced the amplitude modulations of N450 in the right-frontal and posterior parietal regions, but decreased the amplitude modulations of SP in these regions. Uniquely, a stronger information flow from centro-parietal region to right-frontal region in the theta band was observed for iI condition than for cI condition. CONCLUSION: All these findings showed that top-down conflict adaptation is implemented by: (1 enhancing the sensitivity to conflict detection and the adaptation to conflict resolution; (2 modulating the effective connectivity between parietal region and right-frontal region.

  12. Experimental evolution and the dynamics of adaptation and genome evolution in microbial populations.

    Science.gov (United States)

    Lenski, Richard E

    2017-10-01

    Evolution is an on-going process, and it can be studied experimentally in organisms with rapid generations. My team has maintained 12 populations of Escherichia coli in a simple laboratory environment for >25 years and 60 000 generations. We have quantified the dynamics of adaptation by natural selection, seen some of the populations diverge into stably coexisting ecotypes, described changes in the bacteria's mutation rate, observed the new ability to exploit a previously untapped carbon source, characterized the dynamics of genome evolution and used parallel evolution to identify the genetic targets of selection. I discuss what the future might hold for this particular experiment, briefly highlight some other microbial evolution experiments and suggest how the fields of experimental evolution and microbial ecology might intersect going forward.

  13. A New Fuzzy Harmony Search Algorithm Using Fuzzy Logic for Dynamic Parameter Adaptation

    Directory of Open Access Journals (Sweden)

    Cinthia Peraza

    2016-10-01

    Full Text Available In this paper, a new fuzzy harmony search algorithm (FHS for solving optimization problems is presented. FHS is based on a recent method using fuzzy logic for dynamic adaptation of the harmony memory accepting (HMR and pitch adjustment (PArate parameters that improve the convergence rate of traditional harmony search algorithm (HS. The objective of the method is to dynamically adjust the parameters in the range from 0.7 to 1. The impact of using fixed parameters in the harmony search algorithm is discussed and a strategy for efficiently tuning these parameters using fuzzy logic is presented. The FHS algorithm was successfully applied to different benchmarking optimization problems. The results of simulation and comparison studies demonstrate the effectiveness and efficiency of the proposed approach.

  14. Dynamic Analysis and Adaptive Sliding Mode Controller for a Chaotic Fractional Incommensurate Order Financial System

    Science.gov (United States)

    Hajipour, Ahmad; Tavakoli, Hamidreza

    2017-12-01

    In this study, the dynamic behavior and chaos control of a chaotic fractional incommensurate-order financial system are investigated. Using well-known tools of nonlinear theory, i.e. Lyapunov exponents, phase diagrams and bifurcation diagrams, we observe some interesting phenomena, e.g. antimonotonicity, crisis phenomena and route to chaos through a period doubling sequence. Adopting largest Lyapunov exponent criteria, we find that the system yields chaos at the lowest order of 2.15. Next, in order to globally stabilize the chaotic fractional incommensurate order financial system with uncertain dynamics, an adaptive fractional sliding mode controller is designed. Numerical simulations are used to demonstrate the effectiveness of the proposed control method.

  15. Distributed neural network control for adaptive synchronization of uncertain dynamical multiagent systems.

    Science.gov (United States)

    Peng, Zhouhua; Wang, Dan; Zhang, Hongwei; Sun, Gang

    2014-08-01

    This paper addresses the leader-follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive synchronization controllers are proposed based on the state information of neighboring agents. The control design is developed for both undirected and directed communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case where a neighborhood observer is proposed based on relative output information of neighboring agents. Then, distributed observer-based synchronization controllers are derived and a parameter-dependent Riccati inequality is employed to prove the stability. This design has a favorable decouple property between the observer and the controller designs for nonlinear multiagent systems. For both cases, the developed controllers guarantee that the state of each agent synchronizes to that of the leader with bounded residual errors. Two illustrative examples validate the efficacy of the proposed methods.

  16. Adaptive Pulsed Laser Line Extraction for Terrain Reconstruction using a Dynamic Vision Sensor

    Directory of Open Access Journals (Sweden)

    Christian eBrandli

    2014-01-01

    Full Text Available Mobile robots need to know the terrain in which they are moving for path planning and obstacle avoidance. This paper proposes the combination of a bio-inspired, redundancy-suppressing dynamic vision sensor with a pulsed line laser to allow fast terrain reconstruction. A stable laser stripe extraction is achieved by exploiting the sensor’s ability to capture the temporal dynamics in a scene. An adaptive temporal filter for the sensor output allows a reliable reconstruction of 3D terrain surfaces. Laser stripe extractions up to pulsing frequencies of 500Hz were achieved using a line laser of 3mW at a distance of 45cm using an event-based algorithm that exploits the sparseness of the sensor output. As a proof of concept, unstructured rapid prototype terrain samples have been successfully reconstructed with an accuracy of 2mm.

  17. Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming

    Science.gov (United States)

    Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai

    2013-09-01

    In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

  18. Dynamic Learning from Adaptive Neural Control of Uncertain Robots with Guaranteed Full-State Tracking Precision

    Directory of Open Access Journals (Sweden)

    Min Wang

    2017-01-01

    Full Text Available A dynamic learning method is developed for an uncertain n-link robot with unknown system dynamics, achieving predefined performance attributes on the link angular position and velocity tracking errors. For a known nonsingular initial robotic condition, performance functions and unconstrained transformation errors are employed to prevent the violation of the full-state tracking error constraints. By combining two independent Lyapunov functions and radial basis function (RBF neural network (NN approximator, a novel and simple adaptive neural control scheme is proposed for the dynamics of the unconstrained transformation errors, which guarantees uniformly ultimate boundedness of all the signals in the closed-loop system. In the steady-state control process, RBF NNs are verified to satisfy the partial persistent excitation (PE condition. Subsequently, an appropriate state transformation is adopted to achieve the accurate convergence of neural weight estimates. The corresponding experienced knowledge on unknown robotic dynamics is stored in NNs with constant neural weight values. Using the stored knowledge, a static neural learning controller is developed to improve the full-state tracking performance. A comparative simulation study on a 2-link robot illustrates the effectiveness of the proposed scheme.

  19. A Self-adaptive Dynamic Evaluation Model for Diabetes Mellitus, Based on Evolutionary Strategies

    Directory of Open Access Journals (Sweden)

    An-Jiang Lu

    2016-03-01

    Full Text Available In order to evaluate diabetes mellitus objectively and accurately, this paper builds a self-adaptive dynamic evaluation model for diabetes mellitus, based on evolutionary strategies. First of all, on the basis of a formalized description of the evolutionary process of diabetes syndromes, using a state transition function, it judges whether a disease is evolutionary, through an excitation parameter. It then, provides evidence for the rebuilding of the evaluation index system. After that, by abstracting and rebuilding the composition of evaluation indexes, it makes use of a heuristic algorithm to determine the composition of the evolved evaluation index set of diabetes mellitus, It then, calculates the weight of each index in the evolved evaluation index set of diabetes mellitus by building a dependency matrix and realizes the self-adaptive dynamic evaluation of diabetes mellitus under an evolutionary environment. Using this evaluation model, it is possible to, quantify all kinds of diagnoses and treatment experiences of diabetes and finally to adopt ideal diagnoses and treatment measures for different patients with diabetics.

  20. Exploiting the Adaptation Dynamics to Predict the Distribution of Beneficial Fitness Effects.

    Directory of Open Access Journals (Sweden)

    Sona John

    Full Text Available Adaptation of asexual populations is driven by beneficial mutations and therefore the dynamics of this process, besides other factors, depends on the distribution of beneficial fitness effects. It is known that on uncorrelated fitness landscapes, this distribution can only be of three types: truncated, exponential and power law. We performed extensive stochastic simulations to study the adaptation dynamics on rugged fitness landscapes, and identified two quantities that can be used to distinguish the underlying distribution of beneficial fitness effects. The first quantity studied here is the fitness difference between successive mutations that spread in the population, which is found to decrease in the case of truncated distributions, remains nearly a constant for exponentially decaying distributions and increases when the fitness distribution decays as a power law. The second quantity of interest, namely, the rate of change of fitness with time also shows quantitatively different behaviour for different beneficial fitness distributions. The patterns displayed by the two aforementioned quantities are found to hold good for both low and high mutation rates. We discuss how these patterns can be exploited to determine the distribution of beneficial fitness effects in microbial experiments.

  1. An Adaptive Learning Based Network Selection Approach for 5G Dynamic Environments

    Directory of Open Access Journals (Sweden)

    Xiaohong Li

    2018-03-01

    Full Text Available Networks will continue to become increasingly heterogeneous as we move toward 5G. Meanwhile, the intelligent programming of the core network makes the available radio resource be more changeable rather than static. In such a dynamic and heterogeneous network environment, how to help terminal users select optimal networks to access is challenging. Prior implementations of network selection are usually applicable for the environment with static radio resources, while they cannot handle the unpredictable dynamics in 5G network environments. To this end, this paper considers both the fluctuation of radio resources and the variation of user demand. We model the access network selection scenario as a multiagent coordination problem, in which a bunch of rationally terminal users compete to maximize their benefits with incomplete information about the environment (no prior knowledge of network resource and other users’ choices. Then, an adaptive learning based strategy is proposed, which enables users to adaptively adjust their selections in response to the gradually or abruptly changing environment. The system is experimentally shown to converge to Nash equilibrium, which also turns out to be both Pareto optimal and socially optimal. Extensive simulation results show that our approach achieves significantly better performance compared with two learning and non-learning based approaches in terms of load balancing, user payoff and the overall bandwidth utilization efficiency. In addition, the system has a good robustness performance under the condition with non-compliant terminal users.

  2. Reactive power and voltage control strategy based on dynamic and adaptive segment for DG inverter

    Science.gov (United States)

    Zhai, Jianwei; Lin, Xiaoming; Zhang, Yongjun

    2018-03-01

    The inverter of distributed generation (DG) can support reactive power to help solve the problem of out-of-limit voltage in active distribution network (ADN). Therefore, a reactive voltage control strategy based on dynamic and adaptive segment for DG inverter is put forward to actively control voltage in this paper. The proposed strategy adjusts the segmented voltage threshold of Q(U) droop curve dynamically and adaptively according to the voltage of grid-connected point and the power direction of adjacent downstream line. And then the reactive power reference of DG inverter can be got through modified Q(U) control strategy. The reactive power of inverter is controlled to trace the reference value. The proposed control strategy can not only control the local voltage of grid-connected point but also help to maintain voltage within qualified range considering the terminal voltage of distribution feeder and the reactive support for adjacent downstream DG. The scheme using the proposed strategy is compared with the scheme without the reactive support of DG inverter and the scheme using the Q(U) control strategy with constant segmented voltage threshold. The simulation results suggest that the proposed method has a significant improvement on solving the problem of out-of-limit voltage, restraining voltage variation and improving voltage quality.

  3. Dynamic modeling and adaptive vibration suppression of a high-speed macro-micro manipulator

    Science.gov (United States)

    Yang, Yi-ling; Wei, Yan-ding; Lou, Jun-qiang; Fu, Lei; Fang, Sheng; Chen, Te-huan

    2018-05-01

    This paper presents a dynamic modeling and microscopic vibration suppression for a flexible macro-micro manipulator dedicated to high-speed operation. The manipulator system mainly consists of a macro motion stage and a flexible micromanipulator bonded with one macro-fiber-composite actuator. Based on Hamilton's principle and the Bouc-Wen hysteresis equation, the nonlinear dynamic model is obtained. Then, a hybrid control scheme is proposed to simultaneously suppress the elastic vibration during and after the motor motion. In particular, the hybrid control strategy is composed of a trajectory planning approach and an adaptive variable structure control. Moreover, two optimization indices regarding the comprehensive torques and synthesized vibrations are designed, and the optimal trajectories are acquired using a genetic algorithm. Furthermore, a nonlinear fuzzy regulator is used to adjust the switching gain in the variable structure control. Thus, a fuzzy variable structure control with nonlinear adaptive control law is achieved. A series of experiments are performed to verify the effectiveness and feasibility of the established system model and hybrid control strategy. The excited vibration during the motor motion and the residual vibration after the motor motion are decreased. Meanwhile, the settling time is shortened. Both the manipulation stability and operation efficiency of the manipulator are improved by the proposed hybrid strategy.

  4. Adaptative synchronization in multi-output fractional-order complex dynamical networks and secure communications

    Science.gov (United States)

    Mata-Machuca, Juan L.; Aguilar-López, Ricardo

    2018-01-01

    This work deals with the adaptative synchronization of complex dynamical networks with fractional-order nodes and its application in secure communications employing chaotic parameter modulation. The complex network is composed of multiple fractional-order systems with mismatch parameters and the coupling functions are given to realize the network synchronization. We introduce a fractional algebraic synchronizability condition (FASC) and a fractional algebraic identifiability condition (FAIC) which are used to know if the synchronization and parameters estimation problems can be solved. To overcome these problems, an adaptative synchronization methodology is designed; the strategy consists in proposing multiple receiver systems which tend to follow asymptotically the uncertain transmitters systems. The coupling functions and parameters of the receiver systems are adjusted continually according to a convenient sigmoid-like adaptative controller (SLAC), until the measurable output errors converge to zero, hence, synchronization between transmitter and receivers is achieved and message signals are recovered. Indeed, the stability analysis of the synchronization error is based on the fractional Lyapunov direct method. Finally, numerical results corroborate the satisfactory performance of the proposed scheme by means of the synchronization of a complex network consisting of several fractional-order unified chaotic systems.

  5. High Dynamic Range adaptive ΔΣ-based Focal Plane Array architecture

    KAUST Repository

    Yao, Shun

    2012-10-16

    In this paper, an Adaptive Delta-Sigma based architecture for High Dynamic Range (HDR) Focal Plane Arrays is presented. The noise shaping effect of the Delta-Sigma modulation in the low end, and the distortion noise induced in the high end of Photo-diode current were analyzed in detail. The proposed architecture can extend the DR for about 20N log2 dB at the high end of Photo-diode current with an N bit Up-Down counter. At the low end, it can compensate for the larger readout noise by employing Extended Counting. The Adaptive Delta-Sigma architecture employing a 4-bit Up-Down counter achieved about 160dB in the DR, with a Peak SNR (PSNR) of 80dB at the high end. Compared to the other HDR architectures, the Adaptive Delta-Sigma based architecture provides the widest DR with the best SNR performance in the extended range.

  6. Adaptive digital fringe projection technique for high dynamic range three-dimensional shape measurement.

    Science.gov (United States)

    Lin, Hui; Gao, Jian; Mei, Qing; He, Yunbo; Liu, Junxiu; Wang, Xingjin

    2016-04-04

    It is a challenge for any optical method to measure objects with a large range of reflectivity variation across the surface. Image saturation results in incorrect intensities in captured fringe pattern images, leading to phase and measurement errors. This paper presents a new adaptive digital fringe projection technique which avoids image saturation and has a high signal to noise ratio (SNR) in the three-dimensional (3-D) shape measurement of objects that has a large range of reflectivity variation across the surface. Compared to previous high dynamic range 3-D scan methods using many exposures and fringe pattern projections, which consumes a lot of time, the proposed technique uses only two preliminary steps of fringe pattern projection and image capture to generate the adapted fringe patterns, by adaptively adjusting the pixel-wise intensity of the projected fringe patterns based on the saturated pixels in the captured images of the surface being measured. For the bright regions due to high surface reflectivity and high illumination by the ambient light and surfaces interreflections, the projected intensity is reduced just to be low enough to avoid image saturation. Simultaneously, the maximum intensity of 255 is used for those dark regions with low surface reflectivity to maintain high SNR. Our experiments demonstrate that the proposed technique can achieve higher 3-D measurement accuracy across a surface with a large range of reflectivity variation.

  7. Adaptive Control for Linear Uncertain Systems with Unmodeled Dynamics Revisited via Optimal Control Modification

    Science.gov (United States)

    Nguyen, Nhan

    2013-01-01

    This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.

  8. Analyses of guide update approaches for vector evaluated particle swarm optimisation on dynamic multi-objective optimisation problems

    CSIR Research Space (South Africa)

    Helbig, M

    2012-06-01

    Full Text Available not indicate whether Pareto-dominance is used to update guides. Therefore, it is assumed that the original version of VEPSO updates the local and global guides according to the particles? fitness with regards to only one objective, i.e. the objective... that were used to study the influence of guide update approaches on the performance of DVEPSO. Five benchmark functions were used of various DMOO Types, namely DIMP2 [10], FDA3Camara [11], dMOP2 [12], dMOP3 [12] and HE2 [13]. Various types of DMOOPs...

  9. Moving finite elements: A continuously adaptive method for computational fluid dynamics

    International Nuclear Information System (INIS)

    Glasser, A.H.; Miller, K.; Carlson, N.

    1991-01-01

    Moving Finite Elements (MFE), a recently developed method for computational fluid dynamics, promises major advances in the ability of computers to model the complex behavior of liquids, gases, and plasmas. Applications of computational fluid dynamics occur in a wide range of scientifically and technologically important fields. Examples include meteorology, oceanography, global climate modeling, magnetic and inertial fusion energy research, semiconductor fabrication, biophysics, automobile and aircraft design, industrial fluid processing, chemical engineering, and combustion research. The improvements made possible by the new method could thus have substantial economic impact. Moving Finite Elements is a moving node adaptive grid method which has a tendency to pack the grid finely in regions where it is most needed at each time and to leave it coarse elsewhere. It does so in a manner which is simple and automatic, and does not require a large amount of human ingenuity to apply it to each particular problem. At the same time, it often allows the time step to be large enough to advance a moving shock by many shock thicknesses in a single time step, moving the grid smoothly with the solution and minimizing the number of time steps required for the whole problem. For 2D problems (two spatial variables) the grid is composed of irregularly shaped and irregularly connected triangles which are very flexible in their ability to adapt to the evolving solution. While other adaptive grid methods have been developed which share some of these desirable properties, this is the only method which combines them all. In many cases, the method can save orders of magnitude of computing time, equivalent to several generations of advancing computer hardware

  10. Flexible and adaptive water systems operations through more informed and dynamic decisions

    Science.gov (United States)

    Castelletti, A.; Giuliani, M.

    2016-12-01

    Timely adapting the operations of water systems to be resilient against rapid changes in both hydroclimatic and socioeconomic forcing is generally recommended as a part of planning and managing water resources under uncertain futures. A great opportunity to make the operations more flexible and adaptive is offered by the unprecedented amount of information that is becoming available to water system operators, providing a wide range of data at increasingly higher temporal and spatial resolution. Yet, many water systems are still operated using very simple information systems, typically based on basic statistical analysis and the operator's experience. In this work, we discuss the potential offered by incorporating improved information to enhance water systems operation and increase their ability of adapting to different external conditions and resolving potential conflicts across sectors. In particular, we focus on the use of different variables associated to different dynamics of the system (slow and fast) diversely impacting the operating objectives on the short-, medium- and long-term. The multi-purpose operations of the Hoa Binh reservoir in the Red River Basin (Vietnam) is used to demonstrate our approach. Numerical results show that our procedure is able to automatically select the most valuable information for improving the Hoa Binh operations and mitigating the conflict between short-term objectives, i.e. hydropower production and flood control. Moreover, we also successfully identify low-frequency climate information associated to El-Nino Southern Oscillation for improving the performance in terms of long-term objectives, i.e. water supply. Finally, we assess the value of better informing operational decisions for adapting the system operations to changing conditions by considering different climate change projections.

  11. The puzzle of partial migration: Adaptive dynamics and evolutionary game theory perspectives.

    Science.gov (United States)

    De Leenheer, Patrick; Mohapatra, Anushaya; Ohms, Haley A; Lytle, David A; Cushing, J M

    2017-01-07

    We consider the phenomenon of partial migration which is exhibited by populations in which some individuals migrate between habitats during their lifetime, but others do not. First, using an adaptive dynamics approach, we show that partial migration can be explained on the basis of negative density dependence in the per capita fertilities alone, provided that this density dependence is attenuated for increasing abundances of the subtypes that make up the population. We present an exact formula for the optimal proportion of migrants which is expressed in terms of the vital rates of migrant and non-migrant subtypes only. We show that this allocation strategy is both an evolutionary stable strategy (ESS) as well as a convergence stable strategy (CSS). To establish the former, we generalize the classical notion of an ESS because it is based on invasion exponents obtained from linearization arguments, which fail to capture the stabilizing effects of the nonlinear density dependence. These results clarify precisely when the notion of a "weak ESS", as proposed in Lundberg (2013) for a related model, is a genuine ESS. Secondly, we use an evolutionary game theory approach, and confirm, once again, that partial migration can be attributed to negative density dependence alone. In this context, the result holds even when density dependence is not attenuated. In this case, the optimal allocation strategy towards migrants is the same as the ESS stemming from the analysis based on the adaptive dynamics. The key feature of the population models considered here is that they are monotone dynamical systems, which enables a rather comprehensive mathematical analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions.

    Science.gov (United States)

    Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick

    2018-01-01

    When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. Copyright © 2017 The Authors. Cognitive Science published by Wiley

  13. An adaptive immune optimization algorithm with dynamic lattice searching operation for fast optimization of atomic clusters

    International Nuclear Information System (INIS)

    Wu, Xia; Wu, Genhua

    2014-01-01

    Highlights: • A high efficient method for optimization of atomic clusters is developed. • Its performance is studied by optimizing Lennard-Jones clusters and Ag clusters. • The method is proved to be quite efficient. • A new Ag 61 cluster with stacking-fault face-centered cubic motif is found. - Abstract: Geometrical optimization of atomic clusters is performed by a development of adaptive immune optimization algorithm (AIOA) with dynamic lattice searching (DLS) operation (AIOA-DLS method). By a cycle of construction and searching of the dynamic lattice (DL), DLS algorithm rapidly makes the clusters more regular and greatly reduces the potential energy. DLS can thus be used as an operation acting on the new individuals after mutation operation in AIOA to improve the performance of the AIOA. The AIOA-DLS method combines the merit of evolutionary algorithm and idea of dynamic lattice. The performance of the proposed method is investigated in the optimization of Lennard-Jones clusters within 250 atoms and silver clusters described by many-body Gupta potential within 150 atoms. Results reported in the literature are reproduced, and the motif of Ag 61 cluster is found to be stacking-fault face-centered cubic, whose energy is lower than that of previously obtained icosahedron

  14. Adaptive Indoor Positioning Model Based on WLAN-Fingerprinting for Dynamic and Multi-Floor Environments

    Directory of Open Access Journals (Sweden)

    Iyad Husni Alshami

    2017-08-01

    Full Text Available The Global Positioning System demonstrates the significance of Location Based Services but it cannot be used indoors due to the lack of line of sight between satellites and receivers. Indoor Positioning Systems are needed to provide indoor Location Based Services. Wireless LAN fingerprints are one of the best choices for Indoor Positioning Systems because of their low cost, and high accuracy, however they have many drawbacks: creating radio maps is time consuming, the radio maps will become outdated with any environmental change, different mobile devices read the received signal strength (RSS differently, and peoples’ presence in LOS between access points and mobile device affects the RSS. This research proposes a new Adaptive Indoor Positioning System model (called DIPS based on: a dynamic radio map generator, RSS certainty technique and peoples’ presence effect integration for dynamic and multi-floor environments. Dynamic in our context refers to the effects of people and device heterogeneity. DIPS can achieve 98% and 92% positioning accuracy for floor and room positioning, and it achieves 1.2 m for point positioning error. RSS certainty enhanced the positioning accuracy for floor and room for different mobile devices by 11% and 9%. Then by considering the peoples’ presence effect, the error is reduced by 0.2 m. In comparison with other works, DIPS achieves better positioning without extra devices.

  15. Iterative Adaptive Dynamic Programming for Solving Unknown Nonlinear Zero-Sum Game Based on Online Data.

    Science.gov (United States)

    Zhu, Yuanheng; Zhao, Dongbin; Li, Xiangjun

    2017-03-01

    H ∞ control is a powerful method to solve the disturbance attenuation problems that occur in some control systems. The design of such controllers relies on solving the zero-sum game (ZSG). But in practical applications, the exact dynamics is mostly unknown. Identification of dynamics also produces errors that are detrimental to the control performance. To overcome this problem, an iterative adaptive dynamic programming algorithm is proposed in this paper to solve the continuous-time, unknown nonlinear ZSG with only online data. A model-free approach to the Hamilton-Jacobi-Isaacs equation is developed based on the policy iteration method. Control and disturbance policies and value are approximated by neural networks (NNs) under the critic-actor-disturber structure. The NN weights are solved by the least-squares method. According to the theoretical analysis, our algorithm is equivalent to a Gauss-Newton method solving an optimization problem, and it converges uniformly to the optimal solution. The online data can also be used repeatedly, which is highly efficient. Simulation results demonstrate its feasibility to solve the unknown nonlinear ZSG. When compared with other algorithms, it saves a significant amount of online measurement time.

  16. Reduced short term adaptation to robot generated dynamic environment in children affected by Cerebral Palsy.

    Science.gov (United States)

    Masia, Lorenzo; Frascarelli, Flaminia; Morasso, Pietro; Di Rosa, Giuseppe; Petrarca, Maurizio; Castelli, Enrico; Cappa, Paolo

    2011-05-21

    It is known that healthy adults can quickly adapt to a novel dynamic environment, generated by a robotic manipulandum as a structured disturbing force field. We suggest that it may be of clinical interest to evaluate to which extent this kind of motor learning capability is impaired in children affected by cerebal palsy. We adapted the protocol already used with adults, which employs a velocity dependant viscous field, and compared the performance of a group of subjects affected by Cerebral Palsy (CP group, 7 subjects) with a Control group of unimpaired age-matched children. The protocol included a familiarization phase (FA), during which no force was applied, a force field adaptation phase (CF), and a wash-out phase (WO) in which the field was removed. During the CF phase the field was shut down in a number of randomly selected "catch" trials, which were used in order to evaluate the "learning index" for each single subject and the two groups. Lateral deviation, speed and acceleration peaks and average speed were evaluated for each trajectory; a directional analysis was performed in order to inspect the role of the limb's inertial anisotropy in the different experimental phases. During the FA phase the movements of the CP subjects were more curved, displaying greater and variable directional error; over the course of the CF phase both groups showed a decreasing trend in the lateral error and an after-effect at the beginning of the wash-out, but the CP group had a non significant adaptation rate and a lower learning index, suggesting that CP subjects have reduced ability to learn to compensate external force. Moreover, a directional analysis of trajectories confirms that the control group is able to better predict the force field by tuning the kinematic features of the movements along different directions in order to account for the inertial anisotropy of arm. Spatial abnormalities in children affected by cerebral palsy may be related not only to disturbance in

  17. Reduced short term adaptation to robot generated dynamic environment in children affected by Cerebral Palsy

    Directory of Open Access Journals (Sweden)

    Di Rosa Giuseppe

    2011-05-01

    Full Text Available Abstract Background It is known that healthy adults can quickly adapt to a novel dynamic environment, generated by a robotic manipulandum as a structured disturbing force field. We suggest that it may be of clinical interest to evaluate to which extent this kind of motor learning capability is impaired in children affected by cerebal palsy. Methods We adapted the protocol already used with adults, which employs a velocity dependant viscous field, and compared the performance of a group of subjects affected by Cerebral Palsy (CP group, 7 subjects with a Control group of unimpaired age-matched children. The protocol included a familiarization phase (FA, during which no force was applied, a force field adaptation phase (CF, and a wash-out phase (WO in which the field was removed. During the CF phase the field was shut down in a number of randomly selected "catch" trials, which were used in order to evaluate the "learning index" for each single subject and the two groups. Lateral deviation, speed and acceleration peaks and average speed were evaluated for each trajectory; a directional analysis was performed in order to inspect the role of the limb's inertial anisotropy in the different experimental phases. Results During the FA phase the movements of the CP subjects were more curved, displaying greater and variable directional error; over the course of the CF phase both groups showed a decreasing trend in the lateral error and an after-effect at the beginning of the wash-out, but the CP group had a non significant adaptation rate and a lower learning index, suggesting that CP subjects have reduced ability to learn to compensate external force. Moreover, a directional analysis of trajectories confirms that the control group is able to better predict the force field by tuning the kinematic features of the movements along different directions in order to account for the inertial anisotropy of arm. Conclusions Spatial abnormalities in children affected

  18. Adaptive dynamic programming for discrete-time linear quadratic regulation based on multirate generalised policy iteration

    Science.gov (United States)

    Chun, Tae Yoon; Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho

    2018-06-01

    In this paper, we propose two multirate generalised policy iteration (GPI) algorithms applied to discrete-time linear quadratic regulation problems. The proposed algorithms are extensions of the existing GPI algorithm that consists of the approximate policy evaluation and policy improvement steps. The two proposed schemes, named heuristic dynamic programming (HDP) and dual HDP (DHP), based on multirate GPI, use multi-step estimation (M-step Bellman equation) at the approximate policy evaluation step for estimating the value function and its gradient called costate, respectively. Then, we show that these two methods with the same update horizon can be considered equivalent in the iteration domain. Furthermore, monotonically increasing and decreasing convergences, so called value iteration (VI)-mode and policy iteration (PI)-mode convergences, are proved to hold for the proposed multirate GPIs. Further, general convergence properties in terms of eigenvalues are also studied. The data-driven online implementation methods for the proposed HDP and DHP are demonstrated and finally, we present the results of numerical simulations performed to verify the effectiveness of the proposed methods.

  19. Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

    Science.gov (United States)

    Takiyama, Ken

    2017-12-01

    How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

  20. Adaptive fuzzy dynamic surface control for the chaotic permanent magnet synchronous motor using Nussbaum gain

    Energy Technology Data Exchange (ETDEWEB)

    Luo, Shaohua [School of Automation, Chongqing University, Chongqing 400044, China and College of Mechanical Engineering, Hunan University of Arts and Science, Hunan 415000 (China)

    2014-09-01

    This paper is concerned with the problem of adaptive fuzzy dynamic surface control (DSC) for the permanent magnet synchronous motor (PMSM) system with chaotic behavior, disturbance and unknown control gain and parameters. Nussbaum gain is adopted to cope with the situation that the control gain is unknown. And the unknown items can be estimated by fuzzy logic system. The proposed controller guarantees that all the signals in the closed-loop system are bounded and the system output eventually converges to a small neighborhood of the desired reference signal. Finally, the numerical simulations indicate that the proposed scheme can suppress the chaos of PMSM and show the effectiveness and robustness of the proposed method.

  1. Adaptive polarization image fusion based on regional energy dynamic weighted average

    Institute of Scientific and Technical Information of China (English)

    ZHAO Yong-qiang; PAN Quan; ZHANG Hong-cai

    2005-01-01

    According to the principle of polarization imaging and the relation between Stokes parameters and the degree of linear polarization, there are much redundant and complementary information in polarized images. Since man-made objects and natural objects can be easily distinguished in images of degree of linear polarization and images of Stokes parameters contain rich detailed information of the scene, the clutters in the images can be removed efficiently while the detailed information can be maintained by combining these images. An algorithm of adaptive polarization image fusion based on regional energy dynamic weighted average is proposed in this paper to combine these images. Through an experiment and simulations,most clutters are removed by this algorithm. The fusion method is used for different light conditions in simulation, and the influence of lighting conditions on the fusion results is analyzed.

  2. A self-adapting herding model: The agent judge-abilities influence the dynamic behaviors

    Science.gov (United States)

    Dong, Linrong

    2008-10-01

    We propose a self-adapting herding model, in which the financial markets consist of agent clusters with different sizes and market desires. The ratio of successful exchange and merger depends on the volatility of the market and the market desires of the agent clusters. The desires are assigned in term of the wealth of the agent clusters when they merge. After an exchange, the beneficial cluster’s desire keeps on the same, the losing one’s desire is altered which is correlative with the agent judge-ability. A parameter R is given to all agents to denote the judge-ability. The numerical calculation shows that the dynamic behaviors of the market are influenced distinctly by R, which includes the exponential magnitudes of the probability distribution of sizes of the agent clusters and the volatility autocorrelation of the returns, the intensity and frequency of the volatility.

  3. 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.

  4. Quantum Dynamics with Short-Time Trajectories and Minimal Adaptive Basis Sets.

    Science.gov (United States)

    Saller, Maximilian A C; Habershon, Scott

    2017-07-11

    Methods for solving the time-dependent Schrödinger equation via basis set expansion of the wave function can generally be categorized as having either static (time-independent) or dynamic (time-dependent) basis functions. We have recently introduced an alternative simulation approach which represents a middle road between these two extremes, employing dynamic (classical-like) trajectories to create a static basis set of Gaussian wavepackets in regions of phase-space relevant to future propagation of the wave function [J. Chem. Theory Comput., 11, 8 (2015)]. Here, we propose and test a modification of our methodology which aims to reduce the size of basis sets generated in our original scheme. In particular, we employ short-time classical trajectories to continuously generate new basis functions for short-time quantum propagation of the wave function; to avoid the continued growth of the basis set describing the time-dependent wave function, we employ Matching Pursuit to periodically minimize the number of basis functions required to accurately describe the wave function. Overall, this approach generates a basis set which is adapted to evolution of the wave function while also being as small as possible. In applications to challenging benchmark problems, namely a 4-dimensional model of photoexcited pyrazine and three different double-well tunnelling problems, we find that our new scheme enables accurate wave function propagation with basis sets which are around an order-of-magnitude smaller than our original trajectory-guided basis set methodology, highlighting the benefits of adaptive strategies for wave function propagation.

  5. Dynamics of the exponential integrate-and-fire model with slow currents and adaptation.

    Science.gov (United States)

    Barranca, Victor J; Johnson, Daniel C; Moyher, Jennifer L; Sauppe, Joshua P; Shkarayev, Maxim S; Kovačič, Gregor; Cai, David

    2014-08-01

    In order to properly capture spike-frequency adaptation with a simplified point-neuron model, we study approximations of Hodgkin-Huxley (HH) models including slow currents by exponential integrate-and-fire (EIF) models that incorporate the same types of currents. We optimize the parameters of the EIF models under the external drive consisting of AMPA-type conductance pulses using the current-voltage curves and the van Rossum metric to best capture the subthreshold membrane potential, firing rate, and jump size of the slow current at the neuron's spike times. Our numerical simulations demonstrate that, in addition to these quantities, the approximate EIF-type models faithfully reproduce bifurcation properties of the HH neurons with slow currents, which include spike-frequency adaptation, phase-response curves, critical exponents at the transition between a finite and infinite number of spikes with increasing constant external drive, and bifurcation diagrams of interspike intervals in time-periodically forced models. Dynamics of networks of HH neurons with slow currents can also be approximated by corresponding EIF-type networks, with the approximation being at least statistically accurate over a broad range of Poisson rates of the external drive. For the form of external drive resembling realistic, AMPA-like synaptic conductance response to incoming action potentials, the EIF model affords great savings of computation time as compared with the corresponding HH-type model. Our work shows that the EIF model with additional slow currents is well suited for use in large-scale, point-neuron models in which spike-frequency adaptation is important.

  6. The dynamics of socio-psychological adaptation of adolescents engaged in artistic creativity

    Directory of Open Access Journals (Sweden)

    Chernaya Yu.S.

    2017-07-01

    Full Text Available this article presents a study of the dynamics of socio-psychological adaptation in adolescents during the course of pictorial arts. 60 teenagers aged 13 to 17 years have been participating in a longitudinal study for three years, systematically involved and not involved in pictorial art. It has been found that the creative adolescents have lower level of neuro-psychological adaptation and higher level of subjective feelings of loneliness than non-creative adolescents. But creative teenagers have significantly higher self-esteem, level of aspiration and satisfaction in achieving success and lower anxiety in relationships with adults. The influence of the creative group reflected on such personal qualities as: self-confidence, credibility among peers, ability to do things with their hands, social identity, loneliness, frustration needs in achieving success, problems and fears in relations with adults. The personal characteristics of creative adolescents have been identified. These characteristics distinguish them from others teenagers, and the effect of the creative group and creative activity indirectly on the personal qualities of adolescents.

  7. Evolutionary dynamics of molecular markers during local adaptation: a case study in Drosophila subobscura

    Directory of Open Access Journals (Sweden)

    Matos Margarida

    2009-06-01

    Full Text Available Abstract Here we present a correction to our article "Evolutionary dynamics of molecular markers during local adaptation: a case study in Drosophila subobscura". We have recently detected an error concerning the application of the Ln RH formula – a test to detect positive selection – to our microsatellite data. Here we provide the corrected data and discuss its implications for our overall findings. The corrections presented here have produced some changes relative to our previous results, namely in a locus (dsub14 that presents indications of being affected by positive selection. In general, our populations present less consistent indications of positive selection for this particular locus in both periods studied – between generations 3 and 14 and between generation 14 and 40 of laboratory adaptation. Despite this, the main findings of our study regarding the possibility of positive selection acting on that particular microsatellite still hold. As previously concluded in our article, further studies should be performed on this specific microsatellite locus (and neighboring areas to elucidate in greater detail the evolutionary forces acting on this specific region of the O chromosome of Drosophila subobscura.

  8. Physiological complexity and system adaptability: evidence from postural control dynamics of older adults.

    Science.gov (United States)

    Manor, Brad; Costa, Madalena D; Hu, Kun; Newton, Elizabeth; Starobinets, Olga; Kang, Hyun Gu; Peng, C K; Novak, Vera; Lipsitz, Lewis A

    2010-12-01

    The degree of multiscale complexity in human behavioral regulation, such as that required for postural control, appears to decrease with advanced aging or disease. To help delineate causes and functional consequences of complexity loss, we examined the effects of visual and somatosensory impairment on the complexity of postural sway during quiet standing and its relationship to postural adaptation to cognitive dual tasking. Participants of the MOBILIZE Boston Study were classified into mutually exclusive groups: controls [intact vision and foot somatosensation, n = 299, 76 ± 5 (SD) yr old], visual impairment only (Postural sway (i.e., center-of-pressure) dynamics were assessed during quiet standing and cognitive dual tasking, and a complexity index was quantified using multiscale entropy analysis. Postural sway speed and area, which did not correlate with complexity, were also computed. During quiet standing, the complexity index (mean ± SD) was highest in controls (9.5 ± 1.2) and successively lower in the visual (9.1 ± 1.1), somatosensory (8.6 ± 1.6), and combined (7.8 ± 1.3) impairment groups (P = 0.001). Dual tasking resulted in increased sway speed and area but reduced complexity (P postural sway speed from quiet standing to dual-tasking conditions. Sensory impairments contributed to decreased postural sway complexity, which reflected reduced adaptive capacity of the postural control system. Relatively low baseline complexity may, therefore, indicate control systems that are more vulnerable to cognitive and other stressors.

  9. A Dynamically Adaptable Impedance-Matching System for Midrange Wireless Power Transfer with Misalignment

    Directory of Open Access Journals (Sweden)

    Thuc Phi Duong

    2015-07-01

    Full Text Available To enable the geometrical freedom envisioned for wireless power transfer (WPT, fast dynamic adaptation to unpredictable changes in receiver position is needed. In this paper, we propose an adaptive impedance-searching system that achieves good impedance matching quickly. For fast and robust operation, the proposed method consists of three steps: system calibration, coarse search, and fine search. The proposed WPT system is characterized using distance variation and lateral and angular misalignment between coils. The measured results indicate that the proposed method significantly reduces searching time from a few minutes to approximately one second. Furthermore, the proposed system achieves impedance matching with good accuracy. The robust impedance-searching capability of the proposed system significantly improves power transfer efficiency. At 6.78 MHz, we achieve a maximum efficiency of 89.7% and a high efficiency of >80% up to a distance of 50 cm. When the center-to-center misalignment is 35 cm, the efficiency is improved from 48.4% to 74.1% with the proposed method. At a distance of 40 cm, the efficiency is higher than 74% for up to 60° of angular rotation. These results agree well with the simulated results obtained using a lumped-element circuit model.

  10. An adaptive cubature formula for efficient reliability assessment of nonlinear structural dynamic systems

    Science.gov (United States)

    Xu, Jun; Kong, Fan

    2018-05-01

    Extreme value distribution (EVD) evaluation is a critical topic in reliability analysis of nonlinear structural dynamic systems. In this paper, a new method is proposed to obtain the EVD. The maximum entropy method (MEM) with fractional moments as constraints is employed to derive the entire range of EVD. Then, an adaptive cubature formula is proposed for fractional moments assessment involved in MEM, which is closely related to the efficiency and accuracy for reliability analysis. Three point sets, which include a total of 2d2 + 1 integration points in the dimension d, are generated in the proposed formula. In this regard, the efficiency of the proposed formula is ensured. Besides, a "free" parameter is introduced, which makes the proposed formula adaptive with the dimension. The "free" parameter is determined by arranging one point set adjacent to the boundary of the hyper-sphere which contains the bulk of total probability. In this regard, the tail distribution may be better reproduced and the fractional moments could be evaluated with accuracy. Finally, the proposed method is applied to a ten-storey shear frame structure under seismic excitations, which exhibits strong nonlinearity. The numerical results demonstrate the efficacy of the proposed method.

  11. Micro-Level Adaptation, Macro-Level Selection, and the Dynamics of Market Partitioning.

    Science.gov (United States)

    García-Díaz, César; van Witteloostuijn, Arjen; Péli, Gábor

    2015-01-01

    This paper provides a micro-foundation for dual market structure formation through partitioning processes in marketplaces by developing a computational model of interacting economic agents. We propose an agent-based modeling approach, where firms are adaptive and profit-seeking agents entering into and exiting from the market according to their (lack of) profitability. Our firms are characterized by large and small sunk costs, respectively. They locate their offerings along a unimodal demand distribution over a one-dimensional product variety, with the distribution peak constituting the center and the tails standing for the peripheries. We found that large firms may first advance toward the most abundant demand spot, the market center, and release peripheral positions as predicted by extant dual market explanations. However, we also observed that large firms may then move back toward the market fringes to reduce competitive niche overlap in the center, triggering nonlinear resource occupation behavior. Novel results indicate that resource release dynamics depend on firm-level adaptive capabilities, and that a minimum scale of production for low sunk cost firms is key to the formation of the dual structure.

  12. “Push” dynamics in policy experimentation: Downscaling climate change adaptation programs in Canada

    Directory of Open Access Journals (Sweden)

    Adam Wellstead

    2016-12-01

    Full Text Available Policy experiments have often been touted as valuable mechanisms for ensuring sustainability transitions and climate change adaptation. However problems exist both in the definition of ‘experiments’, and in their design and realization. While valuable, most experiments examined in the literature to date have been small-scale micro-level deployments or evaluations of policy tools in which the most problematic element revolves around their “scaling-up” or diffusion. The literature on the subject has generally neglected the problems and issues related to another class of experiments in which macro or meso-level initiatives are ‘scaled-down’ to the micro-level. This paper examines a recent effort of this kind in Canada involving the creation of Regional Adaptation Collaboratives (RACs across the country whose main purpose is to push national level initiatives down to the regions and localities. As the discussion shows, this top-down process has its own dynamics distinct from those involved in ‘scaling up’ and should be examined as a separate category of policy experiments in its own right.

  13. Dynamic Speed Adaptation for Path Tracking Based on Curvature Information and Speed Limits.

    Science.gov (United States)

    Gámez Serna, Citlalli; Ruichek, Yassine

    2017-06-14

    A critical concern of autonomous vehicles is safety. Different approaches have tried to enhance driving safety to reduce the number of fatal crashes and severe injuries. As an example, Intelligent Speed Adaptation (ISA) systems warn the driver when the vehicle exceeds the recommended speed limit. However, these systems only take into account fixed speed limits without considering factors like road geometry. In this paper, we consider road curvature with speed limits to automatically adjust vehicle's speed with the ideal one through our proposed Dynamic Speed Adaptation (DSA) method. Furthermore, 'curve analysis extraction' and 'speed limits database creation' are also part of our contribution. An algorithm that analyzes GPS information off-line identifies high curvature segments and estimates the speed for each curve. The speed limit database contains information about the different speed limit zones for each traveled path. Our DSA senses speed limits and curves of the road using GPS information and ensures smooth speed transitions between current and ideal speeds. Through experimental simulations with different control algorithms on real and simulated datasets, we prove that our method is able to significantly reduce lateral errors on sharp curves, to respect speed limits and consequently increase safety and comfort for the passenger.

  14. MEKANISME SEGMENTASI LAJU BIT PADA DYNAMIC ADAPTIVE STREAMING OVER HTTP (DASH UNTUK APLIKASI VIDEO STREAMING

    Directory of Open Access Journals (Sweden)

    Muhammad Audy Bazly

    2015-12-01

    Full Text Available This paper aims to analyze Internet-based streaming video service in the communication media with variable bit rates. The proposed scheme on Dynamic Adaptive Streaming over HTTP (DASH using the internet network that adapts to the protocol Hyper Text Transfer Protocol (HTTP. DASH technology allows a video in the video segmentation into several packages that will distreamingkan. DASH initial stage is to compress the video source to lower the bit rate video codec uses H.26. Video compressed further in the segmentation using MP4Box generates streaming packets with the specified duration. These packages are assembled into packets in a streaming media format Presentation Description (MPD or known as MPEG-DASH. Streaming video format MPEG-DASH run on a platform with the player bitdash teritegrasi bitcoin. With this scheme, the video will have several variants of the bit rates that gave rise to the concept of scalability of streaming video services on the client side. The main target of the mechanism is smooth the MPEG-DASH streaming video display on the client. The simulation results show that the scheme based scalable video streaming MPEG- DASH able to improve the quality of image display on the client side, where the procedure bufering videos can be made constant and fine for the duration of video views

  15. Dynamic models of farmers adaptation to climate change (case of rice farmers in Cemoro Watershed, Central Java, Indonesia)

    Science.gov (United States)

    Sugihardjo; Sutrisno, J.; Setyono, P.; Suntoro

    2018-03-01

    Farming activities are generally very sensitive to climate change variations. Global climate change will result in changes of patterns and distribution of rainfall. The impact of changing patterns and distribution of rainfall is the occurrence of early season shifts and periods of planting. Therefore, farmers need to adapt to the occurrence of climate change to avoid the decrease productivity on the farm land. This study aims to examine the impacts of climate change adaptation that farmers practiced on the farming productivity. The analysis is conducted dynamically using the Powersim 2.5. The result of analysis shows that the use of Planting Calendar and Integrated Crops Management technology can increase the rice productivity of certain area unity. Both technologies are the alternatives for farmers to adapt to climate change. Both farmers who adapt to climate change and do not adapt to climate change, experience an increase in rice production, time after time. However, farmers who adapt to climate change, increase their production faster than farmers who do not adapt to climate change. The use of the Planting Calendar and Integrated Crops Management strategy together as a farmers’ adaptation strategy is able to increase production compared to non-adaptive farmers.

  16. Output Feedback Adaptive Dynamic Surface Control of Permanent Magnet Synchronous Motor with Uncertain Time Delays via RBFNN

    Directory of Open Access Journals (Sweden)

    Shaohua Luo

    2014-01-01

    Full Text Available This paper focuses on an adaptive dynamic surface control based on the Radial Basis Function Neural Network for a fourth-order permanent magnet synchronous motor system wherein the unknown parameters, disturbances, chaos, and uncertain time delays are presented. Neural Network systems are used to approximate the nonlinearities and an adaptive law is employed to estimate accurate parameters. Then, a simple and effective controller has been obtained by introducing dynamic surface control technique on the basis of first-order filters. Asymptotically tracking stability in the sense of uniformly ultimate boundedness is achieved in a short time. Finally, the performance of the proposed control has been illustrated through simulation results.

  17. Pinning adaptive synchronization of a class of uncertain complex dynamical networks with multi-link against network deterioration

    International Nuclear Information System (INIS)

    Li, Lixiang; Li, Weiwei; Kurths, Jürgen; Luo, Qun; Yang, Yixian; Li, Shudong

    2015-01-01

    For the reason that the uncertain complex dynamic network with multi-link is quite close to various practical networks, there is superiority in the fields of research and application. In this paper, we focus upon pinning adaptive synchronization for uncertain complex dynamic networks with multi-link against network deterioration. The pinning approach can be applied to adapt uncertain coupling factors of deteriorated networks which can compensate effects of uncertainty. Several new synchronization criterions for networks with multi-link are derived, which ensure the synchronized states to be local or global stable with uncertainty and deterioration. Results of simulation are shown to demonstrate the feasibility and usefulness of our method

  18. Adaptive control of robotic manipulators

    Science.gov (United States)

    Seraji, H.

    1987-01-01

    The author presents a novel approach to adaptive control of manipulators to achieve trajectory tracking by the joint angles. The central concept in this approach is the utilization of the manipulator inverse as a feedforward controller. The desired trajectory is applied as an input to the feedforward controller which behaves as the inverse of the manipulator at any operating point; the controller output is used as the driving torque for the manipulator. The controller gains are then updated by an adaptation algorithm derived from MRAC (model reference adaptive control) theory to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal are also used to enhance closed-loop stability and to achieve faster adaptation. The proposed control scheme is computationally fast and does not require a priori knowledge of the complex dynamic model or the parameter values of the manipulator or the payload.

  19. Societal transformation and adaptation necessary to manage dynamics in flood hazard and risk mitigation (TRANS-ADAPT)

    Science.gov (United States)

    Fuchs, Sven; Thaler, Thomas; Bonnefond, Mathieu; Clarke, Darren; Driessen, Peter; Hegger, Dries; Gatien-Tournat, Amandine; Gralepois, Mathilde; Fournier, Marie; Mees, Heleen; Murphy, Conor; Servain-Courant, Sylvie

    2015-04-01

    Facing the challenges of climate change, this project aims to analyse and to evaluate the multiple use of flood alleviation schemes with respect to social transformation in communities exposed to flood hazards in Europe. The overall goals are: (1) the identification of indicators and parameters necessary for strategies to increase societal resilience, (2) an analysis of the institutional settings needed for societal transformation, and (3) perspectives of changing divisions of responsibilities between public and private actors necessary to arrive at more resilient societies. This proposal assesses societal transformations from the perspective of changing divisions of responsibilities between public and private actors necessary to arrive at more resilient societies. Yet each risk mitigation measure is built on a narrative of exchanges and relations between people and therefore may condition the outputs. As such, governance is done by people interacting and defining risk mitigation measures as well as climate change adaptation are therefore simultaneously both outcomes of, and productive to, public and private responsibilities. Building off current knowledge this project will focus on different dimensions of adaptation and mitigation strategies based on social, economic and institutional incentives and settings, centring on the linkages between these different dimensions and complementing existing flood risk governance arrangements. The policy dimension of adaptation, predominantly decisions on the societal admissible level of vulnerability and risk, will be evaluated by a human-environment interaction approach using multiple methods and the assessment of social capacities of stakeholders across scales. As such, the challenges of adaptation to flood risk will be tackled by converting scientific frameworks into practical assessment and policy advice. In addressing the relationship between these dimensions of adaptation on different temporal and spatial scales, this

  20. Linear hypergeneralization of learned dynamics across movement speeds reveals anisotropic, gain-encoding primitives for motor adaptation.

    Science.gov (United States)

    Joiner, Wilsaan M; Ajayi, Obafunso; Sing, Gary C; Smith, Maurice A

    2011-01-01

    The ability to generalize learned motor actions to new contexts is a key feature of the motor system. For example, the ability to ride a bicycle or swing a racket is often first developed at lower speeds and later applied to faster velocities. A number of previous studies have examined the generalization of motor adaptation across movement directions and found that the learned adaptation decays in a pattern consistent with the existence of motor primitives that display narrow Gaussian tuning. However, few studies have examined the generalization of motor adaptation across movement speeds. Following adaptation to linear velocity-dependent dynamics during point-to-point reaching arm movements at one speed, we tested the ability of subjects to transfer this adaptation to short-duration higher-speed movements aimed at the same target. We found near-perfect linear extrapolation of the trained adaptation with respect to both the magnitude and the time course of the velocity profiles associated with the high-speed movements: a 69% increase in movement speed corresponded to a 74% extrapolation of the trained adaptation. The close match between the increase in movement speed and the corresponding increase in adaptation beyond what was trained indicates linear hypergeneralization. Computational modeling shows that this pattern of linear hypergeneralization across movement speeds is not compatible with previous models of adaptation in which motor primitives display isotropic Gaussian tuning of motor output around their preferred velocities. Instead, we show that this generalization pattern indicates that the primitives involved in the adaptation to viscous dynamics display anisotropic tuning in velocity space and encode the gain between motor output and motion state rather than motor output itself.

  1. Adaptation in constitutional dynamic libraries and networks, switching between orthogonal metalloselection and photoselection processes.

    Science.gov (United States)

    Vantomme, Ghislaine; Jiang, Shimei; Lehn, Jean-Marie

    2014-07-02

    Constitutional dynamic libraries of hydrazones (a)A(b)B and acylhydrazones (a)A(c)C undergo reorganization and adaptation in response to a chemical effector (metal cations) or a physical stimulus (light). The set of hydrazones [(1)A(1)B, (1)A(2)B, (2)A(1)B, (2)A(2)B] undergoes metalloselection on addition of zinc cations which drive the amplification of Zn((1)A(2)B)2 by selection of the fittest component (1)A(2)B. The set of acylhydrazones [E-(1)A(1)C, (1)A(2)C, (2)A(1)C, (2)A(2)C] undergoes photoselection by irradiation of the system, which causes photoisomerization of E-(1)A(1)C into Z-(1)A(1)C with amplification of the latter. The set of acyl hydrazones [E-(1)A(1)C, (1)A(3)C, (2)A(1)C, (2)A(3)C] undergoes a dual adaptation via component exchange and selection in response to two orthogonal external agents: a chemical effector, metal cations, and a physical stimulus, light irradiation. Metalloselection takes place on addition of zinc cations which drive the amplification of Zn((1)A(3)C)2 by selection of the fittest constituent (1)A(3)C. Photoselection is obtained on irradiation of the acylhydrazones that leads to photoisomerization from E-(1)A(1)C to Z-(1)A(1)C configuration with amplification of the latter. These changes may be represented by square constitutional dynamic networks that display up-regulation of the pairs of agonists ((1)A(2)B, (2)A(1)B), (Z-(1)A(1)C, (2)A(2)C), ((1)A(3)C, (2)A(1)C), (Z-(1)A(1)C, (2)A(3)C) and the simultaneous down-regulation of the pairs of antagonists ((1)A(1)B, (2)A(2)B), ((1)A(2)C, (2)A(1)C), (E-(1)A(1)C, (2)A(3)C), ((1)A(3)C, (2)A(1)C). The orthogonal dual adaptation undergone by the set of acylhydrazones amounts to a network switching process.

  2. An efficient scenario-based and fuzzy self-adaptive learning particle swarm optimization approach for dynamic economic emission dispatch considering load and wind power uncertainties

    International Nuclear Information System (INIS)

    Bahmani-Firouzi, Bahman; Farjah, Ebrahim; Azizipanah-Abarghooee, Rasoul

    2013-01-01

    Renewable energy resources such as wind power plants are playing an ever-increasing role in power generation. This paper extends the dynamic economic emission dispatch problem by incorporating wind power plant. This problem is a multi-objective optimization approach in which total electrical power generation costs and combustion emissions are simultaneously minimized over a short-term time span. A stochastic approach based on scenarios is suggested to model the uncertainty associated with hourly load and wind power forecasts. A roulette wheel technique on the basis of probability distribution functions of load and wind power is implemented to generate scenarios. As a result, the stochastic nature of the suggested problem is emancipated by decomposing it into a set of equivalent deterministic problem. An improved multi-objective particle swarm optimization algorithm is applied to obtain the best expected solutions for the proposed stochastic programming framework. To enhance the overall performance and effectiveness of the particle swarm optimization, a fuzzy adaptive technique, θ-search and self-adaptive learning strategy for velocity updating are used to tune the inertia weight factor and to escape from local optima, respectively. The suggested algorithm goes through the search space in the polar coordinates instead of the Cartesian one; whereby the feasible space is more compact. In order to evaluate the efficiency and feasibility of the suggested framework, it is applied to two test systems with small and large scale characteristics. - Highlights: ► Formulates multi-objective DEED problem under a stochastic programming framework. ► Considers uncertainties related to forecasted values of load demand and wind power. ► Proposes an interactive fuzzy satisfying method based on the novel FSALPSO. ► Presents a new self-adaptive learning strategy to improve original PSO algorithm

  3. A novel adaptive control scheme for dynamic performance improvement of DFIG-Based wind turbines

    International Nuclear Information System (INIS)

    Song, Zhanfeng; Shi, Tingna; Xia, Changliang; Chen, Wei

    2012-01-01

    A novel adaptive current controller for DFIG-based wind turbines is introduced in this paper. The attractiveness of the proposed strategy results from its ability to actively estimate and actively compensate for the plant dynamics and external disturbances in real time. Thus, the control strategy can successfully drive the rotor current to track the reference value, ensuring that the performance degradation caused by grid disturbances, cross-coupling terms and parameter uncertainties can be successfully suppressed. Besides, the two-parameter tuning feature makes the control strategy practical and easy to implement in commercial wind turbines. To quantify the controller performances, the transfer function description of the controller is derived. General disturbance rejection, robustness against parameter uncertainties, bandwidth and stability are also addressed. Simulation results, together with the time-domain responses, proved the stability and the strong robustness of the control system against parameter uncertainties and grid disturbances. Significant tracking and disturbance rejection performances are achieved. -- Highlights: ► The controller can compensate for plant dynamics and external disturbances. ► Performance degradation caused by disturbance can be successfully suppressed. ► General disturbance rejection of the proposed strategy is addressed. ► The stability and the strong robustness of the control system are proved.

  4. Adaptive resolution simulation of a biomolecule and its hydration shell: Structural and dynamical properties

    International Nuclear Information System (INIS)

    Fogarty, Aoife C.; Potestio, Raffaello; Kremer, Kurt

    2015-01-01

    A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydration shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations

  5. An adaptively refined XFEM with virtual node polygonal elements for dynamic crack problems

    Science.gov (United States)

    Teng, Z. H.; Sun, F.; Wu, S. C.; Zhang, Z. B.; Chen, T.; Liao, D. M.

    2018-02-01

    By introducing the shape functions of virtual node polygonal (VP) elements into the standard extended finite element method (XFEM), a conforming elemental mesh can be created for the cracking process. Moreover, an adaptively refined meshing with the quadtree structure only at a growing crack tip is proposed without inserting hanging nodes into the transition region. A novel dynamic crack growth method termed as VP-XFEM is thus formulated in the framework of fracture mechanics. To verify the newly proposed VP-XFEM, both quasi-static and dynamic cracked problems are investigated in terms of computational accuracy, convergence, and efficiency. The research results show that the present VP-XFEM can achieve good agreement in stress intensity factor and crack growth path with the exact solutions or experiments. Furthermore, better accuracy, convergence, and efficiency of different models can be acquired, in contrast to standard XFEM and mesh-free methods. Therefore, VP-XFEM provides a suitable alternative to XFEM for engineering applications.

  6. Adaptive resolution simulation of a biomolecule and its hydration shell: Structural and dynamical properties

    Energy Technology Data Exchange (ETDEWEB)

    Fogarty, Aoife C., E-mail: fogarty@mpip-mainz.mpg.de; Potestio, Raffaello, E-mail: potestio@mpip-mainz.mpg.de; Kremer, Kurt, E-mail: kremer@mpip-mainz.mpg.de [Max Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz (Germany)

    2015-05-21

    A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydration shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations.

  7. Highly Dynamic and Adaptive Traffic Congestion Avoidance in Real-Time Inspired by Honey Bee Behavior

    Science.gov (United States)

    Wedde, Horst F.; Lehnhoff, Sebastian; van Bonn, Bernhard; Bay, Z.; Becker, S.; Böttcher, S.; Brunner, C.; Büscher, A.; Fürst, T.; Lazarescu, A. M.; Rotaru, E.; Senge, S.; Steinbach, B.; Yilmaz, F.; Zimmermann, T.

    Traffic congestions have become a major problem in metropolitan areas world-wide, within and between cities, to an extent where they make driving and transportation times largely unpredictable. Due to the highly dynamic character of congestion building and dissolving this phenomenon appears even to resist a formal treatment. Static approaches, and even more their global management, have proven counterproductive in practice. Given the latest progress in VANET technology and the remarkable commercially driven efforts like in the European C2C consortium, or the VSC Project in the US, allow meanwhile to tackle various aspects of traffic regulation through VANET communication. In this paper we introduce a novel, completely decentralized multi-agent routing algorithm (termed BeeJamA) which we have derived from the foraging behavior of honey bees. It is highly dynamic, adaptive, robust, and scalable, and it allows for both avoiding congestions, and minimizing traveling times to individual destinations. Vehicle guidance is provided well ahead of every intersection, depending on the individual speeds. Thus strict deadlines are imposed on, and respected by, the BeeJamA algorithm. We report on extensive simulation experiments which show the superior performance of BeeJamA over conventional approaches.

  8. High-dynamic range compressive spectral imaging by grayscale coded aperture adaptive filtering

    Directory of Open Access Journals (Sweden)

    Nelson Eduardo Diaz

    2015-09-01

    Full Text Available The coded aperture snapshot spectral imaging system (CASSI is an imaging architecture which senses the three dimensional informa-tion of a scene with two dimensional (2D focal plane array (FPA coded projection measurements. A reconstruction algorithm takes advantage of the compressive measurements sparsity to recover the underlying 3D data cube. Traditionally, CASSI uses block-un-block coded apertures (BCA to spatially modulate the light. In CASSI the quality of the reconstructed images depends on the design of these coded apertures and the FPA dynamic range. This work presents a new CASSI architecture based on grayscaled coded apertu-res (GCA which reduce the FPA saturation and increase the dynamic range of the reconstructed images. The set of GCA is calculated in a real-time adaptive manner exploiting the information from the FPA compressive measurements. Extensive simulations show the attained improvement in the quality of the reconstructed images when GCA are employed.  In addition, a comparison between traditional coded apertures and GCA is realized with respect to noise tolerance.

  9. Analysis of Static and Dynamic E-Reference Content at a Multi-Campus University Shows, that Updated Content is Associated with Greater Annual Usage

    Directory of Open Access Journals (Sweden)

    Laura Costello

    2016-03-01

    Full Text Available Objective – To discover whether there is a difference in use over time between dynamically updated and changing subscription e-reference titles and collections, and static purchased e-reference titles and collections. Design – Case study. Setting – A multi-campus Canadian university with 9,200 students enrolled in both graduate and undergraduate programs. Subjects – E-reference book packages and individual e-reference titles. Methods – The author compared data from individual e-reference books and packages. First, individual subscription e-reference books that periodically added updated content were compared to individually purchased e-reference books that remained static after purchase. The author then compared two e-reference book packages that provided new and updated content to two static e-reference book packages. The author compared data from patron usage to new content added over time using regression analysis. Main Results – As the library acquired e-reference titles, dynamic title subscriptions added to the collection were associated with 2,246 to 4,635 views per subscription while static title additions were associated with 8 to 123 views per purchase. The author also found that there was a strong linear relationship between views and dynamic titles added to the collection (R2=0.79 and a very weak linear relationship (R2=0.18 with views when static titles are added to the collection. Regression analysis of dynamic e-reference collections revealed that the number of titles added to each collection was strongly associated with views of the material (R2=0.99, while static e-reference collections were less strongly linked (R2=0.43. Conclusion – Dynamic e-reference titles and collections experienced increases in usage each year while static titles and collections experienced decreases in usage. This indicates that collections and titles that offer new content to users each year will continue to see growth in usage while static

  10. Application of Non-Kolmogorovian Probability and Quantum Adaptive Dynamics to Unconscious Inference in Visual Perception Process

    Science.gov (United States)

    Accardi, Luigi; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

    2016-07-01

    Recently a novel quantum information formalism — quantum adaptive dynamics — was developed and applied to modelling of information processing by bio-systems including cognitive phenomena: from molecular biology (glucose-lactose metabolism for E.coli bacteria, epigenetic evolution) to cognition, psychology. From the foundational point of view quantum adaptive dynamics describes mutual adapting of the information states of two interacting systems (physical or biological) as well as adapting of co-observations performed by the systems. In this paper we apply this formalism to model unconscious inference: the process of transition from sensation to perception. The paper combines theory and experiment. Statistical data collected in an experimental study on recognition of a particular ambiguous figure, the Schröder stairs, support the viability of the quantum(-like) model of unconscious inference including modelling of biases generated by rotation-contexts. From the probabilistic point of view, we study (for concrete experimental data) the problem of contextuality of probability, its dependence on experimental contexts. Mathematically contextuality leads to non-Komogorovness: probability distributions generated by various rotation contexts cannot be treated in the Kolmogorovian framework. At the same time they can be embedded in a “big Kolmogorov space” as conditional probabilities. However, such a Kolmogorov space has too complex structure and the operational quantum formalism in the form of quantum adaptive dynamics simplifies the modelling essentially.

  11. Failure of large transformation projects from the viewpoint of complex adaptive systems: Management principles for dealing with project dynamics

    NARCIS (Netherlands)

    Janssen, M.; Voort, H. van der; Veenstra, A.F.E. van

    2015-01-01

    Many large transformation projects do not result in the outcomes desired or envisioned by the stakeholders. This type of project is characterised by dynamics which are both caused by and result of uncertainties and unexpected behaviour. In this paper a complex adaptive system (CAS) view was adopted

  12. Dynamic adaptation of cardiac baroreflex sensitivity to prolonged exposure to microgravity: data from a 16-day spaceflight

    NARCIS (Netherlands)

    Di Rienzo, Marco; Castiglioni, Paolo; Iellamo, Ferdinando; Volterrani, Maurizio; Pagani, Massimo; Mancia, Giuseppe; Karemaker, John M.; Parati, Gianfranco

    2008-01-01

    Di Rienzo M, Castiglioni P, Iellamo F, Volterrani M, Pagani M, Mancia G, Karemaker JM, Parati G. Dynamic adaptation of cardiac baroreflex sensitivity to prolonged exposure to microgravity: data from a 16-day spaceflight. J Appl Physiol 105: 1569-1575, 2008. First published August 28, 2008;

  13. STEADY ESTIMATION ALGORITHMS OF THE DYNAMIC SYSTEMS CONDITION ON THE BASIS OF CONCEPTS OF THE ADAPTIVE FILTRATION AND CONTROL

    Directory of Open Access Journals (Sweden)

    H.Z. Igamberdiyev

    2014-07-01

    Full Text Available Dynamic systems condition estimation regularization algorithms in the conditions of signals and hindrances statistical characteristics aprioristic uncertainty are offered. Regular iterative algorithms of strengthening matrix factor elements of the Kalman filter, allowing to adapt the filter to changing hindrance-alarm conditions are developed. Steady adaptive estimation algorithms of a condition vector in the aprioristic uncertainty conditions of covariance matrixes of object noise and the measurements hindrances providing a certain roughness of filtration process in relation to changing statistical characteristics of signals information parameters are offered. Offered practical realization results of the dynamic systems condition estimation algorithms are given at the adaptive management systems synthesis problems solution by technological processes of granulation drying of an ammophos pulp and receiving ammonia.

  14. Adaptive spacetime method using Riemann jump conditions for coupled atomistic-continuum dynamics

    International Nuclear Information System (INIS)

    Kraczek, B.; Miller, S.T.; Haber, R.B.; Johnson, D.D.

    2010-01-01

    We combine the Spacetime Discontinuous Galerkin (SDG) method for elastodynamics with the mathematically consistent Atomistic Discontinuous Galerkin (ADG) method in a new scheme that concurrently couples continuum and atomistic models of dynamic response in solids. The formulation couples non-overlapping continuum and atomistic models across sharp interfaces by weakly enforcing jump conditions, for both momentum balance and kinematic compatibility, using Riemann values to preserve the characteristic structure of the underlying hyperbolic system. Momentum balances to within machine-precision accuracy over every element, on each atom, and over the coupled system, with small, controllable energy dissipation in the continuum region that ensures numerical stability. When implemented on suitable unstructured spacetime grids, the continuum SDG model offers linear computational complexity in the number of elements and powerful adaptive analysis capabilities that readily bridge between atomic and continuum scales in both space and time. A special trace operator for the atomic velocities and an associated atomistic traction field enter the jump conditions at the coupling interface. The trace operator depends on parameters that specify, at the scale of the atomic spacing, the position of the coupling interface relative to the atoms. In a key finding, we demonstrate that optimizing these parameters suppresses spurious reflections at the coupling interface without the use of non-physical damping or special boundary conditions. We formulate the implicit SDG-ADG coupling scheme in up to three spatial dimensions, and describe an efficient iterative solution scheme that outperforms common explicit schemes, such as the Velocity Verlet integrator. Numerical examples, in 1dxtime and employing both linear and nonlinear potentials, demonstrate the performance of the SDG-ADG method and show how adaptive spacetime meshing reconciles disparate time steps and resolves atomic-scale signals in

  15. A feasibility study of dynamic adaptive radiotherapy for nonsmall cell lung cancer

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Minsun, E-mail: mk688@uw.edu [Department of Radiation Oncology, University of Washington, Seattle, Washington 98195-6043 (United States); Phillips, Mark H. [Departments of Radiation Oncology and Neurological Surgery, University of Washington, Seattle, Washington 98195-6043 (United States)

    2016-05-15

    Purpose: The final state of the tumor at the end of a radiotherapy course is dependent on the doses given in each fraction during the treatment course. This study investigates the feasibility of using dynamic adaptive radiotherapy (DART) in treating lung cancers assuming CBCT is available to observe midtreatment tumor states. DART adapts treatment plans using a dynamic programming technique to consider the expected changes of the tumor in the optimization process. Methods: DART is constructed using a stochastic control formalism framework. It minimizes the total expected number of tumor cells at the end of a treatment course, which is equivalent to maximizing tumor control probability, subject to the uncertainty inherent in the tumor response. This formulation allows for nonstationary dose distributions as well as nonstationary fractional doses as needed to achieve a series of optimal plans that are conformal to the tumor over time, i.e., spatiotemporally optimal plans. Sixteen phantom cases with various sizes and locations of tumors and organs-at-risk (OAR) were generated using in-house software. Each case was planned with DART and conventional IMRT prescribing 60 Gy in 30 fractions. The observations of the change in the tumor volume over a treatment course were simulated using a two-level cell population model. Monte Carlo simulations of the treatment course for each case were run to account for uncertainty in the tumor response. The same OAR dose constraints were applied for both methods. The frequency of replanning was varied between 1, 2, 5 (weekly), and 29 times (daily). The final average tumor dose and OAR doses have been compared to quantify the potential dosimetric benefits of DART. Results: The average tumor max, min, mean, and D95 doses using DART relative to these using conventional IMRT were 124.0%–125.2%, 102.1%–114.7%, 113.7%–123.4%, and 102.0%–115.9% (range dependent on the frequency of replanning). The average relative maximum doses for the

  16. Imperialist Competitive Algorithm with Dynamic Parameter Adaptation Using Fuzzy Logic Applied to the Optimization of Mathematical Functions

    Directory of Open Access Journals (Sweden)

    Emer Bernal

    2017-01-01

    Full Text Available In this paper we are presenting a method using fuzzy logic for dynamic parameter adaptation in the imperialist competitive algorithm, which is usually known by its acronym ICA. The ICA algorithm was initially studied in its original form to find out how it works and what parameters have more effect upon its results. Based on this study, several designs of fuzzy systems for dynamic adjustment of the ICA parameters are proposed. The experiments were performed on the basis of solving complex optimization problems, particularly applied to benchmark mathematical functions. A comparison of the original imperialist competitive algorithm and our proposed fuzzy imperialist competitive algorithm was performed. In addition, the fuzzy ICA was compared with another metaheuristic using a statistical test to measure the advantage of the proposed fuzzy approach for dynamic parameter adaptation.

  17. Gamma-Ray Burst Dynamics and Afterglow Radiation from Adaptive Mesh Refinement, Special Relativistic Hydrodynamic Simulations

    Science.gov (United States)

    De Colle, Fabio; Granot, Jonathan; López-Cámara, Diego; Ramirez-Ruiz, Enrico

    2012-02-01

    We report on the development of Mezcal-SRHD, a new adaptive mesh refinement, special relativistic hydrodynamics (SRHD) code, developed with the aim of studying the highly relativistic flows in gamma-ray burst sources. The SRHD equations are solved using finite-volume conservative solvers, with second-order interpolation in space and time. The correct implementation of the algorithms is verified by one-dimensional (1D) and multi-dimensional tests. The code is then applied to study the propagation of 1D spherical impulsive blast waves expanding in a stratified medium with ρvpropr -k , bridging between the relativistic and Newtonian phases (which are described by the Blandford-McKee and Sedov-Taylor self-similar solutions, respectively), as well as to a two-dimensional (2D) cylindrically symmetric impulsive jet propagating in a constant density medium. It is shown that the deceleration to nonrelativistic speeds in one dimension occurs on scales significantly larger than the Sedov length. This transition is further delayed with respect to the Sedov length as the degree of stratification of the ambient medium is increased. This result, together with the scaling of position, Lorentz factor, and the shock velocity as a function of time and shock radius, is explained here using a simple analytical model based on energy conservation. The method used for calculating the afterglow radiation by post-processing the results of the simulations is described in detail. The light curves computed using the results of 1D numerical simulations during the relativistic stage correctly reproduce those calculated assuming the self-similar Blandford-McKee solution for the evolution of the flow. The jet dynamics from our 2D simulations and the resulting afterglow light curves, including the jet break, are in good agreement with those presented in previous works. Finally, we show how the details of the dynamics critically depend on properly resolving the structure of the relativistic flow.

  18. GAMMA-RAY BURST DYNAMICS AND AFTERGLOW RADIATION FROM ADAPTIVE MESH REFINEMENT, SPECIAL RELATIVISTIC HYDRODYNAMIC SIMULATIONS

    International Nuclear Information System (INIS)

    De Colle, Fabio; Ramirez-Ruiz, Enrico; Granot, Jonathan; López-Cámara, Diego

    2012-01-01

    We report on the development of Mezcal-SRHD, a new adaptive mesh refinement, special relativistic hydrodynamics (SRHD) code, developed with the aim of studying the highly relativistic flows in gamma-ray burst sources. The SRHD equations are solved using finite-volume conservative solvers, with second-order interpolation in space and time. The correct implementation of the algorithms is verified by one-dimensional (1D) and multi-dimensional tests. The code is then applied to study the propagation of 1D spherical impulsive blast waves expanding in a stratified medium with ρ∝r –k , bridging between the relativistic and Newtonian phases (which are described by the Blandford-McKee and Sedov-Taylor self-similar solutions, respectively), as well as to a two-dimensional (2D) cylindrically symmetric impulsive jet propagating in a constant density medium. It is shown that the deceleration to nonrelativistic speeds in one dimension occurs on scales significantly larger than the Sedov length. This transition is further delayed with respect to the Sedov length as the degree of stratification of the ambient medium is increased. This result, together with the scaling of position, Lorentz factor, and the shock velocity as a function of time and shock radius, is explained here using a simple analytical model based on energy conservation. The method used for calculating the afterglow radiation by post-processing the results of the simulations is described in detail. The light curves computed using the results of 1D numerical simulations during the relativistic stage correctly reproduce those calculated assuming the self-similar Blandford-McKee solution for the evolution of the flow. The jet dynamics from our 2D simulations and the resulting afterglow light curves, including the jet break, are in good agreement with those presented in previous works. Finally, we show how the details of the dynamics critically depend on properly resolving the structure of the relativistic flow.

  19. Stochastic dynamics of adaptive trait and neutral marker driven by eco-evolutionary feedbacks.

    Science.gov (United States)

    Billiard, Sylvain; Ferrière, Régis; Méléard, Sylvie; Tran, Viet Chi

    2015-11-01

    How the neutral diversity is affected by selection and adaptation is investigated in an eco-evolutionary framework. In our model, we study a finite population in continuous time, where each individual is characterized by a trait under selection and a completely linked neutral marker. Population dynamics are driven by births and deaths, mutations at birth, and competition between individuals. Trait values influence ecological processes (demographic events, competition), and competition generates selection on trait variation, thus closing the eco-evolutionary feedback loop. The demographic effects of the trait are also expected to influence the generation and maintenance of neutral variation. We consider a large population limit with rare mutation, under the assumption that the neutral marker mutates faster than the trait under selection. We prove the convergence of the stochastic individual-based process to a new measure-valued diffusive process with jumps that we call Substitution Fleming-Viot Process (SFVP). When restricted to the trait space this process is the Trait Substitution Sequence first introduced by Metz et al. (1996). During the invasion of a favorable mutation, a genetical bottleneck occurs and the marker associated with this favorable mutant is hitchhiked. By rigorously analysing the hitchhiking effect and how the neutral diversity is restored afterwards, we obtain the condition for a time-scale separation; under this condition, we show that the marker distribution is approximated by a Fleming-Viot distribution between two trait substitutions. We discuss the implications of the SFVP for our understanding of the dynamics of neutral variation under eco-evolutionary feedbacks and illustrate the main phenomena with simulations. Our results highlight the joint importance of mutations, ecological parameters, and trait values in the restoration of neutral diversity after a selective sweep.

  20. GAMMA-RAY BURST DYNAMICS AND AFTERGLOW RADIATION FROM ADAPTIVE MESH REFINEMENT, SPECIAL RELATIVISTIC HYDRODYNAMIC SIMULATIONS

    Energy Technology Data Exchange (ETDEWEB)

    De Colle, Fabio; Ramirez-Ruiz, Enrico [Astronomy and Astrophysics Department, University of California, Santa Cruz, CA 95064 (United States); Granot, Jonathan [Racah Institute of Physics, Hebrew University, Jerusalem 91904 (Israel); Lopez-Camara, Diego [Instituto de Ciencias Nucleares, Universidad Nacional Autonoma de Mexico, Ap. 70-543, 04510 D.F. (Mexico)

    2012-02-20

    We report on the development of Mezcal-SRHD, a new adaptive mesh refinement, special relativistic hydrodynamics (SRHD) code, developed with the aim of studying the highly relativistic flows in gamma-ray burst sources. The SRHD equations are solved using finite-volume conservative solvers, with second-order interpolation in space and time. The correct implementation of the algorithms is verified by one-dimensional (1D) and multi-dimensional tests. The code is then applied to study the propagation of 1D spherical impulsive blast waves expanding in a stratified medium with {rho}{proportional_to}r{sup -k}, bridging between the relativistic and Newtonian phases (which are described by the Blandford-McKee and Sedov-Taylor self-similar solutions, respectively), as well as to a two-dimensional (2D) cylindrically symmetric impulsive jet propagating in a constant density medium. It is shown that the deceleration to nonrelativistic speeds in one dimension occurs on scales significantly larger than the Sedov length. This transition is further delayed with respect to the Sedov length as the degree of stratification of the ambient medium is increased. This result, together with the scaling of position, Lorentz factor, and the shock velocity as a function of time and shock radius, is explained here using a simple analytical model based on energy conservation. The method used for calculating the afterglow radiation by post-processing the results of the simulations is described in detail. The light curves computed using the results of 1D numerical simulations during the relativistic stage correctly reproduce those calculated assuming the self-similar Blandford-McKee solution for the evolution of the flow. The jet dynamics from our 2D simulations and the resulting afterglow light curves, including the jet break, are in good agreement with those presented in previous works. Finally, we show how the details of the dynamics critically depend on properly resolving the structure of the

  1. Dynamic genetic linkage of intermediate blood pressure phenotypes during postural adaptations in a founder population

    Science.gov (United States)

    Arenas, I. A.; Tremblay, J.; Deslauriers, B.; Sandoval, J.; Šeda, O.; Gaudet, D.; Merlo, E.; Kotchen, T.; Cowley, A. W.

    2013-01-01

    Blood pressure (BP) is a dynamic phenotype that varies rapidly to adjust to changing environmental conditions. Standing upright is a recent evolutionary trait, and genetic factors that influence postural adaptations may contribute to BP variability. We studied the effect of posture on the genetics of BP and intermediate BP phenotypes. We included 384 sib-pairs in 64 sib-ships from families ascertained by early-onset hypertension and dyslipidemia. Blood pressure, three hemodynamic and seven neuroendocrine intermediate BP phenotypes were measured with subjects lying supine and standing upright. The effect of posture on estimates of heritability and genetic covariance was investigated in full pedigrees. Linkage was conducted on 196 candidate genes by sib-pair analyses, and empirical estimates of significance were obtained. A permutation algorithm was implemented to study the postural effect on linkage. ADRA1A, APO, CAST, CORIN, CRHR1, EDNRB, FGF2, GC, GJA1, KCNB2, MMP3, NPY, NR3C2, PLN, TGFBR2, TNFRSF6, and TRHR showed evidence of linkage with any phenotype in the supine position and not upon standing, whereas AKR1B1, CD36, EDNRA, F5, MMP9, PKD2, PON1, PPARG, PPARGC1A, PRKCA, and RET were specifically linked to standing phenotypes. Genetic profiling was undertaken to show genetic interactions among intermediate BP phenotypes and genes specific to each posture. When investigators perform genetic studies exclusively on a single posture, important genetic components of BP are missed. Supine and standing BPs have distinct genetic signatures. Standardized maneuvers influence the results of genetic investigations into BP, thus reflecting its dynamic regulation. PMID:23269701

  2. Probing spatial locality in ionic liquids with the grand canonical adaptive resolution molecular dynamics technique

    Science.gov (United States)

    Shadrack Jabes, B.; Krekeler, C.; Klein, R.; Delle Site, L.

    2018-05-01

    We employ the Grand Canonical Adaptive Resolution Simulation (GC-AdResS) molecular dynamics technique to test the spatial locality of the 1-ethyl 3-methyl imidazolium chloride liquid. In GC-AdResS, atomistic details are kept only in an open sub-region of the system while the environment is treated at coarse-grained level; thus, if spatial quantities calculated in such a sub-region agree with the equivalent quantities calculated in a full atomistic simulation, then the atomistic degrees of freedom outside the sub-region play a negligible role. The size of the sub-region fixes the degree of spatial locality of a certain quantity. We show that even for sub-regions whose radius corresponds to the size of a few molecules, spatial properties are reasonably reproduced thus suggesting a higher degree of spatial locality, a hypothesis put forward also by other researchers and that seems to play an important role for the characterization of fundamental properties of a large class of ionic liquids.

  3. Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems.

    Science.gov (United States)

    Wei, Qinglai; Liu, Derong; Lin, Hanquan

    2016-03-01

    In this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear systems. The present value iteration ADP algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. A novel convergence analysis is developed to guarantee that the iterative value function converges to the optimal performance index function. Initialized by different initial functions, it is proven that the iterative value function will be monotonically nonincreasing, monotonically nondecreasing, or nonmonotonic and will converge to the optimum. In this paper, for the first time, the admissibility properties of the iterative control laws are developed for value iteration algorithms. It is emphasized that new termination criteria are established to guarantee the effectiveness of the iterative control laws. Neural networks are used to approximate the iterative value function and compute the iterative control law, respectively, for facilitating the implementation of the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the present method.

  4. Adaptive evolution of cooperation through Darwinian dynamics in Public Goods games.

    Science.gov (United States)

    Deng, Kuiying; Chu, Tianguang

    2011-01-01

    The linear or threshold Public Goods game (PGG) is extensively accepted as a paradigmatic model to approach the evolution of cooperation in social dilemmas. Here we explore the significant effect of nonlinearity of the structures of public goods on the evolution of cooperation within the well-mixed population by adopting Darwinian dynamics, which simultaneously consider the evolution of populations and strategies on a continuous adaptive landscape, and extend the concept of evolutionarily stable strategy (ESS) as a coalition of strategies that is both convergent-stable and resistant to invasion. Results show (i) that in the linear PGG contributing nothing is an ESS, which contradicts experimental data, (ii) that in the threshold PGG contributing the threshold value is a fragile ESS, which cannot resist the invasion of contributing nothing, and (iii) that there exists a robust ESS of contributing more than half in the sigmoid PGG if the return rate is relatively high. This work reveals the significant effect of the nonlinearity of the structures of public goods on the evolution of cooperation, and suggests that, compared with the linear or threshold PGG, the sigmoid PGG might be a more proper model for the evolution of cooperation within the well-mixed population.

  5. Direct calculation of 1-octanol-water partition coefficients from adaptive biasing force molecular dynamics simulations.

    Science.gov (United States)

    Bhatnagar, Navendu; Kamath, Ganesh; Chelst, Issac; Potoff, Jeffrey J

    2012-07-07

    The 1-octanol-water partition coefficient log K(ow) of a solute is a key parameter used in the prediction of a wide variety of complex phenomena such as drug availability and bioaccumulation potential of trace contaminants. In this work, adaptive biasing force molecular dynamics simulations are used to determine absolute free energies of hydration, solvation, and 1-octanol-water partition coefficients for n-alkanes from methane to octane. Two approaches are evaluated; the direct transfer of the solute from 1-octanol to water phase, and separate transfers of the solute from the water or 1-octanol phase to vacuum, with both methods yielding statistically indistinguishable results. Calculations performed with the TIP4P and SPC∕E water models and the TraPPE united-atom force field for n-alkanes show that the choice of water model has a negligible effect on predicted free energies of transfer and partition coefficients for n-alkanes. A comparison of calculations using wet and dry octanol phases shows that the predictions for log K(ow) using wet octanol are 0.2-0.4 log units lower than for dry octanol, although this is within the statistical uncertainty of the calculation.

  6. Self: an adaptive pressure arising from self-organization, chaotic dynamics, and neural Darwinism.

    Science.gov (United States)

    Bruzzo, Angela Alessia; Vimal, Ram Lakhan Pandey

    2007-12-01

    In this article, we establish a model to delineate the emergence of "self" in the brain making recourse to the theory of chaos. Self is considered as the subjective experience of a subject. As essential ingredients of subjective experiences, our model includes wakefulness, re-entry, attention, memory, and proto-experiences. The stability as stated by chaos theory can potentially describe the non-linear function of "self" as sensitive to initial conditions and can characterize it as underlying order from apparently random signals. Self-similarity is discussed as a latent menace of a pathological confusion between "self" and "others". Our test hypothesis is that (1) consciousness might have emerged and evolved from a primordial potential or proto-experience in matter, such as the physical attractions and repulsions experienced by electrons, and (2) "self" arises from chaotic dynamics, self-organization and selective mechanisms during ontogenesis, while emerging post-ontogenically as an adaptive pressure driven by both volume and synaptic-neural transmission and influencing the functional connectivity of neural nets (structure).

  7. Dynamic implicit 3D adaptive mesh refinement for non-equilibrium radiation diffusion

    Science.gov (United States)

    Philip, B.; Wang, Z.; Berrill, M. A.; Birke, M.; Pernice, M.

    2014-04-01

    The time dependent non-equilibrium radiation diffusion equations are important for solving the transport of energy through radiation in optically thick regimes and find applications in several fields including astrophysics and inertial confinement fusion. The associated initial boundary value problems that are encountered often exhibit a wide range of scales in space and time and are extremely challenging to solve. To efficiently and accurately simulate these systems we describe our research on combining techniques that will also find use more broadly for long term time integration of nonlinear multi-physics systems: implicit time integration for efficient long term time integration of stiff multi-physics systems, local control theory based step size control to minimize the required global number of time steps while controlling accuracy, dynamic 3D adaptive mesh refinement (AMR) to minimize memory and computational costs, Jacobian Free Newton-Krylov methods on AMR grids for efficient nonlinear solution, and optimal multilevel preconditioner components that provide level independent solver convergence.

  8. Dynamic implicit 3D adaptive mesh refinement for non-equilibrium radiation diffusion

    International Nuclear Information System (INIS)

    Philip, B.; Wang, Z.; Berrill, M.A.; Birke, M.; Pernice, M.

    2014-01-01

    The time dependent non-equilibrium radiation diffusion equations are important for solving the transport of energy through radiation in optically thick regimes and find applications in several fields including astrophysics and inertial confinement fusion. The associated initial boundary value problems that are encountered often exhibit a wide range of scales in space and time and are extremely challenging to solve. To efficiently and accurately simulate these systems we describe our research on combining techniques that will also find use more broadly for long term time integration of nonlinear multi-physics systems: implicit time integration for efficient long term time integration of stiff multi-physics systems, local control theory based step size control to minimize the required global number of time steps while controlling accuracy, dynamic 3D adaptive mesh refinement (AMR) to minimize memory and computational costs, Jacobian Free Newton–Krylov methods on AMR grids for efficient nonlinear solution, and optimal multilevel preconditioner components that provide level independent solver convergence

  9. Improvements in Dynamic Balance Using an Adaptive Snowboard with the Nintendo Wii.

    Science.gov (United States)

    Sullivan, Brendan; Harding, Alexandra G; Dingley, John; Gras, Laura Z

    2012-08-01

    The purpose of this case report is to see if a novel balance board could improve balance and gait of a subject with dynamic balance impairments and enjoyment of virtual rehabilitation training. A novel Adaptive Snowboard™ (developed by two of the authors, B.S. and J.D.) was used in conjunction with the Nintendo(®) (Redmond, WA) Wii™ snowboarding and wakeboarding games with a participant in a physical therapy outpatient clinic. Baseline measurements were taken for gait velocity and stride length, Four Square Step Test, Star Balance Excursion Test, Sensory Organization Test, and the Intrinsic Motivation Inventory. Two 60-90-minute sessions per week for 5 weeks included seven to nine trials of Wii snowboarding or wakeboarding games. Improvements were seen in every outcome measure. This study had comparable results to studies performed using a wobble board in that improvements in balance were made. Use of virtual snowboard simulation improved the subject's balance, gait speed, and stride length, as well as being an enjoyable activity.

  10. Adaptive Dynamic Programming for Discrete-Time Zero-Sum Games.

    Science.gov (United States)

    Wei, Qinglai; Liu, Derong; Lin, Qiao; Song, Ruizhuo

    2018-04-01

    In this paper, a novel adaptive dynamic programming (ADP) algorithm, called "iterative zero-sum ADP algorithm," is developed to solve infinite-horizon discrete-time two-player zero-sum games of nonlinear systems. The present iterative zero-sum ADP algorithm permits arbitrary positive semidefinite functions to initialize the upper and lower iterations. A novel convergence analysis is developed to guarantee the upper and lower iterative value functions to converge to the upper and lower optimums, respectively. When the saddle-point equilibrium exists, it is emphasized that both the upper and lower iterative value functions are proved to converge to the optimal solution of the zero-sum game, where the existence criteria of the saddle-point equilibrium are not required. If the saddle-point equilibrium does not exist, the upper and lower optimal performance index functions are obtained, respectively, where the upper and lower performance index functions are proved to be not equivalent. Finally, simulation results and comparisons are shown to illustrate the performance of the present method.

  11. COLLABORATIVE RESEARCH: CONTINUOUS DYNAMIC GRID ADAPTATION IN A GLOBAL ATMOSPHERIC MODEL: APPLICATION AND REFINEMENT

    Energy Technology Data Exchange (ETDEWEB)

    Gutowski, William J.; Prusa, Joseph M.; Smolarkiewicz, Piotr K.

    2012-05-08

    This project had goals of advancing the performance capabilities of the numerical general circulation model EULAG and using it to produce a fully operational atmospheric global climate model (AGCM) that can employ either static or dynamic grid stretching for targeted phenomena. The resulting AGCM combined EULAG's advanced dynamics core with the "physics" of the NCAR Community Atmospheric Model (CAM). Effort discussed below shows how we improved model performance and tested both EULAG and the coupled CAM-EULAG in several ways to demonstrate the grid stretching and ability to simulate very well a wide range of scales, that is, multi-scale capability. We leveraged our effort through interaction with an international EULAG community that has collectively developed new features and applications of EULAG, which we exploited for our own work summarized here. Overall, the work contributed to over 40 peer-reviewed publications and over 70 conference/workshop/seminar presentations, many of them invited. 3a. EULAG Advances EULAG is a non-hydrostatic, parallel computational model for all-scale geophysical flows. EULAG's name derives from its two computational options: EULerian (flux form) or semi-LAGrangian (advective form). The model combines nonoscillatory forward-in-time (NFT) numerical algorithms with a robust elliptic Krylov solver. A signature feature of EULAG is that it is formulated in generalized time-dependent curvilinear coordinates. In particular, this enables grid adaptivity. In total, these features give EULAG novel advantages over many existing dynamical cores. For EULAG itself, numerical advances included refining boundary conditions and filters for optimizing model performance in polar regions. We also added flexibility to the model's underlying formulation, allowing it to work with the pseudo-compressible equation set of Durran in addition to EULAG's standard anelastic formulation. Work in collaboration with others also extended the

  12. The importance of socio-ecological system dynamics in understanding adaptation to global change in the forestry sector.

    Science.gov (United States)

    Blanco, Victor; Brown, Calum; Holzhauer, Sascha; Vulturius, Gregor; Rounsevell, Mark D A

    2017-07-01

    Adaptation is necessary to cope with or take advantage of the effects of climate change on socio-ecological systems. This is especially important in the forestry sector, which is sensitive to the ecological and economic impacts of climate change, and where the adaptive decisions of owners play out over long periods of time. Relatively little is known about how successful these decisions are likely to be in meeting demands for ecosystem services in an uncertain future. We explore adaptation to global change in the forestry sector using CRAFTY-Sweden; an agent-based model that represents large-scale land-use dynamics, based on the demand and supply of ecosystem services. Future impacts and adaptation within the Swedish forestry sector were simulated for scenarios of socio-economic change (Shared Socio-economic Pathways) and climatic change (Representative Concentration Pathways, for three climate models), between 2010 and 2100. Substantial differences were found in the competitiveness and coping ability of land owners implementing different management strategies through time. Generally, multi-objective management was found to provide the best basis for adaptation. Across large regions, however, a combination of management strategies was better at meeting ecosystem service demands. Results also show that adaptive capacity evolves through time in response to external (global) drivers and interactions between individual actors. This suggests that process-based models are more appropriate for the study of autonomous adaptation and future adaptive and coping capacities than models based on indicators, discrete time snapshots or exogenous proxies. Nevertheless, a combination of planned and autonomous adaptation by institutions and forest owners is likely to be more successful than either group acting alone. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Solving kinetic equations with adaptive mesh in phase space for rarefied gas dynamics and plasma physics (Invited)

    International Nuclear Information System (INIS)

    Kolobov, Vladimir; Arslanbekov, Robert; Frolova, Anna

    2014-01-01

    The paper describes an Adaptive Mesh in Phase Space (AMPS) technique for solving kinetic equations with deterministic mesh-based methods. The AMPS technique allows automatic generation of adaptive Cartesian mesh in both physical and velocity spaces using a Tree-of-Trees data structure. We illustrate advantages of AMPS for simulations of rarefied gas dynamics and electron kinetics on low temperature plasmas. In particular, we consider formation of the velocity distribution functions in hypersonic flows, particle kinetics near oscillating boundaries, and electron kinetics in a radio-frequency sheath. AMPS provide substantial savings in computational cost and increased efficiency of the mesh-based kinetic solvers

  14. Solving kinetic equations with adaptive mesh in phase space for rarefied gas dynamics and plasma physics (Invited)

    Energy Technology Data Exchange (ETDEWEB)

    Kolobov, Vladimir [CFD Research Corporation, Huntsville, AL 35805, USA and The University of Alabama in Huntsville, Huntsville, AL 35805 (United States); Arslanbekov, Robert [CFD Research Corporation, Huntsville, AL 35805 (United States); Frolova, Anna [Computing Center of the Russian Academy of Sciences, Moscow, 119333 (Russian Federation)

    2014-12-09

    The paper describes an Adaptive Mesh in Phase Space (AMPS) technique for solving kinetic equations with deterministic mesh-based methods. The AMPS technique allows automatic generation of adaptive Cartesian mesh in both physical and velocity spaces using a Tree-of-Trees data structure. We illustrate advantages of AMPS for simulations of rarefied gas dynamics and electron kinetics on low temperature plasmas. In particular, we consider formation of the velocity distribution functions in hypersonic flows, particle kinetics near oscillating boundaries, and electron kinetics in a radio-frequency sheath. AMPS provide substantial savings in computational cost and increased efficiency of the mesh-based kinetic solvers.

  15. Adaptive control of two-wheeled mobile balance robot capable to adapt different surfaces using a novel artificial neural network–based real-time switching dynamic controller

    Directory of Open Access Journals (Sweden)

    Ali Unluturk

    2017-03-01

    Full Text Available In this article, a novel real-time artificial neural network–based adaptable switching dynamic controller is developed and practically implemented. It will be used for real-time control of two-wheeled balance robot which can balance itself upright position on different surfaces. In order to examine the efficiency of the proposed controller, a two-wheeled mobile balance robot is designed and a test platform for experimental setup is made for balance problem on different surfaces. In a developed adaptive controller algorithm which is capable to adapt different surfaces, mean absolute target angle deviation error, mean absolute target displacement deviation error and mean absolute controller output data are employed for surface estimation by using artificial neural network. In a designed two-wheeled mobile balance robot system, robot tilt angle is estimated via Kalman filter from accelerometer and gyroscope sensor signals. Furthermore, a visual robot control interface is developed in C++ software development environment so that robot controller parameters can be changed as desired. In addition, robot balance angle, linear displacement and controller output can be observed online on personal computer. According to the real-time experimental results, the proposed novel type controller gives more effective results than the classic ones.

  16. State updating and calibration period selection to improve dynamic monthly streamflow forecasts for an environmental flow management application

    Science.gov (United States)

    Gibbs, Matthew S.; McInerney, David; Humphrey, Greer; Thyer, Mark A.; Maier, Holger R.; Dandy, Graeme C.; Kavetski, Dmitri

    2018-02-01

    Monthly to seasonal streamflow forecasts provide useful information for a range of water resource management and planning applications. This work focuses on improving such forecasts by considering the following two aspects: (1) state updating to force the models to match observations from the start of the forecast period, and (2) selection of a shorter calibration period that is more representative of the forecast period, compared to a longer calibration period traditionally used. The analysis is undertaken in the context of using streamflow forecasts for environmental flow water management of an open channel drainage network in southern Australia. Forecasts of monthly streamflow are obtained using a conceptual rainfall-runoff model combined with a post-processor error model for uncertainty analysis. This model set-up is applied to two catchments, one with stronger evidence of non-stationarity than the other. A range of metrics are used to assess different aspects of predictive performance, including reliability, sharpness, bias and accuracy. The results indicate that, for most scenarios and metrics, state updating improves predictive performance for both observed rainfall and forecast rainfall sources. Using the shorter calibration period also improves predictive performance, particularly for the catchment with stronger evidence of non-stationarity. The results highlight that a traditional approach of using a long calibration period can degrade predictive performance when there is evidence of non-stationarity. The techniques presented can form the basis for operational monthly streamflow forecasting systems and provide support for environmental decision-making.

  17. Enriching practice of dialectic behaviour therapy with the dynamic maturational model of attachment and adaptation.

    Science.gov (United States)

    Wilkinson, Simon R

    2016-01-01

    The major challenge for a clinician is integration of the wisdom available in the wide range of therapeutic paradigms available. I have found the principles guiding dialectic behaviour therapy (DBT; see Miller, Rathus, & Linehan, 2007, for applying DBT to adolescents) extremely useful in my practice running a general adolescent unit; similarly, the understanding of the different information processing and learning principles associated with each of the Type A and C attachment strategies, as understood in dynamic maturational model (DMM), has guided me through the dark corners of treatment. Specifically, how does DMM inform practice of DBT? As a 'DBTer' might say, 'Where is the wisdom in both points of view?' Nevertheless, DMM is not primarily about treatment. It concerns how different ways of adapting to developmental contingencies bias perceptual propensities, and hence the information available for reflective brain function. Recognition of these twists to knowing what is going on can then be used to inform a variety of therapeutic approaches. The purpose of this article is to look for the signposts in DBT and DMM which together help navigate the comprehensive approach necessary in complicated therapy. In the process, hopefully some more general principles for addressing discomfited adolescents arise for informing future practice. Although many steer shy of using personality disorder diagnoses for adolescents, clinicians are nevertheless addressing, directly or indirectly, the personality development of all adolescents in treatment, regardless of their classical axis I diagnoses, including both those with developing emotional instability and a group of avoidant over-controlled adolescents, which in Norway is growing in prominence. © The Author(s) 2014.

  18. Lineage dynamics and mutation-selection balance in non-adapting asexual populations

    Science.gov (United States)

    Pénisson, Sophie; Sniegowski, Paul D.; Colato, Alexandre; Gerrish, Philip J.

    2013-02-01

    In classical population genetics, mutation-selection balance refers to the equilibrium frequency of a deleterious allele established and maintained under two opposing forces: recurrent mutation, which tends to increase the frequency of the allele; and selection, which tends to decrease its frequency. In a haploid population, if μ denotes the per capita rate of production of the deleterious allele by mutation and s denotes the selective disadvantage of carrying the allele, then the classical mutation-selection balance frequency of the allele is approximated by μ/s. This calculation assumes that lineages carrying the mutant allele in question—the ‘focal allele’—do not accumulate deleterious mutations linked to the focal allele. In principle, indirect selection against the focal allele caused by such additional mutations can decrease the frequency of the focal allele below the classical mutation-selection balance. This effect of indirect selection will be strongest in an asexual population, in which the entire genome is in linkage. Here, we use an approach based on a multitype branching process to investigate this effect, analyzing lineage dynamics under mutation, direct selection, and indirect selection in a non-adapting asexual population. We find that the equilibrium balance between recurrent mutation to the focal allele and the forces of direct and indirect selection against the focal allele is closely approximated by γμ/(s + U) (s = 0 if the focal allele is neutral), where γ ≈ eθθ-(ω+θ)(ω + θ)(Γ(ω + θ) - Γ(ω + θ,θ)), \\theta =U/\\tilde {s}, and \\omega =s/\\tilde {s}; U denotes the genomic deleterious mutation rate and \\tilde {s} denotes the geometric mean selective disadvantage of deleterious mutations elsewhere on the genome. This mutation-selection balance for asexual populations can remain surprisingly invariant over wide ranges of the mutation rate.

  19. The DONE framework: Creation, evaluation, and updating of an interdisciplinary, dynamic framework 2.0 of determinants of nutrition and eating.

    Science.gov (United States)

    Stok, F Marijn; Hoffmann, Stefan; Volkert, Dorothee; Boeing, Heiner; Ensenauer, Regina; Stelmach-Mardas, Marta; Kiesswetter, Eva; Weber, Alisa; Rohm, Harald; Lien, Nanna; Brug, Johannes; Holdsworth, Michelle; Renner, Britta

    2017-01-01

    The question of which factors drive human eating and nutrition is a key issue in many branches of science. We describe the creation, evaluation, and updating of an interdisciplinary, interactive, and evolving "framework 2.0" of Determinants Of Nutrition and Eating (DONE). The DONE framework was created by an interdisciplinary workgroup in a multiphase, multimethod process. Modifiability, relationship strength, and population-level effect of the determinants were rated to identify areas of priority for research and interventions. External experts positively evaluated the usefulness, comprehensiveness, and quality of the DONE framework. An approach to continue updating the framework with the help of experts was piloted. The DONE framework can be freely accessed (http://uni-konstanz.de/DONE) and used in a highly flexible manner: determinants can be sorted, filtered and visualized for both very specific research questions as well as more general queries. The dynamic nature of the framework allows it to evolve as experts can continually add new determinants and ratings. We anticipate this framework will be useful for research prioritization and intervention development.

  20. The DONE framework: Creation, evaluation, and updating of an interdisciplinary, dynamic framework 2.0 of determinants of nutrition and eating

    Science.gov (United States)

    Stok, F. Marijn; Hoffmann, Stefan; Volkert, Dorothee; Boeing, Heiner; Ensenauer, Regina; Stelmach-Mardas, Marta; Kiesswetter, Eva; Weber, Alisa; Rohm, Harald; Lien, Nanna; Brug, Johannes; Holdsworth, Michelle; Renner, Britta

    2017-01-01

    The question of which factors drive human eating and nutrition is a key issue in many branches of science. We describe the creation, evaluation, and updating of an interdisciplinary, interactive, and evolving “framework 2.0” of Determinants Of Nutrition and Eating (DONE). The DONE framework was created by an interdisciplinary workgroup in a multiphase, multimethod process. Modifiability, relationship strength, and population-level effect of the determinants were rated to identify areas of priority for research and interventions. External experts positively evaluated the usefulness, comprehensiveness, and quality of the DONE framework. An approach to continue updating the framework with the help of experts was piloted. The DONE framework can be freely accessed (http://uni-konstanz.de/DONE) and used in a highly flexible manner: determinants can be sorted, filtered and visualized for both very specific research questions as well as more general queries. The dynamic nature of the framework allows it to evolve as experts can continually add new determinants and ratings. We anticipate this framework will be useful for research prioritization and intervention development. PMID:28152005

  1. Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

    Science.gov (United States)

    Yang, Xinxin; Ge, Shuzhi Sam; He, Wei

    2018-04-01

    In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler-Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.

  2. A Parallel, Multi-Scale Watershed-Hydrologic-Inundation Model with Adaptively Switching Mesh for Capturing Flooding and Lake Dynamics

    Science.gov (United States)

    Ji, X.; Shen, C.

    2017-12-01

    Flood inundation presents substantial societal hazards and also changes biogeochemistry for systems like the Amazon. It is often expensive to simulate high-resolution flood inundation and propagation in a long-term watershed-scale model. Due to the Courant-Friedrichs-Lewy (CFL) restriction, high resolution and large local flow velocity both demand prohibitively small time steps even for parallel codes. Here we develop a parallel surface-subsurface process-based model enhanced by multi-resolution meshes that are adaptively switched on or off. The high-resolution overland flow meshes are enabled only when the flood wave invades to floodplains. This model applies semi-implicit, semi-Lagrangian (SISL) scheme in solving dynamic wave equations, and with the assistant of the multi-mesh method, it also adaptively chooses the dynamic wave equation only in the area of deep inundation. Therefore, the model achieves a balance between accuracy and computational cost.

  3. A Near-Hover Adaptive Attitude Control Strategy of a Ducted Fan Micro Aerial Vehicle with Actuator Dynamics

    Directory of Open Access Journals (Sweden)

    Shouzhao Sheng

    2015-09-01

    Full Text Available The aerodynamic parameters of ducted fan micro aerial vehicles (MAVs are difficult and expensive to precisely measure and are, therefore, not available in most cases. Furthermore, the actuator dynamics with risks of potentially destabilizing the overall system are important but often neglected consideration factors in the control system design of ducted fan MAVs. This paper presents a near-hover adaptive attitude control strategy of a prototype ducted fan MAV with actuator dynamics and without any prior information about the behavior of the MAV. The proposed strategy consists of an online parameter estimation algorithm and an adaptive gain scheduling algorithm, with the former accommodating parametric uncertainties, and the latter approximately eliminating the coupling among axes and guaranteeing the control quality of the MAV. The effectiveness of the proposed strategy is verified numerically and experimentally.

  4. FRMAC Updates

    International Nuclear Information System (INIS)

    Mueller, P.

    1995-01-01

    This talks describes updates in the following updates in FRMAC publications concerning radiation emergencies: Monitoring and Analysis Manual; Evaluation and Assessment Manual; Handshake Series (Biannual) including exercises participated in; environmental Data and Instrument Transmission System (EDITS); Plume in a Box with all radiological data stored onto a hand-held computer; and courses given

  5. The adaptation rate of terrestrial ecosystems as a critical factor in global climate dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Fuessler, J S; Gassmann, F [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

    1999-08-01

    A conceptual climate model describing regional two-way atmosphere-vegetation interaction has been extended by a simple qualitative scheme of ecosystem adaptation to drought stress. The results of this explorative study indicate that the role of terrestrial vegetation under different forcing scenarios depends crucially on the rate of the ecosystems adaptation to drought stress. The faster the adaptation of important ecosystems such as forests the better global climate is protected from abrupt climate changes. (author) 1 fig., 3 refs.

  6. Does Attention Play a Role in Dynamic Receptive Field Adaptation to Changing Acoustic Salience in A1?

    OpenAIRE

    Fritz, Jonathan; Elhilali, Mounya; David, Stephen; Shamma, Shihab

    2007-01-01

    Acoustic filter properties of A1 neurons can dynamically adapt to stimulus statistics, classical conditioning, instrumental learning and the changing auditory attentional focus. We have recently developed an experimental paradigm that allows us to view cortical receptive field plasticity on-line as the animal meets different behavioral challenges by attending to salient acoustic cues and changing its cortical filters to enhance performance. We propose that attention is the key trigger that in...

  7. DYNAMISM OF DOT SUBRETINAL DRUSENOID DEPOSITS IN AGE-RELATED MACULAR DEGENERATION DEMONSTRATED WITH ADAPTIVE OPTICS IMAGING.

    Science.gov (United States)

    Zhang, Yuhua; Wang, Xiaolin; Godara, Pooja; Zhang, Tianjiao; Clark, Mark E; Witherspoon, C Douglas; Spaide, Richard F; Owsley, Cynthia; Curcio, Christine A

    2018-01-01

    To investigate the natural history of dot subretinal drusenoid deposits (SDD) in age-related macular degeneration, using high-resolution adaptive optics scanning laser ophthalmoscopy. Six eyes of four patients with intermediate age-related macular degeneration were studied at baseline and 1 year later. Individual dot SDD within the central 30° retina were examined with adaptive optics scanning laser ophthalmoscopy and optical coherence tomography. A total of 269 solitary SDD were identified at baseline. Over 12.25 ± 1.18 months, all 35 Stage 1 SDD progressed to advanced stages. Eighteen (60%) Stage 2 lesions progressed to Stage 3 and 12 (40%) remained at Stage 2. Of 204 Stage 3 SDD, 12 (6.4%) disappeared and the rest remained. Twelve new SDD were identified, including 6 (50%) at Stage 1, 2 (16.7%) at Stage 2, and 4 (33.3%) at Stage 3. The mean percentage of the retina affected by dot SDD, measured by the adaptive optics scanning laser ophthalmoscopy, increased in 5/6 eyes (from 2.31% to 5.08% in the most changed eye) and decreased slightly in 1/6 eye (from 10.67% to 10.54%). Dynamism, the absolute value of the areas affected by new and regressed lesions, ranged from 0.7% to 9.3%. Adaptive optics scanning laser ophthalmoscopy reveals that dot SDD, like drusen, are dynamic.

  8. Adaptive Asymptotical Synchronization for Stochastic Complex Networks with Time-Delay and Markovian Switching

    Directory of Open Access Journals (Sweden)

    Xueling Jiang

    2014-01-01

    Full Text Available The problem of adaptive asymptotical synchronization is discussed for the stochastic complex dynamical networks with time-delay and Markovian switching. By applying the stochastic analysis approach and the M-matrix method for stochastic complex networks, several sufficient conditions to ensure adaptive asymptotical synchronization for stochastic complex networks are derived. Through the adaptive feedback control techniques, some suitable parameters update laws are obtained. Simulation result is provided to substantiate the effectiveness and characteristics of the proposed approach.

  9. An adaptive overcurrent protection in smart distribution grid

    DEFF Research Database (Denmark)

    Bhattarai, Bishnu Prasad; Bak-Jensen, Birgitte; Chaudhary, Sanjay Kumar

    2015-01-01

    existing protection practice. In this study, a combination of a local adaptive and communication assisted central protection is proposed, whereby the relay settings are dynamically updated based on online identification of the network topologies and status of DERs. Particularly, the local adaptive...... protection updates relay settings based on DERs status (ON/OFF) employing locally acquired information, whereas the centralized protection updates the relay settings during major changes in grid topologies: network reconfiguration and switching between islanded and gridconnected modes. The effectiveness......High penetration of distributed energy resources (DERs) creates various protection challenges, such as protection blinding, false tripping, unsynchronized reclosing, etc. Additionally, adaptation of active network management approaches namely demand response and network reconfiguration also threats...

  10. Dynamic structure mediates halophilic adaptation of a DNA polymerase from the deep-sea brines of the Red Sea

    KAUST Repository

    Takahashi, Masateru; Takahashi, Etsuko; Joudeh, Luay I.; Marini, Monica; Das, Gobind; Elshenawy, Mohamed; Akal, Anastassja; Sakashita, Kosuke; Alam, Intikhab; Tehseen, Muhammad; Sobhy, Mohamed Abdelmaboud; Stingl, Ulrich; Merzaban, Jasmeen; Di Fabrizio, Enzo M.; Hamdan, Samir

    2018-01-01

    The deep-sea brines of the Red Sea are remote and unexplored environments characterized by high temperatures, anoxic water, and elevated concentrations of salt and heavy metals. This environment provides a rare system to study the interplay between halophilic and thermophilic adaptation in biologic macromolecules. The present article reports the first DNA polymerase with halophilic and thermophilic features. Biochemical and structural analysis by Raman and circular dichroism spectroscopy showed that the charge distribution on the protein’s surface mediates the structural balance between stability for thermal adaptation and flexibility for counteracting the salt-induced rigid and nonfunctional hydrophobic packing. Salt bridge interactions via increased negative and positive charges contribute to structural stability. Salt tolerance, conversely, is mediated by a dynamic structure that becomes more fixed and functional with increasing salt concentration. We propose that repulsive forces among excess negative charges, in addition to a high percentage of negatively charged random coils, mediate this structural dynamism. This knowledge enabled us to engineer a halophilic version of KOD DNA polymerase.—Takahashi, M., Takahashi, E., Joudeh, L. I., Marini, M., Das, G., Elshenawy, M. M., Akal, A., Sakashita, K., Alam, I., Tehseen, M., Sobhy, M. A., Stingl, U., Merzaban, J. S., Di Fabrizio, E., Hamdan, S. M. Dynamic structure mediates halophilic adaptation of a DNA polymerase from the deep-sea brines of the Red Sea.

  11. Design of an Adaptive Human-Machine System Based on Dynamical Pattern Recognition of Cognitive Task-Load.

    Science.gov (United States)

    Zhang, Jianhua; Yin, Zhong; Wang, Rubin

    2017-01-01

    This paper developed a cognitive task-load (CTL) classification algorithm and allocation strategy to sustain the optimal operator CTL levels over time in safety-critical human-machine integrated systems. An adaptive human-machine system is designed based on a non-linear dynamic CTL classifier, which maps a set of electroencephalogram (EEG) and electrocardiogram (ECG) related features to a few CTL classes. The least-squares support vector machine (LSSVM) is used as dynamic pattern classifier. A series of electrophysiological and performance data acquisition experiments were performed on seven volunteer participants under a simulated process control task environment. The participant-specific dynamic LSSVM model is constructed to classify the instantaneous CTL into five classes at each time instant. The initial feature set, comprising 56 EEG and ECG related features, is reduced to a set of 12 salient features (including 11 EEG-related features) by using the locality preserving projection (LPP) technique. An overall correct classification rate of about 80% is achieved for the 5-class CTL classification problem. Then the predicted CTL is used to adaptively allocate the number of process control tasks between operator and computer-based controller. Simulation results showed that the overall performance of the human-machine system can be improved by using the adaptive automation strategy proposed.

  12. Dynamic structure mediates halophilic adaptation of a DNA polymerase from the deep-sea brines of the Red Sea.

    Science.gov (United States)

    Takahashi, Masateru; Takahashi, Etsuko; Joudeh, Luay I; Marini, Monica; Das, Gobind; Elshenawy, Mohamed M; Akal, Anastassja; Sakashita, Kosuke; Alam, Intikhab; Tehseen, Muhammad; Sobhy, Mohamed A; Stingl, Ulrich; Merzaban, Jasmeen S; Di Fabrizio, Enzo; Hamdan, Samir M

    2018-01-24

    The deep-sea brines of the Red Sea are remote and unexplored environments characterized by high temperatures, anoxic water, and elevated concentrations of salt and heavy metals. This environment provides a rare system to study the interplay between halophilic and thermophilic adaptation in biologic macromolecules. The present article reports the first DNA polymerase with halophilic and thermophilic features. Biochemical and structural analysis by Raman and circular dichroism spectroscopy showed that the charge distribution on the protein's surface mediates the structural balance between stability for thermal adaptation and flexibility for counteracting the salt-induced rigid and nonfunctional hydrophobic packing. Salt bridge interactions via increased negative and positive charges contribute to structural stability. Salt tolerance, conversely, is mediated by a dynamic structure that becomes more fixed and functional with increasing salt concentration. We propose that repulsive forces among excess negative charges, in addition to a high percentage of negatively charged random coils, mediate this structural dynamism. This knowledge enabled us to engineer a halophilic version of KOD DNA polymerase.-Takahashi, M., Takahashi, E., Joudeh, L. I., Marini, M., Das, G., Elshenawy, M. M., Akal, A., Sakashita, K., Alam, I., Tehseen, M., Sobhy, M. A., Stingl, U., Merzaban, J. S., Di Fabrizio, E., Hamdan, S. M. Dynamic structure mediates halophilic adaptation of a DNA polymerase from the deep-sea brines of the Red Sea.

  13. Chaos control of the micro-electro-mechanical resonator by using adaptive dynamic surface technology with extended state observer

    International Nuclear Information System (INIS)

    Luo, Shaohua; Sun, Quanping; Cheng, Wei

    2016-01-01

    This paper addresses chaos control of the micro-electro- mechanical resonator by using adaptive dynamic surface technology with extended state observer. To reveal the mechanism of the micro- electro-mechanical resonator, the phase diagrams and corresponding time histories are given to research the nonlinear dynamics and chaotic behavior, and Homoclinic and heteroclinic chaos which relate closely with the appearance of chaos are presented based on the potential function. To eliminate the effect of chaos, an adaptive dynamic surface control scheme with extended state observer is designed to convert random motion into regular motion without precise system model parameters and measured variables. Putting tracking differentiator into chaos controller solves the ‘explosion of complexity’ of backstepping and poor precision of the first-order filters. Meanwhile, to obtain high performance, a neural network with adaptive law is employed to approximate unknown nonlinear function in the process of controller design. The boundedness of all the signals of the closed-loop system is proved in theoretical analysis. Finally, numerical simulations are executed and extensive results illustrate effectiveness and robustness of the proposed scheme.

  14. Dynamic structure mediates halophilic adaptation of a DNA polymerase from the deep-sea brines of the Red Sea

    KAUST Repository

    Takahashi, Masateru

    2018-01-24

    The deep-sea brines of the Red Sea are remote and unexplored environments characterized by high temperatures, anoxic water, and elevated concentrations of salt and heavy metals. This environment provides a rare system to study the interplay between halophilic and thermophilic adaptation in biologic macromolecules. The present article reports the first DNA polymerase with halophilic and thermophilic features. Biochemical and structural analysis by Raman and circular dichroism spectroscopy showed that the charge distribution on the protein’s surface mediates the structural balance between stability for thermal adaptation and flexibility for counteracting the salt-induced rigid and nonfunctional hydrophobic packing. Salt bridge interactions via increased negative and positive charges contribute to structural stability. Salt tolerance, conversely, is mediated by a dynamic structure that becomes more fixed and functional with increasing salt concentration. We propose that repulsive forces among excess negative charges, in addition to a high percentage of negatively charged random coils, mediate this structural dynamism. This knowledge enabled us to engineer a halophilic version of KOD DNA polymerase.—Takahashi, M., Takahashi, E., Joudeh, L. I., Marini, M., Das, G., Elshenawy, M. M., Akal, A., Sakashita, K., Alam, I., Tehseen, M., Sobhy, M. A., Stingl, U., Merzaban, J. S., Di Fabrizio, E., Hamdan, S. M. Dynamic structure mediates halophilic adaptation of a DNA polymerase from the deep-sea brines of the Red Sea.

  15. Extracting principles for information management adaptability during crisis response : A dynamic capability view

    NARCIS (Netherlands)

    Bharosa, N.; Janssen, M.F.W.H.A.

    2010-01-01

    During crises, relief agency commanders have to make decisions in a complex and uncertain environment, requiring them to continuously adapt to unforeseen environmental changes. In the process of adaptation, the commanders depend on information management systems for information. Yet there are still

  16. Rift Valley fever dynamics in Senegal: a project for pro-active adaptation and improvement of livestock raising management

    Directory of Open Access Journals (Sweden)

    Murielle Lafaye

    2013-11-01

    Full Text Available The multi-disciplinary French project “Adaptation à la Fièvre de la Vallée du Rift” (AdaptFVR has concluded a 10-year constructive interaction between many scientists/partners involved with the Rift Valley fever (RVF dynamics in Senegal. The three targeted objectives reached were (i to produce - in near real-time - validated risk maps for parked livestock exposed to RVF mosquitoes/vectors bites; (ii to assess the impacts on RVF vectors from climate variability at different time-scales including climate change; and (iii to isolate processes improving local livestock management and animal health. Based on these results, concrete, pro-active adaptive actions were taken on site, which led to the establishment of a RVF early warning system (RVFews. Bulletins were released in a timely fashion during the project, tested and validated in close collaboration with the local populations, i.e. the primary users. Among the strategic, adaptive methods developed, conducted and evaluated in terms of cost/benefit analyses are the larvicide campaigns and the coupled bio-mathematical (hydrological and entomological model technologies, which are being transferred to the staff of the “Centre de Suivi Ecologique” (CSE in Dakar during 2013. Based on the results from the AdaptFVR project, other projects with similar conceptual and modelling approaches are currently being implemented, e.g. for urban and rural malaria and dengue in the French Antilles.

  17. A quantitative formulation of the dynamic behaviour of adaptation processes to ionizing radiation

    International Nuclear Information System (INIS)

    Pfandler, S.

    1999-12-01

    The discovery of adaptation processes in cells (i.e., increased resistance to effects of a challenge dose administered after a lower adapting dose) has fuelled the debate on possible cellular processes relevant for low dose exposures. However, numerous experiments on radioadaptive response do not provide a clear picture of the nature of adaptive response and the conditions under which it occurs. This work proposes a model that succeeds in modelling data obtained from various experiments on radioadaptation. The model assumes impaired DNA integrity as triggering signal for induction of adaptation. Induction of adaptive response is seen as two-phase process. First, ionizing radiation induces radicals by water radiolysis which give rise to specific DNA lesions. On the other hand, these lesions must be perceived and, in a way, processed by the cell, thereby creating the final signal necessary for the comprehensive adaptive response. This processing occurs through some event in S-phase and can be halted by local conformational changes of chromatin induced by ionizing radiation. Thus, the model assumes two counteracting processes that have to be balanced for the triggering signal of adaptation to occur, each of them related to different target volumes. This work comprises mathematical treatment of radical formation, DNA lesion induction and inhibition of local initiation of replication which finally provides functions that quantify the reduction of double strand breaks introduced by challenge doses in adapted cells as compared to non-adapted cells. Non-linear regression analyses based upon data from experiments on radioadaptation yield regression curves which describe existing data satisfactorily. Thus, it corroborates the existence of adaptive response as, in principle, universal feature of cells and specifies conditions which favor development of radioadaptation. (author)

  18. Ontario Hydro's DSP update

    International Nuclear Information System (INIS)

    Anon.

    1992-01-01

    Ontario Hydro's Demand/Supply Plan (DSP), the 25 year plan which was submitted in December 1989, is currently being reviewed by the Environmental Assessment Board (EAB). Since 1989 there have been several changes which have led Ontario Hydro to update the original Demand/Supply Plan. This information sheet gives a quick overview of what has changed and how Ontario Hydro is adapting to that change

  19. Molecular diversity analysis and bacterial population dynamics of an adapted seawater microbiota during the degradation of Tunisian zarzatine oil.

    Science.gov (United States)

    Zrafi-Nouira, Ines; Guermazi, Sonda; Chouari, Rakia; Safi, Nimer M D; Pelletier, Eric; Bakhrouf, Amina; Saidane-Mosbahi, Dalila; Sghir, Abdelghani

    2009-07-01

    The indigenous microbiota of polluted coastal seawater in Tunisia was enriched by increasing the concentration of zarzatine crude oil. The resulting adapted microbiota was incubated with zarzatine crude oil as the only carbon and energy source. Crude oil biodegradation capacity and bacterial population dynamics of the microbiota were evaluated every week for 28 days (day 7, day 14, day 21, and day 28). Results show that the percentage of petroleum degradation was 23.9, 32.1, 65.3, and 77.8%, respectively. At day 28, non-aromatic and aromatic hydrocarbon degradation rates reached 92.6 and 68.7%, respectively. Bacterial composition of the adapted microflora was analysed by 16S rRNA gene cloning and sequencing, using total genomic DNA extracted from the adapted microflora at days 0, 7, 14, 21, and 28. Five clone libraries were constructed and a total of 430 sequences were generated and grouped into OTUs using the ARB software package. Phylogenetic analysis of the adapted microbiota shows the presence of four phylogenetic groups: Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes. Diversity indices show a clear decrease in bacterial diversity of the adapted microflora according to the incubation time. The Proteobacteria are the most predominant (>80%) at day 7, day 14 and day 21 but not at day 28 for which the microbiota was reduced to only one OTU affiliated with the genus Kocuria of the Actinobacteria. This study shows that the degradation of zarzatine crude oil components depends on the activity of a specialized and dynamic seawater consortium composed of different phylogenetic taxa depending on the substrate complexity.

  20. Circular Updates

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Circular Updates are periodic sequentially numbered instructions to debriefing staff and observers informing them of changes or additions to scientific and specimen...

  1. Email Updates

    Science.gov (United States)

    ... of this page: https://medlineplus.gov/listserv.html Email Updates To use the sharing features on this ... view your email history or unsubscribe. Prevent MedlinePlus emails from being marked as "spam" or "junk" To ...

  2. Link Climate Effects to Surface Water Quality and Drinking Water Plant Adaptation - A Update on Hydroclimatic Province and WTP-ccam Model

    Science.gov (United States)

    Key points in this presentation are: (1) How and why hydroclimatic province can help precipitation projection for water program engineering and management, (2) Implications of initial research results and planned further monitoring / research activities, (3) Five adaptation t...

  3. Similar temperature dependencies of glycolytic enzymes : An evolutionary adaptation to temperature dynamics?

    NARCIS (Netherlands)

    Cruz, L.A.B.; Hebly, M.; Duong, G.H.; Wahl, S.A.; Pronk, J.T.; Heijnen, J.J.; Daran-Lapujade, P.; Van Gulik, W.M.

    2012-01-01

    Background Temperature strongly affects microbial growth, and many microorganisms have to deal with temperature fluctuations in their natural environment. To understand regulation strategies that underlie microbial temperature responses and adaptation, we studied glycolytic pathway kinetics in

  4. How update schemes influence crowd simulations

    International Nuclear Information System (INIS)

    Seitz, Michael J; Köster, Gerta

    2014-01-01

    Time discretization is a key modeling aspect of dynamic computer simulations. In current pedestrian motion models based on discrete events, e.g. cellular automata and the Optimal Steps Model, fixed-order sequential updates and shuffle updates are prevalent. We propose to use event-driven updates that process events in the order they occur, and thus better match natural movement. In addition, we present a parallel update with collision detection and resolution for situations where computational speed is crucial. Two simulation studies serve to demonstrate the practical impact of the choice of update scheme. Not only do density-speed relations differ, but there is a statistically significant effect on evacuation times. Fixed-order sequential and random shuffle updates with a short update period come close to event-driven updates. The parallel update scheme overestimates evacuation times. All schemes can be employed for arbitrary simulation models with discrete events, such as car traffic or animal behavior. (paper)

  5. AWARE: Adaptive Software Monitoring and Dynamic Reconfiguration for Critical Infrastructure Protection

    Science.gov (United States)

    2015-04-29

    in which we applied these adaptation patterns to an adaptive news web server intended to tolerate extremely heavy, unexpected loads. To address...collection of existing models used as benchmarks for OO-based refactoring and an existing web -based repository called REMODD to provide users with model...invariant properties. Specifically, we developed Avida- MDE (based on the Avida digital evolution platform) to support the automatic generation of software

  6. Speed tracking control of pneumatic motor servo systems using observation-based adaptive dynamic sliding-mode control

    Science.gov (United States)

    Chen, Syuan-Yi; Gong, Sheng-Sian

    2017-09-01

    This study aims to develop an adaptive high-precision control system for controlling the speed of a vane-type air motor (VAM) pneumatic servo system. In practice, the rotor speed of a VAM depends on the input mass air flow, which can be controlled by the effective orifice area (EOA) of an electronic throttle valve (ETV). As the control variable of a second-order pneumatic system is the integral of the EOA, an observation-based adaptive dynamic sliding-mode control (ADSMC) system is proposed to derive the differential of the control variable, namely, the EOA control signal. In the ADSMC system, a proportional-integral-derivative fuzzy neural network (PIDFNN) observer is used to achieve an ideal dynamic sliding-mode control (DSMC), and a supervisor compensator is designed to eliminate the approximation error. As a result, the ADSMC incorporates the robustness of a DSMC and the online learning ability of a PIDFNN. To ensure the convergence of the tracking error, a Lyapunov-based analytical method is employed to obtain the adaptive algorithms required to tune the control parameters of the online ADSMC system. Finally, our experimental results demonstrate the precision and robustness of the ADSMC system for highly nonlinear and time-varying VAM pneumatic servo systems.

  7. A comparative study of cold- and warm-adapted Endonucleases A using sequence analyses and molecular dynamics simulations.

    Directory of Open Access Journals (Sweden)

    Davide Michetti

    Full Text Available The psychrophilic and mesophilic endonucleases A (EndA from Aliivibrio salmonicida (VsEndA and Vibrio cholera (VcEndA have been studied experimentally in terms of the biophysical properties related to thermal adaptation. The analyses of their static X-ray structures was no sufficient to rationalize the determinants of their adaptive traits at the molecular level. Thus, we used Molecular Dynamics (MD simulations to compare the two proteins and unveil their structural and dynamical differences. Our simulations did not show a substantial increase in flexibility in the cold-adapted variant on the nanosecond time scale. The only exception is a more rigid C-terminal region in VcEndA, which is ascribable to a cluster of electrostatic interactions and hydrogen bonds, as also supported by MD simulations of the VsEndA mutant variant where the cluster of interactions was introduced. Moreover, we identified three additional amino acidic substitutions through multiple sequence alignment and the analyses of MD-based protein structure networks. In particular, T120V occurs in the proximity of the catalytic residue H80 and alters the interaction with the residue Y43, which belongs to the second coordination sphere of the Mg2+ ion. This makes T120V an amenable candidate for future experimental mutagenesis.

  8. Development of force adaptation during childhood.

    Science.gov (United States)

    Konczak, Jürgen; Jansen-Osmann, Petra; Kalveram, Karl-Theodor

    2003-03-01

    Humans learn to make reaching movements in novel dynamic environments by acquiring an internal motor model of their limb dynamics. Here, the authors investigated how 4- to 11-year-old children (N = 39) and adults (N = 7) adapted to changes in arm dynamics, and they examined whether those data support the view that the human brain acquires inverse dynamics models (IDM) during development. While external damping forces were applied, the children learned to perform goal-directed forearm flexion movements. After changes in damping, all children showed kinematic aftereffects indicative of a neural controller that still attempted to compensate the no longer existing damping force. With increasing age, the number of trials toward complete adaptation decreased. When damping was present, forearm paths were most perturbed and most variable in the youngest children but were improved in the older children. The findings indicate that the neural representations of limb dynamics are less precise in children and less stable in time than those of adults. Such controller instability might be a primary cause of the high kinematic variability observed in many motor tasks during childhood. Finally, the young children were not able to update those models at the same rate as the older children, who, in turn, adapted more slowly than adults. In conclusion, the ability to adapt to unknown forces is a developmental achievement. The present results are consistent with the view that the acquisition and modification of internal models of the limb dynamics form the basis of that adaptive process.

  9. Dynamic Planar Convex Hull with Optimal Query Time and O(log n · log log n ) Update Time

    DEFF Research Database (Denmark)

    Brodal, Gerth Stølting; Jakob, Riko

    2000-01-01

    The dynamic maintenance of the convex hull of a set of points in the plane is one of the most important problems in computational geometry. We present a data structure supporting point insertions in amortized O(log n · log log log n) time, point deletions in amortized O(log n · log log n) time......, and various queries about the convex hull in optimal O(log n) worst-case time. The data structure requires O(n) space. Applications of the new dynamic convex hull data structure are improved deterministic algorithms for the k-level problem and the red-blue segment intersection problem where all red and all...

  10. An approximately Bayesian delta-rule model explains the dynamics of belief updating in a changing environment

    OpenAIRE

    Nassar, Matthew R.; Wilson, Robert C.; Heasly, Benjamin; Gold, Joshua I.

    2010-01-01

    Maintaining appropriate beliefs about variables needed for effective decision-making can be difficult in a dynamic environment. One key issue is the amount of influence that unexpected outcomes should have on existing beliefs. In general, outcomes that are unexpected because of a fundamental change in the environment should carry more influence than outcomes that are unexpected because of persistent environmental stochasticity. Here we use a novel task to characterize how well human subjects ...

  11. Computational and experimental studies of microvascular void features for passive-adaptation of structural panel dynamic properties

    Science.gov (United States)

    Sears, Nicholas C.; Harne, Ryan L.

    2018-01-01

    The performance, integrity, and safety of built-up structural systems are critical to their effective employment in diverse engineering applications. In conflict with these goals, harmonic or random excitations of structural panels may promote large amplitude oscillations that are particularly harmful when excitation energies are concentrated around natural frequencies. This contributes to fatigue concerns, performance degradation, and failure. While studies have considered active or passive damping treatments that adapt material characteristics and configurations for structural control, it remains to be understood how vibration properties of structural panels may be tailored via internal material transitions. Motivated to fill this knowledge gap, this research explores an idea of adapting the static and dynamic material distribution of panels through embedded microvascular channels and strategically placed voids that permit the internal movement of fluids within the panels for structural dynamic control. Finite element model and experimental investigations probe how redistributing material in the form of microscale voids influences the global vibration modes and natural frequencies of structural panels. Through parameter studies, the relationships among void shape, number, size, and location are quantified towards their contribution to the changing structural dynamics. For the panel composition and boundary conditions considered in this report, the findings reveal that transferring material between strategically placed voids may result in eigenfrequency changes as great as 10.0, 5.0, and 7.4% for the first, second, and third modes, respectively.

  12. Performance enhanced design of chaos controller for the mechanical centrifugal flywheel governor system via adaptive dynamic surface control

    Directory of Open Access Journals (Sweden)

    Shaohua Luo

    2016-09-01

    Full Text Available This paper addresses chaos suppression of the mechanical centrifugal flywheel governor system with output constraint and fully unknown parameters via adaptive dynamic surface control. To have a certain understanding of chaotic nature of the mechanical centrifugal flywheel governor system and subsequently design its controller, the useful tools like the phase diagrams and corresponding time histories are employed. By using tangent barrier Lyapunov function, a dynamic surface control scheme with neural network and tracking differentiator is developed to transform chaos oscillation into regular motion and the output constraint rule is not broken in whole process. Plugging second-order tracking differentiator into chaos controller tackles the “explosion of complexity” of backstepping and improves the accuracy in contrast with the first-order filter. Meanwhile, Chebyshev neural network with adaptive law whose input only depends on a subset of Chebyshev polynomials is derived to learn the behavior of unknown dynamics. The boundedness of all signals of the closed-loop system is verified in stability analysis. Finally, the results of numerical simulations illustrate effectiveness and exhibit the superior performance of the proposed scheme by comparing with the existing ADSC method.

  13. Adaptive wave filtering for dynamic positioning of marine vessels using maximum likelihood identification: Theory and experiments

    Digital Repository Service at National Institute of Oceanography (India)

    Hassani, V.; Sorensen, A.J.; Pascoal, A.M.

    This paper addresses a filtering problem that arises in the design of dynamic positioning systems for ships and offshore rigs subjected to the influence of sea waves. The dynamic model of the vessel captures explicitly the sea state as an uncertain...

  14. Dynamic adaptive policymaking for the sustainable city: The case of automated taxis

    Directory of Open Access Journals (Sweden)

    Warren E. Walker

    2017-06-01

    Full Text Available By 2050, about two-thirds of the world’s people are expected to live in urban areas. But, the economic viability and sustainability of city centers is threatened by problems related to transport, such as pollution, congestion, and parking. Much has been written about automated vehicles and demand responsive transport. The combination of these potentially disruptive developments could reduce these problems. However, implementation is held back by uncertainties, including public acceptance, liability, and privacy. So, their potential to reduce urban transport problems may not be fully realized. We propose an adaptive approach to implementation that takes some actions right away and creates a framework for future actions that allows for adaptations over time as knowledge about performance and acceptance of the new system (called ‘automated taxis’ accumulates and critical events for implementation take place. The adaptive approach is illustrated in the context of a hypothetical large city.

  15. Robust Adaptive Dynamic Programming of Two-Player Zero-Sum Games for Continuous-Time Linear Systems.

    Science.gov (United States)

    Fu, Yue; Fu, Jun; Chai, Tianyou

    2015-12-01

    In this brief, an online robust adaptive dynamic programming algorithm is proposed for two-player zero-sum games of continuous-time unknown linear systems with matched uncertainties, which are functions of system outputs and states of a completely unknown exosystem. The online algorithm is developed using the policy iteration (PI) scheme with only one iteration loop. A new analytical method is proposed for convergence proof of the PI scheme. The sufficient conditions are given to guarantee globally asymptotic stability and suboptimal property of the closed-loop system. Simulation studies are conducted to illustrate the effectiveness of the proposed method.

  16. Adaptive Lighting

    DEFF Research Database (Denmark)

    Petersen, Kjell Yngve; Søndergaard, Karin; Kongshaug, Jesper

    2015-01-01

    Adaptive Lighting Adaptive lighting is based on a partial automation of the possibilities to adjust the colour tone and brightness levels of light in order to adapt to people’s needs and desires. IT support is key to the technical developments that afford adaptive control systems. The possibilities...... offered by adaptive lighting control are created by the ways that the system components, the network and data flow can be coordinated through software so that the dynamic variations are controlled in ways that meaningfully adapt according to people’s situations and design intentions. This book discusses...... differently into an architectural body. We also examine what might occur when light is dynamic and able to change colour, intensity and direction, and when it is adaptive and can be brought into interaction with its surroundings. In short, what happens to an architectural space when artificial lighting ceases...

  17. A Phase-Adaptive Garbage Collector Using Dynamic Heap Partitioning and Opportunistic Collection

    Science.gov (United States)

    Roh, Yangwoo; Kim, Jaesub; Park, Kyu Ho

    Applications usually have their own phases in heap memory usage. The traditional garbage collector fails to match various application phases because the same heuristic on the object behavior is used throughout the entire execution. This paper introduces a phase-adaptive garbage collector which reorganizes the heap layout and adjusts the invocation time of the garbage collection according to the phases. The proposed collector identifies phases by detecting the application methods strongly related to the phase boundaries. The experimental results show that the proposed phase-adaptive collector successfully recognizes application phases and improves the garbage collection time by as much as 41%.

  18. From elite reproduction to elite adaptation: the dynamics of change in personal networks of Slovenian elites

    OpenAIRE

    Iglič, Hajdeja; Rus, Andrej

    2014-01-01

    This article deals with the process of elite adaptation in Slovenia in the period between 1988 and 1995. While negotiated settlement between the old and new elites in Slovenia contributed to high reproduction rates of Slovenian old elites, there was significant change going on within the new and old elites. By looking at their ego networks, we show that the debate on elite reproduction is overlooking an important aspect of change, i.e. the adaptation of elites. We analyze changes in the compo...

  19. Remote Sensing Dynamic Monitoring of Biological Invasive Species Based on Adaptive PCNN and Improved C-V Model

    Directory of Open Access Journals (Sweden)

    PENG Gang

    2014-12-01

    Full Text Available Biological species invasion problem bring serious damage to the ecosystem, and have become one of the six major enviromental problems that affect the future economic development, also have become one of the hot topic in domestic and foreign scholars. Remote sensing technology has been successfully used in the investigation of coastal zone resources, dynamic monitoring of the resources and environment, and other fields. It will cite a new remote sensing image change detection algorithm based on adaptive pulse coupled neural network (PCNN and improved C-V model, for remote sensing dynamic monitoring of biological species invasion. The experimental results show that the algorithm is effective in the test results of biological species invasions.

  20. Synchronization dynamics in a small pacemaker neuronal ensemble via a robust adaptive controller

    International Nuclear Information System (INIS)

    Cornejo-Pérez, O.; Solis-Perales, G.C.; Arenas-Prado, J.A.

    2012-01-01

    The synchronization dynamics of a pacemaker neuronal ensemble under the action of a control command is studied herein. The ensemble corresponds to the pyloric central pattern generator of the stomatogastric ganglion of lobster. The desired dynamics is provided by means of an external master neuron and it is induced via a nonlinear controller. Such a controller is composed of a linearizing-like controller and a high gain observer; the controller is able to counteract uncertainties and external perturbations in the controlled system. Numerical simulations of the robust synchronization dynamics of the master neuron and the pacemaker neuronal ensemble are displayed.

  1. Design and validation of dynamic hierarchies and adaptive layouts using spatial graph grammars

    NARCIS (Netherlands)

    Liao, K.; Kong, J.; Zhang, K.; de Vries, B.; Griffth, D.A.; Chun, Y.; Dean, D.J.

    2017-01-01

    With the thinking paradigm shifting on the evolution of complex adaptive systems, a pattern-based design approach is reviewed and reinterpreted. Although a variety of long-term and lasting explorations on patterns in geographical analysis, environmental planning, and design exist, in-depth

  2. The Dynamic Interplay among EFL Learners' Ambiguity Tolerance, Adaptability, Cultural Intelligence, Learning Approach, and Language Achievement

    Science.gov (United States)

    Alahdadi, Shadi; Ghanizadeh, Afsaneh

    2017-01-01

    A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and…

  3. The Brain Dynamics of Rapid Perceptual Adaptation to Adverse Listening Conditions

    NARCIS (Netherlands)

    Erb, J.; Henry, M.J.; Eisner, F.; Obleser, J.

    2013-01-01

    Listeners show a remarkable ability to quickly adjust to degraded speech input. Here, we aimed to identify the neural mechanisms of such short-term perceptual adaptation. In a sparse-sampling, cardiac-gated functional magnetic resonance imaging (fMRI) acquisition, human listeners heard and repeated

  4. The dynamic interplay among EFL learners’ ambiguity tolerance, adaptability, cultural intelligence, learning approach, and language achievement

    Directory of Open Access Journals (Sweden)

    Shadi Alahdadi

    2017-01-01

    Full Text Available A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and language achievement as manifestations of the above competencies within a single model. The participants comprised one hundred eighty BA and MA Iranian university students studying English language teaching and translation. The instruments used in this study consisted of the translated versions of four questionnaires: second language tolerance of ambiguity scale, adaptability taken from emotional intelligence inventory, cultural intelligence (CQ inventory, and the revised study process questionnaire measuring surface and deep learning. The results estimated via structural equation modeling (SEM revealed that the proposed model containing the variables under study had a good fit with the data. It was found that all the variables except adaptability directly influenced language achievement with deep approach having the highest impact and ambiguity tolerance having the lowest influence. In addition, ambiguity tolerance was a positive and significant predictor of deep approach. CQ was found to be under the influence of both ambiguity tolerance and adaptability. The findings were discussed in the light of the yielded results.

  5. SU-E-J-254: Utility of Pinnacle Dynamic Planning Module Utilizing Deformable Image Registration in Adaptive Radiotherapy

    International Nuclear Information System (INIS)

    Jani, S

    2014-01-01

    Purpose For certain highly conformal treatment techniques, changes in patient anatomy due to weight loss and/or tumor shrinkage can result in significant changes in dose distribution. Recently, the Pinnacle treatment planning system added a Dynamic Planning module utilizing Deformable Image Registration (DIR). The objective of this study was to evaluate the effectiveness of this software in adapting to altered anatomy and adjusting treatment plans to account for it. Methods We simulated significant tumor response by changing patient thickness and altered chin positions using a commercially-available head and neck (H and N) phantom. In addition, we studied 23 CT image sets of fifteen (15) patients with H and N tumors and eight (8) patients with prostate cancer. In each case, we applied deformable image registration through Dynamic Planning module of our Pinnacle Treatment Planning System. The dose distribution of the original CT image set was compared to the newly computed dose without altering any treatment parameter. Result was a dose if we did not adjust the plan to reflect anatomical changes. Results For the H and N phantom, a tumor response of up to 3.5 cm was correctly deformed by the Pinnacle Dynamic module. Recomputed isodose contours on new anatomies were within 1 mm of the expected distribution. The Pinnacle system configuration allowed dose computations resulting from original plans on new anatomies without leaving the planning system. Original and new doses were available side-by-side with both CT image sets. Based on DIR, about 75% of H and N patients (11/15) required a re-plan using new anatomy. Among prostate patients, the DIR predicted near-correct bladder volume in 62% of the patients (5/8). Conclusions The Dynamic Planning module of the Pinnacle system proved to be an accurate and useful tool in our ability to adapt to changes in patient anatomy during a course of radiotherapy

  6. Documentation of the dynamic parameter, water-use, stream and lake flow routing, and two summary output modules and updates to surface-depression storage simulation and initial conditions specification options with the Precipitation-Runoff Modeling System (PRMS)

    Science.gov (United States)

    Regan, R. Steve; LaFontaine, Jacob H.

    2017-10-05

    This report documents seven enhancements to the U.S. Geological Survey (USGS) Precipitation-Runoff Modeling System (PRMS) hydrologic simulation code: two time-series input options, two new output options, and three updates of existing capabilities. The enhancements are (1) new dynamic parameter module, (2) new water-use module, (3) new Hydrologic Response Unit (HRU) summary output module, (4) new basin variables summary output module, (5) new stream and lake flow routing module, (6) update to surface-depression storage and flow simulation, and (7) update to the initial-conditions specification. This report relies heavily upon U.S. Geological Survey Techniques and Methods, book 6, chapter B7, which documents PRMS version 4 (PRMS-IV). A brief description of PRMS is included in this report.

  7. Belief update as social choice

    NARCIS (Netherlands)

    van Benthem, J.; Girard, P.; Roy, O.; Marion, M.

    2011-01-01

    Dynamic epistemic-doxastic logics describe the new knowledge or new beliefs indexBelief of agents after some informational event has happened. Technically, this requires an update rule that turns a doxastic-epistemic modelM(recording the current information state of the agents) and a dynamic ‘event

  8. Dynamic assessment of intelligence is a better reply to adaptive behavior and cognitive plasticity.

    Science.gov (United States)

    Fabio, Rosa Angela

    2005-01-01

    In the present study, the author conducted 3 experiments to examine the dynamic testing of potential intelligence. She investigated the relationship between dynamic measures and other factors such as (a) static measures of intelligence (Raven's Colored Progressive Matrices Test [J. C. Raven, J. H. Court, & J. Raven, 1979] and the D48 [J. D. Black, 1961]) and (b) codifying speed, codifying accuracy, and school performance. The participants were kindergarten children (n = 150), primary school children (n = 287), and teenaged students (n = 198) who were all trained to master problem solving tests with dynamic measures of intelligence. The results showed that dynamic measures predict more accurately the relationships of codifying speed, codifying accuracy, and school performance.

  9. Update report on fracture flow in saturated tuff: Dynamic transport task for the Nevada Nuclear Waste Investigations

    International Nuclear Information System (INIS)

    Janecky, D.R.; Rundberg, R.S.; Ott, M.; Mitchell, A.

    1990-11-01

    This report summarizes the results of continuing experiments on the behavior of tracers during fracture flow in saturated, welded tuff. These experiments were completed during the past year as part of the Dynamic Transport Task of geochemical investigations for the Yucca Mountain Project sponsored by the US Department of Energy. These experiments are designed to investigate the effects of fluid movement in fractures when coupled with matrix diffusion and sorption but isolated from the effects of capillary suction and two-phase flow characteristic of unsaturated conditions. The experiments reported here are continuations of experimental efforts reported previously. The behavior of three tracers [HTO (tritiated water), TcO 4 - (pertechnetate), and sulforhodamine B dye] have been investigated during flow through a saturated column of densely welded tuff from the Topopah Spring Member of the Paintbrush Tuff, Yucca Mountain, Nye County, southern Nevada. 31 refs., 26 figs., 2 tabs

  10. Analysis of Social Network Dynamics with Models from the Theory of Complex Adaptive Systems

    OpenAIRE

    Lymperopoulos , Ilias; Lekakos , George

    2013-01-01

    Part 4: Protocols, Regulation and Social Networking; International audience; The understanding and modeling of social dynamics in a complex and unpredictable world, emerges as a research target of particular importance. Success in this direction can yield valuable knowledge as to how social phenomena form and evolve in varying socioeconomic contexts comprising economic crises, societal disasters, cultural differences and security threats among others. The study of social dynamics occurring in...

  11. High dynamic range adaptive real-time smart camera: an overview of the HDR-ARTiST project

    Science.gov (United States)

    Lapray, Pierre-Jean; Heyrman, Barthélémy; Ginhac, Dominique

    2015-04-01

    Standard cameras capture only a fraction of the information that is visible to the human visual system. This is specifically true for natural scenes including areas of low and high illumination due to transitions between sunlit and shaded areas. When capturing such a scene, many cameras are unable to store the full Dynamic Range (DR) resulting in low quality video where details are concealed in shadows or washed out by sunlight. The imaging technique that can overcome this problem is called HDR (High Dynamic Range) imaging. This paper describes a complete smart camera built around a standard off-the-shelf LDR (Low Dynamic Range) sensor and a Virtex-6 FPGA board. This smart camera called HDR-ARtiSt (High Dynamic Range Adaptive Real-time Smart camera) is able to produce a real-time HDR live video color stream by recording and combining multiple acquisitions of the same scene while varying the exposure time. This technique appears as one of the most appropriate and cheapest solution to enhance the dynamic range of real-life environments. HDR-ARtiSt embeds real-time multiple captures, HDR processing, data display and transfer of a HDR color video for a full sensor resolution (1280 1024 pixels) at 60 frames per second. The main contributions of this work are: (1) Multiple Exposure Control (MEC) dedicated to the smart image capture with alternating three exposure times that are dynamically evaluated from frame to frame, (2) Multi-streaming Memory Management Unit (MMMU) dedicated to the memory read/write operations of the three parallel video streams, corresponding to the different exposure times, (3) HRD creating by combining the video streams using a specific hardware version of the Devebecs technique, and (4) Global Tone Mapping (GTM) of the HDR scene for display on a standard LCD monitor.

  12. Adaptive Neural Output-Feedback Control for a Class of Nonlower Triangular Nonlinear Systems With Unmodeled Dynamics.

    Science.gov (United States)

    Wang, Huanqing; Liu, Peter Xiaoping; Li, Shuai; Wang, Ding

    2017-08-29

    This paper presents the development of an adaptive neural controller for a class of nonlinear systems with unmodeled dynamics and immeasurable states. An observer is designed to estimate system states. The structure consistency of virtual control signals and the variable partition technique are combined to overcome the difficulties appearing in a nonlower triangular form. An adaptive neural output-feedback controller is developed based on the backstepping technique and the universal approximation property of the radial basis function (RBF) neural networks. By using the Lyapunov stability analysis, the semiglobally and uniformly ultimate boundedness of all signals within the closed-loop system is guaranteed. The simulation results show that the controlled system converges quickly, and all the signals are bounded. This paper is novel at least in the two aspects: 1) an output-feedback control strategy is developed for a class of nonlower triangular nonlinear systems with unmodeled dynamics and 2) the nonlinear disturbances and their bounds are the functions of all states, which is in a more general form than existing results.

  13. Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

    Science.gov (United States)

    Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

    2014-06-01

    This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

  14. Observer-based distributed adaptive fault-tolerant containment control of multi-agent systems with general linear dynamics.

    Science.gov (United States)

    Ye, Dan; Chen, Mengmeng; Li, Kui

    2017-11-01

    In this paper, we consider the distributed containment control problem of multi-agent systems with actuator bias faults based on observer method. The objective is to drive the followers into the convex hull spanned by the dynamic leaders, where the input is unknown but bounded. By constructing an observer to estimate the states and bias faults, an effective distributed adaptive fault-tolerant controller is developed. Different from the traditional method, an auxiliary controller gain is designed to deal with the unknown inputs and bias faults together. Moreover, the coupling gain can be adjusted online through the adaptive mechanism without using the global information. Furthermore, the proposed control protocol can guarantee that all the signals of the closed-loop systems are bounded and all the followers converge to the convex hull with bounded residual errors formed by the dynamic leaders. Finally, a decoupled linearized longitudinal motion model of the F-18 aircraft is used to demonstrate the effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Decentralized adaptive neural control for high-order interconnected stochastic nonlinear time-delay systems with unknown system dynamics.

    Science.gov (United States)

    Si, Wenjie; Dong, Xunde; Yang, Feifei

    2018-03-01

    This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, only one adaptive parameter is constructed to overcome the over-parameterization, and neural networks are employed to cope with the difficulties raised by completely unknown system dynamics and stochastic disturbances. And then, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions of high-order large-scale systems for the first time. At last, on the basis of Lyapunov stability theory, the decentralized adaptive neural controller was developed, and it decreases the number of learning parameters. The actual controller can be designed so as to ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges in the small neighborhood of zero. The simulation example is used to further show the validity of the design method. Copyright © 2018 Elsevier Ltd. All rights reserved.

  16. Comparison of the updated solutions of the 6th dynamic AER Benchmark - main steam line break in a NPP with WWER-440

    International Nuclear Information System (INIS)

    Kliem, S.

    2003-01-01

    The 6 th dynamic AER Benchmark is used for the systematic validation of coupled 3D neutron kinetic/thermal hydraulic system codes. It was defined at The 10 th AER-Symposium. In this benchmark, a hypothetical double ended break of one main steam line at full power in a WWER-440 plant is investigated. The main thermal hydraulic features are the consideration of incomplete coolant mixing in the lower and upper plenum of the reactor pressure vessel and an asymmetric operation of the feed water system. For the tuning of the different nuclear cross section data used by the participants, an isothermal re-criticality temperature was defined. The paper gives an overview on the behaviour of the main thermal hydraulic and neutron kinetic parameters in the provided solutions. The differences in the updated solution in comparison to the previous ones are described. Improvements in the modelling of the transient led to a better agreement of a part of the results while for another part the deviations rose up. The sensitivity of the core power behaviour on the secondary side modelling is discussed in detail (Authors)

  17. Understanding the dynamics of the Seguro Popular de Salud policy implementation in Mexico from a complex adaptive systems perspective.

    Science.gov (United States)

    Nigenda, Gustavo; González-Robledo, Luz María; Juárez-Ramírez, Clara; Adam, Taghreed

    2016-05-13

    In 2003, Mexico's Seguro Popular de Salud (SPS), was launched as an innovative financial mechanism implemented to channel new funds to provide health insurance to 50 million Mexicans and to reduce systemic financial inequities. The objective of this article is to understand the complexity and dynamics that contributed to the adaptation of the policy in the implementation stage, how these changes occurred, and why, from a complex and adaptive systems perspective. A complex adaptive systems (CAS) framework was used to carry out a secondary analysis of data obtained from four SPS's implementation evaluations. We first identified key actors, their roles, incentives and power, and their responses to the policy and guidelines. We then developed a causal loop diagram to disentangle the feedback dynamics associated with the modifications of the policy implementation which we then analyzed using a CAS perspective. Implementation variations were identified in seven core design features during the first 10 years of implementation period, and in each case, the SPS's central coordination introduced modifications in response to the reactions of the different actors. We identified several CAS phenomena associated with these changes including phase transitions, network emergence, resistance to change, history dependence, and feedback loops. Our findings generate valuable lessons to policy implementation processes, especially those involving a monetary component, where the emergence of coping mechanisms and other CAS phenomena inevitably lead to modifications of policies and their interpretation by those who implement them. These include the difficulty of implementing strategies that aim to pool funds through solidarity among beneficiaries where the rich support the poor when there are no incentives for the rich to do so. Also, how resistance to change and history dependence can pose significant challenges to implementing changes, where the local actors use their significant power

  18. An adaptive transmission protocol for managing dynamic shared states in collaborative surgical simulation.

    Science.gov (United States)

    Qin, J; Choi, K S; Ho, Simon S M; Heng, P A

    2008-01-01

    A force prediction algorithm is proposed to facilitate virtual-reality (VR) based collaborative surgical simulation by reducing the effect of network latencies. State regeneration is used to correct the estimated prediction. This algorithm is incorporated into an adaptive transmission protocol in which auxiliary features such as view synchronization and coupling control are equipped to ensure the system consistency. We implemented this protocol using multi-threaded technique on a cluster-based network architecture.

  19. Computing the dynamics of biomembranes by combining conservative level set and adaptive finite element methods

    OpenAIRE

    Laadhari , Aymen; Saramito , Pierre; Misbah , Chaouqi

    2014-01-01

    International audience; The numerical simulation of the deformation of vesicle membranes under simple shear external fluid flow is considered in this paper. A new saddle-point approach is proposed for the imposition of the fluid incompressibility and the membrane inextensibility constraints, through Lagrange multipliers defined in the fluid and on the membrane respectively. Using a level set formulation, the problem is approximated by mixed finite elements combined with an automatic adaptive ...

  20. Dancing to a Different Tune: Adaptive Evolution Fine-Tunes Protein Dynamics

    Science.gov (United States)

    2015-09-01

    efficiency at low temperatures when the enzymes from mesophilic bacteria were evolved to have stabilities as high as their thermophilic homologs. The work...wild-type enzyme . This unfolding temperature is relatively high for a non- thermophilic enzyme ,15 as mesophilic enzymes typically unfold below 60 °C...The work described in this thesis provides a case study exploring the molecular changes underlying adaptive evolution in a key allosteric enzyme . It

  1. The brain dynamics of rapid perceptual adaptation to adverse listening conditions.

    Science.gov (United States)

    Erb, Julia; Henry, Molly J; Eisner, Frank; Obleser, Jonas

    2013-06-26

    Listeners show a remarkable ability to quickly adjust to degraded speech input. Here, we aimed to identify the neural mechanisms of such short-term perceptual adaptation. In a sparse-sampling, cardiac-gated functional magnetic resonance imaging (fMRI) acquisition, human listeners heard and repeated back 4-band-vocoded sentences (in which the temporal envelope of the acoustic signal is preserved, while spectral information is highly degraded). Clear-speech trials were included as baseline. An additional fMRI experiment on amplitude modulation rate discrimination quantified the convergence of neural mechanisms that subserve coping with challenging listening conditions for speech and non-speech. First, the degraded speech task revealed an "executive" network (comprising the anterior insula and anterior cingulate cortex), parts of which were also activated in the non-speech discrimination task. Second, trial-by-trial fluctuations in successful comprehension of degraded speech drove hemodynamic signal change in classic "language" areas (bilateral temporal cortices). Third, as listeners perceptually adapted to degraded speech, downregulation in a cortico-striato-thalamo-cortical circuit was observable. The present data highlight differential upregulation and downregulation in auditory-language and executive networks, respectively, with important subcortical contributions when successfully adapting to a challenging listening situation.

  2. Dynamically adapted context-specific hyper-articulation: Feedback from interlocutors affects speakers’ subsequent pronunciations

    Science.gov (United States)

    Buz, Esteban; Tanenhaus, Michael K.; Jaeger, T. Florian

    2016-01-01

    We ask whether speakers can adapt their productions when feedback from their interlocutors suggests that previous productions were perceptually confusable. To address this question, we use a novel web-based task-oriented paradigm for speech recording, in which participants produce instructions towards a (simulated) partner with naturalistic response times. We manipulate (1) whether a target word with a voiceless plosive (e.g., pill) occurs in the presence of a voiced competitor (bill) or an unrelated word (food) and (2) whether or not the simulated partner occasionally misunderstands the target word. Speakers hyper-articulated the target word when a voiced competitor was present. Moreover, the size of the hyper-articulation effect was nearly doubled when partners occasionally misunderstood the instruction. A novel type of distributional analysis further suggests that hyper-articulation did not change the target of production, but rather reduced the probability of perceptually ambiguous or confusable productions. These results were obtained in the absence of explicit clarification requests, and persisted across words and over trials. Our findings suggest that speakers adapt their pronunciations based on the perceived communicative success of their previous productions in the current environment. We discuss why speakers make adaptive changes to their speech and what mechanisms might underlie speakers’ ability to do so. PMID:27375344

  3. Community dynamics and glycoside hydrolase activities of thermophilic bacterial consortia adapted to switchgrass

    Energy Technology Data Exchange (ETDEWEB)

    Gladden, J.M.; Allgaier, M.; Miller, C.S.; Hazen, T.C.; VanderGheynst, J.S.; Hugenholtz, P.; Simmons, B.A.; Singer, S.W.

    2011-05-01

    Industrial-scale biofuel production requires robust enzymatic cocktails to produce fermentable sugars from lignocellulosic biomass. Thermophilic bacterial consortia are a potential source of cellulases and hemicellulases adapted to harsher reaction conditions than commercial fungal enzymes. Compost-derived microbial consortia were adapted to switchgrass at 60 C to develop thermophilic biomass-degrading consortia for detailed studies. Microbial community analysis using small-subunit rRNA gene amplicon pyrosequencing and short-read metagenomic sequencing demonstrated that thermophilic adaptation to switchgrass resulted in low-diversity bacterial consortia with a high abundance of bacteria related to thermophilic paenibacilli, Rhodothermus marinus, and Thermus thermophilus. At lower abundance, thermophilic Chloroflexi and an uncultivated lineage of the Gemmatimonadetes phylum were observed. Supernatants isolated from these consortia had high levels of xylanase and endoglucanase activities. Compared to commercial enzyme preparations, the endoglucanase enzymes had a higher thermotolerance and were more stable in the presence of 1-ethyl-3-methylimidazolium acetate ([C2mim][OAc]), an ionic liquid used for biomass pretreatment. The supernatants were used to saccharify [C2mim][OAc]-pretreated switchgrass at elevated temperatures (up to 80 C), demonstrating that these consortia are an excellent source of enzymes for the development of enzymatic cocktails tailored to more extreme reaction conditions.

  4. THE PLUTO CODE FOR ADAPTIVE MESH COMPUTATIONS IN ASTROPHYSICAL FLUID DYNAMICS

    International Nuclear Information System (INIS)

    Mignone, A.; Tzeferacos, P.; Zanni, C.; Bodo, G.; Van Straalen, B.; Colella, P.

    2012-01-01

    We present a description of the adaptive mesh refinement (AMR) implementation of the PLUTO code for solving the equations of classical and special relativistic magnetohydrodynamics (MHD and RMHD). The current release exploits, in addition to the static grid version of the code, the distributed infrastructure of the CHOMBO library for multidimensional parallel computations over block-structured, adaptively refined grids. We employ a conservative finite-volume approach where primary flow quantities are discretized at the cell center in a dimensionally unsplit fashion using the Corner Transport Upwind method. Time stepping relies on a characteristic tracing step where piecewise parabolic method, weighted essentially non-oscillatory, or slope-limited linear interpolation schemes can be handily adopted. A characteristic decomposition-free version of the scheme is also illustrated. The solenoidal condition of the magnetic field is enforced by augmenting the equations with a generalized Lagrange multiplier providing propagation and damping of divergence errors through a mixed hyperbolic/parabolic explicit cleaning step. Among the novel features, we describe an extension of the scheme to include non-ideal dissipative processes, such as viscosity, resistivity, and anisotropic thermal conduction without operator splitting. Finally, we illustrate an efficient treatment of point-local, potentially stiff source terms over hierarchical nested grids by taking advantage of the adaptivity in time. Several multidimensional benchmarks and applications to problems of astrophysical relevance assess the potentiality of the AMR version of PLUTO in resolving flow features separated by large spatial and temporal disparities.

  5. SWCD: a sliding window and self-regulated learning-based background updating method for change detection in videos

    Science.gov (United States)

    Işık, Şahin; Özkan, Kemal; Günal, Serkan; Gerek, Ömer Nezih

    2018-03-01

    Change detection with background subtraction process remains to be an unresolved issue and attracts research interest due to challenges encountered on static and dynamic scenes. The key challenge is about how to update dynamically changing backgrounds from frames with an adaptive and self-regulated feedback mechanism. In order to achieve this, we present an effective change detection algorithm for pixelwise changes. A sliding window approach combined with dynamic control of update parameters is introduced for updating background frames, which we called sliding window-based change detection. Comprehensive experiments on related test videos show that the integrated algorithm yields good objective and subjective performance by overcoming illumination variations, camera jitters, and intermittent object motions. It is argued that the obtained method makes a fair alternative in most types of foreground extraction scenarios; unlike case-specific methods, which normally fail for their nonconsidered scenarios.

  6. An adaptive cryptographic accelerator for network storage security on dynamically reconfigurable platform

    Science.gov (United States)

    Tang, Li; Liu, Jing-Ning; Feng, Dan; Tong, Wei

    2008-12-01

    Existing security solutions in network storage environment perform poorly because cryptographic operations (encryption and decryption) implemented in software can dramatically reduce system performance. In this paper we propose a cryptographic hardware accelerator on dynamically reconfigurable platform for the security of high performance network storage system. We employ a dynamic reconfigurable platform based on a FPGA to implement a PowerPCbased embedded system, which executes cryptographic algorithms. To reduce the reconfiguration latency, we apply prefetch scheduling. Moreover, the processing elements could be dynamically configured to support different cryptographic algorithms according to the request received by the accelerator. In the experiment, we have implemented AES (Rijndael) and 3DES cryptographic algorithms in the reconfigurable accelerator. Our proposed reconfigurable cryptographic accelerator could dramatically increase the performance comparing with the traditional software-based network storage systems.

  7. The Analysis of Closed-form Solution for Energy Detector Dynamic Threshold Adaptation in Cognitive Radio

    Directory of Open Access Journals (Sweden)

    R. Bozovic

    2017-12-01

    Full Text Available Spectrum sensing is the most important process in cognitive radio in order to ensure interference avoidance to primary users. For optimal performance of cognitive radio, it is substantial to monitor and promptly react to dynamic changes in its operating environment. In this paper, energy detector based spectrum sensing is considered. Under the assumption that detected signal can be modelled according to an autoregressive model, noise variance is estimated from that noisy signal, as well as primary user signal power. A closed-form solution for optimal decision threshold in dynamic electromagnetic environment is proposed and analyzed.

  8. Harm reduction as a complex adaptive system: A dynamic framework for analyzing Tanzanian policies concerning heroin use.

    Science.gov (United States)

    Ratliff, Eric A; Kaduri, Pamela; Masao, Frank; Mbwambo, Jessie K K; McCurdy, Sheryl A

    2016-04-01

    Contrary to popular belief, policies on drug use are not always based on scientific evidence or composed in a rational manner. Rather, decisions concerning drug policies reflect the negotiation of actors' ambitions, values, and facts as they organize in different ways around the perceived problems associated with illicit drug use. Drug policy is thus best represented as a complex adaptive system (CAS) that is dynamic, self-organizing, and coevolving. In this analysis, we use a CAS framework to examine how harm reduction emerged around heroin trafficking and use in Tanzania over the past thirty years (1985-present). This account is an organizational ethnography based on of the observant participation of the authors as actors within this system. We review the dynamic history and self-organizing nature of harm reduction, noting how interactions among system actors and components have coevolved with patterns of heroin us, policing, and treatment activities over time. Using a CAS framework, we describe harm reduction as a complex process where ambitions, values, facts, and technologies interact in the Tanzanian sociopolitical environment. We review the dynamic history and self-organizing nature of heroin policies, noting how the interactions within and between competing prohibitionist and harm reduction policies have changed with patterns of heroin use, policing, and treatment activities over time. Actors learn from their experiences to organize with other actors, align their values and facts, and implement new policies. Using a CAS approach provides researchers and policy actors a better understanding of patterns and intricacies in drug policy. This knowledge of how the system works can help improve the policy process through adaptive action to introduce new actors, different ideas, and avenues for communication into the system. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Performance analysis of a cooperative adaptive cruise controller subject to dynamic time headway

    NARCIS (Netherlands)

    Semsar-Kazerooni, E.; Ploeg, J.

    2013-01-01

    The current paper shows string stability of a platoon of vehicles when the spacing policy within the platoon is dynamic, i.e., it has time-varying parameters. This problem setup is to address the safety issues that arise due to malfunction of some redundant sensing/communicating devices installed on

  10. Towards an Agile Approach to Adapting Dynamic Collaboration Support to Student Needs

    Science.gov (United States)

    Adamson, David; Dyke, Gregory; Jang, Hyeju; Rosé, Carolyn Penstein

    2014-01-01

    This paper investigates the use of conversational agents to scaffold on-line collaborative learning discussions through an approach called Academically Productive Talk (APT). In contrast to past work on dynamic support for collaborative learning, where agents were used to elevate conceptual depth by leading students through directed lines of…

  11. Natural hazards and climate change in Dhaka: future trends, social adaptation and informal dynamics

    Science.gov (United States)

    Thiele-Eich, I.; Aßheuer, T.; Simmer, C.; Braun, B.

    2009-04-01

    Similar to many megacities in the world, Dhaka is regularly threatened by natural hazards. Risks associated with floods and cyclones in particular are expected to increase in the years to come because of global climate change and rapid urbanization. Greater Dhaka is expected to grow from 13.5 million inhabitants in 2007 to 22 million inhabitants by 2025. The vast majority of this growth will take place in informal settlements. Due to the setting of Greater Dhaka in a deltaic plain, the sprawl of slums is primarily taking place in wetlands, swamps and other flood-prone areas. Slum dwellers and informal businesses are vulnerable, but have somehow learned to cope with seasonal floods and developed specific adaptation strategies. An increase of precipitation extremes and tropical cyclones, however, would put considerable stress on the adaptability of the social and economic system. DhakaHazard, a joint research project of the Department of Meteorology at the University of Bonn and the Department of Geography at the University of Cologne, takes up these issues in an interdisciplinary approach. The project, which begun in November 2008, aims to achieve two main objectives: To link analyses of informal social and economic adaptation strategies to models on future climate change and weather extremes. To estimate more accurately the future frequency and magnitude of weather extremes and floods which are crucial for the future adaptability of informal systems. To fulfill these objectives, scientists at the Meteorological Institute are studying the evolution of natural hazards in Bangladesh, while researchers at the Department of Geography are undertaking the task of assessing these hazards from a social point of view. More specifically, the meteorologists are identifying global and regional weather conditions resulting in flooding of the Greater Dhaka region, while possible variations in flood-inducing weather patterns are analyzed by evaluating their frequency and magnitude

  12. Dynamic stabbing queries with sub-logarithmic local updates for overlapping intervals : Proc. 12th International Computer Science Symposium in Russia

    NARCIS (Netherlands)

    Khramtcova, Elena; Löffler, Maarten

    2017-01-01

    We present a data structure to maintain a set of intervals on the real line subject to fast insertions and deletions of the intervals, stabbing queries, and local updates. Intuitively, a local update replaces an interval by another one of roughly the same size and location. We investigate whether

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

    Science.gov (United States)

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

    2018-05-01

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

  14. Obtainment of nuclear power plant dynamic parameters by adaptive mesh technique

    International Nuclear Information System (INIS)

    Carvalho Miranda, W. de.

    1979-01-01

    This thesis involves the problem in determination of the parameters of the Mathematical Model of a Nuclear Reactor, including non-linearity which is considered as a bi-linear system. Being a non-linear model, the determination of its parameters cannot be made with the classical techniques as in obtaining its experimental frequency response. In the present work, we examine the possibility of using a model with parameters that adapt according to a algorithm of Newton type minimization, showing that in the case of the single parameter determination, the method is successful. This work was done, using the CSMP (Continuous System Modelling Program) of IBM 1130 of IME. (author)

  15. Full Quantum Dynamics Simulation of a Realistic Molecular System Using the Adaptive Time-Dependent Density Matrix Renormalization Group Method.

    Science.gov (United States)

    Yao, Yao; Sun, Ke-Wei; Luo, Zhen; Ma, Haibo

    2018-01-18

    The accurate theoretical interpretation of ultrafast time-resolved spectroscopy experiments relies on full quantum dynamics simulations for the investigated system, which is nevertheless computationally prohibitive for realistic molecular systems with a large number of electronic and/or vibrational degrees of freedom. In this work, we propose a unitary transformation approach for realistic vibronic Hamiltonians, which can be coped with using the adaptive time-dependent density matrix renormalization group (t-DMRG) method to efficiently evolve the nonadiabatic dynamics of a large molecular system. We demonstrate the accuracy and efficiency of this approach with an example of simulating the exciton dissociation process within an oligothiophene/fullerene heterojunction, indicating that t-DMRG can be a promising method for full quantum dynamics simulation in large chemical systems. Moreover, it is also shown that the proper vibronic features in the ultrafast electronic process can be obtained by simulating the two-dimensional (2D) electronic spectrum by virtue of the high computational efficiency of the t-DMRG method.

  16. Variation in body mass dynamics among sites in Black Brant Branta bernicla nigricans supports adaptivity of mass loss during moult

    Science.gov (United States)

    Fondell, Thomas F.; Flint, Paul L.; Schmutz, Joel A.; Schamber, Jason L.; Nicolai, Christopher A.

    2013-01-01

    Birds employ varying strategies to accommodate the energetic demands of moult, one important example being changes in body mass. To understand better their physiological and ecological significance, we tested three hypotheses concerning body mass dynamics during moult. We studied Black Brant in 2006 and 2007 moulting at three sites in Alaska which varied in food availability, breeding status and whether geese undertook a moult migration. First we predicted that if mass loss during moult were simply the result of inadequate food resources then mass loss would be highest where food was least available. Secondly, we predicted that if mass loss during moult were adaptive, allowing birds to reduce activity during moult, then birds would gain mass prior to moult where feeding conditions allowed and mass loss would be positively related to mass at moult initiation. Thirdly, we predicted that if mass loss during moult were adaptive, allowing birds to regain flight sooner, then across sites and groups, mass at the end of the flightless period would converge on a theoretical optimum, i.e. the mass that permits the earliest possible return to flight. Mass loss was greatest where food was most available and thus our results did not support the prediction that mass loss resulted from inadequate food availability. Mass at moult initiation was positively related to both food availability and mass loss. In addition, among sites and years, variation in mass was high at moult initiation but greatly reduced at the end of the flightless period, appearing to converge. Thus, our results supported multiple predictions that mass loss during moult was adaptive and that the optimal moulting strategy was to gain mass prior to the flightless period, then through behavioural modifications use these body reserves to reduce activity and in so doing also reduce wing loading. Geese that undertook a moult migration initiated moult at the highest mass, indicating that they were more than able to

  17. Dynamic modelling of water demand, water availability and adaptation strategies for power plants to global change

    International Nuclear Information System (INIS)

    Koch, Hagen; Voegele, Stefan

    2009-01-01

    According to the latest IPCC reports, the frequency of hot and dry periods will increase in many regions of the world in the future. For power plant operators, the increasing possibility of water shortages is an important challenge that they have to face. Shortages of electricity due to water shortages could have an influence on industries as well as on private households. Climate change impact analyses must analyse the climate effects on power plants and possible adaptation strategies for the power generation sector. Power plants have lifetimes of several decades. Their water demand changes with climate parameters in the short- and medium-term. In the long-term, the water demand will change as old units are phased out and new generating units appear in their place. In this paper, we describe the integration of functions for the calculation of the water demand of power plants into a water resources management model. Also included are both short-term reactive and long-term planned adaptation. This integration allows us to simulate the interconnection between the water demand of power plants and water resources management, i.e. water availability. Economic evaluation functions for water shortages are also integrated into the water resources management model. This coupled model enables us to analyse scenarios of socio-economic and climate change, as well as the effects of water management actions. (author)

  18. Similar temperature dependencies of glycolytic enzymes: an evolutionary adaptation to temperature dynamics?

    Directory of Open Access Journals (Sweden)

    Cruz Luisa Ana B

    2012-12-01

    Full Text Available Abstract Background Temperature strongly affects microbial growth, and many microorganisms have to deal with temperature fluctuations in their natural environment. To understand regulation strategies that underlie microbial temperature responses and adaptation, we studied glycolytic pathway kinetics in Saccharomyces cerevisiae during temperature changes. Results Saccharomyces cerevisiae was grown under different temperature regimes and glucose availability conditions. These included glucose-excess batch cultures at different temperatures and glucose-limited chemostat cultures, subjected to fast linear temperature shifts and circadian sinoidal temperature cycles. An observed temperature-independent relation between intracellular levels of glycolytic metabolites and residual glucose concentration for all experimental conditions revealed that it is the substrate availability rather than temperature that determines intracellular metabolite profiles. This observation corresponded with predictions generated in silico with a kinetic model of yeast glycolysis, when the catalytic capacities of all glycolytic enzymes were set to share the same normalized temperature dependency. Conclusions From an evolutionary perspective, such similar temperature dependencies allow cells to adapt more rapidly to temperature changes, because they result in minimal perturbations of intracellular metabolite levels, thus circumventing the need for extensive modification of enzyme levels.

  19. Hedgehog signaling mediates adaptive variation in a dynamic functional system in the cichlid feeding apparatus.

    Science.gov (United States)

    Hu, Yinan; Albertson, R Craig

    2014-06-10

    Adaptive variation in the craniofacial skeleton is a key component of resource specialization and habitat divergence in vertebrates, but the proximate genetic mechanisms that underlie complex patterns of craniofacial variation are largely unknown. Here we demonstrate that the Hedgehog (Hh) signaling pathway mediates widespread variation across a complex functional system that affects the kinematics of lower jaw depression--the opercular four-bar linkage apparatus--among Lake Malawi cichlids. By using a combined quantitative trait locus mapping and population genetics approach, we show that allelic variation in the Hh receptor, ptch1, affects the development of distinct bony elements in the head that represent two of three movable links in this functional system. The evolutionarily derived allele is found in species that feed from the water column, and is associated with shifts in anatomy that translate to a four-bar system capable of faster jaw rotation. Alternatively, the ancestral allele is found in species that feed on attached algae, and is associated with the development of a four-bar system that predicts slower jaw movement. Experimental manipulation of the Hh pathway during cichlid development recapitulates functionally salient natural variation in craniofacial geometry. In all, these results significantly extend our understanding of the mechanisms that fine-tune the craniofacial skeletal complex during adaptation to new foraging niches.

  20. COLLABORATIVE RESEARCH: CONTINUOUS DYNAMIC GRID ADAPTATION IN A GLOBAL ATMOSPHERIC MODEL: APPLICATION AND REFINEMENT

    Energy Technology Data Exchange (ETDEWEB)

    Prusa, Joseph

    2012-05-08

    This project had goals of advancing the performance capabilities of the numerical general circulation model EULAG and using it to produce a fully operational atmospheric global climate model (AGCM) that can employ either static or dynamic grid stretching for targeted phenomena. The resulting AGCM combined EULAG's advanced dynamics core with the physics of the NCAR Community Atmospheric Model (CAM). Effort discussed below shows how we improved model performance and tested both EULAG and the coupled CAM-EULAG in several ways to demonstrate the grid stretching and ability to simulate very well a wide range of scales, that is, multi-scale capability. We leveraged our effort through interaction with an international EULAG community that has collectively developed new features and applications of EULAG, which we exploited for our own work summarized here. Overall, the work contributed to over 40 peer- reviewed publications and over 70 conference/workshop/seminar presentations, many of them invited.

  1. EDV supported dynamic fire protection concept adaptation during dismantling of nuclear facilities

    International Nuclear Information System (INIS)

    Mummert, Maxi; Traichel, Anke; Dilger, Matthias

    2013-01-01

    Fire protection concepts are supposed to be a decision guide for the definition of measures and priorities in fire fighting and fire prevention. In case of reactor dismantling a fire protection concept for the actual status is required. Following the fuel removal from the reactor the protection goals are reduced to the safe confinement of radioactive materials and the restriction of radiation exposure. A dynamic fire protection concept was developed to allow the compliance with the required protection measures with respect to the protection targets. The implementation of the dynamic fire protection concept simplifies the planning of the dismantling steps and to adjust the fire protection measured in the frame of changes in the plant.

  2. DARAL: A Dynamic and Adaptive Routing Algorithm for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Francisco José Estévez

    2016-06-01

    Full Text Available The evolution of Smart City projects is pushing researchers and companies to develop more efficient embedded hardware and also more efficient communication technologies. These communication technologies are the focus of this work, presenting a new routing algorithm based on dynamically-allocated sub-networks and node roles. Among these features, our algorithm presents a fast set-up time, a reduced overhead and a hierarchical organization, which allows for the application of complex management techniques. This work presents a routing algorithm based on a dynamically-allocated hierarchical clustering, which uses the link quality indicator as a reference parameter, maximizing the network coverage and minimizing the control message overhead and the convergence time. The present work based its test scenario and analysis in the density measure, considered as a node degree. The routing algorithm is compared with some of the most well known routing algorithms for different scenario densities.

  3. Dynamic Fungal Cell Wall Architecture in Stress Adaptation and Immune Evasion.

    Science.gov (United States)

    Hopke, Alex; Brown, Alistair J P; Hall, Rebecca A; Wheeler, Robert T

    2018-04-01

    Deadly infections from opportunistic fungi have risen in frequency, largely because of the at-risk immunocompromised population created by advances in modern medicine and the HIV/AIDS pandemic. This review focuses on dynamics of the fungal polysaccharide cell wall, which plays an outsized role in fungal pathogenesis and therapy because it acts as both an environmental barrier and as the major interface with the host immune system. Human fungal pathogens use architectural strategies to mask epitopes from the host and prevent immune surveillance, and recent work elucidates how biotic and abiotic stresses present during infection can either block or enhance masking. The signaling components implicated in regulating fungal immune recognition can teach us how cell wall dynamics are controlled, and represent potential targets for interventions designed to boost or dampen immunity. Copyright © 2018 Elsevier Ltd. All rights reserved.

  4. Adaptive dynamic inversion robust control for BTT missile based on wavelet neural network

    Science.gov (United States)

    Li, Chuanfeng; Wang, Yongji; Deng, Zhixiang; Wu, Hao

    2009-10-01

    A new nonlinear control strategy incorporated the dynamic inversion method with wavelet neural networks is presented for the nonlinear coupling system of Bank-to-Turn(BTT) missile in reentry phase. The basic control law is designed by using the dynamic inversion feedback linearization method, and the online learning wavelet neural network is used to compensate the inversion error due to aerodynamic parameter errors, modeling imprecise and external disturbance in view of the time-frequency localization properties of wavelet transform. Weights adjusting laws are derived according to Lyapunov stability theory, which can guarantee the boundedness of all signals in the whole system. Furthermore, robust stability of the closed-loop system under this tracking law is proved. Finally, the six degree-of-freedom(6DOF) simulation results have shown that the attitude angles can track the anticipant command precisely under the circumstances of existing external disturbance and in the presence of parameter uncertainty. It means that the dependence on model by dynamic inversion method is reduced and the robustness of control system is enhanced by using wavelet neural network(WNN) to reconstruct inversion error on-line.

  5. Rotor-bearing system integrated with shape memory alloy springs for ensuring adaptable dynamics and damping enhancement-Theory and experiment

    DEFF Research Database (Denmark)

    Enemark, Søren; Santos, Ilmar F.

    2016-01-01

    nonlinear coupled dynamics of the rotor-bearing system. The nonlinear forces from the thermomechanical shape memory alloy springs and from the passive magnetic bearings are coupled to the rotor and bearing housing dynamics. The equations of motion describing rotor tilt and bearing housing lateral motion......Helical pseudoelastic shape memory alloy (SMA) springs are integrated into a dynamic system consisting of a rigid rotor supported by passive magnetic bearings. The aim is to determine the utility of SMAs for vibration attenuation via their mechanical hysteresis, and for adaptation of the dynamic...

  6. Sequence History Update Tool

    Science.gov (United States)

    Khanampompan, Teerapat; Gladden, Roy; Fisher, Forest; DelGuercio, Chris

    2008-01-01

    The Sequence History Update Tool performs Web-based sequence statistics archiving for Mars Reconnaissance Orbiter (MRO). Using a single UNIX command, the software takes advantage of sequencing conventions to automatically extract the needed statistics from multiple files. This information is then used to populate a PHP database, which is then seamlessly formatted into a dynamic Web page. This tool replaces a previous tedious and error-prone process of manually editing HTML code to construct a Web-based table. Because the tool manages all of the statistics gathering and file delivery to and from multiple data sources spread across multiple servers, there is also a considerable time and effort savings. With the use of The Sequence History Update Tool what previously took minutes is now done in less than 30 seconds, and now provides a more accurate archival record of the sequence commanding for MRO.

  7. A Passive Dynamic Walking Model Based on Knee-Bend Behaviour: Stability and Adaptability for Walking down Steep Slopes

    Directory of Open Access Journals (Sweden)

    Kang An

    2013-10-01

    Full Text Available This paper presents a passive dynamic walking model based on knee-bend behaviour, which is inspired by the way human beings walk. The length and mass parameters of human beings are used in the walking model. The knee-bend mechanism of the stance leg is designed in the phase between knee-strike and heel-strike. q* which is the angular difference of the stance leg between the two events, knee-strike and knee-bend, is adjusted in order to find a stable walking motion. The results show that the stable periodic walking motion on a slope of r <0.4 can be found by adjusting q*. Furthermore, with a particular q* in the range of 0.12adaptable than the conventional walking motion, especially for steep slopes.

  8. Discrete-Time Nonzero-Sum Games for Multiplayer Using Policy-Iteration-Based Adaptive Dynamic Programming Algorithms.

    Science.gov (United States)

    Zhang, Huaguang; Jiang, He; Luo, Chaomin; Xiao, Geyang

    2017-10-01

    In this paper, we investigate the nonzero-sum games for a class of discrete-time (DT) nonlinear systems by using a novel policy iteration (PI) adaptive dynamic programming (ADP) method. The main idea of our proposed PI scheme is to utilize the iterative ADP algorithm to obtain the iterative control policies, which not only ensure the system to achieve stability but also minimize the performance index function for each player. This paper integrates game theory, optimal control theory, and reinforcement learning technique to formulate and handle the DT nonzero-sum games for multiplayer. First, we design three actor-critic algorithms, an offline one and two online ones, for the PI scheme. Subsequently, neural networks are employed to implement these algorithms and the corresponding stability analysis is also provided via the Lyapunov theory. Finally, a numerical simulation example is presented to demonstrate the effectiveness of our proposed approach.

  9. Analytic-Numerical Approach to Solving Singularly Perturbed Parabolic Equations with the Use of Dynamic Adapted Meshes

    Directory of Open Access Journals (Sweden)

    D. V. Lukyanenko

    2016-01-01

    Full Text Available The main objective of the paper is to present a new analytic-numerical approach to singularly perturbed reaction-diffusion-advection models with solutions containing moving interior layers (fronts. We describe some methods to generate the dynamic adapted meshes for an efficient numerical solution of such problems. It is based on a priori information about the moving front properties provided by the asymptotic analysis. In particular, for the mesh construction we take into account a priori asymptotic evaluation of the location and speed of the moving front, its width and structure. Our algorithms significantly reduce the CPU time and enhance the stability of the numerical process compared with classical approaches.The article is published in the authors’ wording.

  10. A Secure, Scalable and Elastic Autonomic Computing Systems Paradigm: Supporting Dynamic Adaptation of Self-* Services from an Autonomic Cloud

    Directory of Open Access Journals (Sweden)

    Abdul Jaleel

    2018-05-01

    Full Text Available Autonomic computing embeds self-management features in software systems using external feedback control loops, i.e., autonomic managers. In existing models of autonomic computing, adaptive behaviors are defined at the design time, autonomic managers are statically configured, and the running system has a fixed set of self-* capabilities. An autonomic computing design should accommodate autonomic capability growth by allowing the dynamic configuration of self-* services, but this causes security and integrity issues. A secure, scalable and elastic autonomic computing system (SSE-ACS paradigm is proposed to address the runtime inclusion of autonomic managers, ensuring secure communication between autonomic managers and managed resources. Applying the SSE-ACS concept, a layered approach for the dynamic adaptation of self-* services is presented with an online ‘Autonomic_Cloud’ working as the middleware between Autonomic Managers (offering the self-* services and Autonomic Computing System (requiring the self-* services. A stock trading and forecasting system is used for simulation purposes. The security impact of the SSE-ACS paradigm is verified by testing possible attack cases over the autonomic computing system with single and multiple autonomic managers running on the same and different machines. The common vulnerability scoring system (CVSS metric shows a decrease in the vulnerability severity score from high (8.8 for existing ACS to low (3.9 for SSE-ACS. Autonomic managers are introduced into the system at runtime from the Autonomic_Cloud to test the scalability and elasticity. With elastic AMs, the system optimizes the Central Processing Unit (CPU share resulting in an improved execution time for business logic. For computing systems requiring the continuous support of self-management services, the proposed system achieves a significant improvement in security, scalability, elasticity, autonomic efficiency, and issue resolving time

  11. Molecular dynamics of mesophilic-like mutants of a cold-adapted enzyme: insights into distal effects induced by the mutations.

    Directory of Open Access Journals (Sweden)

    Elena Papaleo

    Full Text Available Networks and clusters of intramolecular interactions, as well as their "communication" across the three-dimensional architecture have a prominent role in determining protein stability and function. Special attention has been dedicated to their role in thermal adaptation. In the present contribution, seven previously experimentally characterized mutants of a cold-adapted α-amylase, featuring mesophilic-like behavior, have been investigated by multiple molecular dynamics simulations, essential dynamics and analyses of correlated motions and electrostatic interactions. Our data elucidate the molecular mechanisms underlying the ability of single and multiple mutations to globally modulate dynamic properties of the cold-adapted α-amylase, including both local and complex unpredictable distal effects. Our investigation also shows, in agreement with the experimental data, that the conversion of the cold-adapted enzyme in a warm-adapted variant cannot be completely achieved by the introduction of few mutations, also providing the rationale behind these effects. Moreover, pivotal residues, which are likely to mediate the effects induced by the mutations, have been identified from our analyses, as well as a group of suitable candidates for protein engineering. In fact, a subset of residues here identified (as an isoleucine, or networks of mesophilic-like salt bridges in the proximity of the catalytic site should be considered, in experimental studies, to get a more efficient modification of the features of the cold-adapted enzyme.

  12. The Dynamics of Lateral Gene Transfer in Genus Leishmania - A Route for Adaptation and Species Diversification.

    Science.gov (United States)

    Vikeved, Elisabet; Backlund, Anders; Alsmark, Cecilia

    2016-01-01

    The genome of Leishmania major harbours a comparably high proportion of genes of prokaryote origin, acquired by lateral gene transfer (LGT). Some of these are present in closely related trypanosomatids, while some are detected in Leishmania only. We have evaluated the impact and destiny of LGT in genus Leishmania. To study the dynamics and fate of LGTs we have performed phylogenetic, as well as nucleotide and amino acid composition analyses within orthologous groups of LGTs detected in Leishmania. A set of universal trypanosomatid LGTs was added as a reference group. Both groups of LGTs have, to some extent, ameliorated to resemble the recipient genomes. However, while virtually all of the universal trypanosomatid LGTs are distributed and conserved in the entire genus Leishmania, the LGTs uniquely present in genus Leishmania are more prone to gene loss and display faster rates of evolution. Furthermore, a PCR based approach has been employed to ascertain the presence of a set of twenty LGTs uniquely present in genus Leishmania, and three universal trypanosomatid LGTs, in ten additional strains of Leishmania. Evolutionary rates and predicted expression levels of these LGTs have also been estimated. Ten of the twenty LGTs are distributed and conserved in all species investigated, while the remainder have been subjected to modifications, or undergone pseudogenization, degradation or loss in one or more species. LGTs unique to the genus Leishmania have been acquired after the divergence of Leishmania from the other trypanosomatids, and are evolving faster than their recipient genomes. This implies that LGT in genus Leishmania is a continuous and dynamic process contributing to species differentiation and speciation. This study also highlights the importance of carefully evaluating these dynamic genes, e.g. as LGTs have been suggested as potential drug targets.

  13. The Dynamics of Lateral Gene Transfer in Genus Leishmania - A Route for Adaptation and Species Diversification.

    Directory of Open Access Journals (Sweden)

    Elisabet Vikeved

    2016-01-01

    Full Text Available The genome of Leishmania major harbours a comparably high proportion of genes of prokaryote origin, acquired by lateral gene transfer (LGT. Some of these are present in closely related trypanosomatids, while some are detected in Leishmania only. We have evaluated the impact and destiny of LGT in genus Leishmania.To study the dynamics and fate of LGTs we have performed phylogenetic, as well as nucleotide and amino acid composition analyses within orthologous groups of LGTs detected in Leishmania. A set of universal trypanosomatid LGTs was added as a reference group. Both groups of LGTs have, to some extent, ameliorated to resemble the recipient genomes. However, while virtually all of the universal trypanosomatid LGTs are distributed and conserved in the entire genus Leishmania, the LGTs uniquely present in genus Leishmania are more prone to gene loss and display faster rates of evolution. Furthermore, a PCR based approach has been employed to ascertain the presence of a set of twenty LGTs uniquely present in genus Leishmania, and three universal trypanosomatid LGTs, in ten additional strains of Leishmania. Evolutionary rates and predicted expression levels of these LGTs have also been estimated. Ten of the twenty LGTs are distributed and conserved in all species investigated, while the remainder have been subjected to modifications, or undergone pseudogenization, degradation or loss in one or more species.LGTs unique to the genus Leishmania have been acquired after the divergence of Leishmania from the other trypanosomatids, and are evolving faster than their recipient genomes. This implies that LGT in genus Leishmania is a continuous and dynamic process contributing to species differentiation and speciation. This study also highlights the importance of carefully evaluating these dynamic genes, e.g. as LGTs have been suggested as potential drug targets.

  14. The Dynamics of Lateral Gene Transfer in Genus Leishmania - A Route for Adaptation and Species Diversification

    Science.gov (United States)

    Vikeved, Elisabet; Backlund, Anders; Alsmark, Cecilia

    2016-01-01

    Background The genome of Leishmania major harbours a comparably high proportion of genes of prokaryote origin, acquired by lateral gene transfer (LGT). Some of these are present in closely related trypanosomatids, while some are detected in Leishmania only. We have evaluated the impact and destiny of LGT in genus Leishmania. Methodology/Principal Findings To study the dynamics and fate of LGTs we have performed phylogenetic, as well as nucleotide and amino acid composition analyses within orthologous groups of LGTs detected in Leishmania. A set of universal trypanosomatid LGTs was added as a reference group. Both groups of LGTs have, to some extent, ameliorated to resemble the recipient genomes. However, while virtually all of the universal trypanosomatid LGTs are distributed and conserved in the entire genus Leishmania, the LGTs uniquely present in genus Leishmania are more prone to gene loss and display faster rates of evolution. Furthermore, a PCR based approach has been employed to ascertain the presence of a set of twenty LGTs uniquely present in genus Leishmania, and three universal trypanosomatid LGTs, in ten additional strains of Leishmania. Evolutionary rates and predicted expression levels of these LGTs have also been estimated. Ten of the twenty LGTs are distributed and conserved in all species investigated, while the remainder have been subjected to modifications, or undergone pseudogenization, degradation or loss in one or more species. Conclusions/Significance LGTs unique to the genus Leishmania have been acquired after the divergence of Leishmania from the other trypanosomatids, and are evolving faster than their recipient genomes. This implies that LGT in genus Leishmania is a continuous and dynamic process contributing to species differentiation and speciation. This study also highlights the importance of carefully evaluating these dynamic genes, e.g. as LGTs have been suggested as potential drug targets. PMID:26730948

  15. A conceptual framework for addressing complexity and unfolding transition dynamics when developing sustainable adaptation strategies in urban water management.

    Science.gov (United States)

    Fratini, C F; Elle, M; Jensen, M B; Mikkelsen, P S

    2012-01-01

    To achieve a successful and sustainable adaptation to climate change we need to transform the way we think about change. Much water management research has focused on technical innovation with a range of new solutions developed to achieve a 'more sustainable and integrated urban water management cycle'. But Danish municipalities and utility companies are struggling to bring such solutions into practice. 'Green infrastructure', for example, requires the consideration of a larger range of aspects related to the urban context than the traditional urban water system optimization. There is the need for standardized methods and guidelines to organize transdisciplinary processes where different types of knowledge and perspectives are taken into account. On the basis of the macro-meso-micro pattern inspired by complexity science and transition theory, we developed a conceptual framework to organize processes addressing the complexity characterizing urban water management in the context of climate change. In this paper the framework is used to organize a research process aiming at understanding and unfolding urban dynamics for sustainable transition. The final goal is to enable local authorities and utilities to create the basis for managing and catalysing the technical and organizational innovation necessary for a sustainable transition towards climate change adaptation in urban areas.

  16. The smartag framework for the dynamic reconstruction of adaptive web content

    OpenAIRE

    Belk, Mario

    2009-01-01

    Mass customization should be more than just configuring a specific component (hardware or software), but should be seen as the co-design of an entire system, including services, experiences and human satisfaction at the individual as well as at the community level. The main objective of this thesis is to implement and evaluate a dynamic Web-based framework, called smarTag, for achieving mass customization on the Web based on human factors. SmarTag is an easy to use framework that enables any ...

  17. Towards Real-Time Maneuver Detection: Automatic State and Dynamics Estimation with the Adaptive Optimal Control Based Estimator

    Science.gov (United States)

    Lubey, D.; Scheeres, D.

    Tracking objects in Earth orbit is fraught with complications. This is due to the large population of orbiting spacecraft and debris that continues to grow, passive (i.e. no direct communication) and data-sparse observations, and the presence of maneuvers and dynamics mismodeling. Accurate orbit determination in this environment requires an algorithm to capture both a system's state and its state dynamics in order to account for mismodelings. Previous studies by the authors yielded an algorithm called the Optimal Control Based Estimator (OCBE) - an algorithm that simultaneously estimates a system's state and optimal control policies that represent dynamic mismodeling in the system for an arbitrary orbit-observer setup. The stochastic properties of these estimated controls are then used to determine the presence of mismodelings (maneuver detection), as well as characterize and reconstruct the mismodelings. The purpose of this paper is to develop the OCBE into an accurate real-time orbit tracking and maneuver detection algorithm by automating the algorithm and removing its linear assumptions. This results in a nonlinear adaptive estimator. In its original form the OCBE had a parameter called the assumed dynamic uncertainty, which is selected by the user with each new measurement to reflect the level of dynamic mismodeling in the system. This human-in-the-loop approach precludes real-time application to orbit tracking problems due to their complexity. This paper focuses on the Adaptive OCBE, a version of the estimator where the assumed dynamic uncertainty is chosen automatically with each new measurement using maneuver detection results to ensure that state uncertainties are properly adjusted to account for all dynamic mismodelings. The paper also focuses on a nonlinear implementation of the estimator. Originally, the OCBE was derived from a nonlinear cost function then linearized about a nominal trajectory, which is assumed to be ballistic (i.e. the nominal optimal

  18. Dynamic mesh adaptation for front evolution using discontinuous Galerkin based weighted condition number relaxation

    International Nuclear Information System (INIS)

    Greene, Patrick T.; Schofield, Samuel P.; Nourgaliev, Robert

    2017-01-01

    A new mesh smoothing method designed to cluster cells near a dynamically evolving interface is presented. The method is based on weighted condition number mesh relaxation with the weight function computed from a level set representation of the interface. The weight function is expressed as a Taylor series based discontinuous Galerkin projection, which makes the computation of the derivatives of the weight function needed during the condition number optimization process a trivial matter. For cases when a level set is not available, a fast method for generating a low-order level set from discrete cell-centered fields, such as a volume fraction or index function, is provided. Results show that the low-order level set works equally well as the actual level set for mesh smoothing. Meshes generated for a number of interface geometries are presented, including cases with multiple level sets. Lastly, dynamic cases with moving interfaces show the new method is capable of maintaining a desired resolution near the interface with an acceptable number of relaxation iterations per time step, which demonstrates the method's potential to be used as a mesh relaxer for arbitrary Lagrangian Eulerian (ALE) methods.

  19. An adaptive scheme for robot localization and mapping with dynamically configurable inter-beacon range measurements.

    Science.gov (United States)

    Torres-González, Arturo; Martinez-de Dios, Jose Ramiro; Ollero, Anibal

    2014-04-25

    This work is motivated by robot-sensor network cooperation techniques where sensor nodes (beacons) are used as landmarks for range-only (RO) simultaneous localization and mapping (SLAM). This paper presents a RO-SLAM scheme that actuates over the measurement gathering process using mechanisms that dynamically modify the rate and variety of measurements that are integrated in the SLAM filter. It includes a measurement gathering module that can be configured to collect direct robot-beacon and inter-beacon measurements with different inter-beacon depth levels and at different rates. It also includes a supervision module that monitors the SLAM performance and dynamically selects the measurement gathering configuration balancing SLAM accuracy and resource consumption. The proposed scheme has been applied to an extended Kalman filter SLAM with auxiliary particle filters for beacon initialization (PF-EKF SLAM) and validated with experiments performed in the CONET Integrated Testbed. It achieved lower map and robot errors (34% and 14%, respectively) than traditional methods with a lower computational burden (16%) and similar beacon energy consumption.

  20. Dynamic Mesh Adaptation for Front Evolution Using Discontinuous Galerkin Based Weighted Condition Number Mesh Relaxation

    Energy Technology Data Exchange (ETDEWEB)

    Greene, Patrick T. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Schofield, Samuel P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Nourgaliev, Robert [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-06-21

    A new mesh smoothing method designed to cluster mesh cells near a dynamically evolving interface is presented. The method is based on weighted condition number mesh relaxation with the weight function being computed from a level set representation of the interface. The weight function is expressed as a Taylor series based discontinuous Galerkin projection, which makes the computation of the derivatives of the weight function needed during the condition number optimization process a trivial matter. For cases when a level set is not available, a fast method for generating a low-order level set from discrete cell-centered elds, such as a volume fraction or index function, is provided. Results show that the low-order level set works equally well for the weight function as the actual level set. Meshes generated for a number of interface geometries are presented, including cases with multiple level sets. Dynamic cases for moving interfaces are presented to demonstrate the method's potential usefulness to arbitrary Lagrangian Eulerian (ALE) methods.