Clipping in neurocontrol by adaptive dynamic programming.
Fairbank, Michael; Prokhorov, Danil; Alonso, Eduardo
2014-10-01
In adaptive dynamic programming, neurocontrol, and reinforcement learning, the objective is for an agent to learn to choose actions so as to minimize a total cost function. In this paper, we show that when discretized time is used to model the motion of the agent, it can be very important to do clipping on the motion of the agent in the final time step of the trajectory. By clipping, we mean that the final time step of the trajectory is to be truncated such that the agent stops exactly at the first terminal state reached, and no distance further. We demonstrate that when clipping is omitted, learning performance can fail to reach the optimum, and when clipping is done properly, learning performance can improve significantly. The clipping problem we describe affects algorithms that use explicit derivatives of the model functions of the environment to calculate a learning gradient. These include backpropagation through time for control and methods based on dual heuristic programming. However, the clipping problem does not significantly affect methods based on heuristic dynamic programming, temporal differences learning, or policy-gradient learning algorithms.
Robust adaptive dynamic programming and feedback stabilization of nonlinear systems.
Jiang, Yu; Jiang, Zhong-Ping
2014-05-01
This paper studies the robust optimal control design for a class of uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (RADP). The objective is to fill up a gap in the past literature of adaptive dynamic programming (ADP) where dynamic uncertainties or unmodeled dynamics are not addressed. A key strategy is to integrate tools from modern nonlinear control theory, such as the robust redesign and the backstepping techniques as well as the nonlinear small-gain theorem, with the theory of ADP. The proposed RADP methodology can be viewed as an extension of ADP to uncertain nonlinear systems. Practical learning algorithms are developed in this paper, and have been applied to the controller design problems for a jet engine and a one-machine power system. PMID:24808035
Robust adaptive dynamic programming with an application to power systems.
Jiang, Yu; Jiang, Zhong-Ping
2013-07-01
This brief presents a novel framework of robust adaptive dynamic programming (robust-ADP) aimed at computing globally stabilizing and suboptimal control policies in the presence of dynamic uncertainties. A key strategy is to integrate ADP theory with techniques in modern nonlinear control with a unique objective of filling up a gap in the past literature of ADP without taking into account dynamic uncertainties. Neither the system dynamics nor the system order are required to be precisely known. As an illustrative example, the computational algorithm is applied to the controller design of a two-machine power system. PMID:24808528
Adaptive dynamic programming as a theory of sensorimotor control.
Jiang, Yu; Jiang, Zhong-Ping
2014-08-01
Many characteristics of sensorimotor control can be explained by models based on optimization and optimal control theories. However, most of the previous models assume that the central nervous system has access to the precise knowledge of the sensorimotor system and its interacting environment. This viewpoint is difficult to be justified theoretically and has not been convincingly validated by experiments. To address this problem, this paper presents a new computational mechanism for sensorimotor control from a perspective of adaptive dynamic programming (ADP), which shares some features of reinforcement learning. The ADP-based model for sensorimotor control suggests that a command signal for the human movement is derived directly from the real-time sensory data, without the need to identify the system dynamics. An iterative learning scheme based on the proposed ADP theory is developed, along with rigorous convergence analysis. Interestingly, the computational model as advocated here is able to reproduce the motor learning behavior observed in experiments where a divergent force field or velocity-dependent force field was present. In addition, this modeling strategy provides a clear way to perform stability analysis of the overall system. Hence, we conjecture that human sensorimotor systems use an ADP-type mechanism to control movements and to achieve successful adaptation to uncertainties present in the environment.
Adaptive dynamic programming as a theory of sensorimotor control.
Jiang, Yu; Jiang, Zhong-Ping
2014-08-01
Many characteristics of sensorimotor control can be explained by models based on optimization and optimal control theories. However, most of the previous models assume that the central nervous system has access to the precise knowledge of the sensorimotor system and its interacting environment. This viewpoint is difficult to be justified theoretically and has not been convincingly validated by experiments. To address this problem, this paper presents a new computational mechanism for sensorimotor control from a perspective of adaptive dynamic programming (ADP), which shares some features of reinforcement learning. The ADP-based model for sensorimotor control suggests that a command signal for the human movement is derived directly from the real-time sensory data, without the need to identify the system dynamics. An iterative learning scheme based on the proposed ADP theory is developed, along with rigorous convergence analysis. Interestingly, the computational model as advocated here is able to reproduce the motor learning behavior observed in experiments where a divergent force field or velocity-dependent force field was present. In addition, this modeling strategy provides a clear way to perform stability analysis of the overall system. Hence, we conjecture that human sensorimotor systems use an ADP-type mechanism to control movements and to achieve successful adaptation to uncertainties present in the environment. PMID:24962078
Adaption of a corrector module to the IMP dynamics program
NASA Technical Reports Server (NTRS)
1972-01-01
The corrector module of the RAEIOS program and the IMP dynamics computer program were combined to achieve a date-fitting capability with the more general spacecraft dynamics models of the IMP program. The IMP dynamics program presents models of spacecraft dynamics for satellites with long, flexible booms. The properties of the corrector are discussed and a description is presented of the performance criteria and search logic for parameter estimation. A description is also given of the modifications made to add the corrector to the IMP program. This includes subroutine descriptions, common definitions, definition of input, and a description of output.
Recursive dynamic programming for adaptive sequence and structure alignment
Thiele, R.; Zimmer, R.; Lengauer, T.
1995-12-31
We propose a new alignment procedure that is capable of aligning protein sequences and structures in a unified manner. Recursive dynamic programming (RDP) is a hierarchical method which, on each level of the hierarchy, identifies locally optimal solutions and assembles them into partial alignments of sequences and/or structures. In contrast to classical dynamic programming, RDP can also handle alignment problems that use objective functions not obeying the principle of prefix optimality, e.g. scoring schemes derived from energy potentials of mean force. For such alignment problems, RDP aims at computing solutions that are near-optimal with respect to the involved cost function and biologically meaningful at the same time. Towards this goal, RDP maintains a dynamic balance between different factors governing alignment fitness such as evolutionary relationships and structural preferences. As in the RDP method gaps are not scored explicitly, the problematic assignment of gap cost parameters is circumvented. In order to evaluate the RDP approach we analyse whether known and accepted multiple alignments based on structural information can be reproduced with the RDP method.
Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong
2015-04-01
Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro-dynamic programming (NDP). Initially, Karhunen-Loève decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite-dimensional slow subsystem of ordinary differential equations that accurately describes the dominant dynamics of the PDE system. Subsequently, the optimal control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton-Jacobi-Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive optimal control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed-loop PDE system with the adaptive optimal control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion-convection-reaction process and applied to a temperature cooling fin of high-speed aerospace vehicle, and the achieved results show its effectiveness.
Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong
2015-04-01
Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro-dynamic programming (NDP). Initially, Karhunen-Loève decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite-dimensional slow subsystem of ordinary differential equations that accurately describes the dominant dynamics of the PDE system. Subsequently, the optimal control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton-Jacobi-Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive optimal control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed-loop PDE system with the adaptive optimal control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion-convection-reaction process and applied to a temperature cooling fin of high-speed aerospace vehicle, and the achieved results show its effectiveness. PMID:25794375
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.
NASA Astrophysics Data System (ADS)
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.
Zhong, Xiangnan; He, Haibo; Zhang, Huaguang; Wang, Zhanshan
2014-12-01
In this paper, we develop and analyze an optimal control method for a class of discrete-time nonlinear Markov jump systems (MJSs) with unknown system dynamics. Specifically, an identifier is established for the unknown systems to approximate system states, and an optimal control approach for nonlinear MJSs is developed to solve the Hamilton-Jacobi-Bellman equation based on the adaptive dynamic programming technique. We also develop detailed stability analysis of the control approach, including the convergence of the performance index function for nonlinear MJSs and the existence of the corresponding admissible control. Neural network techniques are used to approximate the proposed performance index function and the control law. To demonstrate the effectiveness of our approach, three simulation studies, one linear case, one nonlinear case, and one single link robot arm case, are used to validate the performance of the proposed optimal control method.
Zhong, Xiangnan; He, Haibo; Zhang, Huaguang; Wang, Zhanshan
2014-12-01
In this paper, we develop and analyze an optimal control method for a class of discrete-time nonlinear Markov jump systems (MJSs) with unknown system dynamics. Specifically, an identifier is established for the unknown systems to approximate system states, and an optimal control approach for nonlinear MJSs is developed to solve the Hamilton-Jacobi-Bellman equation based on the adaptive dynamic programming technique. We also develop detailed stability analysis of the control approach, including the convergence of the performance index function for nonlinear MJSs and the existence of the corresponding admissible control. Neural network techniques are used to approximate the proposed performance index function and the control law. To demonstrate the effectiveness of our approach, three simulation studies, one linear case, one nonlinear case, and one single link robot arm case, are used to validate the performance of the proposed optimal control method. PMID:25420238
Liu, Derong; Li, Hongliang; Wang, Ding
2015-06-01
In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted optimal control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms.
Finite-approximation-error-based discrete-time iterative adaptive dynamic programming.
Wei, Qinglai; Wang, Fei-Yue; Liu, Derong; Yang, Xiong
2014-12-01
In this paper, a new iterative adaptive dynamic programming (ADP) algorithm is developed to solve optimal control problems for infinite horizon discrete-time nonlinear systems with finite approximation errors. First, a new generalized value iteration algorithm of ADP is developed to make the iterative performance index function converge to the solution of the Hamilton-Jacobi-Bellman equation. The generalized value iteration algorithm permits an arbitrary positive semi-definite function to initialize it, which overcomes the disadvantage of traditional value iteration algorithms. When the iterative control law and iterative performance index function in each iteration cannot accurately be obtained, for the first time a new "design method of the convergence criteria" for the finite-approximation-error-based generalized value iteration algorithm is established. A suitable approximation error can be designed adaptively to make the iterative performance index function converge to a finite neighborhood of the optimal performance index function. Neural networks are used to implement the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the developed method. PMID:25265640
Fair Energy Scheduling for Vehicle-to-Grid Networks Using Adaptive Dynamic Programming.
Xie, Shengli; Zhong, Weifeng; Xie, Kan; Yu, Rong; Zhang, Yan
2016-08-01
Research on the smart grid is being given enormous supports worldwide due to its great significance in solving environmental and energy crises. Electric vehicles (EVs), which are powered by clean energy, are adopted increasingly year by year. It is predictable that the huge charge load caused by high EV penetration will have a considerable impact on the reliability of the smart grid. Therefore, fair energy scheduling for EV charge and discharge is proposed in this paper. By using the vehicle-to-grid technology, the scheduler controls the electricity loads of EVs considering fairness in the residential distribution network. We propose contribution-based fairness, in which EVs with high contributions have high priorities to obtain charge energy. The contribution value is defined by both the charge/discharge energy and the timing of the action. EVs can achieve higher contribution values when discharging during the load peak hours. However, charging during this time will decrease the contribution values seriously. We formulate the fair energy scheduling problem as an infinite-horizon Markov decision process. The methodology of adaptive dynamic programming is employed to maximize the long-term fairness by processing online network training. The numerical results illustrate that the proposed EV energy scheduling is able to mitigate and flatten the peak load in the distribution network. Furthermore, contribution-based fairness achieves a fast recovery of EV batteries that have deeply discharged and guarantee fairness in the full charge time of all EVs.
Fair Energy Scheduling for Vehicle-to-Grid Networks Using Adaptive Dynamic Programming.
Xie, Shengli; Zhong, Weifeng; Xie, Kan; Yu, Rong; Zhang, Yan
2016-08-01
Research on the smart grid is being given enormous supports worldwide due to its great significance in solving environmental and energy crises. Electric vehicles (EVs), which are powered by clean energy, are adopted increasingly year by year. It is predictable that the huge charge load caused by high EV penetration will have a considerable impact on the reliability of the smart grid. Therefore, fair energy scheduling for EV charge and discharge is proposed in this paper. By using the vehicle-to-grid technology, the scheduler controls the electricity loads of EVs considering fairness in the residential distribution network. We propose contribution-based fairness, in which EVs with high contributions have high priorities to obtain charge energy. The contribution value is defined by both the charge/discharge energy and the timing of the action. EVs can achieve higher contribution values when discharging during the load peak hours. However, charging during this time will decrease the contribution values seriously. We formulate the fair energy scheduling problem as an infinite-horizon Markov decision process. The methodology of adaptive dynamic programming is employed to maximize the long-term fairness by processing online network training. The numerical results illustrate that the proposed EV energy scheduling is able to mitigate and flatten the peak load in the distribution network. Furthermore, contribution-based fairness achieves a fast recovery of EV batteries that have deeply discharged and guarantee fairness in the full charge time of all EVs. PMID:26930694
Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems.
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.
Policy iteration adaptive dynamic programming algorithm for discrete-time nonlinear systems.
Liu, Derong; Wei, Qinglai
2014-03-01
This paper is concerned with a new discrete-time policy iteration adaptive dynamic programming (ADP) method for solving the infinite horizon optimal control problem of nonlinear systems. The idea is to use an iterative ADP technique to obtain the iterative control law, which optimizes the iterative performance index function. The main contribution of this paper is to analyze the convergence and stability properties of policy iteration method for discrete-time nonlinear systems for the first time. It shows that the iterative performance index function is nonincreasingly convergent to the optimal solution of the Hamilton-Jacobi-Bellman equation. It is also proven that any of the iterative control laws can stabilize the nonlinear systems. Neural networks are used to approximate the performance index function and compute the optimal control law, respectively, for facilitating the implementation of the iterative ADP algorithm, where the convergence of the weight matrices is analyzed. Finally, the numerical results and analysis are presented to illustrate the performance of the developed method. PMID:24807455
Water Resource Adaptation Program
The Water Resource Adaptation Program (WRAP) contributes to the U.S. Environmental Protection Agency’s (U.S. EPA) efforts to provide water resource managers and decision makers with the tools needed to adapt water resources to demographic and economic development, and future clim...
Karemere, Hermès; Ribesse, Nathalie; Kahindo, Jean-Bosco; Macq, Jean
2015-01-01
Introduction In many African countries, first referral hospitals received little attention from development agencies until recently. We report the evolution of two of them in an unstable region like Eastern Democratic Republic of Congo when receiving the support from development aid program. Specifically, we aimed at studying how actors’ network and institutional framework evolved over time and what could matter the most when looking at their performance in such an environment. Methods We performed two cases studies between 2006 and 2010. We used multiple sources of data: reports to document events; health information system for hospital services production, and “key-informants” interviews to interpret the relation between interventions and services production. Our analysis was inspired from complex adaptive system theory. It started from the analysis of events implementation, to explore interaction process between the main agents in each hospital, and the consequence it could have on hospital health services production. This led to the development of new theoretical propositions. Results Two events implemented in the frame of the development aid program were identified by most of the key-informants interviewed as having the greatest impact on hospital performance: the development of a hospital plan and the performance based financing. They resulted in contrasting interaction process between the main agents between the two hospitals. Two groups of services production were reviewed: consultation at outpatient department and admissions, and surgery. The evolution of both groups of services production were different between both hospitals. Conclusion By studying two first referral hospitals through the lens of a Complex Adaptive System, their performance in a context of development aid takes a different meaning. Success is not only measured through increased hospital production but through meaningful process of hospital agents’” network adaptation. Expected
Zhang, Jilie; Zhang, Huaguang; Liu, Zhenwei; Wang, Yingchun
2015-07-01
In this paper, we consider the problem of developing a controller for continuous-time nonlinear systems where the equations governing the system are unknown. Using the measurements, two new online schemes are presented for synthesizing a controller without building or assuming a model for the system, by two new implementation schemes based on adaptive dynamic programming (ADP). To circumvent the requirement of the prior knowledge for systems, a precompensator is introduced to construct an augmented system. The corresponding Hamilton-Jacobi-Bellman (HJB) equation is solved by adaptive dynamic programming, which consists of the least-squared technique, neural network approximator and policy iteration (PI) algorithm. The main idea of our method is to sample the information of state, state derivative and input to update the weighs of neural network by least-squared technique. The update process is implemented in the framework of PI. In this paper, two new implementation schemes are presented. Finally, several examples are given to illustrate the effectiveness of our schemes.
Zhang, Jilie; Zhang, Huaguang; Liu, Zhenwei; Wang, Yingchun
2015-07-01
In this paper, we consider the problem of developing a controller for continuous-time nonlinear systems where the equations governing the system are unknown. Using the measurements, two new online schemes are presented for synthesizing a controller without building or assuming a model for the system, by two new implementation schemes based on adaptive dynamic programming (ADP). To circumvent the requirement of the prior knowledge for systems, a precompensator is introduced to construct an augmented system. The corresponding Hamilton-Jacobi-Bellman (HJB) equation is solved by adaptive dynamic programming, which consists of the least-squared technique, neural network approximator and policy iteration (PI) algorithm. The main idea of our method is to sample the information of state, state derivative and input to update the weighs of neural network by least-squared technique. The update process is implemented in the framework of PI. In this paper, two new implementation schemes are presented. Finally, several examples are given to illustrate the effectiveness of our schemes. PMID:25704057
Adaptive Dynamic Bayesian Networks
Ng, B M
2007-10-26
A discrete-time Markov process can be compactly modeled as a dynamic Bayesian network (DBN)--a graphical model with nodes representing random variables and directed edges indicating causality between variables. Each node has a probability distribution, conditional on the variables represented by the parent nodes. A DBN's graphical structure encodes fixed conditional dependencies between variables. But in real-world systems, conditional dependencies between variables may be unknown a priori or may vary over time. Model errors can result if the DBN fails to capture all possible interactions between variables. Thus, we explore the representational framework of adaptive DBNs, whose structure and parameters can change from one time step to the next: a distribution's parameters and its set of conditional variables are dynamic. This work builds on recent work in nonparametric Bayesian modeling, such as hierarchical Dirichlet processes, infinite-state hidden Markov networks and structured priors for Bayes net learning. In this paper, we will explain the motivation for our interest in adaptive DBNs, show how popular nonparametric methods are combined to formulate the foundations for adaptive DBNs, and present preliminary results.
Wang, Fei-Yue; Jin, Ning; Liu, Derong; Wei, Qinglai
2011-01-01
In this paper, we study the finite-horizon optimal control problem for discrete-time nonlinear systems using the adaptive dynamic programming (ADP) approach. The idea is to use an iterative ADP algorithm to obtain the optimal control law which makes the performance index function close to the greatest lower bound of all performance indices within an ε-error bound. The optimal number of control steps can also be obtained by the proposed ADP algorithms. A convergence analysis of the proposed ADP algorithms in terms of performance index function and control policy is made. In order to facilitate the implementation of the iterative ADP algorithms, neural networks are used for approximating the performance index function, computing the optimal control policy, and modeling the nonlinear system. Finally, two simulation examples are employed to illustrate the applicability of the proposed method. PMID:20876014
Yu, Rong; Zhong, Weifeng; Xie, Shengli; Zhang, Yan; Zhang, Yun
2016-02-01
As the next-generation power grid, smart grid will be integrated with a variety of novel communication technologies to support the explosive data traffic and the diverse requirements of quality of service (QoS). Cognitive radio (CR), which has the favorable ability to improve the spectrum utilization, provides an efficient and reliable solution for smart grid communications networks. In this paper, we study the QoS differential scheduling problem in the CR-based smart grid communications networks. The scheduler is responsible for managing the spectrum resources and arranging the data transmissions of smart grid users (SGUs). To guarantee the differential QoS, the SGUs are assigned to have different priorities according to their roles and their current situations in the smart grid. Based on the QoS-aware priority policy, the scheduler adjusts the channels allocation to minimize the transmission delay of SGUs. The entire transmission scheduling problem is formulated as a semi-Markov decision process and solved by the methodology of adaptive dynamic programming. A heuristic dynamic programming (HDP) architecture is established for the scheduling problem. By the online network training, the HDP can learn from the activities of primary users and SGUs, and adjust the scheduling decision to achieve the purpose of transmission delay minimization. Simulation results illustrate that the proposed priority policy ensures the low transmission delay of high priority SGUs. In addition, the emergency data transmission delay is also reduced to a significantly low level, guaranteeing the differential QoS in smart grid.
Yu, Rong; Zhong, Weifeng; Xie, Shengli; Zhang, Yan; Zhang, Yun
2016-02-01
As the next-generation power grid, smart grid will be integrated with a variety of novel communication technologies to support the explosive data traffic and the diverse requirements of quality of service (QoS). Cognitive radio (CR), which has the favorable ability to improve the spectrum utilization, provides an efficient and reliable solution for smart grid communications networks. In this paper, we study the QoS differential scheduling problem in the CR-based smart grid communications networks. The scheduler is responsible for managing the spectrum resources and arranging the data transmissions of smart grid users (SGUs). To guarantee the differential QoS, the SGUs are assigned to have different priorities according to their roles and their current situations in the smart grid. Based on the QoS-aware priority policy, the scheduler adjusts the channels allocation to minimize the transmission delay of SGUs. The entire transmission scheduling problem is formulated as a semi-Markov decision process and solved by the methodology of adaptive dynamic programming. A heuristic dynamic programming (HDP) architecture is established for the scheduling problem. By the online network training, the HDP can learn from the activities of primary users and SGUs, and adjust the scheduling decision to achieve the purpose of transmission delay minimization. Simulation results illustrate that the proposed priority policy ensures the low transmission delay of high priority SGUs. In addition, the emergency data transmission delay is also reduced to a significantly low level, guaranteeing the differential QoS in smart grid. PMID:25910254
Cultural Adaptation in Outdoor Programming
ERIC Educational Resources Information Center
Fabrizio, Sheila M.; Neill, James
2005-01-01
Outdoor programs often intentionally provide a different culture and the challenge of working out how to adapt. Failure to adapt, however, can cause symptoms of culture shock, including homesickness, negative personal behavior, and interpersonal conflict. This article links cross-cultural and outdoor programming literature and provides case…
Adaptive critics for dynamic optimization.
Kulkarni, Raghavendra V; Venayagamoorthy, Ganesh Kumar
2010-06-01
A novel action-dependent adaptive critic design (ACD) is developed for dynamic optimization. The proposed combination of a particle swarm optimization-based actor and a neural network critic is demonstrated through dynamic sleep scheduling of wireless sensor motes for wildlife monitoring. The objective of the sleep scheduler is to dynamically adapt the sleep duration to node's battery capacity and movement pattern of animals in its environment in order to obtain snapshots of the animal on its trajectory uniformly. Simulation results show that the sleep time of the node determined by the actor critic yields superior quality of sensory data acquisition and enhanced node longevity. PMID:20223635
Parallel Programming Strategies for Irregular Adaptive Applications
NASA Technical Reports Server (NTRS)
Biswas, Rupak; Biegel, Bryan (Technical Monitor)
2001-01-01
Achieving scalable performance for dynamic irregular applications is eminently challenging. Traditional message-passing approaches have been making steady progress towards this goal; however, they suffer from complex implementation requirements. The use of a global address space greatly simplifies the programming task, but can degrade the performance for such computations. In this work, we examine two typical irregular adaptive applications, Dynamic Remeshing and N-Body, under competing programming methodologies and across various parallel architectures. The Dynamic Remeshing application simulates flow over an airfoil, and refines localized regions of the underlying unstructured mesh. The N-Body experiment models two neighboring Plummer galaxies that are about to undergo a merger. Both problems demonstrate dramatic changes in processor workloads and interprocessor communication with time; thus, dynamic load balancing is a required component.
Criticality of Adaptive Control Dynamics
NASA Astrophysics Data System (ADS)
Patzelt, Felix; Pawelzik, Klaus
2011-12-01
We show, that stabilization of a dynamical system can annihilate observable information about its structure. This mechanism induces critical points as attractors in locally adaptive control. It also reveals, that previously reported criticality in simple controllers is caused by adaptation and not by other controller details. We apply these results to a real-system example: human balancing behavior. A model of predictive adaptive closed-loop control subject to some realistic constraints is introduced and shown to reproduce experimental observations in unprecedented detail. Our results suggests, that observed error distributions in between the Lévy and Gaussian regimes may reflect a nearly optimal compromise between the elimination of random local trends and rare large errors.
Adaptive Dynamic Event Tree in RAVEN code
Alfonsi, Andrea; Rabiti, Cristian; Mandelli, Diego; Cogliati, Joshua Joseph; Kinoshita, Robert Arthur
2014-11-01
RAVEN is a software tool that is focused on performing statistical analysis of stochastic dynamic systems. RAVEN has been designed in a high modular and pluggable way in order to enable easy integration of different programming languages (i.e., C++, Python) and coupling with other applications (system codes). Among the several capabilities currently present in RAVEN, there are five different sampling strategies: Monte Carlo, Latin Hyper Cube, Grid, Adaptive and Dynamic Event Tree (DET) sampling methodologies. The scope of this paper is to present a new sampling approach, currently under definition and implementation: an evolution of the DET me
Adapted Aquatics Programming: A Professional Guide.
ERIC Educational Resources Information Center
Lepore, Monica; Gayle, G. William; Stevens, Shawn F.
This book is designed to help aquatic instructors in meeting the needs of individuals with disabilities in general or adapted aquatics programs. Part 1, "Foundations of Adapted Aquatics," introduces various philosophies and issues having to do with initiating adapted aquatics programs. Chapters address the benefits of aquatic activity, models for…
Adaptive EAGLE dynamic solution adaptation and grid quality enhancement
NASA Technical Reports Server (NTRS)
Luong, Phu Vinh; Thompson, J. F.; Gatlin, B.; Mastin, C. W.; Kim, H. J.
1992-01-01
In the effort described here, the elliptic grid generation procedure in the EAGLE grid code was separated from the main code into a subroutine, and a new subroutine which evaluates several grid quality measures at each grid point was added. The elliptic grid routine can now be called, either by a computational fluid dynamics (CFD) code to generate a new adaptive grid based on flow variables and quality measures through multiple adaptation, or by the EAGLE main code to generate a grid based on quality measure variables through static adaptation. Arrays of flow variables can be read into the EAGLE grid code for use in static adaptation as well. These major changes in the EAGLE adaptive grid system make it easier to convert any CFD code that operates on a block-structured grid (or single-block grid) into a multiple adaptive code.
Dynamic optimization and adaptive controller design
NASA Astrophysics Data System (ADS)
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.
Multithreaded Model for Dynamic Load Balancing Parallel Adaptive PDE Computations
NASA Technical Reports Server (NTRS)
Chrisochoides, Nikos
1995-01-01
We present a multithreaded model for the dynamic load-balancing of numerical, adaptive computations required for the solution of Partial Differential Equations (PDE's) on multiprocessors. Multithreading is used as a means of exploring concurrency in the processor level in order to tolerate synchronization costs inherent to traditional (non-threaded) parallel adaptive PDE solvers. Our preliminary analysis for parallel, adaptive PDE solvers indicates that multithreading can be used an a mechanism to mask overheads required for the dynamic balancing of processor workloads with computations required for the actual numerical solution of the PDE's. Also, multithreading can simplify the implementation of dynamic load-balancing algorithms, a task that is very difficult for traditional data parallel adaptive PDE computations. Unfortunately, multithreading does not always simplify program complexity, often makes code re-usability not an easy task, and increases software complexity.
Dynamic adaptivity of "smart" piezoelectric structures
NASA Astrophysics Data System (ADS)
Tzou, Horn-Sen; Zhong, Jianping P.
1990-10-01
Active smart" space and machine structures with adaptive dynamic characteristics have long been interested in a variety of high-performance systems, e.g., flexible robots, flexible space structures, "smart" machines, etc. In this paper, an active adaptive structure made of piezoelectric materials is proposed and evaluated. The structural adaptivity is achieved by a voltage feedback (open or closed loops) utilizing the converse piezoelectric effect. A mathematical model is proposed and the electrodynamic equations of motion and the generalized boundary conditions of a generic piezoelectric shell subjected to mechanical and electrical excitations are derived using Hamilton's principle and the linear piezoelectric theory. The dynamic adaptivity of the structure is introduced using a feedback control system. The theory is demonstrated in a case study in which the structural adaptivity (natural frequency) is investigated.
Wittler, R.; McBain, S.; Stalnaker, C.; Bizier, P.; DeBarry, P.
2003-01-01
Two adaptive management programs, the Glen Canyon Dam Adaptive Management Program (GCDAMP) and the Trinity River Restoration Program (TRRP) are examined. In both cases, the focus is on managing the aquatic and riparian systems downstream of a large dam and water supply project. The status of the two programs, lessons learned by the program managers and the Adaptive Environmental Assessment and Management (AEAM) evolution of the TRRP are discussed. The Trinity River illustrates some of the scientific uncertainities that a program faces and the ways the program evolves from concept through implementation.
ERIC Educational Resources Information Center
Shih, Ching-Hsiang; Shih, Ching-Tien; Wu, Hsiao-Ling
2010-01-01
The latest research adopted software technology to redesign the mouse driver, and turned a mouse into a useful pointing assistive device for people with multiple disabilities who cannot easily or possibly use a standard mouse, to improve their pointing performance through a new operation method, Extended Dynamic Pointing Assistive Program (EDPAP),…
Earth and ocean dynamics program
NASA Technical Reports Server (NTRS)
Vonbun, F. O.
1976-01-01
The objectives and requirements of the Earth and Ocean Dynamics Programs are outlined along with major goals and experiments. Spaceborne as well as ground systems needed to accomplish program goals are listed and discussed along with program accomplishments.
Syntactic adaptability of programming languages
Gusev, V.V.
1994-11-01
Development of programming languages has to contend with a variety of conflicting criteria. Moreover, as in any other creative field, it is not always possible to arrive at a clear formulation of these criteria. Nevertheless, one of the main criteria is problem orientation, be it numerical algorithms, database management, simulation of hydraulic systems, or other applications. Idealizing, we can say that the programming language is based on a model of the application domain. This model may vary in its scope, covering some aspects of the application domain and ignoring others. Thus, for one application domain we may have a whole spectrum of models and correspondingly a whole spectrum of languages. Some are special-purpose languages designed for a specific class of problems, others are more general. Both special-purpose and general-purpose languages have definite advantages and find their own clientele, who are willing to ignore their shortcomings.
Automated adaptive inference of phenomenological dynamical models
Daniels, Bryan C.; Nemenman, Ilya
2015-01-01
Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved. PMID:26293508
Global view of bionetwork dynamics: adaptive landscape.
Ao, Ping
2009-02-01
Based on recent work, I will give a nontechnical brief review of a powerful quantitative concept in biology, adaptive landscape, initially proposed by S. Wright over 70 years ago, reintroduced by one of the founders of molecular biology and by others in different biological contexts, but apparently forgotten by modern biologists for many years. Nevertheless, this concept finds an increasingly important role in the development of systems biology and bionetwork dynamics modeling, from phage lambda genetic switch to endogenous network for cancer genesis and progression. It is an ideal quantification to describe the robustness and stability of bionetworks. Here, I will first introduce five landmark proposals in biology on this concept, to demonstrate an important common thread in theoretical biology. Then I will discuss a few recent results, focusing on the studies showing theoretical consistency of adaptive landscape. From the perspective of a working scientist and of what is needed logically for a dynamical theory when confronting empirical data, the adaptive landscape is useful both metaphorically and quantitatively, and has captured an essential aspect of biological dynamical processes. Though at the theoretical level the adaptive landscape must exist and it can be used across hierarchical boundaries in biology, many associated issues are indeed vague in their initial formulations and their quantitative realizations are not easy, and are good research topics for quantitative biologists. I will discuss three types of open problems associated with the adaptive landscape in a broader perspective.
Adaptive optics program at TMT
NASA Astrophysics Data System (ADS)
Boyer, C.; Adkins, Sean; Andersen, David R.; Atwood, Jenny; Bo, Yong; Byrnes, Peter; Caputa, Kris; Cavaco, Jeff; Ellerbroek, Brent; Gilles, Luc; Gregory, James; Herriot, Glen; Hickson, Paul; Ljusic, Zoran; Manter, Darren; Marois, Christian; Otárola, Angel; Pagès, Hubert; Schoeck, Matthias; Sinquin, Jean-Christophe; Smith, Malcolm; Spano, Paolo; Szeto, Kei; Tang, Jinlong; Travouillon, Tony; Véran, Jean-Pierre; Wang, Lianqi; Wei, Kai
2014-07-01
The TMT first light Adaptive Optics (AO) facility consists of the Narrow Field Infra-Red AO System (NFIRAOS) and the associated Laser Guide Star Facility (LGSF). NFIRAOS is a 60 × 60 laser guide star (LGS) multi-conjugate AO (MCAO) system, which provides uniform, diffraction-limited performance in the J, H, and K bands over 17-30 arc sec diameter fields with 50 per cent sky coverage at the galactic pole, as required to support the TMT science cases. NFIRAOS includes two deformable mirrors, six laser guide star wavefront sensors, and three low-order, infrared, natural guide star wavefront sensors within each client instrument. The first light LGSF system includes six sodium lasers required to generate the NFIRAOS laser guide stars. In this paper, we will provide an update on the progress in designing, modeling and validating the TMT first light AO systems and their components over the last two years. This will include pre-final design and prototyping activities for NFIRAOS, preliminary design and prototyping activities for the LGSF, design and prototyping for the deformable mirrors, fabrication and tests for the visible detectors, benchmarking and comparison of different algorithms and processing architecture for the Real Time Controller (RTC) and development and tests of prototype candidate lasers. Comprehensive and detailed AO modeling is continuing to support the design and development of the first light AO facility. Main modeling topics studied during the last two years include further studies in the area of wavefront error budget, sky coverage, high precision astrometry for the galactic center and other observations, high contrast imaging with NFIRAOS and its first light instruments, Point Spread Function (PSF) reconstruction for LGS MCAO, LGS photon return and sophisticated low order mode temporal filtering.
Adaptive wavelet simulation of global ocean dynamics
NASA Astrophysics Data System (ADS)
Kevlahan, N. K.-R.; Dubos, T.; Aechtner, M.
2015-07-01
In order to easily enforce solid-wall boundary conditions in the presence of complex coastlines, we propose a new mass and energy conserving Brinkman penalization for the rotating shallow water equations. This penalization does not lead to higher wave speeds in the solid region. The error estimates for the penalization are derived analytically and verified numerically for linearized one dimensional equations. The penalization is implemented in a conservative dynamically adaptive wavelet method for the rotating shallow water equations on the sphere with bathymetry and coastline data from NOAA's ETOPO1 database. This code could form the dynamical core for a future global ocean model. The potential of the dynamically adaptive ocean model is illustrated by using it to simulate the 2004 Indonesian tsunami and wind-driven gyres.
Implementing an Adaptive Testing Program in an Instructional Programs Environment.
ERIC Educational Resources Information Center
McKinley, Robert L.; Reckase, Mark D.
The purpose of this paper is to identify and discuss some of the problems presented by the use of computerized adaptive testing (CAT) in an instructional programs environment versus large scale testing applications, and to describe an actual implementation of CAT in an instructional programs setting. This particular application is in the…
Dynamic Load Balancing for Adaptive Unstructured Grids
NASA Technical Reports Server (NTRS)
Biswas, Rupak; Saini, Subhash (Technical Monitor)
1998-01-01
Dynamic mesh adaptation on unstructured grids is a powerful tool for computing unsteady three-dimensional problems that require grid modifications to efficiently resolve solution features. By locally refining and coarsening the mesh to capture phenomena of interest, such procedures make standard computational methods more cost effective. Highly refined meshes are required to accurately capture shock waves, contact discontinuities, vortices, and shear layers in fluid flow problems. Adaptive meshes have also proved to be useful in several other areas of computational science and engineering like computer vision and graphics, semiconductor device modeling, and structural mechanics. Local mesh adaptation provides the opportunity to obtain solutions that are comparable to those obtained on globally-refined grids but at a much lower cost. Additional information is contained in the original extended abstract.
Advanced solar dynamic technology program
NASA Technical Reports Server (NTRS)
Calogeras, James
1990-01-01
Viewgraphs and discussion on Advanced Solar Dynamic Technology Program are presented. Topics covered include: advanced solar dynamic technology program; advanced concentrators; advanced heat receivers; power conversion systems; dished all metal honeycomb sandwich panels; Stirling cavity heat pipe receiver; Brayton solar receiver; and thermal energy storage technology.
Target tracking with dynamically adaptive correlation
NASA Astrophysics Data System (ADS)
Gaxiola, Leopoldo N.; Diaz-Ramirez, Victor H.; Tapia, Juan J.; García-Martínez, Pascuala
2016-04-01
A reliable algorithm for target tracking based on dynamically adaptive correlation filtering is presented. The algorithm is capable of tracking with high accuracy the location of a target in an input video sequence without using an offline training process. The target is selected at the beginning of the algorithm. Afterwards, a composite correlation filter optimized for distortion tolerant pattern recognition is designed to recognize the target in the next frame. The filter is dynamically adapted to each frame using information of current and past scene observations. Results obtained with the proposed algorithm in synthetic and real-life video sequences, are analyzed and compared with those obtained with recent state-of-the-art tracking algorithms in terms of objective metrics.
Adaptive-network models of collective dynamics
NASA Astrophysics Data System (ADS)
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
Synaptic dynamics: linear model and adaptation algorithm.
Yousefi, Ali; Dibazar, Alireza A; Berger, Theodore W
2014-08-01
In this research, temporal processing in brain neural circuitries is addressed by a dynamic model of synaptic connections in which the synapse model accounts for both pre- and post-synaptic processes determining its temporal dynamics and strength. Neurons, which are excited by the post-synaptic potentials of hundred of the synapses, build the computational engine capable of processing dynamic neural stimuli. Temporal dynamics in neural models with dynamic synapses will be analyzed, and learning algorithms for synaptic adaptation of neural networks with hundreds of synaptic connections are proposed. The paper starts by introducing a linear approximate model for the temporal dynamics of synaptic transmission. The proposed linear model substantially simplifies the analysis and training of spiking neural networks. Furthermore, it is capable of replicating the synaptic response of the non-linear facilitation-depression model with an accuracy better than 92.5%. In the second part of the paper, a supervised spike-in-spike-out learning rule for synaptic adaptation in dynamic synapse neural networks (DSNN) is proposed. The proposed learning rule is a biologically plausible process, and it is capable of simultaneously adjusting both pre- and post-synaptic components of individual synapses. The last section of the paper starts with presenting the rigorous analysis of the learning algorithm in a system identification task with hundreds of synaptic connections which confirms the learning algorithm's accuracy, repeatability and scalability. The DSNN is utilized to predict the spiking activity of cortical neurons and pattern recognition tasks. The DSNN model is demonstrated to be a generative model capable of producing different cortical neuron spiking patterns and CA1 Pyramidal neurons recordings. A single-layer DSNN classifier on a benchmark pattern recognition task outperforms a 2-Layer Neural Network and GMM classifiers while having fewer numbers of free parameters and
Cardiac fluid dynamics anticipates heart adaptation.
Pedrizzetti, Gianni; Martiniello, Alfonso R; Bianchi, Valter; D'Onofrio, Antonio; Caso, Pio; Tonti, Giovanni
2015-01-21
Hemodynamic forces represent an epigenetic factor during heart development and are supposed to influence the pathology of the grown heart. Cardiac blood motion is characterized by a vortical dynamics, and it is common belief that the cardiac vortex has a role in disease progressions or regression. Here we provide a preliminary demonstration about the relevance of maladaptive intra-cardiac vortex dynamics in the geometrical adaptation of the dysfunctional heart. We employed an in vivo model of patients who present a stable normal heart function in virtue of the cardiac resynchronization therapy (CRT, bi-ventricular pace-maker) and who are expected to develop left ventricle remodeling if pace-maker was switched off. Intra-ventricular fluid dynamics is analyzed by echocardiography (Echo-PIV). Under normal conditions, the flow presents a longitudinal alignment of the intraventricular hemodynamic forces. When pacing is temporarily switched off, flow forces develop a misalignment hammering onto lateral walls, despite no other electro-mechanical change is noticed. Hemodynamic forces result to be the first event that evokes a physiological activity anticipating cardiac changes and could help in the prediction of longer term heart adaptations.
Emerging hierarchies in dynamically adapting webs
NASA Astrophysics Data System (ADS)
Katifori, Eleni; Graewer, Johannes; Magnasco, Marcelo; Modes, Carl
Transport networks play a key role across four realms of eukaryotic life: slime molds, fungi, plants, and animals. In addition to the developmental algorithms that build them, many also employ adaptive strategies to respond to stimuli, damage, and other environmental changes. We model these adapting network architectures using a generic dynamical system on weighted graphs and find in simulation that these networks ultimately develop a hierarchical organization of the final weighted architecture accompanied by the formation of a system-spanning backbone. We quantify the hierarchical organization of the networks by developing an algorithm that decomposes the architecture to multiple scales and analyzes how the organization in each scale relates to that of the scale above and below it. The methodologies developed in this work are applicable to a wide range of systems including the slime mold physarum polycephalum, human microvasculature, and force chains in granular media.
Adaptation dynamics in densely clustered chemoreceptors.
Pontius, William; Sneddon, Michael W; Emonet, Thierry
2013-01-01
In many sensory systems, transmembrane receptors are spatially organized in large clusters. Such arrangement may facilitate signal amplification and the integration of multiple stimuli. However, this organization likely also affects the kinetics of signaling since the cytoplasmic enzymes that modulate the activity of the receptors must localize to the cluster prior to receptor modification. Here we examine how these spatial considerations shape signaling dynamics at rest and in response to stimuli. As a model system, we use the chemotaxis pathway of Escherichia coli, a canonical system for the study of how organisms sense, respond, and adapt to environmental stimuli. In bacterial chemotaxis, adaptation is mediated by two enzymes that localize to the clustered receptors and modulate their activity through methylation-demethylation. Using a novel stochastic simulation, we show that distributive receptor methylation is necessary for successful adaptation to stimulus and also leads to large fluctuations in receptor activity in the steady state. These fluctuations arise from noise in the number of localized enzymes combined with saturated modification kinetics between the localized enzymes and the receptor substrate. An analytical model explains how saturated enzyme kinetics and large fluctuations can coexist with an adapted state robust to variation in the expression levels of the pathway constituents, a key requirement to ensure the functionality of individual cells within a population. This contrasts with the well-mixed covalent modification system studied by Goldbeter and Koshland in which mean activity becomes ultrasensitive to protein abundances when the enzymes operate at saturation. Large fluctuations in receptor activity have been quantified experimentally and may benefit the cell by enhancing its ability to explore empty environments and track shallow nutrient gradients. Here we clarify the mechanistic relationship of these large fluctuations to well
Actin Filament Segmentation Using Dynamic Programming
Li, Hongsheng; Shen, Tian; Huang, Xiaolei
2011-01-01
We introduce a novel algorithm for actin filament segmentation in 2D TIRFM image sequences. This problem is difficult because actin filaments dynamically change shapes during their growth, and the TIRFM images are usually noisy. We ask a user to specify the two tips of a filament of interest in the first frame. We then model the segmentation problem in an image sequence as a temporal chain, where its states are tip locations; given candidate tip locations, actin filaments' body points are inferred by a dynamic programming method, which adaptively generates candidate solutions. Combining candidate tip locations and their inferred body points, the temporal chain model is efficiently optimized using another dynamic programming method. Evaluation on noisy TIRFM image sequences demonstrates the accuracy and robustness of this approach. PMID:21761674
Improvements to the adaptive maneuvering logic program
NASA Technical Reports Server (NTRS)
Burgin, George H.
1986-01-01
The Adaptive Maneuvering Logic (AML) computer program simulates close-in, one-on-one air-to-air combat between two fighter aircraft. Three important improvements are described. First, the previously available versions of AML were examined for their suitability as a baseline program. The selected program was then revised to eliminate some programming bugs which were uncovered over the years. A listing of this baseline program is included. Second, the equations governing the motion of the aircraft were completely revised. This resulted in a model with substantially higher fidelity than the original equations of motion provided. It also completely eliminated the over-the-top problem, which occurred in the older versions when the AML-driven aircraft attempted a vertical or near vertical loop. Third, the requirements for a versatile generic, yet realistic, aircraft model were studied and implemented in the program. The report contains detailed tables which make the generic aircraft to be either a modern, high performance aircraft, an older high performance aircraft, or a previous generation jet fighter.
Nitric oxide regulates vascular adaptive mitochondrial dynamics.
Miller, Matthew W; Knaub, Leslie A; Olivera-Fragoso, Luis F; Keller, Amy C; Balasubramaniam, Vivek; Watson, Peter A; Reusch, Jane E B
2013-06-15
Cardiovascular disease risk factors, such as diabetes, hypertension, dyslipidemia, obesity, and physical inactivity, are all correlated with impaired endothelial nitric oxide synthase (eNOS) function and decreased nitric oxide (NO) production. NO-mediated regulation of mitochondrial biogenesis has been established in many tissues, yet the role of eNOS in vascular mitochondrial biogenesis and dynamics is unclear. We hypothesized that genetic eNOS deletion and 3-day nitric oxide synthase (NOS) inhibition in rodents would result in impaired mitochondrial biogenesis and defunct fission/fusion and autophagy profiles within the aorta. We observed a significant, eNOS expression-dependent decrease in mitochondrial electron transport chain (ETC) protein subunits from complexes I, II, III, and V in eNOS heterozygotes and eNOS null mice compared with age-matched controls. In response to NOS inhibition with NG-nitro-L-arginine methyl ester (L-NAME) treatment in Sprague Dawley rats, significant decreases were observed in ETC protein subunits from complexes I, III, and IV as well as voltage-dependent anion channel 1. Decreased protein content of upstream regulators of mitochondrial biogenesis, cAMP response element-binding protein and peroxisome proliferator-activated receptor-γ coactivator-1α, were observed in response to 3-day L-NAME treatment. Both genetic eNOS deletion and NOS inhibition resulted in decreased manganese superoxide dismutase protein. L-NAME treatment resulted in significant changes to mitochondrial dynamic protein profiles with decreased fusion, increased fission, and minimally perturbed autophagy. In addition, L-NAME treatment blocked mitochondrial adaptation to an exercise intervention in the aorta. These results suggest that eNOS/NO play a role in basal and adaptive mitochondrial biogenesis in the vasculature and regulation of mitochondrial turnover. PMID:23585138
Constitutional dynamic chemistry: bridge from supramolecular chemistry to adaptive chemistry.
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.
The Giant Magellan Telescope adaptive optics program
NASA Astrophysics Data System (ADS)
Bouchez, Antonin H.; Acton, D. Scott; Agapito, Guido; Arcidiacono, Carmelo; Bennet, Francis; Biliotti, Valdemaro; Bonaglia, Marco; Briguglio, Runa; Brusa-Zappellini, Guido; Busoni, Lorenzo; Carbonaro, Luca; Codona, Johanan L.; Conan, Rodolphe; Connors, Thomas; Durney, Oliver; Espeland, Brady; Esposito, Simone; Fini, Luca; Gardhouse, Rusty; Gauron, Thomas M.; Hart, Michael; Hinz, Philip M.; Kanneganti, Srikrishna; Kibblewhite, Edward J.; Knox, Russell P.; McLeod, Brian A.; McMahon, Thomas; Montoya, Manny; Norton, Timothy J.; Ordway, Mark P.; d'Orgeville, Celine; Parcell, Simon; Piatrou, Piotr K.; Pinna, Enrico; Price, Ian; Puglisi, Alfio; Quiros-Pacheco, Fernando; Riccardi, Armando; Roll, John B.; Trancho, Gelys; Uhlendorf, Kristina; Vaitheeswaran, Vidhya; van Dam, Marcos A.; Weaver, David; Xompero, Marco
2012-07-01
The Giant Magellan Telescope adaptive optics system will be an integral part of the telescope, providing laser guide star generation, wavefront sensing, and wavefront correction to most of the currently envisioned instruments. The system will provide three observing modes: Natural Guidestar AO (NGSAO), Laser Tomography AO (LTAO), and Ground Layer AO (GLAO). Every AO observing mode will use the telescope’s segmented adaptive secondary mirror to deliver a corrected beam directly to the instruments. High-order wavefront sensing for the NGSAO and LTAO modes is provided by a set of wavefront sensors replicated for each instrument and fed by visible light reflected off the cryostat window. An infrared natural guidestar wavefront sensor with open-loop AO correction is also required to sense tip-tilt, focus, segment piston, and dynamic calibration errors in the LTAO mode. GLAO mode wavefront sensing is provided by laser guidestars over a ~5 arcminute field of view, and natural guidestars over wider fields. A laser guidestar facility will project 120 W of 589 nm laser light in 6 beacons from the periphery of the primary mirror. An off-axis phasing camera and primary and secondary mirror metrology systems will ensure that the telescope optics remain phased. We describe the system requirements, overall architecture, and innovative solutions found to the challenges presented by high-order AO on a segmented extremely large telescope. Further details may be found in specific papers on each of the observing modes and major subsystems.
Dynamic adaptive chemistry for turbulent flame simulations
NASA Astrophysics Data System (ADS)
Yang, Hongtao; Ren, Zhuyin; Lu, Tianfeng; Goldin, Graham M.
2013-02-01
The use of large chemical mechanisms in flame simulations is computationally expensive due to the large number of chemical species and the wide range of chemical time scales involved. This study investigates the use of dynamic adaptive chemistry (DAC) for efficient chemistry calculations in turbulent flame simulations. DAC is achieved through the directed relation graph (DRG) method, which is invoked for each computational fluid dynamics cell/particle to obtain a small skeletal mechanism that is valid for the local thermochemical condition. Consequently, during reaction fractional steps, one needs to solve a smaller set of ordinary differential equations governing chemical kinetics. Test calculations are performed in a partially-stirred reactor (PaSR) involving both methane/air premixed and non-premixed combustion with chemistry described by the 53-species GRI-Mech 3.0 mechanism and the 129-species USC-Mech II mechanism augmented with recently updated NO x pathways, respectively. Results show that, in the DAC approach, the DRG reduction threshold effectively controls the incurred errors in the predicted temperature and species concentrations. The computational saving achieved by DAC increases with the size of chemical kinetic mechanisms. For the PaSR simulations, DAC achieves a speedup factor of up to three for GRI-Mech 3.0 and up to six for USC-Mech II in simulation time, while at the same time maintaining good accuracy in temperature and species concentration predictions.
Adaptive time stepping in biomolecular dynamics.
Franklin, J; Doniach, S
2005-09-22
We present an adaptive time stepping scheme based on the extrapolative method of Barth and Schlick [LN, J. Chem. Phys. 109, 1633 (1998)] to numerically integrate the Langevin equation with a molecular-dynamics potential. This approach allows us to use (on average) a time step for the strong nonbonded force integration corresponding to half the period of the fastest bond oscillation, without compromising the slow degrees of freedom in the problem. We show with simple examples how the dynamic step size stabilizes integration operators, and discuss some of the limitations of such stability. The method introduced uses a slightly more accurate inner integrator than LN to accommodate the larger steps. The adaptive time step approach reproduces temporal features of the bovine pancreatic trypsin inhibitor (BPTI) test system (similar to the one used in the original introduction of LN) compared to short-time integrators, but with energies that are shifted with respect to both LN, and traditional stochastic versions of Verlet. Although the introduction of longer steps has the effect of systematically heating the bonded components of the potential, the temporal fluctuations of the slow degrees of freedom are reproduced accurately. The purpose of this paper is to display a mechanism by which the resonance traditionally associated with using time steps corresponding to half the period of oscillations in molecular dynamics can be avoided. This has theoretical utility in terms of designing numerical integration schemes--the key point is that by factoring a propagator so that time steps are not constant one can recover stability with an overall (average) time step at a resonance frequency. There are, of course, limitations to this approach associated with the complicated, nonlinear nature of the molecular-dynamics (MD) potential (i.e., it is not as straightforward as the linear test problem we use to motivate the method). While the basic notion remains in the full Newtonian problem
The CHARA Array Adaptive Optics Program
NASA Astrophysics Data System (ADS)
Ten Brummelaar, Theo; Che, Xiao; McAlister, Harold A.; Ireland, Michael; Monnier, John D.; Mourard, Denis; Ridgway, Stephen T.; sturmann, judit; Sturmann, Laszlo; Turner, Nils H.; Tuthill, Peter
2016-01-01
The CHARA array is an optical/near infrared interferometer consisting of six 1-meter diameter telescopes the longest baseline of which is 331 meters. With sub-millisecond angular resolution, the CHARA array is able to spatially resolve nearby stellar systems to reveal the detailed structures. To improve the sensitivity and scientific throughput, the CHARA array was funded by NSF-ATI in 2011, and by NSF-MRI in 2015, for an upgrade of adaptive optics (AO) systems to all six telescopes. The initial grant covers Phase I of the adaptive optics system, which includes an on-telescope Wavefront Sensor and non-common-path (NCP) error correction. The WFS use a fairly standard Shack-Hartman design and will initially close the tip tilt servo and log wavefront errors for use in data reduction and calibration. The second grant provides the funding for deformable mirrors for each telescope which will be used closed loop to remove atmospheric aberrations from the beams. There are then over twenty reflections after the WFS at the telescopes that bring the light several hundred meters into the beam combining laboratory. Some of these, including the delay line and beam reducing optics, are powered elements, and some of them, in particular the delay lines and telescope Coude optics, are continually moving. This means that the NCP problems in an interferometer are much greater than those found in more standard telescope systems. A second, slow AO system is required in the laboratory to correct for these NCP errors. We will breifly describe the AO system, and it's current status, as well as discuss the new science enabled by the system with a focus on our YSO program.
Dynamical genetic programming in XCSF.
Preen, Richard J; Bull, Larry
2013-01-01
A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to artificial neural networks. This paper presents results from an investigation into using a temporally dynamic symbolic representation within the XCSF learning classifier system. In particular, dynamical arithmetic networks are used to represent the traditional condition-action production system rules to solve continuous-valued reinforcement learning problems and to perform symbolic regression, finding competitive performance with traditional genetic programming on a number of composite polynomial tasks. In addition, the network outputs are later repeatedly sampled at varying temporal intervals to perform multistep-ahead predictions of a financial time series.
Controlling robot manipulators by dynamic programming
NASA Astrophysics Data System (ADS)
Richard, Marc J.; Cheng, Li
1995-02-01
A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems. In this article, we provide a detailed presentation of the mechanical and electrical implications of robots equipped with DC motor actuators. This model takes into account all non-linear aspects of the system. Then, we develop computational algorithms for optimal control based on dynamic programming. The robot's trajectory must be predefined, but performance criteria and constraints applying to the system are not limited and we may adapt them freely to the robot and the task being studied. As an example, a manipulator arm with 3 degress of freedom is analyzed.
Designing and Implementing Effective Adapted Physical Education Programs
ERIC Educational Resources Information Center
Kelly, Luke E.
2011-01-01
"Designing and Implementing Effective Adapted Physical Education Programs" was written to assist adapted and general physical educators who are dedicated to ensuring that the physical and motor needs of all their students are addressed in physical education. While it is anticipated that adapted physical educators, where available, will typically…
Probabilistic dual heuristic programming-based adaptive critic
NASA Astrophysics Data System (ADS)
Herzallah, Randa
2010-02-01
Adaptive critic (AC) methods have common roots as generalisations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, non-linear and non-stationary environments. In this study, a novel probabilistic dual heuristic programming (DHP)-based AC controller is proposed. Distinct to current approaches, the proposed probabilistic (DHP) AC method takes uncertainties of forward model and inverse controller into consideration. Therefore, it is suitable for deterministic and stochastic control problems characterised by functional uncertainty. Theoretical development of the proposed method is validated by analytically evaluating the correct value of the cost function which satisfies the Bellman equation in a linear quadratic control problem. The target value of the probabilistic critic network is then calculated and shown to be equal to the analytically derived correct value. Full derivation of the Riccati solution for this non-standard stochastic linear quadratic control problem is also provided. Moreover, the performance of the proposed probabilistic controller is demonstrated on linear and non-linear control examples.
The Branching Bifurcation of Adaptive Dynamics
NASA Astrophysics Data System (ADS)
Della Rossa, Fabio; Dercole, Fabio; Landi, Pietro
2015-06-01
We unfold the bifurcation involving the loss of evolutionary stability of an equilibrium of the canonical equation of Adaptive Dynamics (AD). The equation deterministically describes the expected long-term evolution of inheritable traits — phenotypes or strategies — of coevolving populations, in the limit of rare and small mutations. In the vicinity of a stable equilibrium of the AD canonical equation, a mutant type can invade and coexist with the present — resident — types, whereas the fittest always win far from equilibrium. After coexistence, residents and mutants effectively diversify, according to the enlarged canonical equation, only if natural selection favors outer rather than intermediate traits — the equilibrium being evolutionarily unstable, rather than stable. Though the conditions for evolutionary branching — the joint effect of resident-mutant coexistence and evolutionary instability — have been known for long, the unfolding of the bifurcation has remained a missing tile of AD, the reason being related to the nonsmoothness of the mutant invasion fitness after branching. In this paper, we develop a methodology that allows the approximation of the invasion fitness after branching in terms of the expansion of the (smooth) fitness before branching. We then derive a canonical model for the branching bifurcation and perform its unfolding around the loss of evolutionary stability. We cast our analysis in the simplest (but classical) setting of asexual, unstructured populations living in an isolated, homogeneous, and constant abiotic environment; individual traits are one-dimensional; intra- as well as inter-specific ecological interactions are described in the vicinity of a stationary regime.
Neural network with dynamically adaptable neurons
NASA Technical Reports Server (NTRS)
Tawel, Raoul (Inventor)
1994-01-01
This invention is an adaptive neuron for use in neural network processors. The adaptive neuron participates in the supervised learning phase of operation on a co-equal basis with the synapse matrix elements by adaptively changing its gain in a similar manner to the change of weights in the synapse IO elements. In this manner, training time is decreased by as much as three orders of magnitude.
Recruitment dynamics in adaptive social networks
Shkarayev, Maxim S.; Schwartz, Ira B.; Shaw, Leah 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). PMID:25395989
Microcomputer Network for Computerized Adaptive Testing (CAT): Program Listing.
ERIC Educational Resources Information Center
Quan, Baldwin; And Others
This program listing is a supplement to the Microcomputer Network for Computerized Adaptive Testing (CAT). The driver textfile program allows access to major subprograms of the CAT project. The test administration textfile program gives examinees a prescribed set of subtests. The parameter management textfile program establishes a file containing…
Strategic Defense Initiative Organization adaptive structures program overview
NASA Astrophysics Data System (ADS)
Obal, Michael; Sater, Janet M.
In the currently envisioned architecture none of the Strategic Defense System (SDS) elements to be deployed will receive scheduled maintenance. Assessments of performance capability due to changes caused by the uncertain effects of environments will be difficult, at best. In addition, the system will have limited ability to adjust in order to maintain its required performance levels. The Materials and Structures Office of the Strategic Defense Initiative Organization (SDIO) has begun to address solutions to these potential difficulties via an adaptive structures technology program that combines health and environment monitoring with static and dynamic structural control. Conceivable system benefits include improved target tracking and hit-to-kill performance, on-orbit system health monitoring and reporting, and threat attack warning and assessment.
Fluid dynamics computer programs for NERVA turbopump
NASA Technical Reports Server (NTRS)
Brunner, J. J.
1972-01-01
During the design of the NERVA turbopump, numerous computer programs were developed for the analyses of fluid dynamic problems within the machine. Program descriptions, example cases, users instructions, and listings for the majority of these programs are presented.
Henrichon, Carole; Robichaud-Ekstrand, Sylvie
2002-09-01
This descriptive correlational study compares adaptive strategies and adaptation according to participation to an outpatient education program "A vous de jouer". Participants more frequently use seeking social support strategies, and eating less fat, participating in physical activity, managing stress behaviors and returning to work. Distancing/escape avoidance strategies are negatively correlated with healthy life style habits, whereas positive reappraisal/problem solving, and seeking social support strategies are positively associated. Positive reappraisal/problem solving, program participation, and the non-use of distancing/escape avoidance strategies, predict adaptation. The use of these adaptive strategies and behaviors is therefore advantageous to coronary patients.
A boundedness result for the direct heuristic dynamic programming.
Liu, Feng; Sun, Jian; Si, Jennie; Guo, Wentao; Mei, Shengwei
2012-08-01
Approximate/adaptive dynamic programming (ADP) has been studied extensively in recent years for its potential scalability to solve large state and control space problems, including those involving continuous states and continuous controls. The applicability of ADP algorithms, especially the adaptive critic designs has been demonstrated in several case studies. Direct heuristic dynamic programming (direct HDP) is one of the ADP algorithms inspired by the adaptive critic designs. It has been shown applicable to industrial scale, realistic and complex control problems. In this paper, we provide a uniformly ultimately boundedness (UUB) result for the direct HDP learning controller under mild and intuitive conditions. By using a Lyapunov approach we show that the estimation errors of the learning parameters or the weights in the action and critic networks remain UUB. This result provides a useful controller convergence guarantee for the first time for the direct HDP design. PMID:22397949
A boundedness result for the direct heuristic dynamic programming.
Liu, Feng; Sun, Jian; Si, Jennie; Guo, Wentao; Mei, Shengwei
2012-08-01
Approximate/adaptive dynamic programming (ADP) has been studied extensively in recent years for its potential scalability to solve large state and control space problems, including those involving continuous states and continuous controls. The applicability of ADP algorithms, especially the adaptive critic designs has been demonstrated in several case studies. Direct heuristic dynamic programming (direct HDP) is one of the ADP algorithms inspired by the adaptive critic designs. It has been shown applicable to industrial scale, realistic and complex control problems. In this paper, we provide a uniformly ultimately boundedness (UUB) result for the direct HDP learning controller under mild and intuitive conditions. By using a Lyapunov approach we show that the estimation errors of the learning parameters or the weights in the action and critic networks remain UUB. This result provides a useful controller convergence guarantee for the first time for the direct HDP design.
Lessons Learned from the Everglades Collaborative Adaptive Management Program
Recent technical papers explore whether adaptive management (AM) is useful for environmental management and restoration efforts and discuss the many challenges to overcome for successful implementation, especially for large-scale restoration programs (McLain and Lee 1996; Levine ...
Everglades Collaborative Adaptive Management Program Progress
When the Comprehensive Everglades Restoration Plan (CERP) was authorized in 2000, adaptive management (AM) was recognized as a necessary tool to address uncertainty in achieving the broad goals and objectives for restoring a highly managed system. The Everglades covers18,000 squ...
Dynamics of adaptive structures: Design through simulations
NASA Technical Reports Server (NTRS)
Park, K. C.; Alexander, S.
1993-01-01
The use of a helical bi-morph actuator/sensor concept by mimicking the change of helical waveform in bacterial flagella is perhaps the first application of bacterial motions (living species) to longitudinal deployment of space structures. However, no dynamical considerations were analyzed to explain the waveform change mechanisms. The objective is to review various deployment concepts from the dynamics point of view and introduce the dynamical considerations from the outset as part of design considerations. Specifically, the impact of the incorporation of the combined static mechanisms and dynamic design considerations on the deployment performance during the reconfiguration stage is studied in terms of improved controllability, maneuvering duration, and joint singularity index. It is shown that intermediate configurations during articulations play an important role for improved joint mechanisms design and overall structural deployability.
Adaptation and dynamics of cat retinal ganglion cells.
Enroth-Cugell, C; Shapley, R M
1973-09-01
1. The impulse/quantum (I/Q) ratio was measured as a function of background illumination for rod-dominated, pure central, linear square-wave responses of retinal ganglion cells in the cat.2. The I/Q ratio was constant at low backgrounds (dark adapted state) and inversely proportional to the 0.9 power of the background at high backgrounds (the light adapted state). There was an abrupt transition from the dark-adapted state to the light-adapted state.3. It was possible to define the adaptation level at a particular background as the ratio (I/Q ratio at that background)/(dark adapted I/Q ratio).4. The time course of the square-wave response was correlated with the adaptation level. The response was sustained in the dark-adapted state, partially transient at the transition level, and progressively more transient the lower the impulse/quantum ratio of the ganglion cell became. This was true both for on-centre and off-centre cells.5. The frequency response of the central response mechanism at different adaptation levels was measured. It was a low-pass characteristic in the dark-adapted state and became progressively more of a bandpass characteristic as the cell became more light-adapted.6. The rapidity of onset of adaptation was measured with a time-varying adapting light. The impulse/quantum ratio is reset within 100 msec of the onset of the conditioning light, and is kept at the new value throughout the time the conditioning light is on.7. These results can be explained by a nonlinear feedback model. In the model, it is postulated that the exponential function of the horizontal cell potential controls transmission from rods to bipolars. This model has an abrupt transition from dark- to light-adapted states, and its response dynamics are correlated with adaptation level.
Adaptive gauge cooling for complex Langevin dynamics
NASA Astrophysics Data System (ADS)
Bongiovanni, L.; Aarts, G.; Seiler, E.; Sexty, D.; Stamatescu, I. O.
In the case of nonabelian gauge theories with a complex weight, a controlled exploration of the complexified configuration space during a complex Langevin process requires the use of SL(N,C) gauge cooling, in order to minimize the distance from SU(N). Here we show that adaptive gauge cooling can lead to an efficient implementation of this idea. First results for SU(3) Yang-Mills theory in the presence of a nonzero theta-term are presented as well.
Analog forecasting with dynamics-adapted kernels
NASA Astrophysics Data System (ADS)
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.
Applications of analysis of dynamic adaptations in parameter trajectories
van Riel, Natal A. W.; Tiemann, Christian A.; Vanlier, Joep; Hilbers, Peter A. J.
2013-01-01
Metabolic profiling in combination with pathway-based analyses and computational modelling are becoming increasingly important in clinical and preclinical research. Modelling multi-factorial, progressive diseases requires the integration of molecular data at the metabolome, proteome and transcriptome levels. Also the dynamic interaction of organs and tissues needs to be considered. The processes involved cover time scales that are several orders of magnitude different. We report applications of a computational approach to bridge the scales and different levels of biological detail. Analysis of dynamic adaptations in parameter trajectories (ADAPTs) aims to investigate phenotype transitions during disease development and after a therapeutic intervention. ADAPT is based on a time-dependent evolution of model parameters to describe the dynamics of metabolic adaptations. The progression of metabolic adaptations is predicted by identifying necessary dynamic changes in the model parameters to describe the transition between experimental data obtained during different stages. To get a better understanding of the concept, the ADAPT approach is illustrated in a theoretical study. Its application in research on progressive changes in lipoprotein metabolism is also discussed. PMID:23853705
Adaptive dynamic FBG interrogation utilising erbium-doped fibre
NASA Astrophysics Data System (ADS)
John, R. N.; Read, I.; MacPherson, W. N.
2013-04-01
A dynamic fibre Bragg grating interrogation scheme is investigated using two-wave mixing in erbium-doped fibre, capable of adapting to quasistatic strain and temperature drifts. An interference pattern set up in the erbium-doped fibre creates, due to the photorefractive effect, a dynamic grating capable of wavelength demodulating the FBG signal. The presence of a dynamic grating was verified and then dynamic strain signals from a fibre stretcher were measured. The adaptive nature of the technique was successfully demonstrated by heating the FBG while it underwent dynamic straining leading to detection unlike an alternative arrayed waveguide grating system which simultaneously failed detection. Two gratings were then wavelength division multiplexed with the signal grating receiving approximately 30dB greater signal showing that there was little cross talk in the system.
Brain-wide neuronal dynamics during motor adaptation in zebrafish
Ahrens, Misha B; Li, Jennifer M; Orger, Michael B; Robson, Drew N; Schier, Alexander F; Engert, Florian; Portugues, Ruben
2013-01-01
A fundamental question in neuroscience is how entire neural circuits generate behavior and adapt it to changes in sensory feedback. Here we use two-photon calcium imaging to record activity of large populations of neurons at the cellular level throughout the brain of larval zebrafish expressing a genetically-encoded calcium sensor, while the paralyzed 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 neural response properties, and provide anatomical maps of the corresponding sites. A subset of these signals occurred during behavioral 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 behavior. PMID:22622571
The Adaptive Physical Education Program: Its Design and Curriculum.
ERIC Educational Resources Information Center
Henn, Joan M.
The booklet describes a program designed to improve the play skills of seriously disturbed, multiply handicapped children (5 to 13 years old) through gross motor skill development. A six step process is described for the adaptive physical education program: assessment, development of interdisciplinary goals, interventions, development of goals for…
Teaching Adaptability of Object-Oriented Programming Language Curriculum
ERIC Educational Resources Information Center
Zhu, Xiao-dong
2012-01-01
The evolution of object-oriented programming languages includes update of their own versions, update of development environments, and reform of new languages upon old languages. In this paper, the evolution analysis of object-oriented programming languages is presented in term of the characters and development. The notion of adaptive teaching upon…
Adaptive Programming Improves Outcomes in Drug Court: An Experimental Trial
Marlowe, Douglas B.; Festinger, David S.; Dugosh, Karen L.; Benasutti, Kathleen M.; Fox, Gloria; Croft, Jason R.
2011-01-01
Prior studies in Drug Courts reported improved outcomes when participants were matched to schedules of judicial status hearings based on their criminological risk level. The current experiment determined whether incremental efficacy could be gained by periodically adjusting the schedule of status hearings and clinical case-management sessions in response to participants’ ensuing performance in the program. The adjustments were made pursuant to a priori criteria specified in an adaptive algorithm. Results confirmed that participants in the full adaptive condition (n = 62) were more than twice as likely as those assigned to baseline-matching only (n = 63) to be drug-abstinent during the first 18 weeks of the program; however, graduation rates and the average time to case resolution were not significantly different. The positive effects of the adaptive program appear to have stemmed from holding noncompliant participants more accountable for meeting their attendance obligations in the program. Directions for future research and practice implications are discussed. PMID:22923854
Adaptive planning for applications with dynamic objectives
NASA Technical Reports Server (NTRS)
Hadavi, Khosrow; Hsu, Wen-Ling; Pinedo, Michael
1992-01-01
We devise a qualitative control layer to be integrated into a real-time multi-agent reactive planner. The reactive planning system consists of distributed planning agents attending to various perspectives of the task environment. Each perspective corresponds to an objective. The set of objectives considered are sometimes in conflict with each other. Each agent receives information about events as they occur, and a set of actions based on heuristics can be taken by the agents. Within the qualitative control scheme, we use a set of qualitative feature vectors to describe the effects of applying actions. A qualitative transition vector is used to denote the qualitative distance between the current state and the target state. We will then apply on-line learning at the qualitative control level to achieve adaptive planning. Our goal is to design a mechanism to refine the heuristics used by the reactive planner every time an action is taken toward achieving the objectives, using feedback from the results of the actions. When the outcome is compared with expectations, our prior objectives may be modified and a new set of objectives (or a new assessment of the relative importance of the different objectives) can be introduced. Because we are able to obtain better estimates of the time-varying objectives, the reactive strategies can be improved and better prediction can be achieved.
ERIC Educational Resources Information Center
Reinschmidt, Kerstin M.; Teufel-Shone, Nicolette I.; Bradford, Gail; Drummond, Rebecca L.; Torres, Emma; Redondo, Floribella; Elenes, Jo Jean; Sanders, Alicia; Gastelum, Sylvia; Moore-Monroy, Martha; Barajas, Salvador; Fernandez, Lourdes; Alvidrez, Rosy; de Zapien, Jill Guernsey; Staten, Lisa K.
2010-01-01
Diabetes health disparities among Hispanic populations have been countered with federally funded health promotion and disease prevention programs. Dissemination has focused on program adaptation to local cultural contexts for greater acceptability and sustainability. Taking a broader approach and drawing on our experience in Mexican American…
On the dynamics of some grid adaption schemes
NASA Technical Reports Server (NTRS)
Sweby, Peter K.; Yee, Helen C.
1994-01-01
The dynamics of a one-parameter family of mesh equidistribution schemes coupled with finite difference discretisations of linear and nonlinear convection-diffusion model equations is studied numerically. It is shown that, when time marched to steady state, the grid adaption not only influences the stability and convergence rate of the overall scheme, but can also introduce spurious dynamics to the numerical solution procedure.
Dynamics and Adaptive Control for Stability Recovery of Damaged Aircraft
NASA Technical Reports Server (NTRS)
Nguyen, Nhan; Krishnakumar, Kalmanje; Kaneshige, John; Nespeca, Pascal
2006-01-01
This paper presents a recent study of a damaged generic transport model as part of a NASA research project to investigate adaptive control methods for stability recovery of damaged aircraft operating in off-nominal flight conditions under damage and or failures. Aerodynamic modeling of damage effects is performed using an aerodynamic code to assess changes in the stability and control derivatives of a generic transport aircraft. Certain types of damage such as damage to one of the wings or horizontal stabilizers can cause the aircraft to become asymmetric, thus resulting in a coupling between the longitudinal and lateral motions. Flight dynamics for a general asymmetric aircraft is derived to account for changes in the center of gravity that can compromise the stability of the damaged aircraft. An iterative trim analysis for the translational motion is developed to refine the trim procedure by accounting for the effects of the control surface deflection. A hybrid direct-indirect neural network, adaptive flight control is proposed as an adaptive law for stabilizing the rotational motion of the damaged aircraft. The indirect adaptation is designed to estimate the plant dynamics of the damaged aircraft in conjunction with the direct adaptation that computes the control augmentation. Two approaches are presented 1) an adaptive law derived from the Lyapunov stability theory to ensure that the signals are bounded, and 2) a recursive least-square method for parameter identification. A hardware-in-the-loop simulation is conducted and demonstrates the effectiveness of the direct neural network adaptive flight control in the stability recovery of the damaged aircraft. A preliminary simulation of the hybrid adaptive flight control has been performed and initial data have shown the effectiveness of the proposed hybrid approach. Future work will include further investigations and high-fidelity simulations of the proposed hybrid adaptive Bight control approach.
Adaptable and dynamic soft colloidal photonics (Presentation Recording)
NASA Astrophysics Data System (ADS)
Kuehne, Alexander J. C.; Go, Dennis
2015-10-01
Existent photonic systems are highly integrated with the active component being completely isolated from the environment as a result of their complex format. There are almost no example for periodic photonic materials, which can interact with their environment by being sensitive to external stimuli while providing the corresponding photonic response. Due to this lack of interaction with the outside world, smart optical components, which are self-healing or adaptable, are almost impossible to achieve. I am going to present an aqueous colloidal system, consisting of core-shell particles with a solid core and a soft shell, bearing both negatively and positively charged groups. The described soft colloids exhibit like charges over a broad range of pH, where they repel each other resulting in a pefect and defect-free photonic crystal. In the absence of a net charge the colloids acquire the arrangement of an amorphous photonic glass. We showcase the applicability of our colloidal system for photonic applications by temporal programming of the photonic system and dynamic switching between ordered and amorphous particle arrangements. We can decrease the pH slowly allowing the particles to transit from negative through neutral to positive, and have them arrange accordingly from crystalline to amorphous and back to crystalline. Thus, we achieve a pre-programmable and autonomous dynamic modulation of the crystallinity of the colloidal arrays and their photonic response. References [1] Go, D., Kodger, T. E., Sprakel, J., and Kuehne, A. J.C. Soft matter. 2014, 10(40), 8060-8065.
Improving Voluntary Environmental Management Programs: Facilitating Learning and Adaptation
NASA Astrophysics Data System (ADS)
Genskow, Kenneth D.; Wood, Danielle M.
2011-05-01
Environmental planners and managers face unique challenges understanding and documenting the effectiveness of programs that rely on voluntary actions by private landowners. Programs, such as those aimed at reducing nonpoint source pollution or improving habitat, intend to reach those goals by persuading landowners to adopt behaviors and management practices consistent with environmental restoration and protection. Our purpose with this paper is to identify barriers for improving voluntary environmental management programs and ways to overcome them. We first draw upon insights regarding data, learning, and adaptation from the adaptive management and performance management literatures, describing three key issues: overcoming information constraints, structural limitations, and organizational culture. Although these lessons are applicable to a variety of voluntary environmental management programs, we then present the issues in the context of on-going research for nonpoint source water quality pollution. We end the discussion by highlighting important elements for advancing voluntary program efforts.
Enhancing Functional Performance using Sensorimotor Adaptability Training Programs
NASA Technical Reports Server (NTRS)
Bloomberg, J. J.; Mulavara, A. P.; Peters, B. T.; Brady, R.; Audas, C.; Ruttley, T. M.; Cohen, H. S.
2009-01-01
During the acute phase of adaptation to novel gravitational environments, sensorimotor disturbances have the potential to disrupt the ability of astronauts to perform functional tasks. The goal of this project is to develop a sensorimotor adaptability (SA) training program designed to facilitate recovery of functional capabilities when astronauts transition to different gravitational environments. The project conducted a series of studies that investigated the efficacy of treadmill training combined with a variety of sensory challenges designed to increase adaptability including alterations in visual flow, body loading, and support surface stability.
Sex speeds adaptation by altering the dynamics of molecular evolution.
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.
Sex speeds adaptation by altering the dynamics of molecular evolution.
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. PMID:26909573
Sex Speeds Adaptation by Altering the Dynamics of Molecular Evolution
McDonald, Michael J.; Rice, Daniel P.; Desai, Michael M.
2016-01-01
Sex and recombination are pervasive throughout nature despite their substantial costs1. Understanding the evolutionary forces that maintain these phenomena is a central challenge in biology2,3. One longstanding hypothesis argues that sex is beneficial because recombination speeds adaptation4. Theory has proposed a number of 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)5,6 or by separating them from deleterious load (the ruby in the rubbish effect)7,8. Previous experiments confirm that sex can increase the rate of adaptation9–17, but these studies did not observe the evolutionary dynamics that drive this effect at the genomic level. Here, we present the first comparison between the sequence-level dynamics of adaptation in experimental sexual and asexual 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. PMID:26909573
Dynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture
Disney, Adam; Reynolds, John
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.
Program Structure Combines Segmentation and Dynamic Storage
NASA Technical Reports Server (NTRS)
Tiffany, S. H.
1982-01-01
Programing techniques incorporate advantages of overlaying into segmented loads while retaining all dynamic load advantages of segmentation, employing those capabilities that best suit mode of operation, whether batch or interactive. User is allowed to load a program automatically in a variable manner, based solely on a single data input to the program, to maintain minimal field lengths for interactive use.
Specifying Imperative ML-Like Programs Using Dynamic Logic
NASA Astrophysics Data System (ADS)
Maingaud, Séverine; Balat, Vincent; Bubel, Richard; Hähnle, Reiner; Miquel, Alexandre
We present a logical system suited for specification and verification of imperative ML programs. The specification language combines dynamic logic (DL), explicit state updates and second-order functional arithmetic. Its proof system is based on a Gentzen-style sequent calculus (adapted to modal logic) with facilities for symbolic evaluation. We illustrate the system with some example, and give a full Kripke-style semantics in order to prove its correctness.
Gradient-based adaptation of continuous dynamic model structures
NASA Astrophysics Data System (ADS)
La Cava, William G.; Danai, Kourosh
2016-01-01
A gradient-based method of symbolic adaptation is introduced for a class of continuous dynamic models. The proposed model structure adaptation method starts with the first-principles model of the system and adapts its structure after adjusting its individual components in symbolic form. A key contribution of this work is its introduction of the model's parameter sensitivity as the measure of symbolic changes to the model. This measure, which is essential to defining the structural sensitivity of the model, not only accommodates algebraic evaluation of candidate models in lieu of more computationally expensive simulation-based evaluation, but also makes possible the implementation of gradient-based optimisation in symbolic adaptation. The proposed method is applied to models of several virtual and real-world systems that demonstrate its potential utility.
Adaptive hybrid intelligent control for uncertain nonlinear dynamical systems.
Wang, Chi-Hsu; Lin, Tsung-Chih; Lee, Tsu-Tian; Liu, Han-Leih
2002-01-01
A new hybrid direct/indirect adaptive fuzzy neural network (FNN) controller with a state observer and supervisory controller for a class of uncertain nonlinear dynamic systems is developed in this paper. The hybrid adaptive FNN controller, the free parameters of which can be tuned on-line by an observer-based output feedback control law and adaptive law, is a combination of direct and indirect adaptive FNN controllers. A weighting factor, which can be adjusted by the tradeoff between plant knowledge and control knowledge, is adopted to sum together the control efforts from indirect adaptive FNN controller and direct adaptive FNN controller. Furthermore, a supervisory controller is appended into the FNN controller to force the state to be within the constraint set. Therefore, if the FNN controller cannot maintain the stability, the supervisory controller starts working to guarantee stability. On the other hand, if the FNN controller works well, the supervisory controller will be deactivated. The overall adaptive scheme guarantees the global stability of the resulting closed-loop system in the sense that all signals involved are uniformly bounded. Two nonlinear systems, namely, inverted pendulum system and Chua's (1989) chaotic circuit, are fully illustrated to track sinusoidal signals. The resulting hybrid direct/indirect FNN control systems show better performances, i.e., tracking error and control effort can be made smaller and it is more flexible during the design process.
Adaptable Constrained Genetic Programming: Extensions and Applications
NASA Technical Reports Server (NTRS)
Janikow, Cezary Z.
2005-01-01
An evolutionary algorithm applies evolution-based principles to problem solving. To solve a problem, the user defines the space of potential solutions, the representation space. Sample solutions are encoded in a chromosome-like structure. The algorithm maintains a population of such samples, which undergo simulated evolution by means of mutation, crossover, and survival of the fittest principles. Genetic Programming (GP) uses tree-like chromosomes, providing very rich representation suitable for many problems of interest. GP has been successfully applied to a number of practical problems such as learning Boolean functions and designing hardware circuits. To apply GP to a problem, the user needs to define the actual representation space, by defining the atomic functions and terminals labeling the actual trees. The sufficiency principle requires that the label set be sufficient to build the desired solution trees. The closure principle allows the labels to mix in any arity-consistent manner. To satisfy both principles, the user is often forced to provide a large label set, with ad hoc interpretations or penalties to deal with undesired local contexts. This unfortunately enlarges the actual representation space, and thus usually slows down the search. In the past few years, three different methodologies have been proposed to allow the user to alleviate the closure principle by providing means to define, and to process, constraints on mixing the labels in the trees. Last summer we proposed a new methodology to further alleviate the problem by discovering local heuristics for building quality solution trees. A pilot system was implemented last summer and tested throughout the year. This summer we have implemented a new revision, and produced a User's Manual so that the pilot system can be made available to other practitioners and researchers. We have also designed, and partly implemented, a larger system capable of dealing with much more powerful heuristics.
Serial and parallel dynamic adaptation of general hybrid meshes
NASA Astrophysics Data System (ADS)
Kavouklis, Christos
The Navier-Stokes equations are a standard mathematical representation of viscous fluid flow. Their numerical solution in three dimensions remains a computationally intensive and challenging task, despite recent advances in computer speed and memory. A strategy to increase accuracy of Navier-Stokes simulations, while maintaining computing resources to a minimum, is local refinement of the associated computational mesh in regions of large solution gradients and coarsening in regions where the solution does not vary appreciably. In this work we consider adaptation of general hybrid meshes for Computational Fluid Dynamics (CFD) applications. Hybrid meshes are composed of four types of elements; hexahedra, prisms, pyramids and tetrahedra, and have been proven a promising technology in accurately resolving fluid flow for complex geometries. The first part of this dissertation is concerned with the design and implementation of a serial scheme for the adaptation of general three dimensional hybrid meshes. We have defined 29 refinement types, for all four kinds of elements. The core of the present adaptation scheme is an iterative algorithm that flags mesh edges for refinement, so that the adapted mesh is conformal. Of primary importance is considered the design of a suitable dynamic data structure that facilitates refinement and coarsening operations and furthermore minimizes memory requirements. A special dynamic list is defined for mesh elements, in contrast with the usual tree structures. It contains only elements of the current adaptation step and minimal information that is utilized to reconstruct parent elements when the mesh is coarsened. In the second part of this work, a new parallel dynamic mesh adaptation and load balancing algorithm for general hybrid meshes is presented. Partitioning of a hybrid mesh reduces to partitioning of the corresponding dual graph. Communication among processors is based on the faces of the interpartition boundary. The distributed
Parallel tetrahedral mesh adaptation with dynamic load balancing
Oliker, Leonid; Biswas, Rupak; Gabow, Harold N.
2000-06-28
The ability to dynamically adapt an unstructured grid is a powerful tool for efficiently solving computational problems with evolving physical features. In this paper, we report on our experience parallelizing an edge-based adaptation scheme, called 3D-TAG, using message passing. Results show excellent speedup when a realistic helicopter rotor mesh is randomly refined. However, performance deteriorates when the mesh is refined using a solution-based error indicator since mesh adaptation for practical problems occurs in a localized region, creating a severe load imbalance. To address this problem, we have developed PLUM, a global dynamic load balancing framework for adaptive numerical computations. Even though PLUM primarily balances processor workloads for the solution phase, it reduces the load imbalance problem within mesh adaptation by repartitioning the mesh after targeting edges for refinement but before the actual subdivision. This dramatically improves the performance of parallel 3D-TAG since refinement occurs in a more load balanced fashion. We also present optimal and heuristic algorithms that, when applied to the default mapping of a parallel repartitioner, significantly reduce the data redistribution overhead. Finally, portability is examined by comparing performance on three state-of-the-art parallel machines.
Parallel Tetrahedral Mesh Adaptation with Dynamic Load Balancing
NASA Technical Reports Server (NTRS)
Oliker, Leonid; Biswas, Rupak; Gabow, Harold N.
1999-01-01
The ability to dynamically adapt an unstructured grid is a powerful tool for efficiently solving computational problems with evolving physical features. In this paper, we report on our experience parallelizing an edge-based adaptation scheme, called 3D_TAG. using message passing. Results show excellent speedup when a realistic helicopter rotor mesh is randomly refined. However. performance deteriorates when the mesh is refined using a solution-based error indicator since mesh adaptation for practical problems occurs in a localized region., creating a severe load imbalance. To address this problem, we have developed PLUM, a global dynamic load balancing framework for adaptive numerical computations. Even though PLUM primarily balances processor workloads for the solution phase, it reduces the load imbalance problem within mesh adaptation by repartitioning the mesh after targeting edges for refinement but before the actual subdivision. This dramatically improves the performance of parallel 3D_TAG since refinement occurs in a more load balanced fashion. We also present optimal and heuristic algorithms that, when applied to the default mapping of a parallel repartitioner, significantly reduce the data redistribution overhead. Finally, portability is examined by comparing performance on three state-of-the-art parallel machines.
A Context-Adaptive Model for Program Evaluation.
ERIC Educational Resources Information Center
Lynch, Brian K.
1990-01-01
Presents an adaptable, context-sensitive model for ESL/EFL program evaluation, consisting of seven steps that guide an evaluator through consideration of relevant issues, information, and design elements. Examples from an evaluation of the Reading for Science and Technology Project at the University of Guadalajara, Mexico are given. (31…
Adaptive network dynamics and evolution of leadership in collective migration
NASA Astrophysics Data System (ADS)
Pais, Darren; Leonard, Naomi E.
2014-01-01
The evolution of leadership in migratory populations depends not only on costs and benefits of leadership investments but also on the opportunities for individuals to rely on cues from others through social interactions. We derive an analytically tractable adaptive dynamic network model of collective migration with fast timescale migration dynamics and slow timescale adaptive dynamics of individual leadership investment and social interaction. For large populations, our analysis of bifurcations with respect to investment cost explains the observed hysteretic effect associated with recovery of migration in fragmented environments. Further, we show a minimum connectivity threshold above which there is evolutionary branching into leader and follower populations. For small populations, we show how the topology of the underlying social interaction network influences the emergence and location of leaders in the adaptive system. Our model and analysis can be extended to study the dynamics of collective tracking or collective learning more generally. Thus, this work may inform the design of robotic networks where agents use decentralized strategies that balance direct environmental measurements with agent interactions.
A Comparison of Three Programming Models for Adaptive Applications
NASA Technical Reports Server (NTRS)
Shan, Hong-Zhang; Singh, Jaswinder Pal; Oliker, Leonid; Biswa, Rupak; Kwak, Dochan (Technical Monitor)
2000-01-01
We study the performance and programming effort for two major classes of adaptive applications under three leading parallel programming models. We find that all three models can achieve scalable performance on the state-of-the-art multiprocessor machines. The basic parallel algorithms needed for different programming models to deliver their best performance are similar, but the implementations differ greatly, far beyond the fact of using explicit messages versus implicit loads/stores. Compared with MPI and SHMEM, CC-SAS (cache-coherent shared address space) provides substantial ease of programming at the conceptual and program orchestration level, which often leads to the performance gain. However it may also suffer from the poor spatial locality of physically distributed shared data on large number of processors. Our CC-SAS implementation of the PARMETIS partitioner itself runs faster than in the other two programming models, and generates more balanced result for our application.
Dynamic Programming: An Introduction by Example
ERIC Educational Resources Information Center
Zietz, Joachim
2007-01-01
The author introduces some basic dynamic programming techniques, using examples, with the help of the computer algebra system "Maple". The emphasis is on building confidence and intuition for the solution of dynamic problems in economics. To integrate the material better, the same examples are used to introduce different techniques. One covers the…
Dynamic Load Balancing for Adaptive Meshes using Symmetric Broadcast Networks
NASA Technical Reports Server (NTRS)
Das, Sajal K.; Harvey, Daniel J.; Biswas, Rupak; Saini, Subhash (Technical Monitor)
1998-01-01
Many scientific applications involve grids that lack a uniform underlying structure. These applications are often dynamic in the sense that the grid structure significantly changes between successive phases of execution. In parallel computing environments, mesh adaptation of grids through selective refinement/coarsening has proven to be an effective approach. However, achieving load balance while minimizing inter-processor communication and redistribution costs is a difficult problem. Traditional dynamic load balancers are mostly inadequate because they lack a global view across processors. In this paper, we compare a novel load balancer that utilizes symmetric broadcast networks (SBN) to a successful global load balancing environment (PLUM) created to handle adaptive unstructured applications. Our experimental results on the IBM SP2 demonstrate that performance of the proposed SBN load balancer is comparable to results achieved under PLUM.
Effects of adaptive dynamical linking in networked games
NASA Astrophysics Data System (ADS)
Yang, Zhihu; Li, Zhi; Wu, Te; Wang, Long
2013-10-01
The role of dynamical topologies in the evolution of cooperation has received considerable attention, as some studies have demonstrated that dynamical networks are much better than static networks in terms of boosting cooperation. Here we study a dynamical model of evolution of cooperation on stochastic dynamical networks in which there are no permanent partners to each agent. Whenever a new link is created, its duration is randomly assigned without any bias or preference. We allow the agent to adaptively adjust the duration of each link during the evolution in accordance with the feedback from game interactions. By Monte Carlo simulations, we find that cooperation can be remarkably promoted by this adaptive dynamical linking mechanism both for the game of pairwise interactions, such as the Prisoner's Dilemma game (PDG), and for the game of group interactions, illustrated by the public goods game (PGG). And the faster the adjusting rate, the more successful the evolution of cooperation. We also show that in this context weak selection favors cooperation much more than strong selection does. What is particularly meaningful is that the prosperity of cooperation in this study indicates that the rationality and selfishness of a single agent in adjusting social ties can lead to the progress of altruism of the whole population.
Space station structures and dynamics test program
NASA Technical Reports Server (NTRS)
Moore, Carleton J.; Townsend, John S.; Ivey, Edward W.
1987-01-01
The design, construction, and operation of a low-Earth orbit space station poses unique challenges for development and implementation of new technology. The technology arises from the special requirement that the station be built and constructed to function in a weightless environment, where static loads are minimal and secondary to system dynamics and control problems. One specific challenge confronting NASA is the development of a dynamics test program for: (1) defining space station design requirements, and (2) identifying the characterizing phenomena affecting the station's design and development. A general definition of the space station dynamic test program, as proposed by MSFC, forms the subject of this report. The test proposal is a comprehensive structural dynamics program to be launched in support of the space station. The test program will help to define the key issues and/or problems inherent to large space structure analysis, design, and testing. Development of a parametric data base and verification of the math models and analytical analysis tools necessary for engineering support of the station's design, construction, and operation provide the impetus for the dynamics test program. The philosophy is to integrate dynamics into the design phase through extensive ground testing and analytical ground simulations of generic systems, prototype elements, and subassemblies. On-orbit testing of the station will also be used to define its capability.
Hybrid Differential Dynamic Programming with Stochastic Search
NASA Technical Reports Server (NTRS)
Aziz, Jonathan; Parker, Jeffrey; Englander, Jacob
2016-01-01
Differential dynamic programming (DDP) has been demonstrated as a viable approach to low-thrust trajectory optimization, namely with the recent success of NASAs Dawn mission. The Dawn trajectory was designed with the DDP-based Static Dynamic Optimal Control algorithm used in the Mystic software. Another recently developed method, Hybrid Differential Dynamic Programming (HDDP) is a variant of the standard DDP formulation that leverages both first-order and second-order state transition matrices in addition to nonlinear programming (NLP) techniques. Areas of improvement over standard DDP include constraint handling, convergence properties, continuous dynamics, and multi-phase capability. DDP is a gradient based method and will converge to a solution nearby an initial guess. In this study, monotonic basin hopping (MBH) is employed as a stochastic search method to overcome this limitation, by augmenting the HDDP algorithm for a wider search of the solution space.
Hybrid Differential Dynamic Programming with Stochastic Search
NASA Technical Reports Server (NTRS)
Aziz, Jonathan; Parker, Jeffrey; Englander, Jacob A.
2016-01-01
Differential dynamic programming (DDP) has been demonstrated as a viable approach to low-thrust trajectory optimization, namely with the recent success of NASA's Dawn mission. The Dawn trajectory was designed with the DDP-based Static/Dynamic Optimal Control algorithm used in the Mystic software.1 Another recently developed method, Hybrid Differential Dynamic Programming (HDDP),2, 3 is a variant of the standard DDP formulation that leverages both first-order and second-order state transition matrices in addition to nonlinear programming (NLP) techniques. Areas of improvement over standard DDP include constraint handling, convergence properties, continuous dynamics, and multi-phase capability. DDP is a gradient based method and will converge to a solution nearby an initial guess. In this study, monotonic basin hopping (MBH) is employed as a stochastic search method to overcome this limitation, by augmenting the HDDP algorithm for a wider search of the solution space.
Program of Research in Structures and Dynamics
NASA Technical Reports Server (NTRS)
1988-01-01
The Structures and Dynamics Program was first initiated in 1972 with the following two major objectives: to provide a basic understanding and working knowledge of some key areas pertinent to structures, solid mechanics, and dynamics technology including computer aided design; and to provide a comprehensive educational and research program at the NASA Langley Research Center leading to advanced degrees in the structures and dynamics areas. During the operation of the program the research work was done in support of the activities of both the Structures and Dynamics Division and the Loads and Aeroelasticity Division. During the period of 1972 to 1986 the Program provided support for two full-time faculty members, one part-time faculty member, three postdoctoral fellows, one research engineer, eight programmers, and 28 graduate research assistants. The faculty and staff of the program have published 144 papers and reports, and made 70 presentations at national and international meetings, describing their research findings. In addition, they organized and helped in the organization of 10 workshops and national symposia in the structures and dynamics areas. The graduate research assistants and the students enrolled in the program have written 20 masters theses and 2 doctoral dissertations. The overall progress is summarized.
NASA Astrophysics Data System (ADS)
Chai, Runqi; Savvaris, Al; Tsourdos, Antonios
2016-06-01
In this paper, a fuzzy physical programming (FPP) method has been introduced for solving multi-objective Space Manoeuvre Vehicles (SMV) skip trajectory optimization problem based on hp-adaptive pseudospectral methods. The dynamic model of SMV is elaborated and then, by employing hp-adaptive pseudospectral methods, the problem has been transformed to nonlinear programming (NLP) problem. According to the mission requirements, the solutions were calculated for each single-objective scenario. To get a compromised solution for each target, the fuzzy physical programming (FPP) model is proposed. The preference function is established with considering the fuzzy factor of the system such that a proper compromised trajectory can be acquired. In addition, the NSGA-II is tested to obtain the Pareto-optimal solution set and verify the Pareto optimality of the FPP solution. Simulation results indicate that the proposed method is effective and feasible in terms of dealing with the multi-objective skip trajectory optimization for the SMV.
Glassy Dynamics in the Adaptive Immune Response Prevents Autoimmune Disease
NASA Astrophysics Data System (ADS)
Sun, Jun; Earl, David J.; Deem, Michael W.
2005-09-01
The immune system normally protects the human host against death by infection. However, when an immune response is mistakenly directed at self-antigens, autoimmune disease can occur. We describe a model of protein evolution to simulate the dynamics of the adaptive immune response to antigens. Computer simulations of the dynamics of antibody evolution show that different evolutionary mechanisms, namely, gene segment swapping and point mutation, lead to different evolved antibody binding affinities. Although a combination of gene segment swapping and point mutation can yield a greater affinity to a specific antigen than point mutation alone, the antibodies so evolved are highly cross reactive and would cause autoimmune disease, and this is not the chosen dynamics of the immune system. We suggest that in the immune system’s search for antibodies, a balance has evolved between binding affinity and specificity.
An Efficient Dynamically Adaptive Mesh for Potentially Singular Solutions
NASA Astrophysics Data System (ADS)
Ceniceros, Hector D.; Hou, Thomas Y.
2001-09-01
We develop an efficient dynamically adaptive mesh generator for time-dependent problems in two or more dimensions. The mesh generator is motivated by the variational approach and is based on solving a new set of nonlinear elliptic PDEs for the mesh map. When coupled to a physical problem, the mesh map evolves with the underlying solution and maintains high adaptivity as the solution develops complicated structures and even singular behavior. The overall mesh strategy is simple to implement, avoids interpolation, and can be easily incorporated into a broad range of applications. The efficacy of the mesh is first demonstrated by two examples of blowing-up solutions to the 2-D semilinear heat equation. These examples show that the mesh can follow with high adaptivity a finite-time singularity process. The focus of applications presented here is however the baroclinic generation of vorticity in a strongly layered 2-D Boussinesq fluid, a challenging problem. The moving mesh follows effectively the flow resolving both its global features and the almost singular shear layers developed dynamically. The numerical results show the fast collapse to small scales and an exponential vorticity growth.
Generalization in Adaptation to Stable and Unstable Dynamics
Kadiallah, Abdelhamid; Franklin, David W.; Burdet, Etienne
2012-01-01
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. PMID:23056191
NASA Astrophysics Data System (ADS)
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.
Space station structures and dynamics test program
NASA Technical Reports Server (NTRS)
Bugg, Frank M.; Ivey, E. W.; Moore, C. J.; Townsend, John S.
1987-01-01
The design, construction, and operation of a low-Earth orbit space station poses challenges for development and implementation of technology. One specific challenge is the development of a dynamics test program for defining the space station design requirements, and identifying and characterizing phenomena affecting the space station's design and development. The test proposal, as outlined, is a comprehensive structural dynamics program to be launched in support of the space station (SS). Development of a parametric data base and verification of the mathematical models and analytical analysis tools necessary for engineering support of the station's design, construction, and operation provide the impetus for the dynamics test program. The four test phases planned are discussed: testing of SS applicable structural concepts; testing of SS prototypes; testing of actual SS structural hardware; and on-orbit testing of SS construction.
Interactive Beam-Dynamics Program
2001-01-08
TRACE3D is an interactive program that calculates the envelopes of a bunched beam, including linear space-charge forces, through a user-defined system. The transport system may consist of the following elements: drift, thin lens, quadrupole, permanent magnet quadrupole, solenoid, doublet, triplet, bending magnet, edge angle (for bend), RF gap, radio-frequency-quadrupole cell, RF cavity, coupled-cavity tank, user-desired element, coordinate rotation, and identical element. The beam is represented by a 6X6 matrix defining a hyper-ellipsoid in six-dimensional phasemore » space. The projection of this hyperellipsoid on any two-dimensional plane is an ellipse that defines the boundary of the beam in that plane.« less
A comparison of three programming models for adaptive applications on the Origin2000
Shan, Hongzhang; Singh, Jaswinder Pal; Oliker, Leonid; Biswas, Rupak
2001-05-30
Adaptive applications have computational workloads and communication patterns which change unpredictably at runtime, requiring dynamic load balancing to achieve scalable performance on parallel machines. Efficient parallel implementations of such adaptive applications is therefore a challenging task. In this paper, we compare the performance of and the programming effort required for two major classes of adaptive applications under three leading parallel programming models on an SGI Origin2000 system, a machine which supports all three models efficiently. Results indicate that the three models deliver comparable performance; however, the implementations differ significantly beyond merely using explicit messages versus implicit loads/stores even though the basic parallel algorithms are similar. Compared with the message-passing (using MPI) and SHMEM programming models, the cache-coherent shared address space (CC-SAS) model provides substantial ease of programming at both the conceptual and program orchestration levels, often accompanied by performance gains. However, CC-SAS currently has portability limitations and may suffer from poor spatial locality of physically distributed shared data on large numbers of processors.
Configurational forces and variational mesh adaptation in solid dynamics
NASA Astrophysics Data System (ADS)
Zielonka, Matias G.
This thesis is concerned with the exploration and development of a variational finite element mesh adaption framework for non-linear solid dynamics and its conceptual links with the theory of dynamic configurational forces. The distinctive attribute of this methodology is that the underlying variational principle of the problem under study is used to supply both the discretized fields and the mesh on which the discretization is supported. To this end a mixed-multifield version of Hamilton's principle of stationary action and Lagrange-d'Alembert, principle is proposed, a fresh perspective on the theory of dynamic configurational forces is presented, and a unifying variational formulation that generalizes the framework to systems with general dissipative behavior is developed. A mixed finite element formulation with independent spatial interpolations for deformations and velocities and a mixed variational integrator with independent time interpolations for the resulting nodal parameters is constructed. This discretization is supported on a continuously deforming mesh that is not prescribed at the outset but computed as part of the solution. The resulting space-time discretization satisfies exact discrete configurational force balance and exhibits excellent long term global energy stability behavior. The robustness of the mesh adaption framework is assessed and demonstrated with a set of examples and convergence tests.
Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks
NASA Technical Reports Server (NTRS)
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.
Elucidating Microbial Adaptation Dynamics via Autonomous Exposure and Sampling
NASA Astrophysics Data System (ADS)
Grace, J. M.; Verseux, C.; Gentry, D.; Moffet, A.; Thayabaran, R.; Wong, N.; Rothschild, L.
2013-12-01
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[Wielgoss et al., 2013]. Although such studies inform fundamental questions about the way adaptation and even speciation occur, they are often limited by labor-intensive manual techniques[Wassmann et al., 2010]. 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[Alcántara-Díaz et al., 2004; Goldman and Travisano, 2011]. 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
Configuring Airspace Sectors with Approximate Dynamic Programming
NASA Technical Reports Server (NTRS)
Bloem, Michael; Gupta, Pramod
2010-01-01
In response to changing traffic and staffing conditions, supervisors dynamically configure airspace sectors by assigning them to control positions. A finite horizon airspace sector configuration problem models this supervisor decision. The problem is to select an airspace configuration at each time step while considering a workload cost, a reconfiguration cost, and a constraint on the number of control positions at each time step. Three algorithms for this problem are proposed and evaluated: a myopic heuristic, an exact dynamic programming algorithm, and a rollouts approximate dynamic programming algorithm. On problem instances from current operations with only dozens of possible configurations, an exact dynamic programming solution gives the optimal cost value. The rollouts algorithm achieves costs within 2% of optimal for these instances, on average. For larger problem instances that are representative of future operations and have thousands of possible configurations, excessive computation time prohibits the use of exact dynamic programming. On such problem instances, the rollouts algorithm reduces the cost achieved by the heuristic by more than 15% on average with an acceptable computation time.
Dynamic programming in applied optimization problems
NASA Astrophysics Data System (ADS)
Zavalishchin, Dmitry
2015-11-01
Features of the use dynamic programming in applied problems are investigated. In practice such problems as finding the critical paths in network planning and control, finding the optimal supply plan in transportation problem, objects territorial distribution are traditionally solved by special methods of operations research. It should be noted that the dynamic programming is not provided computational advantages, but facilitates changes and modifications of tasks. This follows from the Bellman's optimality principle. The features of the multistage decision processes construction in applied problems are provided.
Dynamic and adaptive data-management in ATLAS
NASA Astrophysics Data System (ADS)
Lassnig, Mario; Garonne, Vincent; Branco, Miguel; Molfetas, Angelos
2010-04-01
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.
Adaptive mesh refinement for 1-dimensional gas dynamics
Hedstrom, G.; Rodrigue, G.; Berger, M.; Oliger, J.
1982-01-01
We consider the solution of the one-dimensional equation of gas-dynamics. Accurate numerical solutions are difficult to obtain on a given spatial mesh because of the existence of physical regions where components of the exact solution are either discontinuous or have large gradient changes. Numerical methods treat these phenomena in a variety of ways. In this paper, the method of adaptive mesh refinement is used. A thorough description of this method for general hyperbolic systems is given elsewhere and only properties of the method pertinent to the system are elaborated.
Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems
NASA Astrophysics Data System (ADS)
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
Experimental Dynamic Characterization of a Reconfigurable Adaptive Precision Truss
NASA Technical Reports Server (NTRS)
Hinkle, J. D.; Peterson, L. D.
1994-01-01
The dynamic behavior of a reconfigurable adaptive truss structure with non-linear joints is investigated. The objective is to experimentally examine the effects of the local non-linearities on the global dynamics of the structure. Amplitude changes in the frequency response functions are measured at micron levels of motion. The amplitude and frequency variations of a number of modes indicate a non-linear Coulomb friction response. Hysteretic bifurcation behavior is also measured at an amplitude approximately equal to the specified free-play in the joint. Under the 1 g pre-load, however, the non-linearity was dominantly characteristic of Coulomb friction with little evidence of free-play stiffening.
Adaptive integral dynamic surface control of a hypersonic flight vehicle
NASA Astrophysics Data System (ADS)
Aslam Butt, Waseem; Yan, Lin; Amezquita S., Kendrick
2015-07-01
In this article, non-linear adaptive dynamic surface air speed and flight path angle control designs are presented for the longitudinal dynamics of a flexible hypersonic flight vehicle. The tracking performance of the control design is enhanced by introducing a novel integral term that caters to avoiding a large initial control signal. To ensure feasibility, the design scheme incorporates magnitude and rate constraints on the actuator commands. The uncertain non-linear functions are approximated by an efficient use of the neural networks to reduce the computational load. A detailed stability analysis shows that all closed-loop signals are uniformly ultimately bounded and the ? tracking performance is guaranteed. The robustness of the design scheme is verified through numerical simulations of the flexible flight vehicle model.
Inter-limb interference during bimanual adaptation to dynamic environments.
Casadio, Maura; Sanguineti, Vittorio; Squeri, Valentina; Masia, Lorenzo; Morasso, Pietro
2010-05-01
Skillful manipulation of objects often requires the spatio-temporal coordination of both hands and, at the same time, the compensation of environmental forces. In bimanual coordination, movements of the two hands may be coupled because each hand needs to compensate the forces generated by the other hand or by an object operated by both hands (dynamic coupling), or because the two hands share the same workspace (spatial coupling). We examined how spatial coupling influences bimanual coordination, by looking at the adaptation of velocity-dependent force fields during a task in which the two hands simultaneously perform center-out reaching movements with the same initial position and the same targets, equally spaced on a circle. Subjects were randomly allocated to two groups, which differed in terms of the force fields they were exposed to: in one group (CW-CW), force fields had equal clockwise orientations in both hands; in the other group (CCW-CW), they had opposite orientations. In both groups, in randomly selected trials (catch trials) of the adaptation phase, the force fields were unexpectedly removed. Adaptation was quantified in terms of the changes of directional error for both hand trajectories. Bimanual coordination was quantified in terms of inter-limb longitudinal and sideways displacements, in force field and in catch trials. Experimental results indicate that both arms could simultaneously adapt to the two force fields. However, in the CCW-CW group, adaptation was incomplete for the movements from the central position to the more distant targets with respect to the body. In addition, in this group the left hand systematically leads in the movements toward targets on the left of the starting position, whereas the right hand leads in the movements to targets on the right. We show that these effects are due to a gradual sideways shift of the hands, so that during movements the left hand tends to consistently remain at the left of the right hand. These
Selective host molecules obtained by dynamic adaptive chemistry.
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.
Efficient dynamic optimization of logic programs
NASA Technical Reports Server (NTRS)
Laird, Phil
1992-01-01
A summary is given of the dynamic optimization approach to speed up learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term 'optimal' relative to the source of input instances and sketch an algorithm that can come within a logarithmic factor of optimal with high probability. Finally, we show that finding high-utility unfolding operations (such as EBG) can be reduced to clause reordering.
Two Characterizations of Optimality in Dynamic Programming
Karatzas, Ioannis; Sudderth, William D.
2010-06-15
It holds in great generality that a plan is optimal for a dynamic programming problem, if and only if it is 'thrifty' and 'equalizing.' An alternative characterization of an optimal plan, that applies in many economic models, is that the plan must satisfy an appropriate Euler equation and a transversality condition. Here we explore the connections between these two characterizations.
Open Groups: Adaptations in Implementing a Parent Training Program
Brock, Donna-Jean P.; Marek, Lydia I.; Matteo-Kerney, Cheryl; Bagby, Tammy
2013-01-01
Background: Programs that focus on positive parenting have been shown to improve parental attitudes, knowledge, and behaviors, and increase parent and child bonding. These programs are typically conducted in a closed group format. However, when individual or community needs are more immediate, programmers sometimes opt for an open group format. To determine the effectiveness of this adaptation to an open group format, the present study compared both groups on parental outcomes. Methods: Both closed and open group formats were offered and implemented between January 2009 and December 2012. Participants for both formats were recruited through similar means and the format placement for each family was determined by the immediacy of the need for an intervention, the time lapse until a new cycle would begin, and scheduling flexibility. Chi-Square analyses were conducted to determine demographic differences between the two groups and gain scores were calculated from the pre- and post-test AAPI-2 scales within a mixed MANOVA to determine group format effectiveness. Results: Though open groups contained higher risk families; parental outcome improvements were significant for both groups. All participants, regardless of group membership, demonstrated the same statistically significant improvements following completion of the program. Conclusion: Findings provide support for adapting group formats when necessary to fit community and individual needs. PMID:24688972
Frequency adaptation for enhanced radiation force amplitude in dynamic elastography.
Ouared, Abderrahmane; Montagnon, Emmanuel; Kazemirad, Siavash; Gaboury, Louis; Robidoux, André; Cloutier, Guy
2015-08-01
In remote dynamic elastography, the amplitude of the generated displacement field is directly related to the amplitude of the radiation force. Therefore, displacement improvement for better tissue characterization requires the optimization of the radiation force amplitude by increasing the push duration and/or the excitation amplitude applied on the transducer. The main problem of these approaches is that the Food and Drug Administration (FDA) thresholds for medical applications and transducer limitations may be easily exceeded. In the present study, the effect of the frequency used for the generation of the radiation force on the amplitude of the displacement field was investigated. We found that amplitudes of displacements generated by adapted radiation force sequences were greater than those generated by standard nonadapted ones (i.e., single push acoustic radiation force impulse and supersonic shear imaging). Gains in magnitude were between 20 to 158% for in vitro measurements on agar-gelatin phantoms, and 170 to 336% for ex vivo measurements on a human breast sample, depending on focus depths and attenuations of tested samples. The signal-to-noise ratio was also improved more than 4-fold with adapted sequences. We conclude that frequency adaptation is a complementary technique that is efficient for the optimization of displacement amplitudes. This technique can be used safely to optimize the deposited local acoustic energy without increasing the risk of damaging tissues and transducer elements.
Structural dynamic health monitoring of adaptive CFRP structures
NASA Astrophysics Data System (ADS)
Kaiser, Stephan; Melcher, Joerg; Breitbach, Elmar J.; Sachau, Delf
1999-07-01
The DLR Institute of Structural Mechanics is engaged in the construction and optimization of adaptive structures for aerospace and terrestrial applications. Due to the FFS- Project, one of the recent works of the Institute is the reduction of buffet induced vibration loads at a fin. The construction of modern aircrafts is influenced b the increasing use of fiber composites. They have more specific stiffness and strength properties than metals. On the other hand the layered structure leads to new kinds of damages like delaminations. In the fin interface there are actuators and sensors integrated. Therefore the fin is connected with a controller. For the extension of this adaptive system towards an on-line tool for health monitoring this controller can be used as an identifier of the structure's modal parameters. The most promising procedure is based on MX filters. These filters constitute the filter coefficients from which a fast transformation procedure extracts the modal parameters. The changes of these parameters are related to the location and extent of the damage. So when using the already integrate controller for system identification, one can have a low-cost on-line damage detection for dynamic adaptive structures. First off-line test at CFRP plates have shown the ability to detect delaminations.
Adaptation tunes cortical dynamics to a critical regime during vision
NASA Astrophysics Data System (ADS)
Shew, Woodrow; Clawson, Wesley; Pobst, Jeff; Karimipanah, Yahya; Wright, Nathaniel; Wessel, Ralf; Shew Lab Team; Wessel Lab Team
2015-03-01
A long-standing hypothesis at the interface of physics and neuroscience is that neural networks self-organize to the critical point of a phase transition, thereby optimizing aspects of sensory information processing. This idea is partially supported by strong evidence for critical dynamics observed in the cerebral cortex, but has not been tested in systems with significant sensory input. Thus, the foundations of this hypothesis - the self-organization process and how it manifests during strong sensory input - remain unstudied experimentally. Here we report microelectrode array measurements from visual cortex of turtles during visual stimulation of the retina. We show experimentally and in a computational model that strong sensory input initially elicits cortical network dynamics that are not critical, but adaptive changes in the network rapidly tune the system to criticality. This conclusion is based on observations of multifaceted scaling laws predicted to occur at criticality. Our findings establish sensory adaptation as a self-organizing mechanism which maintains criticality in visual cortex during sensory information processing. Supported by NSF CRCNS Grant 1308174.
Two stage gear tooth dynamics program
NASA Technical Reports Server (NTRS)
Boyd, Linda S.
1989-01-01
The epicyclic gear dynamics program was expanded to add the option of evaluating the tooth pair dynamics for two epicyclic gear stages with peripheral components. This was a practical extension to the program as multiple gear stages are often used for speed reduction, space, weight, and/or auxiliary units. The option was developed for either stage to be a basic planetary, star, single external-external mesh, or single external-internal mesh. The two stage system allows for modeling of the peripherals with an input mass and shaft, an output mass and shaft, and a connecting shaft. Execution of the initial test case indicated an instability in the solution with the tooth paid loads growing to excessive magnitudes. A procedure to trace the instability is recommended as well as a method of reducing the program's computation time by reducing the number of boundary condition iterations.
Effects of adaptive protective behavior on the dynamics of sexually transmitted infections.
Hayashi, Michael A L; Eisenberg, Marisa C
2016-01-01
Sexually transmitted infections (STIs) continue to present a complex and costly challenge to public health programs. The preferences and social dynamics of a population can have a large impact on the course of an outbreak as well as the effectiveness of interventions intended to influence individual behavior. In addition, individuals may alter their sexual behavior in response to the presence of STIs, creating a feedback loop between transmission and behavior. We investigate the consequences of modeling the interaction between STI transmission and prophylactic use with a model that links a Susceptible-Infectious-Susceptible (SIS) system to evolutionary game dynamics that determine the effective contact rate. The combined model framework allows us to address protective behavior by both infected and susceptible individuals. Feedback between behavioral adaptation and prevalence creates a wide range of dynamic behaviors in the combined model, including damped and sustained oscillations as well as bistability, depending on the behavioral parameters and disease growth rate. We found that disease extinction is possible for multiple regions where R0>1, due to behavior adaptation driving the epidemic downward, although conversely endemic prevalence for arbitrarily low R0 is also possible if contact rates are sufficiently high. We also tested how model misspecification might affect disease forecasting and estimation of the model parameters and R0. We found that alternative models that neglect the behavioral feedback or only consider behavior adaptation by susceptible individuals can potentially yield misleading parameter estimates or omit significant features of the disease trajectory. PMID:26362102
Expansion of epicyclic gear dynamic analysis program
NASA Technical Reports Server (NTRS)
Boyd, Linda Smith; Pike, James A.
1987-01-01
The multiple mesh/single stage dynamics program is a gear tooth analysis program which determines detailed geometry, dynamic loads, stresses, and surface damage factors. The program can analyze a variety of both epicyclic and single mesh systems with spur or helical gear teeth including internal, external, and buttress tooth forms. The modifications refine the options for the flexible carrier and flexible ring gear rim and adds three options: a floating Sun gear option; a natural frequency option; and a finite element compliance formulation for helical gear teeth. The option for a floating Sun incorporates two additional degrees of freedom at the Sun center. The natural frequency option evaluates the frequencies of planetary, star, or differential systems as well as the effect of additional springs at the Sun center and those due to a flexible carrier and/or ring gear rim. The helical tooth pair finite element calculated compliance is obtained from an automated element breakup of the helical teeth and then is used with the basic gear dynamic solution and stress postprocessing routines. The flexible carrier or ring gear rim option for planetary and star spur gear systems allows the output torque per carrier and ring gear rim segment to vary based on the dynamic response of the entire system, while the total output torque remains constant.
Analysis of dynamic deformation processes with adaptive KALMAN-filtering
NASA Astrophysics Data System (ADS)
Eichhorn, Andreas
2007-05-01
In this paper the approach of a full system analysis is shown quantifying a dynamic structural ("white-box"-) model for the calculation of thermal deformations of bar-shaped machine elements. The task was motivated from mechanical engineering searching new methods for the precise prediction and computational compensation of thermal influences in the heating and cooling phases of machine tools (i.e. robot arms, etc.). The quantification of thermal deformations under variable dynamic loads requires the modelling of the non-stationary spatial temperature distribution inside the object. Based upon FOURIERS law of heat flow the high-grade non-linear temperature gradient is represented by a system of partial differential equations within the framework of a dynamic Finite Element topology. It is shown that adaptive KALMAN-filtering is suitable to quantify relevant disturbance influences and to identify thermal parameters (i.e. thermal diffusivity) with a deviation of only 0,2%. As result an identified (and verified) parametric model for the realistic prediction respectively simulation of dynamic temperature processes is presented. Classifying the thermal bend as the main deformation quantity of bar-shaped machine tools, the temperature model is extended to a temperature deformation model. In lab tests thermal load steps are applied to an aluminum column. Independent control measurements show that the identified model can be used to predict the columns bend with a mean deviation (
Dynamic modeling and adaptive control for space stations
NASA Technical Reports Server (NTRS)
Ih, C. H. C.; Wang, S. J.
1985-01-01
Of all large space structural systems, space stations present a unique challenge and requirement to advanced control technology. Their operations require control system stability over an extremely broad range of parameter changes and high level of disturbances. During shuttle docking the system mass may suddenly increase by more than 100% and during station assembly the mass may vary even more drastically. These coupled with the inherent dynamic model uncertainties associated with large space structural systems require highly sophisticated control systems that can grow as the stations evolve and cope with the uncertainties and time-varying elements to maintain the stability and pointing of the space stations. The aspects of space station operational properties are first examined, including configurations, dynamic models, shuttle docking contact dynamics, solar panel interaction, and load reduction to yield a set of system models and conditions. A model reference adaptive control algorithm along with the inner-loop plant augmentation design for controlling the space stations under severe operational conditions of shuttle docking, excessive model parameter errors, and model truncation are then investigated. The instability problem caused by the zero-frequency rigid body modes and a proposed solution using plant augmentation are addressed. Two sets of sufficient conditions which guarantee the globablly asymptotic stability for the space station systems are obtained.
Glassy Dynamics in the Adaptive Immune Response Prevents Autoimmune Disease
NASA Astrophysics Data System (ADS)
Sun, Jun; Deem, Michael
2006-03-01
The immune system normally protects the human host against death by infection. However, when an immune response is mistakenly directed at self antigens, autoimmune disease can occur. We describe a model of protein evolution to simulate the dynamics of the adaptive immune response to antigens. Computer simulations of the dynamics of antibody evolution show that different evolutionary mechanisms, namely gene segment swapping and point mutation, lead to different evolved antibody binding affinities. Although a combination of gene segment swapping and point mutation can yield a greater affinity to a specific antigen than point mutation alone, the antibodies so evolved are highly cross-reactive and would cause autoimmune disease, and this is not the chosen dynamics of the immune system. We suggest that in the immune system a balance has evolved between binding affinity and specificity in the mechanism for searching the amino acid sequence space of antibodies. Our model predicts that chronic infection may lead to autoimmune disease as well due to cross-reactivity and suggests a broad distribution for the time of onset of autoimmune disease due to chronic exposure. The slow search of antibody sequence space by point mutation leads to the broad of distribution times.
Patient-adaptive lesion metabolism analysis by dynamic PET images.
Gao, Fei; Liu, Huafeng; Shi, Pengcheng
2012-01-01
Dynamic PET imaging provides important spatial-temporal information for metabolism analysis of organs and tissues, and generates a great reference for clinical diagnosis and pharmacokinetic analysis. Due to poor statistical properties of the measurement data in low count dynamic PET acquisition and disturbances from surrounding tissues, identifying small lesions inside the human body is still a challenging issue. The uncertainties in estimating the arterial input function will also limit the accuracy and reliability of the metabolism analysis of lesions. Furthermore, the sizes of the patients and the motions during PET acquisition will yield mismatch against general purpose reconstruction system matrix, this will also affect the quantitative accuracy of metabolism analyses of lesions. In this paper, we present a dynamic PET metabolism analysis framework by defining a patient adaptive system matrix to improve the lesion metabolism analysis. Both patient size information and potential small lesions are incorporated by simulations of phantoms of different sizes and individual point source responses. The new framework improves the quantitative accuracy of lesion metabolism analysis, and makes the lesion identification more precisely. The requirement of accurate input functions is also reduced. Experiments are conducted on Monte Carlo simulated data set for quantitative analysis and validation, and on real patient scans for assessment of clinical potential. PMID:23286175
iAPBS: a programming interface to Adaptive Poisson-Boltzmann Solver (APBS).
Konecny, Robert; Baker, Nathan A; McCammon, J Andrew
2012-07-26
The Adaptive Poisson-Boltzmann Solver (APBS) is a state-of-the-art suite for performing Poisson-Boltzmann electrostatic calculations on biomolecules. The iAPBS package provides a modular programmatic interface to the APBS library of electrostatic calculation routines. The iAPBS interface library can be linked with a FORTRAN or C/C++ program thus making all of the APBS functionality available from within the application. Several application modules for popular molecular dynamics simulation packages - Amber, NAMD and CHARMM are distributed with iAPBS allowing users of these packages to perform implicit solvent electrostatic calculations with APBS. PMID:22905037
Nonlinear adaptive trajectory tracking using dynamic neural networks.
Poznyak, A S; Yu, W; Sanchez, E N; Perez, J P
1999-01-01
In this paper the adaptive nonlinear identification and trajectory tracking are discussed via dynamic neural networks. By means of a Lyapunov-like analysis we determine stability conditions for the identification error. Then we analyze the trajectory tracking error by a local optimal controller. An algebraic Riccati equation and a differential one are used for the identification and the tracking error analysis. As our main original contributions, we establish two theorems: the first one gives a bound for the identification error and the second one establishes a bound for the tracking error. We illustrate the effectiveness of these results by two examples: the second-order relay system with multiple isolated equilibrium points and the chaotic system given by Duffing equation. PMID:18252641
Eradication of Ebola Based on Dynamic Programming.
Zhu, Jia-Ming; Wang, Lu; Liu, Jia-Bao
2016-01-01
This paper mainly studies the eradication of the Ebola virus, proposing a scientific system, including three modules for the eradication of Ebola virus. Firstly, we build a basic model combined with nonlinear incidence rate and maximum treatment capacity. Secondly, we use the dynamic programming method and the Dijkstra Algorithm to set up M-S (storage) and several delivery locations in West Africa. Finally, we apply the previous results to calculate the total cost, production cost, storage cost, and shortage cost. PMID:27313655
Eradication of Ebola Based on Dynamic Programming
Zhu, Jia-Ming; Wang, Lu; Liu, Jia-Bao
2016-01-01
This paper mainly studies the eradication of the Ebola virus, proposing a scientific system, including three modules for the eradication of Ebola virus. Firstly, we build a basic model combined with nonlinear incidence rate and maximum treatment capacity. Secondly, we use the dynamic programming method and the Dijkstra Algorithm to set up M-S (storage) and several delivery locations in West Africa. Finally, we apply the previous results to calculate the total cost, production cost, storage cost, and shortage cost. PMID:27313655
PAQ: Persistent Adaptive Query Middleware for Dynamic Environments
NASA Astrophysics Data System (ADS)
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.
Fully Threaded Tree for Adaptive Refinement Fluid Dynamics Simulations
NASA Technical Reports Server (NTRS)
Khokhlov, A. M.
1997-01-01
A fully threaded tree (FTT) for adaptive refinement of regular meshes is described. By using a tree threaded at all levels, tree traversals for finding nearest neighbors are avoided. All operations on a tree including tree modifications are O(N), where N is a number of cells, and are performed in parallel. An efficient implementation of the tree is described that requires 2N words of memory. A filtering algorithm for removing high frequency noise during mesh refinement is described. A FTT can be used in various numerical applications. In this paper, it is applied to the integration of the Euler equations of fluid dynamics. An adaptive mesh time stepping algorithm is described in which different time steps are used at different l evels of the tree. Time stepping and mesh refinement are interleaved to avoid extensive buffer layers of fine mesh which were otherwise required ahead of moving shocks. Test examples are presented, and the FTT performance is evaluated. The three dimensional simulation of the interaction of a shock wave and a spherical bubble is carried out that shows the development of azimuthal perturbations on the bubble surface.
Navigating sensory conflict in dynamic environments using adaptive state estimation.
Klein, Theresa J; Jeka, John; Kiemel, Tim; Lewis, M Anthony
2011-12-01
Most conventional robots rely on controlling the location of the center of pressure to maintain balance, relying mainly on foot pressure sensors for information. By contrast,humans rely on sensory data from multiple sources, including proprioceptive, visual, and vestibular sources. Several models have been developed to explain how humans reconcile information from disparate sources to form a stable sense of balance. These models may be useful for developing robots that are able to maintain dynamic balance more readily using multiple sensory sources. Since these information sources may conflict, reliance by the nervous system on any one channel can lead to ambiguity in the system state. In humans, experiments that create conflicts between different sensory channels by moving the visual field or the support surface indicate that sensory information is adaptively reweighted. Unreliable information is rapidly down-weighted,then gradually up-weighted when it becomes valid again.Human balance can also be studied by building robots that model features of human bodies and testing them under similar experimental conditions. We implement a sensory reweighting model based on an adaptive Kalman filter in abipedal robot, and subject it to sensory tests similar to those used on human subjects. Unlike other implementations of sensory reweighting in robots, our implementation includes vision, by using optic flow to calculate forward rotation using a camera (visual modality), as well as a three-axis gyro to represent the vestibular system (non-visual modality), and foot pressure sensors (proprioceptive modality). Our model estimates measurement noise in real time, which is then used to recompute the Kalman gain on each iteration, improving the ability of the robot to dynamically balance. We observe that we can duplicate many important features of postural sw ay in humans, including automatic sensory reweighting,effects, constant phase with respect to amplitude, and a temporal
Joint Chance-Constrained Dynamic Programming
NASA Technical Reports Server (NTRS)
Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J. Bob
2012-01-01
This paper presents a novel dynamic programming algorithm with a joint chance constraint, which explicitly bounds the risk of failure in order to maintain the state within a specified feasible region. A joint chance constraint cannot be handled by existing constrained dynamic programming approaches since their application is limited to constraints in the same form as the cost function, that is, an expectation over a sum of one-stage costs. We overcome this challenge by reformulating the joint chance constraint into a constraint on an expectation over a sum of indicator functions, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the primal variables can be optimized by a standard dynamic programming, while the dual variable is optimized by a root-finding algorithm that converges exponentially. Error bounds on the primal and dual objective values are rigorously derived. We demonstrate the algorithm on a path planning problem, as well as an optimal control problem for Mars entry, descent and landing. The simulations are conducted using a real terrain data of Mars, with four million discrete states at each time step.
On Cognition, Structured Sequence Processing, and Adaptive Dynamical Systems
NASA Astrophysics Data System (ADS)
Petersson, Karl Magnus
2008-11-01
Cognitive neuroscience approaches the brain as a cognitive system: a system that functionally is conceptualized in terms of information processing. We outline some aspects of this concept and consider a physical system to be an information processing device when a subclass of its physical states can be viewed as representational/cognitive and transitions between these can be conceptualized as a process operating on these states by implementing operations on the corresponding representational structures. We identify a generic and fundamental problem in cognition: sequentially organized structured processing. Structured sequence processing provides the brain, in an essential sense, with its processing logic. In an approach addressing this problem, we illustrate how to integrate levels of analysis within a framework of adaptive dynamical systems. We note that the dynamical system framework lends itself to a description of asynchronous event-driven devices, which is likely to be important in cognition because the brain appears to be an asynchronous processing system. We use the human language faculty and natural language processing as a concrete example through out.
General adaptive guidance using nonlinear programming constraint solving methods (FAST)
NASA Astrophysics Data System (ADS)
Skalecki, Lisa; Martin, Marc
An adaptive, general purpose, constraint solving guidance algorithm called FAST (Flight Algorithm to Solve Trajectories) has been developed by the authors in response to the requirements for the Advanced Launch System (ALS). The FAST algorithm can be used for all mission phases for a wide range of Space Transportation Vehicles without code modification because of the general formulation of the nonlinear programming (NLP) problem, ad the general trajectory simulation used to predict constraint values. The approach allows on board re-targeting for severe weather and changes in payload or mission parameters, increasing flight reliability and dependability while reducing the amount of pre-flight analysis that must be performed. The algorithm is described in general in this paper. Three degree of freedom simulation results are presented for application of the algorithm to ascent and reentry phases of an ALS mission, and Mars aerobraking. Flight processor CPU requirement data is also shown.
Dynamic stability of sequential stimulus representations in adapting neuronal networks
Duarte, Renato C. F.; Morrison, Abigail
2014-01-01
The ability to acquire and maintain appropriate representations of time-varying, sequential stimulus events is a fundamental feature of neocortical circuits and a necessary first step toward more specialized information processing. The dynamical properties of such representations depend on the current state of the circuit, which is determined primarily by the ongoing, internally generated activity, setting the ground state from which input-specific transformations emerge. Here, we begin by demonstrating that timing-dependent synaptic plasticity mechanisms have an important role to play in the active maintenance of an ongoing dynamics characterized by asynchronous and irregular firing, closely resembling cortical activity in vivo. Incoming stimuli, acting as perturbations of the local balance of excitation and inhibition, require fast adaptive responses to prevent the development of unstable activity regimes, such as those characterized by a high degree of population-wide synchrony. We establish a link between such pathological network activity, which is circumvented by the action of plasticity, and a reduced computational capacity. Additionally, we demonstrate that the action of plasticity shapes and stabilizes the transient network states exhibited in the presence of sequentially presented stimulus events, allowing the development of adequate and discernible stimulus representations. The main feature responsible for the increased discriminability of stimulus-driven population responses in plastic networks is shown to be the decorrelating action of inhibitory plasticity and the consequent maintenance of the asynchronous irregular dynamic regime both for ongoing activity and stimulus-driven responses, whereas excitatory plasticity is shown to play only a marginal role. PMID:25374534
Algebraic Dynamic Programming over general data structures
2015-01-01
Background Dynamic programming algorithms provide exact solutions to many problems in computational biology, such as sequence alignment, RNA folding, hidden Markov models (HMMs), and scoring of phylogenetic trees. Structurally analogous algorithms compute optimal solutions, evaluate score distributions, and perform stochastic sampling. This is explained in the theory of Algebraic Dynamic Programming (ADP) by a strict separation of state space traversal (usually represented by a context free grammar), scoring (encoded as an algebra), and choice rule. A key ingredient in this theory is the use of yield parsers that operate on the ordered input data structure, usually strings or ordered trees. The computation of ensemble properties, such as a posteriori probabilities of HMMs or partition functions in RNA folding, requires the combination of two distinct, but intimately related algorithms, known as the inside and the outside recursion. Only the inside recursions are covered by the classical ADP theory. Results The ideas of ADP are generalized to a much wider scope of data structures by relaxing the concept of parsing. This allows us to formalize the conceptual complementarity of inside and outside variables in a natural way. We demonstrate that outside recursions are generically derivable from inside decomposition schemes. In addition to rephrasing the well-known algorithms for HMMs, pairwise sequence alignment, and RNA folding we show how the TSP and the shortest Hamiltonian path problem can be implemented efficiently in the extended ADP framework. As a showcase application we investigate the ancient evolution of HOX gene clusters in terms of shortest Hamiltonian paths. Conclusions The generalized ADP framework presented here greatly facilitates the development and implementation of dynamic programming algorithms for a wide spectrum of applications. PMID:26695390
Influence of adaptation on the nonlinear dynamics of a system of competing populations
NASA Astrophysics Data System (ADS)
Dimitrova, Zlatinka I.; Vitanov, Nikolay K.
2000-08-01
We investigate the nonlinear dynamics of a system of populations competing for the same limited resource assuming that they can adapt their growth rates and competition coefficients with respect to the number of individuals of each population. The adaptation leads to an enrichment of the nonlinear dynamics of the system which is demonstrated by a discussion of new orbits in the phase space of the system, completely dependent on the adaptation parameters, as well as by an investigation of the influence of the adaptation parameters on the dynamics of a strange attractor of the model system of ODEs.
A Knowledge-Structure-Based Adaptive Dynamic Assessment System for Calculus Learning
ERIC Educational Resources Information Center
Ting, M.-Y.; Kuo, B.-C.
2016-01-01
The purpose of this study was to investigate the effect of a calculus system that was designed using an adaptive dynamic assessment (DA) framework on performance in the "finding an area using an integral". In this study, adaptive testing and dynamic assessment were combined to provide different test items depending on students'…
Population dynamics determine genetic adaptation to temperature in Daphnia.
Van Doorslaer, Wendy; Stoks, Robby; Duvivier, Cathy; Bednarska, Anna; De Meester, Luc
2009-07-01
Rising temperatures associated with global warming present a challenge to the fate of many aquatic organisms. Although rapid evolutionary response to temperature-mediated selection may allow local persistence of populations under global warming, and therefore is a key aspect of evolutionary biology, solid proof of its occurrence is rare. In this study, we tested for genetic adaptation to an increase in temperature in the water flea Daphnia magna, a keystone species in freshwater systems, by performing a thermal selection experiment under laboratory conditions followed by the quantification of microevolutionary responses to temperature for both life-history traits as well as for intraspecific competitive strength. After three months of selection, we found a microevolutionary response to temperature in performance, but only in one of two culling regimes, highlighting the importance of population dynamics in driving microevolutionary change within populations. Furthermore, there was an evolutionary increase in thermal plasticity in performance. The results of the competition experiment were in agreement with predictions based on performance as quantified in the life table experiment and illustrate that microevolution within a short time frame has the ability to influence the outcome of intraspecific competition.
Dynamic adaptation of the peripheral circulation to cold exposure.
Cheung, Stephen S; Daanen, Hein A M
2012-01-01
Humans residing or working in cold environments exhibit a stronger cold-induced vasodilation (CIVD) reaction in the peripheral microvasculature than those living in warm regions of the world, leading to a general assumption that thermal responses to local cold exposure can be systematically improved by natural acclimatization or specific acclimation. However, it remains unclear whether this improved tolerance is actually due to systematic acclimatization, or alternately due to the genetic pre-disposition or self-selection for such occupations. Longitudinal studies of repeated extremity exposure to cold demonstrate only ambiguous adaptive responses. In field studies, general cold acclimation may lead to increased sympathetic activity that results in reduced finger blood flow. Laboratory studies offer more control over confounding parameters, but in most studies, no consistent changes in peripheral blood flow occur even after repeated exposure for several weeks. Most studies are performed on a limited amount of subjects only, and the variability of the CIVD response demands more subjects to obtain significant results. This review systematically surveys the trainability of CIVD, concluding that repeated local cold exposure does not alter circulatory dynamics in the peripheries, and that humans remain at risk of cold injuries even after extended stays in cold environments.
Dynamics of adaptive immunity against phage in bacterial populations
NASA Astrophysics Data System (ADS)
Bradde, Serena; Vucelja, Marija; Tesileanu, Tiberiu; Balasubramanian, Vijay
The CRISPR (clustered regularly interspaced short palindromic repeats) mechanism allows bacteria to adaptively defend against phages by acquiring short genomic sequences (spacers) that target specific sequences in the viral genome. We propose a population dynamical model where immunity can be both acquired and lost. The model predicts regimes where bacterial and phage populations can co-exist, others where the populations oscillate, and still others where one population is driven to extinction. Our model considers two key parameters: (1) ease of acquisition and (2) spacer effectiveness in conferring immunity. Analytical calculations and numerical simulations show that if spacers differ mainly in ease of acquisition, or if the probability of acquiring them is sufficiently high, bacteria develop a diverse population of spacers. On the other hand, if spacers differ mainly in their effectiveness, their final distribution will be highly peaked, akin to a ``winner-take-all'' scenario, leading to a specialized spacer distribution. Bacteria can interpolate between these limiting behaviors by actively tuning their overall acquisition rate.
Plant toxicity, adaptive herbivory, and plant community dynamics
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.
ERIC Educational Resources Information Center
Olson, Jonathan R.; Welsh, Janet A.; Perkins, Daniel F.
2015-01-01
In this article, we describe how the recent movement towards evidence-based programming has impacted Extension. We review how the emphasis on implementing such programs with strict fidelity to an underlying program model may be at odds with Extension's strong history of adapting programming to meet the unique needs of children, youth, families,…
Automated Flight Routing Using Stochastic Dynamic Programming
NASA Technical Reports Server (NTRS)
Ng, Hok K.; Morando, Alex; Grabbe, Shon
2010-01-01
Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.
Runway Scheduling Using Generalized Dynamic Programming
NASA Technical Reports Server (NTRS)
Montoya, Justin; Wood, Zachary; Rathinam, Sivakumar
2011-01-01
A generalized dynamic programming method for finding a set of pareto optimal solutions for a runway scheduling problem is introduced. The algorithm generates a set of runway fight sequences that are optimal for both runway throughput and delay. Realistic time-based operational constraints are considered, including miles-in-trail separation, runway crossings, and wake vortex separation. The authors also model divergent runway takeoff operations to allow for reduced wake vortex separation. A modeled Dallas/Fort Worth International airport and three baseline heuristics are used to illustrate preliminary benefits of using the generalized dynamic programming method. Simulated traffic levels ranged from 10 aircraft to 30 aircraft with each test case spanning 15 minutes. The optimal solution shows a 40-70 percent decrease in the expected delay per aircraft over the baseline schedulers. Computational results suggest that the algorithm is promising for real-time application with an average computation time of 4.5 seconds. For even faster computation times, two heuristics are developed. As compared to the optimal, the heuristics are within 5% of the expected delay per aircraft and 1% of the expected number of runway operations per hour ad can be 100x faster.
Thom, Ronald M.; Anderson, Michael G.; Tyre, Drew; Fleming, Craig A.
2009-02-28
The paper, “Adaptive Management: Background for Stakeholders in the Missouri River Recovery Program,” introduced the concept of adaptive management (AM), its principles and how they relate to one-another, how AM is applied, and challenges for its implementation. This companion paper describes how the AM principles were applied to specific management actions within the Missouri River Recovery Program to facilitate understanding, decision-making, and stakeholder engagement. For context, we begin with a brief synopsis of the Missouri River Recovery Program (MRRP) and the strategy for implementing adaptive management (AM) within the program; we finish with an example of AM in action within Phase I of the MRPP.
Dynamic programming algorithm for detecting dim infrared moving targets
NASA Astrophysics Data System (ADS)
He, Lisha; Mao, Liangjing; Xie, Lijun
2009-10-01
Infrared (IR) target detection is a key part of airborne infrared weapon system, especially the detection of poor dim moving IR target embedded in complex context. This paper presents an improved Dynamic Programming (DP) algorithm in allusion to low Signal to Noise Ratio (SNR) infrared dim moving targets under cluttered context. The algorithm brings the dim target to prominence by accumulating the energy of pixels in the image sequence, after suppressing the background noise with a mathematical morphology preprocessor. As considering the continuity and stabilization of target's energy and forward direction, this algorithm has well solved the energy scattering problem that exists in the original DP algorithm. An effective energy segmentation threshold is given by a Contrast-Limited Adaptive Histogram Equalization (CLAHE) filter with a regional peak extraction algorithm. Simulation results show that the improved DP tracking algorithm performs well in detecting poor dim targets.
Goal representation heuristic dynamic programming on maze navigation.
Ni, Zhen; He, Haibo; Wen, Jinyu; Xu, Xin
2013-12-01
Goal representation heuristic dynamic programming (GrHDP) is proposed in this paper to demonstrate online learning in the Markov decision process. In addition to the (external) reinforcement signal in literature, we develop an adaptively internal goal/reward representation for the agent with the proposed goal network. Specifically, we keep the actor-critic design in heuristic dynamic programming (HDP) and include a goal network to represent the internal goal signal, to further help the value function approximation. We evaluate our proposed GrHDP algorithm on two 2-D maze navigation problems, and later on one 3-D maze navigation problem. Compared to the traditional HDP approach, the learning performance of the agent is improved with our proposed GrHDP approach. In addition, we also include the learning performance with two other reinforcement learning algorithms, namely Sarsa(λ) and Q-learning, on the same benchmarks for comparison. Furthermore, in order to demonstrate the theoretical guarantee of our proposed method, we provide the characteristics analysis toward the convergence of weights in neural networks in our GrHDP approach. PMID:24805221
Goal representation heuristic dynamic programming on maze navigation.
Ni, Zhen; He, Haibo; Wen, Jinyu; Xu, Xin
2013-12-01
Goal representation heuristic dynamic programming (GrHDP) is proposed in this paper to demonstrate online learning in the Markov decision process. In addition to the (external) reinforcement signal in literature, we develop an adaptively internal goal/reward representation for the agent with the proposed goal network. Specifically, we keep the actor-critic design in heuristic dynamic programming (HDP) and include a goal network to represent the internal goal signal, to further help the value function approximation. We evaluate our proposed GrHDP algorithm on two 2-D maze navigation problems, and later on one 3-D maze navigation problem. Compared to the traditional HDP approach, the learning performance of the agent is improved with our proposed GrHDP approach. In addition, we also include the learning performance with two other reinforcement learning algorithms, namely Sarsa(λ) and Q-learning, on the same benchmarks for comparison. Furthermore, in order to demonstrate the theoretical guarantee of our proposed method, we provide the characteristics analysis toward the convergence of weights in neural networks in our GrHDP approach.
A mathematical programming approach for sequential clustering of dynamic networks
NASA Astrophysics Data System (ADS)
Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia
2016-02-01
A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.
Cultural Adaptation of the Strengthening Families Program 10-14 to Italian Families
ERIC Educational Resources Information Center
Ortega, Enrique; Giannotta, Fabrizia; Latina, Delia; Ciairano, Silvia
2012-01-01
Background: The family context has proven to be a useful target in which to apply prevention efforts aimed at child and adolescent health risk behaviors. There are currently a variety of cultural adaptation models that serve to guide the international adaptation of intervention programs. Objective: The cultural adaptation process and program…
ALEGRA -- A massively parallel h-adaptive code for solid dynamics
Summers, R.M.; Wong, M.K.; Boucheron, E.A.; Weatherby, J.R.
1997-12-31
ALEGRA is a multi-material, arbitrary-Lagrangian-Eulerian (ALE) code for solid dynamics designed to run on massively parallel (MP) computers. It combines the features of modern Eulerian shock codes, such as CTH, with modern Lagrangian structural analysis codes using an unstructured grid. ALEGRA is being developed for use on the teraflop supercomputers to conduct advanced three-dimensional (3D) simulations of shock phenomena important to a variety of systems. ALEGRA was designed with the Single Program Multiple Data (SPMD) paradigm, in which the mesh is decomposed into sub-meshes so that each processor gets a single sub-mesh with approximately the same number of elements. Using this approach the authors have been able to produce a single code that can scale from one processor to thousands of processors. A current major effort is to develop efficient, high precision simulation capabilities for ALEGRA, without the computational cost of using a global highly resolved mesh, through flexible, robust h-adaptivity of finite elements. H-adaptivity is the dynamic refinement of the mesh by subdividing elements, thus changing the characteristic element size and reducing numerical error. The authors are working on several major technical challenges that must be met to make effective use of HAMMER on MP computers.
Versatile and declarative dynamic programming using pair algebras
Steffen, Peter; Giegerich, Robert
2005-01-01
Background Dynamic programming is a widely used programming technique in bioinformatics. In sharp contrast to the simplicity of textbook examples, implementing a dynamic programming algorithm for a novel and non-trivial application is a tedious and error prone task. The algebraic dynamic programming approach seeks to alleviate this situation by clearly separating the dynamic programming recurrences and scoring schemes. Results Based on this programming style, we introduce a generic product operation of scoring schemes. This leads to a remarkable variety of applications, allowing us to achieve optimizations under multiple objective functions, alternative solutions and backtracing, holistic search space analysis, ambiguity checking, and more, without additional programming effort. We demonstrate the method on several applications for RNA secondary structure prediction. Conclusion The product operation as introduced here adds a significant amount of flexibility to dynamic programming. It provides a versatile testbed for the development of new algorithmic ideas, which can immediately be put to practice. PMID:16156887
Adaptive Competency Acquisition: Why LPN-to-ADN Career Mobility Education Programs Work.
ERIC Educational Resources Information Center
Coyle-Rogers, Patricia G.
Adaptive competencies are the skills required to effectively complete a particular task and are the congruencies (balance) between personal skills and task demands. The differences between the adaptive competency acquisition of students in licensed practical nurse (LPN) programs and associate degree nurse (ADN) programs were examined in a…
ERIC Educational Resources Information Center
Massachusetts Inst. of Tech., Cambridge. Dept. of Urban Studies and Planning.
The report of Project ADAPT (Aerospace and Defense Adaptation to Public Technology), describes the design, execution, and forthcoming evaluation of the program. The program's objective was to demonstrate the feasibility of redeploying surplus technical manpower into public service at State and local levels of government. The development of the…
Adaptive control in the presence of unmodeled dynamics. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Rohrs, C. E.
1982-01-01
Stability and robustness properties of a wide class of adaptive control algorithms in the presence of unmodeled dynamics and output disturbances were investigated. The class of adaptive algorithms considered are those commonly referred to as model reference adaptive control algorithms, self-tuning controllers, and dead beat adaptive controllers, developed for both continuous-time systems and discrete-time systems. A unified analytical approach was developed to examine the class of existing adaptive algorithms. It was discovered that all existing algorithms contain an infinite gain operator in the dynamic system that defines command reference errors and parameter errors; it is argued that such an infinite gain operator appears to be generic to all adaptive algorithms, whether they exhibit explicit or implicit parameter identification. It is concluded that none of the adaptive algorithms considered can be used with confidence in a practical control system design, because instability will set in with a high probability.
Pareto optimization in algebraic dynamic programming.
Saule, Cédric; Giegerich, Robert
2015-01-01
Pareto optimization combines independent objectives by computing the Pareto front of its search space, defined as the set of all solutions for which no other candidate solution scores better under all objectives. This gives, in a precise sense, better information than an artificial amalgamation of different scores into a single objective, but is more costly to compute. Pareto optimization naturally occurs with genetic algorithms, albeit in a heuristic fashion. Non-heuristic Pareto optimization so far has been used only with a few applications in bioinformatics. We study exact Pareto optimization for two objectives in a dynamic programming framework. We define a binary Pareto product operator [Formula: see text] on arbitrary scoring schemes. Independent of a particular algorithm, we prove that for two scoring schemes A and B used in dynamic programming, the scoring scheme [Formula: see text] correctly performs Pareto optimization over the same search space. We study different implementations of the Pareto operator with respect to their asymptotic and empirical efficiency. Without artificial amalgamation of objectives, and with no heuristics involved, Pareto optimization is faster than computing the same number of answers separately for each objective. For RNA structure prediction under the minimum free energy versus the maximum expected accuracy model, we show that the empirical size of the Pareto front remains within reasonable bounds. Pareto optimization lends itself to the comparative investigation of the behavior of two alternative scoring schemes for the same purpose. For the above scoring schemes, we observe that the Pareto front can be seen as a composition of a few macrostates, each consisting of several microstates that differ in the same limited way. We also study the relationship between abstract shape analysis and the Pareto front, and find that they extract information of a different nature from the folding space and can be meaningfully combined.
University of Rhode Island Adapted Aquatics Program Manual. Second Edition.
ERIC Educational Resources Information Center
Bloomquist, Lorraine E.
This manual provides guidelines for aquatic teachers of people with disabilities. It is based on experience in teaching American Red Cross Adapted Aquatics and is to be used to complement and accompany the Red Cross Adapted Aquatics materials. Emphasis is placed on successful experiences in a positive, safe, reinforcing environment stressing…
Evolution of taxis responses in virtual bacteria: non-adaptive dynamics.
Goldstein, Richard A; Soyer, Orkun S
2008-05-23
Bacteria are able to sense and respond to a variety of external stimuli, with responses that vary from stimuli to stimuli and from species to species. The best-understood is chemotaxis in the model organism Escherichia coli, where the dynamics and the structure of the underlying pathway are well characterised. It is not clear, however, how well this detailed knowledge applies to mechanisms mediating responses to other stimuli or to pathways in other species. Furthermore, there is increasing experimental evidence that bacteria integrate responses from different stimuli to generate a coherent taxis response. We currently lack a full understanding of the different pathway structures and dynamics and how this integration is achieved. In order to explore different pathway structures and dynamics that can underlie taxis responses in bacteria, we perform a computational simulation of the evolution of taxis. This approach starts with a population of virtual bacteria that move in a virtual environment based on the dynamics of the simple biochemical pathways they harbour. As mutations lead to changes in pathway structure and dynamics, bacteria better able to localise with favourable conditions gain a selective advantage. We find that a certain dynamics evolves consistently under different model assumptions and environments. These dynamics, which we call non-adaptive dynamics, directly couple tumbling probability of the cell to increasing stimuli. Dynamics that are adaptive under a wide range of conditions, as seen in the chemotaxis pathway of E. coli, do not evolve in these evolutionary simulations. However, we find that stimulus scarcity and fluctuations during evolution results in complex pathway dynamics that result both in adaptive and non-adaptive dynamics depending on basal stimuli levels. Further analyses of evolved pathway structures show that effective taxis dynamics can be mediated with as few as two components. The non-adaptive dynamics mediating taxis responses
Yang, Cheng-Hsiung; Wu, Cheng-Lin
2014-01-01
An adaptive control scheme is developed to study the generalized adaptive chaos synchronization with uncertain chaotic parameters behavior between two identical chaotic dynamic systems. This generalized adaptive chaos synchronization controller is designed based on Lyapunov stability theory and an analytic expression of the adaptive controller with its update laws of uncertain chaotic parameters is shown. The generalized adaptive synchronization with uncertain parameters between two identical new Lorenz-Stenflo systems is taken as three examples to show the effectiveness of the proposed method. The numerical simulations are shown to verify the results. PMID:25295292
Dynamic Adaptive Runtime Systems for Advanced Multipole Method-based Science Achievement
NASA Astrophysics Data System (ADS)
Debuhr, Jackson; Anderson, Matthew; Sterling, Thomas; Zhang, Bo
2015-04-01
Multipole methods are a key computational kernel for a large class of scientific applications spanning multiple disciplines. Yet many of these applications are strong scaling constrained when using conventional programming practices. Hardware parallelism continues to grow, emphasizing medium and fine-grained thread parallelism rather than the coarse-grained process parallelism favored by conventional programming practices. Emerging, dynamic task management execution models can go beyond these conventional practices to significantly improve both efficiency and scalability for algorithms like multipole methods which exhibit irregular and time-varying execution properties. We present a new scientific library, DASHMM, built on the ParalleX HPX-5 runtime system, which explores the use of dynamic adaptive runtime techniques to improve scalability and efficiency for multipole-method based scientific computing. DASHMM allows application scientists to rapidly create custom, scalable, and efficient multipole methods, especially targeting the Fast Multipole Method and the Barnes-Hut N-body algorithm. After a discussion of the system and its goals, some application examples will be presented.
Tao, Ye; Xu, Lijia; Zhang, Zhen; Chen, Runfeng; Li, Huanhuan; Xu, Hui; Zheng, Chao; Huang, Wei
2016-08-01
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. PMID:27403886
A Simulation Program for Dynamic Infrared (IR) Spectra
ERIC Educational Resources Information Center
Zoerb, Matthew C.; Harris, Charles B.
2013-01-01
A free program for the simulation of dynamic infrared (IR) spectra is presented. The program simulates the spectrum of two exchanging IR peaks based on simple input parameters. Larger systems can be simulated with minor modifications. The program is available as an executable program for PCs or can be run in MATLAB on any operating system. Source…
Chromatic adaptation-based tone reproduction for high-dynamic-range imaging
NASA Astrophysics Data System (ADS)
Lee, Joohyun; Jeon, Gwanggil; Jeong, Jechang
2009-10-01
We present an adaptive tone reproduction algorithm for displaying high-dynamic-range (HDR) images on conventional low-dynamic-range (LDR) display devices. The proposed algorithm consists of an adaptive tone reproduction operator and chromatic adaptation. The algorithm for dynamic range reduction relies on suitable tone reproduction functions that depend on histogram-based parameter estimation to adjust luminance according to global and local features. Instead of relying only on reduction of dynamic range, this chromatic adaption technique also preserves chromatic appearance and color consistency across scene and display environments. Our experimental results demonstrate that the proposed algorithm achieves good subjective quality while preserving image details. Furthermore, the proposed algorithm is simple and practical for implementation.
A mathematical programming approach to stochastic and dynamic optimization problems
Bertsimas, D.
1994-12-31
We propose three ideas for constructing optimal or near-optimal policies: (1) for systems for which we have an exact characterization of the performance space we outline an adaptive greedy algorithm that gives rise to indexing policies (we illustrate this technique in the context of indexable systems); (2) we use integer programming to construct policies from the underlying descriptions of the performance space (we illustrate this technique in the context of polling systems); (3) we use linear control over polyhedral regions to solve deterministic versions for this class of problems. This approach gives interesting insights for the structure of the optimal policy (we illustrate this idea in the context of multiclass queueing networks). The unifying theme in the paper is the thesis that better formulations lead to deeper understanding and better solution methods. Overall the proposed approach for stochastic and dynamic optimization parallels efforts of the mathematical programming community in the last fifteen years to develop sharper formulations (polyhedral combinatorics and more recently nonlinear relaxations) and leads to new insights ranging from a complete characterization and new algorithms for indexable systems to tight lower bounds and new algorithms with provable a posteriori guarantees for their suboptimality for polling systems, multiclass queueing and loss networks.
Lake eutrophication management modeling using dynamic programming.
Kuo, Jan-Tai; Hsieh, Pin-Hui; Jou, Wei-Shin
2008-09-01
Lake eutrophication problems have received considerable attention in Taiwan, especially because they relate to the quality of drinking water. In this study, steady-state river water quality and lake eutrophication models are solved using dynamic programming algorithms to find the nutrient removal rates for eutrophication control during dry season. The kinetic cycle of chlorophyll-a, phosphorus and nitrogen for a complete-mixed lake is considered in the optimization framework. The Newton-iterative technique is adopted to solve the nonlinear equations for the steady-state lake eutrophication model. The optimization framework is applied to Cheng-Ching Lake in southern Taiwan. Several nutrient loading scenarios for eutrophication control are studied. Optimization results for nutrient removal rates and corresponding wastewater treatment capacities of each reach of the Kao-Ping River define the least cost approach to lake eutrophication control. A natural purification method, structural free water surface wetland, is also suggested to save more investment and improve river water quality at the same time.
STAR adaptation of QR algorithm. [program for solving over-determined systems of linear equations
NASA Technical Reports Server (NTRS)
Shah, S. N.
1981-01-01
The QR algorithm used on a serial computer and executed on the Control Data Corporation 6000 Computer was adapted to execute efficiently on the Control Data STAR-100 computer. How the scalar program was adapted for the STAR-100 and why these adaptations yielded an efficient STAR program is described. Program listings of the old scalar version and the vectorized SL/1 version are presented in the appendices. Execution times for the two versions applied to the same system of linear equations, are compared.
Adaptive-mesh algorithms for computational fluid dynamics
NASA Technical Reports Server (NTRS)
Powell, Kenneth G.; Roe, Philip L.; Quirk, James
1993-01-01
The basic goal of adaptive-mesh algorithms is to distribute computational resources wisely by increasing the resolution of 'important' regions of the flow and decreasing the resolution of regions that are less important. While this goal is one that is worthwhile, implementing schemes that have this degree of sophistication remains more of an art than a science. In this paper, the basic pieces of adaptive-mesh algorithms are described and some of the possible ways to implement them are discussed and compared. These basic pieces are the data structure to be used, the generation of an initial mesh, the criterion to be used to adapt the mesh to the solution, and the flow-solver algorithm on the resulting mesh. Each of these is discussed, with particular emphasis on methods suitable for the computation of compressible flows.
Techniques for grid manipulation and adaptation. [computational fluid dynamics
NASA Technical Reports Server (NTRS)
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.
Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)
2012-05-31
The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.
2014-01-01
Background Anastrepha fraterculus is one of the most important fruit fly plagues in the American continent and only chemical control is applied in the field to diminish its population densities. A better understanding of the genetic variability during the introduction and adaptation of wild A. fraterculus populations to laboratory conditions is required for the development of stable and vigorous experimental colonies and mass-reared strains in support of successful Sterile Insect Technique (SIT) efforts. Methods The present study aims to analyze the dynamics of changes in genetic variability during the first six generations under artificial rearing conditions in two populations: a) a wild population recently introduced to laboratory culture, named TW and, b) a long-established control line, named CL. Results Results showed a declining tendency of genetic variability in TW. In CL, the relatively high values of genetic variability appear to be maintained across generations and could denote an intrinsic capacity to avoid the loss of genetic diversity in time. Discussion The impact of evolutionary forces on this species during the adaptation process as well as the best approach to choose strategies to introduce experimental and mass-reared A. fraterculus strains for SIT programs are discussed. PMID:25471362
Adapting a Multifaceted U.S. HIV Prevention Education Program for Girls in Ghana
ERIC Educational Resources Information Center
Fiscian, Vivian Sarpomaa; Obeng, E. Kwame; Goldstein, Karen; Shea, Judy A.; Turner, Barbara J.
2009-01-01
We adapted a U.S. HIV prevention program to address knowledge gaps and cultural pressures that increase the risk of infection in adolescent Ghanaian girls. The theory-based nine-module HIV prevention program combines didactics and games, an interactive computer program about sugar daddies, and tie-and-dye training to demonstrate an economic…
PSF halo reduction in adaptive optics using dynamic pupil masking.
Osborn, James; Myers, Richard M; Love, Gordon D
2009-09-28
We describe a method to reduce residual speckles in an adaptive optics system which add to the halo of the point spread function (PSF). The halo is particularly problematic in astronomical applications involving the detection of faint companions. Areas of the pupil are selected where the residual wavefront aberrations are large and these are masked using a spatial light modulator. The method is also suitable for smaller telescopes without adaptive optics as a relatively simple method to increase the resolution of the telescope. We describe the principle of the technique and show simulation results. PMID:19907514
PSF halo reduction in adaptive optics using dynamic pupil masking.
Osborn, James; Myers, Richard M; Love, Gordon D
2009-09-28
We describe a method to reduce residual speckles in an adaptive optics system which add to the halo of the point spread function (PSF). The halo is particularly problematic in astronomical applications involving the detection of faint companions. Areas of the pupil are selected where the residual wavefront aberrations are large and these are masked using a spatial light modulator. The method is also suitable for smaller telescopes without adaptive optics as a relatively simple method to increase the resolution of the telescope. We describe the principle of the technique and show simulation results.
Computer simulation program is adaptable to industrial processes
NASA Technical Reports Server (NTRS)
Schultz, F. E.
1966-01-01
The Reaction kinetics ablation program /REKAP/, developed to simulate ablation of various materials, provides mathematical formulations for computer programs which can simulate certain industrial processes. The programs are based on the use of nonsymmetrical difference equations that are employed to solve complex partial differential equation systems.
Adapting GNU random forest program for Unix and Windows
NASA Astrophysics Data System (ADS)
Jirina, Marcel; Krayem, M. Said; Jirina, Marcel, Jr.
2013-10-01
The Random Forest is a well-known method and also a program for data clustering and classification. Unfortunately, the original Random Forest program is rather difficult to use. Here we describe a new version of this program originally written in Fortran 77. The modified program in Fortran 95 needs to be compiled only once and information for different tasks is passed with help of arguments. The program was tested with 24 data sets from UCI MLR and results are available on the net.
Sims, Katharine R E; Alix-Garcia, Jennifer M; Shapiro-Garza, Elizabeth; Fine, Leah R; Radeloff, Volker C; Aronson, Glen; Castillo, Selene; Ramirez-Reyes, Carlos; Yañez-Pagans, Patricia
2014-10-01
Natural resource managers are often expected to achieve both environmental protection and economic development even when there are fundamental trade-offs between these goals. Adaptive management provides a theoretical structure for program administrators to balance social priorities in the presence of trade-offs and to improve conservation targeting. We used the case of Mexico's federal Payments for Hydrological Services program (PSAH) to illustrate the importance of adaptive management for improving program targeting. We documented adaptive elements of PSAH and corresponding changes in program eligibility and selection criteria. To evaluate whether these changes resulted in enrollment of lands of high environmental and social priority, we compared the environmental and social characteristics of the areas enrolled in the program with the characteristics of all forested areas in Mexico, all areas eligible for the program, and all areas submitted for application to the program. The program successfully enrolled areas of both high ecological and social priority, and over time, adaptive changes in the program's criteria for eligibility and selection led to increased enrollment of land scoring high on both dimensions. Three factors facilitated adaptive management in Mexico and are likely to be generally important for conservation managers: a supportive political environment, including financial backing and encouragement to experiment from the federal government; availability of relatively good social and environmental data; and active participation in the review process by stakeholders and outside evaluators.
Sims, Katharine R E; Alix-Garcia, Jennifer M; Shapiro-Garza, Elizabeth; Fine, Leah R; Radeloff, Volker C; Aronson, Glen; Castillo, Selene; Ramirez-Reyes, Carlos; Yañez-Pagans, Patricia
2014-10-01
Natural resource managers are often expected to achieve both environmental protection and economic development even when there are fundamental trade-offs between these goals. Adaptive management provides a theoretical structure for program administrators to balance social priorities in the presence of trade-offs and to improve conservation targeting. We used the case of Mexico's federal Payments for Hydrological Services program (PSAH) to illustrate the importance of adaptive management for improving program targeting. We documented adaptive elements of PSAH and corresponding changes in program eligibility and selection criteria. To evaluate whether these changes resulted in enrollment of lands of high environmental and social priority, we compared the environmental and social characteristics of the areas enrolled in the program with the characteristics of all forested areas in Mexico, all areas eligible for the program, and all areas submitted for application to the program. The program successfully enrolled areas of both high ecological and social priority, and over time, adaptive changes in the program's criteria for eligibility and selection led to increased enrollment of land scoring high on both dimensions. Three factors facilitated adaptive management in Mexico and are likely to be generally important for conservation managers: a supportive political environment, including financial backing and encouragement to experiment from the federal government; availability of relatively good social and environmental data; and active participation in the review process by stakeholders and outside evaluators. PMID:25039240
Atkinson, A.J.; Trenham, P.C.; Fisher, R.N.; Hathaway, S.A.; Johnson, B.S.; Torres, S.G.; Moore, Y.C.
2004-01-01
critical management uncertainties; and 3) implementing long-term monitoring and adaptive management. Ultimately, the success of regional conservation planning depends on the ability of monitoring programs to confront the challenges of adaptively managing and monitoring complex ecosystems and diverse arrays of sensitive species.
ERIC Educational Resources Information Center
Van Hasselt, Vincent B.; Schlessinger, Kari M.; DiCicco, Tina M.; Anzalone, William F.; Leslie, Tricia L.; George, John A.; Werder, Edward J.; Massey, Larry L.
2006-01-01
The present study provides preliminary data concerning the efficacy of the Adolescent Drug Abuse Prevention and Treatment (ADAPT) Program, a collaborative effort involving mental health and law enforcement. ADAPT is a multi-component, cognitive-behavioral outpatient intervention serving children and youth referred directly from local police…
An Extension Education Program to Help Local Governments with Flood Adaptation
ERIC Educational Resources Information Center
Gary, Gretchen; Allred, Shorna; LoGiudice, Elizabeth
2014-01-01
Education is an important tool to increase the capacity of local government officials for community flood adaptation. To address flood adaptation and post-flood stream management in municipalities, Cornell Cooperative Extension and collaborators developed an educational program to increase municipal officials' knowledge about how to work…
A Theory of Secondary Teachers' Adaptations When Implementing a Reading Intervention Program
ERIC Educational Resources Information Center
Leko, Melinda M.; Roberts, Carly A.; Pek, Yvonne
2015-01-01
This study examined the causes and consequences of secondary teachers' adaptations when implementing a research-based reading intervention program. Interview, observation, and artifact data were collected on five middle school intervention teachers, leading to a grounded theory composed of the core component, reconciliation through adaptation, and…
University of Rhode Island Adapted Aquatics Program Manual.
ERIC Educational Resources Information Center
Scraba, Paula J.; Bloomquist, Lorraine E.
An overview is presented of the aquatics course, adapted for persons with disabilities, at the University of Rhode Island. A description of the course includes information on course requirements, objectives, content and learning activities, assignments, modules used in the course, and a course syllabus. A description of the course organization and…
Computer Adaptive Testing for Small Scale Programs and Instructional Systems
ERIC Educational Resources Information Center
Rudner, Lawrence M.; Guo, Fanmin
2011-01-01
This study investigates measurement decision theory (MDT) as an underlying model for computer adaptive testing when the goal is to classify examinees into one of a finite number of groups. The first analysis compares MDT with a popular item response theory model and finds little difference in terms of the percentage of correct classifications. The…
Poot, L; Snippe, H P; van Hateren, J H
1997-09-01
As is well known, dark adaptation in the human visual system is much slower than is recovery from darkness. We show that at high photopic luminances the situation is exactly opposite. First, we study detection thresholds for a small light flash, at various delays from decrement and increment steps in background luminance. Light adaptation is nearly complete within 100 ms after luminance decrements but takes much longer after luminance increments. Second, we compare sensitivity after equally visible pulses or steps in the adaptation luminance and find that detectability is initially the same but recovers much faster for pulses than for increment steps. This suggests that, whereas any residual threshold elevation after a step shows the incomplete luminance adaptation, the initial threshold elevation is caused by the temporal contrast of the background steps and pulses. This hypothesis is further substantiated in a third experiment, whereby we show that manipulating the contrast of a transition between luminances affects only the initial part of the threshold curve, and not later stages.
Quantitative adaptation analytics for assessing dynamic systems of systems: LDRD Final Report
Gauthier, John H.; Miner, Nadine E.; Wilson, Michael L.; Le, Hai D.; Kao, Gio K.; Melander, Darryl J.; Longsine, Dennis Earl; Vander Meer, Jr., Robert C.
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.
Applying Parallel Adaptive Methods with GeoFEST/PYRAMID to Simulate Earth Surface Crustal Dynamics
NASA Technical Reports Server (NTRS)
Norton, Charles D.; Lyzenga, Greg; Parker, Jay; Glasscoe, Margaret; Donnellan, Andrea; Li, Peggy
2006-01-01
This viewgraph presentation reviews the use Adaptive Mesh Refinement (AMR) in simulating the Crustal Dynamics of Earth's Surface. AMR simultaneously improves solution quality, time to solution, and computer memory requirements when compared to generating/running on a globally fine mesh. The use of AMR in simulating the dynamics of the Earth's Surface is spurred by future proposed NASA missions, such as InSAR for Earth surface deformation and other measurements. These missions will require support for large-scale adaptive numerical methods using AMR to model observations. AMR was chosen because it has been successful in computation fluid dynamics for predictive simulation of complex flows around complex structures.
Shaughnessy, M C; Jones, R E
2016-02-01
We develop and demonstrate a method to efficiently use density functional calculations to drive classical dynamics of complex atomic and molecular systems. The method has the potential to scale to systems and time scales unreachable with current ab initio molecular dynamics schemes. It relies on an adapting dataset of independently computed Hellmann-Feynman forces for atomic configurations endowed with a distance metric. The metric on configurations enables fast database lookup and robust interpolation of the stored forces. We discuss mechanisms for the database to adapt to the needs of the evolving dynamics, while maintaining accuracy, and other extensions of the basic algorithm.
Shaughnessy, M C; Jones, R E
2016-02-01
We develop and demonstrate a method to efficiently use density functional calculations to drive classical dynamics of complex atomic and molecular systems. The method has the potential to scale to systems and time scales unreachable with current ab initio molecular dynamics schemes. It relies on an adapting dataset of independently computed Hellmann-Feynman forces for atomic configurations endowed with a distance metric. The metric on configurations enables fast database lookup and robust interpolation of the stored forces. We discuss mechanisms for the database to adapt to the needs of the evolving dynamics, while maintaining accuracy, and other extensions of the basic algorithm. PMID:26669825
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.
Fitness of multidimensional phenotypes in dynamic adaptive landscapes.
Laughlin, Daniel C; Messier, Julie
2015-08-01
Phenotypic traits influence species distributions, but ecology lacks established links between multidimensional phenotypes and fitness for predicting species responses to environmental change. The common focus on single traits rather than multiple trait combinations limits our understanding of their adaptive value, and intraspecific trait covariation has been neglected in ecology despite its importance in evolutionary theory and its likely impact on species distributions. Here, we extend the adaptive landscape framework to ecological sorting of multidimensional phenotypes across environments and discuss how two analytical approaches can be used to quantify fitness as a function of the interaction between the phenotype and the environment. We encourage ecologists to consider how phenotypic integration will constrain species responses to environmental change.
A Dynamically Adaptive Arbitrary Lagrangian-Eulerian Method for Hydrodynamics
Anderson, R W; Pember, R B; Elliott, N S
2004-01-28
A new method that combines staggered grid Arbitrary Lagrangian-Eulerian (ALE) techniques with structured local adaptive mesh refinement (AMR) has been developed for solution of the Euler equations. The novel components of the combined ALE-AMR method hinge upon the integration of traditional AMR techniques with both staggered grid Lagrangian operators as well as elliptic relaxation operators on moving, deforming mesh hierarchies. Numerical examples demonstrate the utility of the method in performing detailed three-dimensional shock-driven instability calculations.
A Dynamically Adaptive Arbitrary Lagrangian-Eulerian Method for Hydrodynamics
Anderson, R W; Pember, R B; Elliott, N S
2002-10-19
A new method that combines staggered grid Arbitrary Lagrangian-Eulerian (ALE) techniques with structured local adaptive mesh refinement (AMR) has been developed for solution of the Euler equations. The novel components of the combined ALE-AMR method hinge upon the integration of traditional AMR techniques with both staggered grid Lagrangian operators as well as elliptic relaxation operators on moving, deforming mesh hierarchies. Numerical examples demonstrate the utility of the method in performing detailed three-dimensional shock-driven instability calculations.
A Rural Special Education Teacher Training Program: Successful Adaptations.
ERIC Educational Resources Information Center
Prater, Greg; And Others
The Rural Special Education Program (RSEP), a partnership between Northern Arizona University (NAU) and Kayenta Unified School District (KUSD), provides training for preservice special education teachers to work with Native American students and their families. To date, the program has provided training for 63 preservice special education…
Modeling for deformable mirrors and the adaptive optics optimization program
Henesian, M.A.; Haney, S.W.; Trenholme, J.B.; Thomas, M.
1997-03-18
We discuss aspects of adaptive optics optimization for large fusion laser systems such as the 192-arm National Ignition Facility (NIF) at LLNL. By way of example, we considered the discrete actuator deformable mirror and Hartmann sensor system used on the Beamlet laser. Beamlet is a single-aperture prototype of the 11-0-5 slab amplifier design for NIF, and so we expect similar optical distortion levels and deformable mirror correction requirements. We are now in the process of developing a numerically efficient object oriented C++ language implementation of our adaptive optics and wavefront sensor code, but this code is not yet operational. Results are based instead on the prototype algorithms, coded-up in an interpreted array processing computer language.
NASA Astrophysics Data System (ADS)
Yi, Guosheng; Wang, Jiang; Deng, Bin; Wei, Xile
2015-05-01
In this paper, we address how adaptation mediated by different biophysical mechanisms modulates neuronal spike initiating dynamics to extracellular electric fields. We incorporate two adaptation currents, i.e., voltage-sensitive potassium current (IM) and calcium-sensitive potassium current (IAHP), into a reduced two-compartment neuron model, and extensively investigate the modeling behavior to a range of electric fields. With phase plane analysis, it is shown whether neuron continues to spike depends on whether adaptation currents could be sufficiently activated to stabilize membrane potential at subthreshold voltages. With stability and bifurcation analysis, we find the steady-state spiking in the neuron with IM occurs through a Hopf bifurcation, whereas it is generated through a saddle-node on invariant circle (SNIC) bifurcation in the cases of IAHP or no adaptation. By identifying the biophysical basis for these dynamics, we observe that IM could alter the competitive outcomes between kinetically mismatched opposite currents to result in a Hopf bifurcation, while IAHP cannot alter these competitive outcomes. From this, we conclude that different modulations of spike initiating dynamics derive from the biophysical mechanism responsible for distinct adaptation currents. Our study suggests that the adaptation mediated by different mechanisms indeed has different effects on neuronal dynamics to electric field stimulus. It could contribute to uncover the underlying mechanism of how neuron encodes electric field signals.
Improve Problem Solving Skills through Adapting Programming Tools
NASA Technical Reports Server (NTRS)
Shaykhian, Linda H.; Shaykhian, Gholam Ali
2007-01-01
There are numerous ways for engineers and students to become better problem-solvers. The use of command line and visual programming tools can help to model a problem and formulate a solution through visualization. The analysis of problem attributes and constraints provide insight into the scope and complexity of the problem. The visualization aspect of the problem-solving approach tends to make students and engineers more systematic in their thought process and help them catch errors before proceeding too far in the wrong direction. The problem-solver identifies and defines important terms, variables, rules, and procedures required for solving a problem. Every step required to construct the problem solution can be defined in program commands that produce intermediate output. This paper advocates improved problem solving skills through using a programming tool. MatLab created by MathWorks, is an interactive numerical computing environment and programming language. It is a matrix-based system that easily lends itself to matrix manipulation, and plotting of functions and data. MatLab can be used as an interactive command line or a sequence of commands that can be saved in a file as a script or named functions. Prior programming experience is not required to use MatLab commands. The GNU Octave, part of the GNU project, a free computer program for performing numerical computations, is comparable to MatLab. MatLab visual and command programming are presented here.
Long-term dynamics of adaptation in asexual populations.
Wiser, Michael J; Ribeck, Noah; Lenski, Richard E
2013-12-13
Experimental studies of evolution have increased greatly in number in recent years, stimulated by the growing power of genomic tools. However, organismal fitness remains the ultimate metric for interpreting these experiments, and the dynamics of fitness remain poorly understood over long time scales. Here, we examine fitness trajectories for 12 Escherichia coli populations during 50,000 generations. Mean fitness appears to increase without bound, consistent with a power law. We also derive this power-law relation theoretically by incorporating clonal interference and diminishing-returns epistasis into a dynamical model of changes in mean fitness over time.
HBT-EP Program: Active MHD Mode Dynamics and Control
NASA Astrophysics Data System (ADS)
Navratil, G. A.; Bialek, J.; Boozer, A. H.; Byrne, P. J.; Donald, G. V.; Hughes, P. E.; Levesque, J. P.; Mauel, M. E.; Peng, Q.; Rhodes, D. J.; Stoafer, C. C.; Hansen, C. J.
2015-11-01
The HBT-EP active mode control research program aims to: (i) quantify external kink dynamics and multimode response to magnetic perturbations, (ii) understand the relationship between control coil configuration, conducting and ferritic wall effects, and active feedback control, and (iii) explore advanced feedback algorithms. Biorthogonal decomposition is used to observe multiple simultaneous resistive wall modes (RWM). A 512 core GPU-based low latency (14 μs) MIMO control system uses 96 inputs and 64 outputs for Adaptive Control of RWMs. An in-vessel adjustable ferritic wall is used to study ferritic RWMs with increased growth rates, RMP response, and disruptivity. A biased electrode in the plasma is used to control the rotation of external kinks and evaluate error fields. A Thomson scattering diagnostic measures Te and ne at 3 spatial points, soon to be extended to 10 points. A quasi-linear sharp-boundary model of the plasma's multimode response to error fields is developed to determine harmful error field structures and associated NTV and resonant torques. Upcoming machine upgrades will allow measurements and control of scrape-off-layer currents, and control of kink modes using optical diagnostics. Supported by U.S. DOE Grant DE-FG02-86ER53222.
Understanding barriers to implementation of an adaptive land management program.
Jacobson, Susan K; Morris, Julie K; Sanders, J Scott; Wiley, Eugene N; Brooks, Michael; Bennetts, Robert E; Percival, H Franklin; Marynowski, Susan
2006-10-01
The Florida Fish and Wildlife Conservation Commission manages over 650,000 ha, including 26 wildlife management and environmental areas. To improve management, they developed an objective-based vegetation management (OBVM) process that focuses on desired conditions of plant communities through an adaptive management framework. Our goals were to understand potential barriers to implementing OBVM and to recommend strategies to overcome barriers. A literature review identified 47 potential barriers in six categories to implementation of adaptive and ecosystem management: logistical, communication, attitudinal, institutional, conceptual, and educational. We explored these barriers through a bureau-wide survey of 90 staff involved in OBVM and personal interviews with area managers, scientists, and administrators. The survey incorporated an organizational culture assessment instrument to gauge how institutional factors might influence OBVM implementation. The survey response rate was 69%. Logistics and communications were the greatest barriers to implementing OBVM. Respondents perceived that the agency had inadequate resources for implementing OBVM and provided inadequate information. About one-third of the respondents believed OBVM would decrease their job flexibility and perceived greater institutional barriers to the approach. The 43% of respondents who believed they would have more responsibility under OBVM also had greater attitudinal barriers. A similar percentage of respondents reported OBVM would not give enough priority to wildlife. Staff believed that current agency culture was hierarchical but preferred a culture that would provide more flexibility for adaptive management and would foster learning from land management activities. In light of the barriers to OBVM, we recommend the following: (1) mitigation of logistical barriers by addressing real and perceived constraints of staff, funds, and other resources in a participatory manner; (2) mitigation of
Understanding barriers to implementation of an adaptive land management program
Jacobson, S.K.; Morris, J.K.; Sanders, J.S.; Wiley, E.N.; Brooks, M.; Bennetts, R.E.; Percival, H.F.; Marynowski, S.
2006-01-01
The Florida Fish and Wildlife Conservation Commission manages over 650,000 ha, including 26 wildlife management and environmental areas. To improve management, they developed an objective-based vegetation management (OBVM) process that focuses on desired conditions of plant communities through an adaptive management framework. Our goals were to understand potential barriers to implementing OBVM and to recommend strategies to overcome barriers. A literature review identified 47 potential barriers in six categories to implementation of adaptive and ecosystem management: logistical, communication, attitudinal, institutional, conceptual, and educational. We explored these barriers through a bureau-wide survey of 90 staff involved in OBVM and personal interviews with area managers, scientists, and administrators. The survey incorporated an organizational culture assessment instrument to gauge how institutional factors might influence OBVM implementation. The survey response rate was 69%. Logistics and communications were the greatest barriers to implementing OBVM. Respondents perceived that the agency had inadequate resources for implementing OBVM and provided inadequate information. About one-third of the respondents believed OBVM would decrease their job flexibility and perceived greater institutional barriers to the approach. The 43% of respondents who believed they would have more responsibility under OBVM also had greater attitudinal barriers. A similar percentage of respondents reported OBVM would not give enough priority to wildlife. Staff believed that current agency culture was hierarchical but preferred a culture that would provide more flexibility for adaptive management and would foster learning from land management activities. In light of the barriers to OBVM, we recommend the following: (1) mitigation of logistical barriers by addressing real and perceived constraints of staff, funds, and other resources in a participatory manner; (2) mitigation of
Evolutionary programming for goal-driven dynamic planning
NASA Astrophysics Data System (ADS)
Vaccaro, James M.; Guest, Clark C.; Ross, David O.
2002-03-01
Many complex artificial intelligence (IA) problems are goal- driven in nature and the opportunity exists to realize the benefits of a goal-oriented solution. In many cases, such as in command and control, a goal-oriented approach may be the only option. One of many appropriate applications for such an approach is War Gaming. War Gaming is an important tool for command and control because it provides a set of alternative courses of actions so that military leaders can contemplate their next move in the battlefield. For instance, when making decisions that save lives, it is necessary to completely understand the consequences of a given order. A goal-oriented approach provides a slowly evolving tractably reasoned solution that inherently follows one of the principles of war: namely concentration on the objective. Future decision-making will depend not only on the battlefield, but also on a virtual world where military leaders can wage wars and determine their options by playing computer war games much like the real world. The problem with these games is that the built-in AI does not learn nor adapt and many times cheats, because the intelligent player has access to all the information, while the user has access to limited information provided on a display. These games are written for the purpose of entertainment and actions are calculated a priori and off-line, and are made prior or during their development. With these games getting more sophisticated in structure and less domain specific in scope, there needs to be a more general intelligent player that can adapt and learn in case the battlefield situations or the rules of engagement change. One such war game that might be considered is Risk. Risk incorporates the principles of war, is a top-down scalable model, and provides a good application for testing a variety of goal- oriented AI approaches. By integrating a goal-oriented hybrid approach, one can develop a program that plays the Risk game effectively and move
Dynamic Reconstruction and Multivariable Control for Force-Actuated, Thin Facesheet Adaptive Optics
NASA Technical Reports Server (NTRS)
Grocott, Simon C. O.; Miller, David W.
1997-01-01
The Multiple Mirror Telescope (MMT) under development at the University of Arizona takes a new approach in adaptive optics placing a large (0.65 m) force-actuated, thin facesheet deformable mirror at the secondary of an astronomical telescope, thus reducing the effects of emissivity which are important in IR astronomy. However, The large size of the mirror and low stiffness actuators used drive the natural frequencies of the mirror down into the bandwidth of the atmospheric distortion. Conventional adaptive optics takes a quasi-static approach to controlling the, deformable mirror. However, flexibility within the control bandwidth calls for a new approach to adaptive optics. Dynamic influence functions are used to characterize the influence of each actuator on the surface of the deformable mirror. A linearized model of atmospheric distortion is combined with dynamic influence functions to produce a dynamic reconstructor. This dynamic reconstructor is recognized as an optimal control problem. Solving the optimal control problem for a system with hundreds of actuators and sensors is formidable. Exploiting the circularly symmetric geometry of the mirror, and a suitable model of atmospheric distortion, the control problem is divided into a number of smaller decoupled control problems using circulant matrix theory. A hierarchic control scheme which seeks to emulate the quasi-static control approach that is generally used in adaptive optics is compared to the proposed dynamic reconstruction technique. Although dynamic reconstruction requires somewhat more computational power to implement, it achieves better performance with less power usage, and is less sensitive than the hierarchic technique.
SIMCA T 1.0: A SAS Computer Program for Simulating Computer Adaptive Testing
ERIC Educational Resources Information Center
Raiche, Gilles; Blais, Jean-Guy
2006-01-01
Monte Carlo methodologies are frequently applied to study the sampling distribution of the estimated proficiency level in adaptive testing. These methods eliminate real situational constraints. However, these Monte Carlo methodologies are not currently supported by the available software programs, and when these programs are available, their…
ERIC Educational Resources Information Center
Firth, Nola; Frydenberg, Erica; Greaves, Daryl
2008-01-01
This study explored the effect of a coping program and a teacher feedback intervention on perceived control and adaptive coping for 98 adolescent students who had specific learning disabilities. The coping program was modified to build personal control and to address the needs of students who have specific learning disabilities. The teacher…
Foshee, Vangie A; Dixon, Kimberly S; Ennett, Susan T; Moracco, Kathryn E; Bowling, J Michael; Chang, Ling-Yin; Moss, Jennifer L
2015-07-01
Adolescents exposed to domestic violence are at increased risk of dating abuse, yet no evaluated dating abuse prevention programs have been designed specifically for this high-risk population. This article describes the process of adapting Families for Safe Dates (FSD), an evidenced-based universal dating abuse prevention program, to this high-risk population, including conducting 12 focus groups and 107 interviews with the target audience. FSD includes six booklets of dating abuse prevention information, and activities for parents and adolescents to do together at home. We adapted FSD for mothers who were victims of domestic violence, but who no longer lived with the abuser, to do with their adolescents who had been exposed to the violence. Through the adaptation process, we learned that families liked the program structure and valued being offered the program and that some of our initial assumptions about this population were incorrect. We identified practices and beliefs of mother victims and attributes of these adolescents that might increase their risk of dating abuse that we had not previously considered. In addition, we learned that some of the content of the original program generated negative family interactions for some. The findings demonstrate the utility of using a careful process to adapt evidence-based interventions (EBIs) to cultural sub-groups, particularly the importance of obtaining feedback on the program from the target audience. Others can follow this process to adapt EBIs to groups other than the ones for which the original EBI was designed.
A quantitative evolutionary theory of adaptive behavior dynamics.
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. PMID:24219847
A quantitative evolutionary theory of adaptive behavior dynamics.
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.
Satellite-tracking and earth-dynamics research programs
NASA Technical Reports Server (NTRS)
1975-01-01
The activities and progress in the satellite tracking and earth dynamics research during the first half of calendar year 1975 are described. Satellite tracking network operations, satellite geodesy and geophysics programs, GEOS 3 project support, and atmospheric research are covered.
Adaptive superposition of finite element meshes in linear and nonlinear dynamic analysis
NASA Astrophysics Data System (ADS)
Yue, Zhihua
2005-11-01
The numerical analysis of transient phenomena in solids, for instance, wave propagation and structural dynamics, is a very important and active area of study in engineering. Despite the current evolutionary state of modern computer hardware, practical analysis of large scale, nonlinear transient problems requires the use of adaptive methods where computational resources are locally allocated according to the interpolation requirements of the solution form. Adaptive analysis of transient problems involves obtaining solutions at many different time steps, each of which requires a sequence of adaptive meshes. Therefore, the execution speed of the adaptive algorithm is of paramount importance. In addition, transient problems require that the solution must be passed from one adaptive mesh to the next adaptive mesh with a bare minimum of solution-transfer error since this form of error compromises the initial conditions used for the next time step. A new adaptive finite element procedure (s-adaptive) is developed in this study for modeling transient phenomena in both linear elastic solids and nonlinear elastic solids caused by progressive damage. The adaptive procedure automatically updates the time step size and the spatial mesh discretization in transient analysis, achieving the accuracy and the efficiency requirements simultaneously. The novel feature of the s-adaptive procedure is the original use of finite element mesh superposition to produce spatial refinement in transient problems. The use of mesh superposition enables the s-adaptive procedure to completely avoid the need for cumbersome multipoint constraint algorithms and mesh generators, which makes the s-adaptive procedure extremely fast. Moreover, the use of mesh superposition enables the s-adaptive procedure to minimize the solution-transfer error. In a series of different solid mechanics problem types including 2-D and 3-D linear elastic quasi-static problems, 2-D material nonlinear quasi-static problems
Input File Creation for the Molecular Dynamics Program LAMMPS.
2001-05-30
The program creates an input data file for the molecular dynamics program LAMMPS. The input file created is a liquid mixture between two walls explicitly composed of particles. The liquid molecules are modeled as a bead-spring molecule. The input data file specifies the position and topology of the starting state. The data structure of input allows for dynamic bond creation (cross-linking) within the LAMMPS code.
An integrated architecture of adaptive neural network control for dynamic systems
Ke, Liu; Tokar, R.; Mcvey, B.
1994-07-01
In this study, an integrated neural network control architecture for nonlinear dynamic systems is presented. Most of the recent emphasis in the neural network control field has no error feedback as the control input which rises the adaptation problem. The integrated architecture in this paper combines feed forward control and error feedback adaptive control using neural networks. The paper reveals the different internal functionality of these two kinds of neural network controllers for certain input styles, e.g., state feedback and error feedback. Feed forward neural network controllers with state feedback establish fixed control mappings which can not adapt when model uncertainties present. With error feedbacks, neural network controllers learn the slopes or the gains respecting to the error feedbacks, which are error driven adaptive control systems. The results demonstrate that the two kinds of control scheme can be combined to realize their individual advantages. Testing with disturbances added to the plant shows good tracking and adaptation.
33 CFR 385.31 - Adaptive management program.
Code of Federal Regulations, 2011 CFR
2011-07-01
...; information developed through the assessment principles contained in the Plan; and future authorized changes... framework is not intended as an artificial constraint on innovation in its implementation. (b) Assessment activities. (1) RECOVER shall develop an assessment program to assess responses of the system...
Intelligent control of non-linear dynamical system based on the adaptive neurocontroller
NASA Astrophysics Data System (ADS)
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.
Structural self-assembly and avalanchelike dynamics in locally adaptive networks
NASA Astrophysics Data System (ADS)
Gräwer, Johannes; Modes, Carl D.; Magnasco, Marcelo O.; Katifori, Eleni
2015-07-01
Transport networks play a key role across four realms of eukaryotic life: slime molds, fungi, plants, and animals. In addition to the developmental algorithms that build them, many also employ adaptive strategies to respond to stimuli, damage, and other environmental changes. We model these adapting network architectures using a generic dynamical system on weighted graphs and find in simulation that these networks ultimately develop a hierarchical organization of the final weighted architecture accompanied by the formation of a system-spanning backbone. In addition, we find that the long term equilibration dynamics exhibit behavior reminiscent of glassy systems characterized by long periods of slow changes punctuated by bursts of reorganization events.
Structural self-assembly and avalanchelike dynamics in locally adaptive networks.
Gräwer, Johannes; Modes, Carl D; Magnasco, Marcelo O; Katifori, Eleni
2015-07-01
Transport networks play a key role across four realms of eukaryotic life: slime molds, fungi, plants, and animals. In addition to the developmental algorithms that build them, many also employ adaptive strategies to respond to stimuli, damage, and other environmental changes. We model these adapting network architectures using a generic dynamical system on weighted graphs and find in simulation that these networks ultimately develop a hierarchical organization of the final weighted architecture accompanied by the formation of a system-spanning backbone. In addition, we find that the long term equilibration dynamics exhibit behavior reminiscent of glassy systems characterized by long periods of slow changes punctuated by bursts of reorganization events. PMID:26274219
NASA Astrophysics Data System (ADS)
Harper, William B.; Shaltens, Richard K.
1993-01-01
Closed Brayton cycle power conversion systems are readily adaptable to any heat source contemplated for space application. The inert gas working fluid can be used directly in gas-cooled reactors and coupled to a variety of heat sources (reactor, isotope or solar) by a heat exchanger. This point is demonstrated by the incorporation in the NASA 2 kWe Solar Dynamic (SD) Space Power Ground Test Demonstration (GTD) Program of the turboalternator-compressor and recuperator from the Brayton Isotope Power System (BIPS) program. This paper will review the goals and status of the SD GTD Program, initiated in April 1992. The performance of the BIPS isotope-heated system will be compared to the solar-heated GTD system incorporating the BIPS components and the applicability of the GTD test bed to dynamics space nuclear power R&D will be discussed.
INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization
Groer, Christopher S; Sullivan, Blair D; Weerapurage, Dinesh P
2012-10-01
It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms we have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.
Slim-hole casing program adapted to horizontal well
Foster, L. )
1993-09-06
A type of slim-hole well design reduced the cost of drilling a horizontal well in the southern North Sea. The basic slim-hole drilling and casing program was similar to that used in conventional directional wells in the field, but with slight modifications for drilling with logging-while-drilling (LWD) tools and running production liners. Nearly 2,600 ft were successfully drilled at over 80[degree] inclination in ARCO British Ltd.'s Pickerill A6 well, the first time in the southern North Sea that a horizontal well was drilled through the reservoir without first casting off the overlying evaporite sequence. The paper describes the well design, the pilot hole plan, the evaluation program for directional drilling, a horizontal sidetrack plan, its evaluation and drilling, hole conditions, liners, well completion, and results.
Workload Model Based Dynamic Adaptation of Social Internet of Vehicles
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
Workload Model Based Dynamic Adaptation of Social Internet of Vehicles.
Alam, Kazi Masudul; Saini, Mukesh; El Saddik, Abdulmotaleb
2015-09-15
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.
Sensor Web Dynamic Measurement Techniques and Adaptive Observing Strategies
NASA Technical Reports Server (NTRS)
Talabac, Stephen J.
2004-01-01
Sensor Web observing systems may have the potential to significantly improve our ability to monitor, understand, and predict the evolution of rapidly evolving, transient, or variable environmental features and events. This improvement will come about by integrating novel data collection techniques, new or improved instruments, emerging communications technologies and protocols, sensor mark-up languages, and interoperable planning and scheduling systems. In contrast to today's observing systems, "event-driven" sensor webs will synthesize real- or near-real time measurements and information from other platforms and then react by reconfiguring the platforms and instruments to invoke new measurement modes and adaptive observation strategies. Similarly, "model-driven" sensor webs will utilize environmental prediction models to initiate targeted sensor measurements or to use a new observing strategy. The sensor web concept contrasts with today's data collection techniques and observing system operations concepts where independent measurements are made by remote sensing and in situ platforms that do not share, and therefore cannot act upon, potentially useful complementary sensor measurement data and platform state information. This presentation describes NASA's view of event-driven and model-driven Sensor Webs and highlights several research and development activities at the Goddard Space Flight Center.
Workload Model Based Dynamic Adaptation of Social Internet of Vehicles.
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
Dynamic Learning Objects to Teach Java Programming Language
ERIC Educational Resources Information Center
Narasimhamurthy, Uma; Al Shawkani, Khuloud
2010-01-01
This article describes a model for teaching Java Programming Language through Dynamic Learning Objects. The design of the learning objects was based on effective learning design principles to help students learn the complex topic of Java Programming. Visualization was also used to facilitate the learning of the concepts. (Contains 1 figure and 2…
A 3-D adaptive mesh refinement algorithm for multimaterial gas dynamics
Puckett, E.G. ); Saltzman, J.S. )
1991-08-12
Adaptive Mesh Refinement (AMR) in conjunction with high order upwind finite difference methods has been used effectively on a variety of problems. In this paper we discuss an implementation of an AMR finite difference method that solves the equations of gas dynamics with two material species in three dimensions. An equation for the evolution of volume fractions augments the gas dynamics system. The material interface is preserved and tracked from the volume fractions using a piecewise linear reconstruction technique. 14 refs., 4 figs.
Enhancement of the flexible spacecraft dynamics program for open spacecraft
NASA Technical Reports Server (NTRS)
1985-01-01
The modifications and additions made to the Flexible Spacecraft Dynamics (FSD) Program are described. The principal addition to the program was the capability to simulate a single axis gimble platform nadir pointing despin control system. The formulation for the single axis gimble equations of motion is a modification of the formulation. The details of the modifications made to the FSD Program are presented. Modifications to existing subroutines are briefly described and a detailed description of new subroutines is given. In addition, e program variables in new labelled COMMON blocks are described in detail. A description of new input symbols for the FSD Program is given.
ERIC Educational Resources Information Center
Benseler, David P., Ed.
This collection papers begins with "Introduction: The Dynamics of Successful Leadership in Foreign Language Programs," then features the following: "The Undergraduate Program: Autonomy and Empowerment" (Wilga M. Rivers); "TA Supervision: Are We Preparing a Future Professoriate?" (Cathy Pons); "Applied Scholarship in Foreign Languages: A Program of…
Measuring Fidelity and Adaptation: Reliability of a Instrument for School-Based Prevention Programs.
Bishop, Dana C; Pankratz, Melinda M; Hansen, William B; Albritton, Jordan; Albritton, Lauren; Strack, Joann
2014-06-01
There is a need to standardize methods for assessing fidelity and adaptation. Such standardization would allow program implementation to be examined in a manner that will be useful for understanding the moderating role of fidelity in dissemination research. This article describes a method for collecting data about fidelity of implementation for school-based prevention programs, including measures of adherence, quality of delivery, dosage, participant engagement, and adaptation. We report about the reliability of these methods when applied by four observers who coded video recordings of teachers delivering All Stars, a middle school drug prevention program. Interrater agreement for scaled items was assessed for an instrument designed to evaluate program fidelity. Results indicated sound interrater reliability for items assessing adherence, dosage, quality of teaching, teacher understanding of concepts, and program adaptations. The interrater reliability for items assessing potential program effectiveness, classroom management, achievement of activity objectives, and adaptation valences was improved by dichotomizing the response options for these items. The item that assessed student engagement demonstrated only modest interrater reliability and was not improved through dichotomization. Several coder pairs were discordant on items that overall demonstrated good interrater reliability. Proposed modifications to the coding manual and protocol are discussed.
Attack diagnosis on binary executables using dynamic program slicing
NASA Astrophysics Data System (ADS)
Huang, Shan; Zheng, Yudi; Zhang, Ruoyu
2011-12-01
Nowadays, the level of the practically used programs is often complex and of such a large scale so that it is not as easy to analyze and debug them as one might expect. And it is quite difficult to diagnose attacks and find vulnerabilities in such large-scale programs. Thus, dynamic program slicing becomes a popular and effective method for program comprehension and debugging since it can reduce the analysis scope greatly and drop useless data that do not influence the final result. Besides, most of existing dynamic slicing tools perform dynamic slicing in the source code level, but the source code is not easy to obtain in practice. We believe that we do need some kinds of systems to help the users understand binary programs. In this paper, we present an approach of diagnosing attacks using dynamic backward program slicing based on binary executables, and provide a dynamic binary slicing tool named DBS to analyze binary executables precisely and efficiently. It computes the set of instructions that may have affected or been affected by slicing criterion set in certain location of the binary execution stream. This tool also can organize the slicing results by function call graphs and control flow graphs clearly and hierarchically.
Satellite tracking and earth dynamics research programs
NASA Technical Reports Server (NTRS)
1982-01-01
The SAO laser site in Arequipa continued routine operations throughout the reporting period except for the months of March and April when upgrading was underway. The laser in Orroral Valley was operational through March. Together with the cooperating stations in Wettzell, Grasse, Kootwikj, San Fernando, Helwan, and Metsahove the laser stations obtained a total of 37,099 quick-look observations on 978 passes of BE-C, Starlette, and LAGEOS. The Network continued to track LAGEOS at highest priority for polar motion and Earth rotation studies, and for other geophysical investigations, including crustal dynamics, Earth and ocean tides, and the general development of precision orbit determination. The Network performed regular tracking of BE-C and Starlette for refined determinations of station coordinate and the Earth's gravity field and for studies of solid earth dynamics. Monthly statistics of the passes and points are given by station and by satellite.
User's guide for Skylab dynamics program, SKYDYN
NASA Technical Reports Server (NTRS)
Hopkins, M. S.
1980-01-01
This user's manual describes the capabilities, required input data, and resulting output of SKYDYN, version of the 6 degree-of-freedom digital program REENTR which was extensively modified for the Honeywell CP-V system and was tailored to the specfic requirements for SKYLAB.
Parallel Molecular Dynamics Program for Molecules
Plimpton, Steve
1995-03-07
ParBond is a parallel classical molecular dynamics code that models bonded molecular systems, typically of an organic nature. It uses classical force fields for both non-bonded Coulombic and Van der Waals interactions and for 2-, 3-, and 4-body bonded (bond, angle, dihedral, and improper) interactions. It integrates Newton''s equation of motion for the molecular system and evaluates various thermodynamical properties of the system as it progresses.
Dynamic self-adaptive remote health monitoring system for diabetics.
Suh, Myung-kyung; Moin, Tannaz; Woodbridge, Jonathan; Lan, Mars; Ghasemzadeh, Hassan; Bui, Alex; Ahmadi, Sheila; Sarrafzadeh, Majid
2012-01-01
Diabetes is the seventh leading cause of death in the United States. In 2010, about 1.9 million new cases of diabetes were diagnosed in people aged 20 years or older. Remote health monitoring systems can help diabetics and their healthcare professionals monitor health-related measurements by providing real-time feedback. However, data-driven methods to dynamically prioritize and generate tasks are not well investigated in the remote health monitoring. This paper presents a task optimization technique used in WANDA (Weight and Activity with Blood Pressure and Other Vital Signs); a wireless health project that leverages sensor technology and wireless communication to monitor the health status of patients with diabetes. WANDA applies data analytics in real-time to improving the quality of care. The developed algorithm minimizes the number of daily tasks required by diabetic patients using association rules that satisfies a minimum support threshold. Each of these tasks maximizes information gain, thereby improving the overall level of care. Experimental results show that the developed algorithm can reduce the number of tasks up to 28.6% with minimum support 0.95, minimum confidence 0.97 and high efficiency. PMID:23366365
Dynamic self-adaptive remote health monitoring system for diabetics.
Suh, Myung-kyung; Moin, Tannaz; Woodbridge, Jonathan; Lan, Mars; Ghasemzadeh, Hassan; Bui, Alex; Ahmadi, Sheila; Sarrafzadeh, Majid
2012-01-01
Diabetes is the seventh leading cause of death in the United States. In 2010, about 1.9 million new cases of diabetes were diagnosed in people aged 20 years or older. Remote health monitoring systems can help diabetics and their healthcare professionals monitor health-related measurements by providing real-time feedback. However, data-driven methods to dynamically prioritize and generate tasks are not well investigated in the remote health monitoring. This paper presents a task optimization technique used in WANDA (Weight and Activity with Blood Pressure and Other Vital Signs); a wireless health project that leverages sensor technology and wireless communication to monitor the health status of patients with diabetes. WANDA applies data analytics in real-time to improving the quality of care. The developed algorithm minimizes the number of daily tasks required by diabetic patients using association rules that satisfies a minimum support threshold. Each of these tasks maximizes information gain, thereby improving the overall level of care. Experimental results show that the developed algorithm can reduce the number of tasks up to 28.6% with minimum support 0.95, minimum confidence 0.97 and high efficiency.
Segmentation of Tracking Sequences Using Dynamically Updated Adaptive Learning
Michailovich, Oleg; Tannenbaum, Allen
2009-01-01
The problem of segmentation of tracking sequences is of central importance in a multitude of applications. In the current paper, a different approach to the problem is discussed. Specifically, the proposed segmentation algorithm is implemented in conjunction with estimation of the dynamic parameters of moving objects represented by the tracking sequence. While the information on objects’ motion allows one to transfer some valuable segmentation priors along the tracking sequence, the segmentation allows substantially reducing the complexity of motion estimation, thereby facilitating the computation. Thus, in the proposed methodology, the processes of segmentation and motion estimation work simultaneously, in a sort of “collaborative” manner. The Bayesian estimation framework is used here to perform the segmentation, while Kalman filtering is used to estimate the motion and to convey useful segmentation information along the image sequence. The proposed method is demonstrated on a number of both computed-simulated and real-life examples, and the obtained results indicate its advantages over some alternative approaches. PMID:19004712
Development of a scalable gas-dynamics solver with adaptive mesh refinement
NASA Astrophysics Data System (ADS)
Korkut, Burak
There are various computational physics areas in which Direct Simulation Monte Carlo (DSMC) and Particle in Cell (PIC) methods are being employed. The accuracy of results from such simulations depend on the fidelity of the physical models being used. The computationally demanding nature of these problems make them ideal candidates to make use of modern supercomputers. The software developed to run such simulations also needs special attention so that the maintainability and extendability is considered with the recent numerical methods and programming paradigms. Suited for gas-dynamics problems, a software called SUGAR (Scalable Unstructured Gas dynamics with Adaptive mesh Refinement) has recently been developed and written in C++ and MPI. Physical and numerical models were added to this framework to simulate ion thruster plumes. SUGAR is used to model the charge-exchange (CEX) reactions occurring between the neutral and ion species as well as the induced electric field effect due to ions. Multiple adaptive mesh refinement (AMR) meshes were used in order to capture different physical length scales present in the flow. A multiple-thruster configuration was run to extend the studies to cases for which there is no axial or radial symmetry present that could only be modeled with a three-dimensional simulation capability. The combined plume structure showed interactions between individual thrusters where AMR capability captured this in an automated way. The back flow for ions was found to occur when CEX and momentum-exchange (MEX) collisions are present and strongly enhanced when the induced electric field is considered. The ion energy distributions in the back flow region were obtained and it was found that the inclusion of the electric field modeling is the most important factor in determining its shape. The plume back flow structure was also examined for a triple-thruster, 3-D geometry case and it was found that the ion velocity in the back flow region appears to be
Adaptive control for space debris removal with uncertain kinematics, dynamics and states
NASA Astrophysics Data System (ADS)
Huang, Panfeng; Zhang, Fan; Meng, Zhongjie; Liu, Zhengxiong
2016-11-01
As the Tethered Space Robot is considered to be a promising solution for the Active Debris Removal, a lot of problems arise in the approaching, capturing and removing phases. Particularly, kinematics and dynamics parameters of the debris are unknown, and parts of the states are unmeasurable according to the specifics of tether, which is a tough problem for the target retrieval/de-orbiting. This work proposes a full adaptive control strategy for the space debris removal via a Tethered Space Robot with unknown kinematics, dynamics and part of the states. First we derive a dynamics model for the retrieval by treating the base satellite (chaser) and the unknown space debris (target) as rigid bodies in the presence of offsets, and involving the flexibility and elasticity of tether. Then, a full adaptive controller is presented including a control law, a dynamic adaption law, and a kinematic adaption law. A modified controller is also presented according to the peculiarities of this system. Finally, simulation results are presented to illustrate the performance of two proposed controllers.
Method and system for training dynamic nonlinear adaptive filters which have embedded memory
NASA Technical Reports Server (NTRS)
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.
Adaptive hp-FEM with dynamical meshes for transient heat and moisture transfer problems
NASA Astrophysics Data System (ADS)
Solin, Pavel; Dubcova, Lenka; Kruis, Jaroslav
2010-04-01
We are concerned with the time-dependent multiphysics problem of heat and moisture transfer in the context of civil engineering applications. The problem is challenging due to its multiscale nature (temperature usually propagates orders of magnitude faster than moisture), different characters of the two fields (moisture exhibits boundary layers which are not present in the temperature field), extremely long integration times (30 years or more), and lack of viable error control mechanisms. In order to solve the problem efficiently, we employ a novel multimesh adaptive higher-order finite element method (hp-FEM) based on dynamical meshes and adaptive time step control. We investigate the possibility to approximate the temperature and humidity fields on individual dynamical meshes equipped with mutually independent adaptivity mechanisms. Numerical examples related to a realistic nuclear reactor vessel simulation are presented.
Adaptive Fuzzy Control of Strict-Feedback Nonlinear Time-Delay Systems With Unmodeled Dynamics.
Yin, Shen; Shi, Peng; Yang, Hongyan
2016-08-01
In this paper, an approximated-based adaptive fuzzy control approach with only one adaptive parameter is presented for a class of single input single output strict-feedback nonlinear systems in order to deal with phenomena like nonlinear uncertainties, unmodeled dynamics, dynamic disturbances, and unknown time delays. Lyapunov-Krasovskii function approach is employed to compensate the unknown time delays in the design procedure. By combining the advances of the hyperbolic tangent function with adaptive fuzzy backstepping technique, the proposed controller guarantees the semi-globally uniformly ultimately boundedness of all the signals in the closed-loop system from the mean square point of view. Two simulation examples are finally provided to show the superior effectiveness of the proposed scheme.
Robust projective lag synchronization in drive-response dynamical networks via adaptive control
NASA Astrophysics Data System (ADS)
Al-mahbashi, G.; Noorani, M. S. Md; Bakar, S. A.; Al-sawalha, M. M.
2016-02-01
This paper investigates the problem of projective lag synchronization behavior in drive-response dynamical networks (DRDNs) with identical and non-identical nodes. An adaptive control method is designed to achieve projective lag synchronization with fully unknown parameters and unknown bounded disturbances. These parameters were estimated by adaptive laws obtained by Lyapunov stability theory. Furthermore, sufficient conditions for synchronization are derived analytically using the Lyapunov stability theory and adaptive control. In addition, the unknown bounded disturbances are also overcome by the proposed control. Finally, analytical results show that the states of the dynamical network with non-delayed coupling can be asymptotically synchronized onto a desired scaling factor under the designed controller. Simulation results show the effectiveness of the proposed method.
NASA Astrophysics Data System (ADS)
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
Helicopter trimming and tracking control using direct neural dynamic programming.
Enns, R; Si, Jennie
2003-01-01
This paper advances a neural-network-based approximate dynamic programming control mechanism that can be applied to complex control problems such as helicopter flight control design. Based on direct neural dynamic programming (DNDP), an approximate dynamic programming methodology, the control system is tailored to learn to maneuver a helicopter. The paper consists of a comprehensive treatise of this DNDP-based tracking control framework and extensive simulation studies for an Apache helicopter. A trim network is developed and seamlessly integrated into the neural dynamic programming (NDP) controller as part of a baseline structure for controlling complex nonlinear systems such as a helicopter. Design robustness is addressed by performing simulations under various disturbance conditions. All designs are tested using FLYRT, a sophisticated industrial scale nonlinear validated model of the Apache helicopter. This is probably the first time that an approximate dynamic programming methodology has been systematically applied to, and evaluated on, a complex, continuous state, multiple-input multiple-output nonlinear system with uncertainty. Though illustrated for helicopters, the DNDP control system framework should be applicable to general purpose tracking control.
MPH program adaptability in a competitive marketplace: the case for continued assessment.
Caron, Rosemary M; Tutko, Holly
2010-06-01
In the last several years, the number of Master of Public Health (MPH) programs has increased rapidly in the US. As such, MPH programs, particularly smaller-sized ones, need to critically examine how their programs are meeting the needs and preferences of local public health practitioners. To assist in this necessity, the University of New Hampshire conducted a comprehensive educational assessment of its effectiveness as a smaller-sized, accredited MPH program. The aim of the assessment was to review the MPH program from the perspective of all stakeholders and then to agree on changes that would contribute to the fulfillment of the program's mission, as well as improve program quality and reach. The program's stakeholders examined the following components: policy development and implementation; target audience; marketing strategies; marketplace position; delivery model; curriculum design; and continuing education. Though assessment activities explored a wide array of program attributes, target audience, curriculum design, and delivery strategy presented significant challenges and opportunities for our smaller MPH Program to remain competitive. The effort put forth into conducting an in-depth assessment of the core components of our program also allowed for a comparison to the increasing number of MPH programs developing regionally. Since public health practice is changing and the education of public health practitioners must be adaptable, we propose that a routine assessment of an institution's MPH program could not only meet this need but also assist with keeping smaller, unbranded MPH programs competitive in a burgeoning marketplace. PMID:20127157
Adaptive wavelet simulation of global ocean dynamics using a new Brinkman volume penalization
NASA Astrophysics Data System (ADS)
Kevlahan, N. K.-R.; Dubos, T.; Aechtner, M.
2015-12-01
In order to easily enforce solid-wall boundary conditions in the presence of complex coastlines, we propose a new mass and energy conserving Brinkman penalization for the rotating shallow water equations. This penalization does not lead to higher wave speeds in the solid region. The error estimates for the penalization are derived analytically and verified numerically for linearized one-dimensional equations. The penalization is implemented in a conservative dynamically adaptive wavelet method for the rotating shallow water equations on the sphere with bathymetry and coastline data from NOAA's ETOPO1 database. This code could form the dynamical core for a future global ocean model. The potential of the dynamically adaptive ocean model is illustrated by using it to simulate the 2004 Indonesian tsunami and wind-driven gyres.
NASA Astrophysics Data System (ADS)
Bargatze, L. F.
2015-12-01
Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted
The tug-of-war: fidelity versus adaptation throughout the health promotion program life cycle.
Bopp, Melissa; Saunders, Ruth P; Lattimore, Diana
2013-06-01
Researchers across multiple fields have described the iterative and nonlinear phases of the translational research process from program development to dissemination. This process can be conceptualized within a "program life cycle" framework that includes overlapping and nonlinear phases: development, adoption, implementation, maintenance, sustainability or termination, and dissemination or diffusion, characterized by tensions between fidelity to the original plan and adaptation for the setting and population. In this article, we describe the life cycle (phases) for research-based health promotion programs, the key influences at each phase, and the issues related to the tug-of-war between fidelity and adaptation throughout the process using a fictionalized case study based on our previous research. This article suggests the importance of reconceptualizing intervention design, involving stakeholders, and monitoring fidelity and adaptation throughout all phases to maintain implementation fidelity and completeness. Intervention fidelity should be based on causal mechanisms to ensure effectiveness, while allowing for appropriate adaption to ensure maximum implementation and sustainability. Recommendations for future interventions include considering the determinants of implementation including contextual factors at each phase, the roles of stakeholders, and the importance of developing a rigorous, adaptive, and flexible definition of implementation fidelity and completeness.
Dynamic Load Balancing for Adaptive Computations on Distributed-Memory Machines
NASA Technical Reports Server (NTRS)
1999-01-01
Dynamic load balancing is central to adaptive mesh-based computations on large-scale parallel computers. The principal investigator has investigated various issues on the dynamic load balancing problem under NASA JOVE and JAG rants. The major accomplishments of the project are two graph partitioning algorithms and a load balancing framework. The S-HARP dynamic graph partitioner is known to be the fastest among the known dynamic graph partitioners to date. It can partition a graph of over 100,000 vertices in 0.25 seconds on a 64- processor Cray T3E distributed-memory multiprocessor while maintaining the scalability of over 16-fold speedup. Other known and widely used dynamic graph partitioners take over a second or two while giving low scalability of a few fold speedup on 64 processors. These results have been published in journals and peer-reviewed flagship conferences.
Langley rotorcraft structural dynamics program: Background, status, accomplishments, plans
NASA Technical Reports Server (NTRS)
Kvaternik, Raymond G.
1989-01-01
Excessive vibration is the most common technical problem to arise as a show stopper in the development of a new rotorcraft. Vibration predictions have not been relied on by the industry during design because of deficiencies in finite element dynamic analyses. A rotorcraft structural dynamics program aimed at meeting the industry's long-term needs in this key technical area was implemented at Langley in 1984. The subject program is a cooperative effort involving NASA, the Army, academia, and the helicopter industry in a series of generic research activities directed at establishing the critical elements of the technology base needed for development of a superior finite element dynamics design analysis capability in the U.S. helicopter industry. An executive overview of the background, status, accomplishments, and future direction of this program is presented.
Discrete neural dynamic programming in wheeled mobile robot control
NASA Astrophysics Data System (ADS)
Hendzel, Zenon; Szuster, Marcin
2011-05-01
In this paper we propose a discrete algorithm for a tracking control of a two-wheeled mobile robot (WMR), using an advanced Adaptive Critic Design (ACD). We used Dual-Heuristic Programming (DHP) algorithm, that consists of two parametric structures implemented as Neural Networks (NNs): an actor and a critic, both realized in a form of Random Vector Functional Link (RVFL) NNs. In the proposed algorithm the control system consists of the DHP adaptive critic, a PD controller and a supervisory term, derived from the Lyapunov stability theorem. The supervisory term guaranties a stable realization of a tracking movement in a learning phase of the adaptive critic structure and robustness in face of disturbances. The discrete tracking control algorithm works online, uses the WMR model for a state prediction and does not require a preliminary learning. Verification has been conducted to illustrate the performance of the proposed control algorithm, by a series of experiments on the WMR Pioneer 2-DX.
Adaptation to the edge of chaos and critical scaling in self-adjusting dynamical systems
NASA Astrophysics Data System (ADS)
Melby, Paul Christian
We present a mechanism for adaptation in dynamical systems. Systems which have this mechanism are called self-adjusting systems. The control parameters in a self-adjusting system are slowly varying, rather than constant. The dynamics of the control parameters are governed by a low-pass filtered feedback from the dynamical variables. We apply this model to several systems, numerically, analytically, and experimentally, and examine the behavior of the control parameters. We observe a high probability of finding the parameter at the boundary between periodicity and chaos. We therefore find that self-adjusting systems adapt to the edge of chaos. In addition, we find that noise in the system drives the parameter away from the edge of chaos on very long timescales so that chaos is suppressed in the system. We show that, with the presence of noise, the parameter can re-enter the chaotic regime. This is called a chaotic outbreak in the system and we find that the distribution of outbreaks is a power-law with the duration of the outbreak. We then study the robustness of adaptation to the edge of chaos by examining the effect of a control force being applied to the parameter. We find the behavior to be very robust, except for very large control forces. Finally, we look at systems of coupled maps and show that, adaptation to the edge of chaos occurs in systems of higher dimensions, as well.
Sharif, Behzad; Derbyshire, J Andrew; Faranesh, Anthony Z; Bresler, Yoram
2010-08-01
MRI of the human heart without explicit cardiac synchronization promises to extend the applicability of cardiac MR to a larger patient population and potentially expand its diagnostic capabilities. However, conventional nongated imaging techniques typically suffer from low image quality or inadequate spatio-temporal resolution and fidelity. Patient-Adaptive Reconstruction and Acquisition in Dynamic Imaging with Sensitivity Encoding (PARADISE) is a highly accelerated nongated dynamic imaging method that enables artifact-free imaging with high spatio-temporal resolutions by utilizing novel computational techniques to optimize the imaging process. In addition to using parallel imaging, the method gains acceleration from a physiologically driven spatio-temporal support model; hence, it is doubly accelerated. The support model is patient adaptive, i.e., its geometry depends on dynamics of the imaged slice, e.g., subject's heart rate and heart location within the slice. The proposed method is also doubly adaptive as it adapts both the acquisition and reconstruction schemes. Based on the theory of time-sequential sampling, the proposed framework explicitly accounts for speed limitations of gradient encoding and provides performance guarantees on achievable image quality. The presented in-vivo results demonstrate the effectiveness and feasibility of the PARADISE method for high-resolution nongated cardiac MRI during short breath-hold. PMID:20665794
Facial Expression Aftereffect Revealed by Adaption to Emotion-Invisible Dynamic Bubbled Faces
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
ADAPT (Analysis of Dynamic Accident Progression Trees) Beta Version 0.9
2010-01-07
The purpose of the ADAPT code is to generate Dynamic Event Trees (DET) using a user specified simulator. ADAPT can utilize any simulation tool which meets a minimal set of requirements. ADAPT is based on the concept of DET which use explicit modeling of the deterministic dynamic processes that take place during a nuclear reactor plant system evolution along with stochastic modeling. When DET are used to model different aspects of Probabilistic Risk Assessment (PRA),more » all accident progression scenarios starting from an initiating event are considered simultaneously. The DET branching occurs at user specified times and/or when an action is required by the system and/or the operator. These outcomes then decide how the dynamic system variables will evolve in time for each DET branch. Since two different outcomes at a DET branching may lead to completely different paths for system evolution, the next branching for these paths may occur not only at different times, but can be based on different branching criteria. The computational infrastructure allows for flexibility in ADAPT to link with different system simulation codes, parallel processing of the scenarios under consideration, on-line scenario management (initiation as well as termination) and user friendly graphical capabilities. The ADAPT system is designed for a distributed computing environment; the scheduler can track multiple concurrent branches simultaneously. The scheduler is modularized so that the DET branching strategy can be modified (e.g. biasing towards the worse case scenario/event). Independent database systems store data from the simulation tasks and the DET structure so that the event tree can be constructed and analyzed later. ADAPT is provided with a user-friendly client which can easily sort through and display the results of an experiment, precluding the need for the user to manually inspect individual simulator runs.« less
NASA Astrophysics Data System (ADS)
Rosenberg, Duane; Fournier, Aimé; Fischer, Paul; Pouquet, Annick
2006-06-01
An object-oriented geophysical and astrophysical spectral-element adaptive refinement (GASpAR) code is introduced. Like most spectral-element codes, GASpAR combines finite-element efficiency with spectral-method accuracy. It is also designed to be flexible enough for a range of geophysics and astrophysics applications where turbulence or other complex multiscale problems arise. The formalism accommodates both conforming and non-conforming elements. Several aspects of this code derive from existing methods, but here are synthesized into a new formulation of dynamic adaptive refinement (DARe) of non-conforming h-type. As a demonstration of the code, several new 2D test cases are introduced that have time-dependent analytic solutions and exhibit localized flow features, including the 2D Burgers equation with straight, curved-radial and oblique-colliding fronts. These are proposed as standard test problems for comparable DARe codes. Quantitative errors are reported for 2D spatial and temporal convergence of DARe.
Qualification of a computer program for drill string dynamics
Stone, C.M.; Carne, T.G.; Caskey, B.C.
1985-01-01
A four point plan for the qualification of the GEODYN drill string dynamics computer program is described. The qualification plan investigates both modal response and transient response of a short drill string subjected to simulated cutting loads applied through a polycrystalline diamond compact (PDC) bit. The experimentally based qualification shows that the analytical techniques included in Phase 1 GEODYN correctly simulate the dynamic response of the bit-drill string system. 6 refs., 8 figs.
Eucb: A C++ program for molecular dynamics trajectory analysis
NASA Astrophysics Data System (ADS)
Tsoulos, Ioannis G.; Stavrakoudis, Athanassios
2011-03-01
Eucb is a standalone program for geometrical analysis of molecular dynamics trajectories of protein systems. The program is written in GNU C++ and it can be installed in any operating system running a C++ compiler. The program performs its analytical tasks based on user supplied keywords. The source code is freely available from http://stavrakoudis.econ.uoi.gr/eucb under LGPL 3 license. Program summaryProgram title:Eucb Catalogue identifier: AEIC_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIC_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 31 169 No. of bytes in distributed program, including test data, etc.: 297 364 Distribution format: tar.gz Programming language: GNU C++ Computer: The tool is designed and tested on GNU/Linux systems Operating system: Unix/Linux systems RAM: 2 MB Supplementary material: Sample data files are available Classification: 3 Nature of problem: Analysis of molecular dynamics trajectories. Solution method: The program finds all possible interactions according to input files and the user instructions. Then it reads all the trajectory frames and finds those frames in which these interactions occur, under certain geometrical criteria. This is a blind search, without a priori knowledge if a certain interaction occurs or not. The program exports time series of these quantities (distance, angles, etc.) and appropriate descriptive statistics. Running time: Depends on the input data and the required options.
ERIC Educational Resources Information Center
Scholl, Mark B.; Cascone, Jason
2010-01-01
The authors present the constructivist resume, an original approach developed to promote professional identity development and career adaptability (i.e., concern, curiosity, confidence, and control) in students completing graduate-level counselor training programs. The authors discuss underlying theories, including Super's (1990; Super, Savickas,…
Cultural Adaptation of the Focus on Kids Program for College Students in China
ERIC Educational Resources Information Center
Li, Xiaoming; Stanton, Bonita; Wang, Bo; Mao, Rong; Zhang, Hongshia; Qu, Minfeng; Sun, Zhifeng; Wang, Jing
2008-01-01
This pilot study was designed to evaluate the efficacy of cultural adaptation of a social cognitive theory-based HIV risk reduction program delivered among college students in China. Three hundred eighty students from four universities in Nanjing, China, were assigned by classroom to either an intervention group receiving the culturally adapted…
Establishing Adaptive Sports Programs for Youth with Moderate to Severe Disabilities
ERIC Educational Resources Information Center
Ryan, Joseph B.; Katsiyannis, Antonis; Cadorette, Deborah; Hodge, Janie; Markham, Michelle
2014-01-01
Children with disabilities are at increased risk of health risk factors including obesity, often because of low levels of physical activity and limited participation in sports. However, organized adaptive sports programs are increasingly available for individuals with disabilities. This article provides recommendations for establishing successful…
Adapting to Changing Expectations: Post-Graduate Students' Experience of an E-Learning Tax Program
ERIC Educational Resources Information Center
Engelbrecht, Elmarie
2005-01-01
In response to the impact of information and communication technology on traditional business and commerce practices, and the empowerment of individuals by the growth of information available on the Internet, educators are challenged to adapt the curricula and delivery modes of educational programs for knowledge workers, such as tax accountants.…
Program of Adaptation Assistance in Foster Families and Particular Features of Its Implementation
ERIC Educational Resources Information Center
Zakirova, Venera G.; Gaysina, Guzel I.; Zhumabaeva, Asia
2015-01-01
Relevance of the problem stated in the article, conditioned by the fact that the successful adaptation of orphans in a foster family requires specialized knowledge and skills, as well as the need of professional support. Therefore, this article aims at substantiation of the effectiveness of the developed pilot program psycho-pedagogical support of…
ERIC Educational Resources Information Center
KANTER, EARL F.; BENDER, RALPH E.
THE PURPOSE OF THIS NATIONAL STUDY WAS TO SUGGEST WAYS OF ADAPTING THE FUTURE FARMERS OF AMERICA (FFA) TO A CHANGING PROGRAM OF VOCATIONAL AGRICULTURE THROUGH IDENTIFYING NEW PURPOSES OF THE FFA AND EVALUATING SELECTED OPERATIONAL GUIDELINES AND NATIONAL AND STATE FFA ACTIVITIES. MEMBERS OF THE UNITED STATES OFFICE OF EDUCATION, HEAD STATE…
An Adapted Dialogic Reading Program for Turkish Kindergarteners from Low Socio-Economic Backgrounds
ERIC Educational Resources Information Center
Ergül, Cevriye; Akoglu, Gözde; Sarica, Ayse D.; Karaman, Gökçe; Tufan, Mümin; Bahap-Kudret, Zeynep; Zülfikar, Deniz
2016-01-01
The study aimed to examine the effectiveness of the Adapted Dialogic Reading Program (ADR) on the language and early literacy skills of Turkish kindergarteners from low socio-economic (SES) backgrounds. The effectiveness of ADR was investigated across six different treatment conditions including classroom and home based implementations in various…
Padhi, Radhakant; Kothari, Mangal
2007-09-01
Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an innovative technique is presented to design an automatic drug administration strategy for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used to design the controller (medication dosage). First, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat the nominal model patients (patients who can be described by the mathematical model used here with the nominal parameter values) effectively. However, since the system parameters for a realistic model patient can be different from that of the nominal model patients, simulation studies for such patients indicate that the nominal controller is either inefficient or, worse, ineffective; i.e. the trajectory of the number of cancer cells either shows non-satisfactory transient behavior or it grows in an unstable manner. Hence, to make the drug dosage history more realistic and patient-specific, a model-following neuro-adaptive controller is augmented to the nominal controller. In this adaptive approach, a neural network trained online facilitates a new adaptive controller. The training process of the neural network is based on Lyapunov stability theory, which guarantees both stability of the cancer cell dynamics as well as boundedness of the network weights. From simulation studies, this adaptive control design approach is found to be very effective to treat the CML disease for realistic patients. Sufficient generality is retained in the mathematical developments so that the technique can be applied to other similar nonlinear control design problems as well.
An adaptable neuromorphic model of orientation selectivity based on floating gate dynamics
Gupta, Priti; Markan, C. M.
2014-01-01
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 in silicon. PMID
Adaptive Network Dynamics - Modeling and Control of Time-Dependent Social Contacts
Schwartz, Ira B.; Shaw, Leah B.; Shkarayev, Maxim S.
2013-01-01
Real networks consisting of social contacts do not possess static connections. That is, social connections may be time dependent due to a variety of individual behavioral decisions based on current network connections. Examples of adaptive networks occur in epidemics, where information about infectious individuals may change the rewiring of healthy people, or in the recruitment of individuals to a cause or fad, where rewiring may optimize recruitment of susceptible individuals. In this paper, we will review some of the dynamical properties of adaptive networks, and show how they predict novel phenomena as well as yield insight into new controls. The applications will be control of epidemic outbreaks and terrorist recruitment modeling. PMID:25414913
An adaptive approach to the dynamic allocation of buffer storage. M.S. Thesis
NASA Technical Reports Server (NTRS)
Crooke, S. C.
1970-01-01
Several strategies for the dynamic allocation of buffer storage are simulated and compared. The basic algorithms investigated, using actual statistics observed in the Univac 1108 EXEC 8 System, include the buddy method and the first-fit method. Modifications are made to the basic methods in an effort to improve and to measure allocation performance. A simulation model of an adaptive strategy is developed which permits interchanging the two different methods, the buddy and the first-fit methods with some modifications. Using an adaptive strategy, each method may be employed in the statistical environment in which its performance is superior to the other method.
Adaptive identification and control of structural dynamics systems using recursive lattice filters
NASA Technical Reports Server (NTRS)
Sundararajan, N.; Montgomery, R. C.; Williams, J. P.
1985-01-01
A new approach for adaptive identification and control of structural dynamic systems by using least squares lattice filters thar are widely used in the signal processing area is presented. Testing procedures for interfacing the lattice filter identification methods and modal control method for stable closed loop adaptive control are presented. The methods are illustrated for a free-free beam and for a complex flexible grid, with the basic control objective being vibration suppression. The approach is validated by using both simulations and experimental facilities available at the Langley Research Center.
NASA Technical Reports Server (NTRS)
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).
Shack-Hartmann wavefront sensor with large dynamic range by adaptive spot search method.
Shinto, Hironobu; Saita, Yusuke; Nomura, Takanori
2016-07-10
A Shack-Hartmann wavefront sensor (SHWFS) that consists of a microlens array and an image sensor has been used to measure the wavefront aberrations of human eyes. However, a conventional SHWFS has finite dynamic range depending on the diameter of the each microlens. The dynamic range cannot be easily expanded without a decrease of the spatial resolution. In this study, an adaptive spot search method to expand the dynamic range of an SHWFS is proposed. In the proposed method, spots are searched with the help of their approximate displacements measured with low spatial resolution and large dynamic range. By the proposed method, a wavefront can be correctly measured even if the spot is beyond the detection area. The adaptive spot search method is realized by using the special microlens array that generates both spots and discriminable patterns. The proposed method enables expanding the dynamic range of an SHWFS with a single shot and short processing time. The performance of the proposed method is compared with that of a conventional SHWFS by optical experiments. Furthermore, the dynamic range of the proposed method is quantitatively evaluated by numerical simulations.
Multi-mesh gear dynamics program evaluation and enhancements
NASA Technical Reports Server (NTRS)
Boyd, L. S.; Pike, J.
1985-01-01
A multiple mesh gear dynamics computer program was continually developed and modified during the last four years. The program can handle epicyclic gear systems as well as single mesh systems with internal, buttress, or helical tooth forms. The following modifications were added under the current funding: variable contact friction, planet cage and ring gear rim flexibility options, user friendly options, dynamic side bands, a speed survey option and the combining of the single and multiple mesh options into one general program. The modified program was evaluated by comparing calculated values to published test data and to test data taken on a Hamilton Standard turboprop reduction gear-box. In general, the correlation between the test data and the analytical data is good.
The adaptive dynamic community detection algorithm based on the non-homogeneous random walking
NASA Astrophysics Data System (ADS)
Xin, Yu; Xie, Zhi-Qiang; Yang, Jing
2016-05-01
With the changing of the habit and custom, people's social activity tends to be changeable. It is required to have a community evolution analyzing method to mine the dynamic information in social network. For that, we design the random walking possibility function and the topology gain function to calculate the global influence matrix of the nodes. By the analysis of the global influence matrix, the clustering directions of the nodes can be obtained, thus the NRW (Non-Homogeneous Random Walk) method for detecting the static overlapping communities can be established. We design the ANRW (Adaptive Non-Homogeneous Random Walk) method via adapting the nodes impacted by the dynamic events based on the NRW. The ANRW combines the local community detection with dynamic adaptive adjustment to decrease the computational cost for ANRW. Furthermore, the ANRW treats the node as the calculating unity, thus the running manner of the ANRW is suitable to the parallel computing, which could meet the requirement of large dataset mining. Finally, by the experiment analysis, the efficiency of ANRW on dynamic community detection is verified.
Macroscopic description of complex adaptive networks coevolving with dynamic node 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. PMID:26066206
Cetinbaş, Murat; Shakhnovich, Eugene I
2013-01-01
Although molecular chaperones are essential components of protein homeostatic machinery, their mechanism of action and impact on adaptation and evolutionary dynamics remain controversial. Here we developed a physics-based ab initio multi-scale model of a living cell for population dynamics simulations to elucidate the effect of chaperones on adaptive evolution. The 6-loci genomes of model cells encode model proteins, whose folding and interactions in cellular milieu can be evaluated exactly from their genome sequences. A genotype-phenotype relationship that is based on a simple yet non-trivially postulated protein-protein interaction (PPI) network determines the cell division rate. Model proteins can exist in native and molten globule states and participate in functional and all possible promiscuous non-functional PPIs. We find that an active chaperone mechanism, whereby chaperones directly catalyze protein folding, has a significant impact on the cellular fitness and the rate of evolutionary dynamics, while passive chaperones, which just maintain misfolded proteins in soluble complexes have a negligible effect on the fitness. We find that by partially releasing the constraint on protein stability, active chaperones promote a deeper exploration of sequence space to strengthen functional PPIs, and diminish the non-functional PPIs. A key experimentally testable prediction emerging from our analysis is that down-regulation of chaperones that catalyze protein folding significantly slows down the adaptation dynamics. PMID:24244114
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.
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
Oluk, Can; Pavan, Andrea; Kafaligonul, Hulusi
2016-01-01
At the early stages of visual processing, information is processed by two major thalamic pathways encoding brightness increments (ON) and decrements (OFF). Accumulating evidence suggests that these pathways interact and merge as early as in primary visual cortex. Using regular and reverse-phi motion in a rapid adaptation paradigm, we investigated the temporal dynamics of within and across pathway mechanisms for motion processing. When the adaptation duration was short (188 ms), reverse-phi and regular motion led to similar adaptation effects, suggesting that the information from the two pathways are combined efficiently at early-stages of motion processing. However, as the adaption duration was increased to 752 ms, reverse-phi and regular motion showed distinct adaptation effects depending on the test pattern used, either engaging spatiotemporal correlation between the same or opposite contrast polarities. Overall, these findings indicate that spatiotemporal correlation within and across ON-OFF pathways for motion processing can be selectively adapted, and support those models that integrate within and across pathway mechanisms for motion processing. PMID:27667401
The AFDM (advanced fluid dynamics model) program: Scope and significance
Bohl, W.R.; Parker, F.R. ); Wilhelm, D. . Inst. fuer Neutronenphysik und Reaktortechnik); Berthier, J. )
1990-01-01
The origins and goals of the advanced fluid dynamics model (AFDM) program are described, and the models, algorithm, and coding used in the resulting AFDM computer program are summarized. A sample fuel-steel boiling pool calculation is presented and compared with a similar SIMMER-II calculation. A subjective assessment of the AFDM developments is given, and areas where future work is possible are detailed. 10 refs.
Effects of an adapted physical activity program on psychophysical health in elderly women
Battaglia, Giuseppe; Bellafiore, Marianna; Alesi, Marianna; Paoli, Antonio; Bianco, Antonino; Palma, Antonio
2016-01-01
Background Several studies have shown the positive effects of adapted physical activity (APA) on physical and mental health (MH) during the lifetime. The aim of this study was to assess the effectiveness of a specific APA intervention program in the improvement of the health-related quality of life (QOL) and functional condition of spine in elderly women. Methods Thirty women were recruited from a senior center and randomly assigned to two groups: control group (CG; age: 69.69±7.94 years, height: 1.57±0.06 m, weight: 68.42±8.18 kg, body mass index [BMI]: 27.88±2.81) and trained group (TG; age: 68.35±6.04 years, height: 1.55±0.05 m, weight: 64.78±10.16 kg, BMI: 26.98±3.07). The APA program was conducted for 8 weeks, with two training sessions/week. CG did not perform any physical activity during the study. Spinal angles were evaluated by SpinalMouse® (Idiag, Volkerswill, Switzerland); health-related QOL was evaluated by SF-36 Health Survey, which assesses physical component summary (PCS-36), mental component summary (MCS-36), and eight subscales: physical functioning, role-physical, bodily pain, general health perception, role-emotional, social functioning, vitality, and MH. All measures were recorded before and after the experimental period. Results In TG, compared to CG, the two-way analysis of variance with repeated measures with Bonferroni post hoc test showed a relevant improvement in lumbar spinal angle (°) and in SF-36 outcomes after the intervention period. We showed a significant increase in physical functioning, bodily pain, and MH subscales and in PCS-36 and MCS-36 scores in TG compared to CG. In particular, from baseline to posttest, we found that in TG, the PCS-36 and MCS-36 scores increased by 13.20% and 11.64%, respectively. Conclusion We believe that an 8-week APA intervention program is able to improve psychophysical heath in elderly people. During the aging process, a dynamic lifestyle, including regular physical activity, is a crucial
Gourbière, Sébastien; Menu, Fréderic
2009-07-01
Many plants, insects, and crustaceans show within-population variability in dormancy length. The question of whether such variability corresponds to a genetic polymorphism of pure strategies or a mixed bet-hedging strategy, and how the level of phenotypic variability can evolve remain unknown for most species. Using an eco-genetic model rooted in a 25-year ecological field study of a Chestnut weevil, Curculio elephas, we show that its diapause-duration variability is more likely to have evolved by the spread of a bet-hedging strategy than by the establishment of a genetic polymorphism. Investigating further the adaptive dynamics of diapause-duration variability, we find two unanticipated patterns of general interest. First, there is a trade-off between the ability of bet-hedging strategies to persist on an ecological time scale and their ability to invade. The optimal strategy (in terms of persistence) cannot invade, whereas suboptimal bet-hedgers are good invaders. Second, we describe an original evolutionary dynamics where each bet-hedging strategy (defined by its rate of prolonged diapause) resists invasion by all others, so that the first type of bet-hedger to appear persists on an evolutionary time scale. Such "evolutionary priority effect" could drive the evolution of maladapted levels of diapause-duration variability.
An adaptive structure data acquisition system using a graphical-based programming language
NASA Technical Reports Server (NTRS)
Baroth, Edmund C.; Clark, Douglas J.; Losey, Robert W.
1992-01-01
An example of the implementation of data fusion using a PC and a graphical programming language is discussed. A schematic of the data acquisition system and user interface panel for an adaptive structure test are presented. The computer programs (a series of icons 'wired' together) are also discussed. The way in which using graphical-based programming software to control a data acquisition system can simplify analysis of data, promote multidisciplinary interaction, and provide users a more visual key to understanding their data are shown.
Adapting high-level language programs for parallel processing using data flow
NASA Technical Reports Server (NTRS)
Standley, Hilda M.
1988-01-01
EASY-FLOW, a very high-level data flow language, is introduced for the purpose of adapting programs written in a conventional high-level language to a parallel environment. The level of parallelism provided is of the large-grained variety in which parallel activities take place between subprograms or processes. A program written in EASY-FLOW is a set of subprogram calls as units, structured by iteration, branching, and distribution constructs. A data flow graph may be deduced from an EASY-FLOW program.
NASA Technical Reports Server (NTRS)
Weeks, Cindy Lou
1986-01-01
Experiments were conducted at NASA Ames Research Center to define multi-tasking software requirements for multiple-instruction, multiple-data stream (MIMD) computer architectures. The focus was on specifying solutions for algorithms in the field of computational fluid dynamics (CFD). The program objectives were to allow researchers to produce usable parallel application software as soon as possible after acquiring MIMD computer equipment, to provide researchers with an easy-to-learn and easy-to-use parallel software language which could be implemented on several different MIMD machines, and to enable researchers to list preferred design specifications for future MIMD computer architectures. Analysis of CFD algorithms indicated that extensions of an existing programming language, adaptable to new computer architectures, provided the best solution to meeting program objectives. The CoFORTRAN Language was written in response to these objectives and to provide researchers a means to experiment with parallel software solutions to CFD algorithms on machines with parallel architectures.
NASA Astrophysics Data System (ADS)
Martinez, N.; Michoud, G.; Cario, A.; Ollivier, J.; Franzetti, B.; Jebbar, M.; Oger, P.; Peters, J.
2016-09-01
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.
Martinez, N; Michoud, G; 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. PMID:27595789
Wei, Heming; Tao, Chuanyi; Zhu, Yinian; Krishnaswamy, Sridhar
2016-04-01
In this paper, a reflective semiconductor optical amplifier (RSOA) is configured to demodulate dynamic spectral shifts of a fiber Bragg grating (FBG) dynamic strain sensor. The FBG sensor and the RSOA source form an adaptive fiber cavity laser. As the reflective spectrum of the FBG sensor changes due to dynamic strains, the wavelength of the laser output shifts accordingly, which is subsequently converted into a corresponding phase shift and demodulated by an unbalanced Michelson interferometer. Due to the short transition time of the RSOA, the RSOA-FBG cavity can respond to dynamic strains at high frequencies extending to megahertz. A demodulator using a PID controller is used to compensate for low-frequency drifts induced by temperature and large quasi-static strains. As the sensitivity of the demodulator is a function of the optical path difference and the FBG spectral width, optimal parameters to obtain high sensitivity are presented. Multiplexing to demodulate multiple FBG sensors is also discussed. PMID:27139682
Martinez, N.; Michoud, G.; 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. PMID:27595789
Adaptive output feedback consensus tracking for linear multi-agent systems with unknown dynamics
NASA Astrophysics Data System (ADS)
Sun, Junyong; Geng, Zhiyong
2015-09-01
In this paper, the consensus tracking problem with unknown dynamics in the leader for the linear multi-agent systems is addressed. Based on the relative output information among the agents, decentralised adaptive consensus protocols with static coupling gains are designed to guarantee that the consensus tracking errors converge to a small neighbourhood around the origin and all the signals in the closed-loop dynamics are uniformly ultimately bounded. Moreover, the result is extended to the case with dynamic coupling gains which are independent of the eigenvalues of the Laplacian matrix. Both of the protocols with static and dynamic coupling gains are designed by using the relative outputs, which are more practical than the state-feedback ones. Finally, the theoretical results are verified through an example.
Quantum Information Biology: From Theory of Open Quantum Systems to Adaptive Dynamics
NASA Astrophysics Data System (ADS)
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.
Global solution for a kinetic chemotaxis model with internal dynamics and its fast adaptation limit
NASA Astrophysics Data System (ADS)
Liao, Jie
2015-12-01
A nonlinear kinetic chemotaxis model with internal dynamics incorporating signal transduction and adaptation is considered. This paper is concerned with: (i) the global solution for this model, and, (ii) its fast adaptation limit to Othmer-Dunbar-Alt type model. This limit gives some insight to the molecular origin of the chemotaxis behaviour. First, by using the Schauder fixed point theorem, the global existence of weak solution is proved based on detailed a priori estimates, under quite general assumptions. However, the Schauder theorem does not provide uniqueness, so additional analysis is required to be developed for uniqueness. Next, the fast adaptation limit of this model is derived by extracting a weak convergence subsequence in measure space. For this limit, the first difficulty is to show the concentration effect on the internal state. Another difficulty is the strong compactness argument on the chemical potential, which is essential for passing the nonlinear kinetic equation to the weak limit.
ERIC Educational Resources Information Center
Lancioni, Giulio E.; Singh, Nirbhay N.; O'Reilly, Mark F.; Sigafoos, Jeff; Didden, Robert; Oliva, Doretta; Severini, Laura
2007-01-01
A program was recently developed to promote adaptive responses and upright head position in students with multiple disabilities through the use of microswitch clusters (i.e., combinations of two microswitches). The five students exposed to the program showed a significant increase in adaptive responses performed with head upright. The first…
An Experimental Trial of Adaptive Programming in Drug Court: Outcomes at 6, 12 and 18 Months
Marlowe, Douglas B.; Festinger, David S.; Dugosh, Karen L.; Benasutti, Kathleen M.; Fox, Gloria; Harron, Ashley
2013-01-01
Objectives Test whether an adaptive program improves outcomes in drug court by adjusting the schedule of court hearings and clinical case-management sessions pursuant to a priori performance criteria. Methods Consenting participants in a misdemeanor drug court were randomly assigned to the adaptive program (n = 62) or to a baseline-matching condition (n = 63) in which they attended court hearings based on the results of a criminal risk assessment. Outcome measures were re-arrest rates at 18 months post-entry to the drug court and urine drug test results and structured interview results at 6 and 12 months post-entry. Results Although previously published analyses revealed significantly fewer positive drug tests for participants in the adaptive condition during the first 18 weeks of drug court, current analyses indicate the effects converged during the ensuing year. Between-group differences in new arrest rates, urine drug test results and self-reported psychosocial problems were small and non-statistically significant at 6, 12 and 18 months post-entry. A non-significant trend (p = .10) suggests there may have been a small residual impact (Cramer's ν = .15) on new misdemeanor arrests after 18 months. Conclusions Adaptive programming shows promise for enhancing short-term outcomes in drug courts; however, additional efforts are needed to extend the effects beyond the first 4 to 6 months of enrollment. PMID:25346652
Melis, Theodore S.; Walters, Carl; Korman, Josh
2015-01-01
With a focus on resources of the Colorado River ecosystem below Glen Canyon Dam, the Glen Canyon Dam Adaptive Management Program has included a variety of experimental policy tests, ranging from manipulation of water releases from the dam to removal of non-native fish within Grand Canyon National Park. None of these field-scale experiments has yet produced unambiguous results in terms of management prescriptions. But there has been adaptive learning, mostly from unanticipated or surprising resource responses relative to predictions from ecosystem modeling. Surprise learning opportunities may often be viewed with dismay by some stakeholders who might not be clear about the purpose of science and modeling in adaptive management. However, the experimental results from the Glen Canyon Dam program actually represent scientific successes in terms of revealing new opportunities for developing better river management policies. A new long-term experimental management planning process for Glen Canyon Dam operations, started in 2011 by the U.S. Department of the Interior, provides an opportunity to refocus management objectives, identify and evaluate key uncertainties about the influence of dam releases, and refine monitoring for learning over the next several decades. Adaptive learning since 1995 is critical input to this long-term planning effort. Embracing uncertainty and surprise outcomes revealed by monitoring and ecosystem modeling will likely continue the advancement of resource objectives below the dam, and may also promote efficient learning in other complex programs.
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. PMID:27212938
NASA Astrophysics Data System (ADS)
Zhao, Dongya; Li, Shaoyuan; Zhu, Quanmin
2016-03-01
In this study, a new adaptive synchronised tracking control approach is developed for the operation of multiple robotic manipulators in the presence of uncertain kinematics and dynamics. In terms of the system synchronisation and adaptive control, the proposed approach can stabilise position tracking of each robotic manipulator while coordinating its motion with the other robotic manipulators. On the other hand, the developed approach can cope with kinematic and dynamic uncertainties. The corresponding stability analysis is presented to lay a foundation for theoretical understanding of the underlying issues as well as an assurance for safely operating real systems. Illustrative examples are bench tested to validate the effectiveness of the proposed approach. In addition, to face the challenging issues, this study provides an exemplary showcase with effectively to integrate several cross boundary theoretical results to formulate an interdisciplinary solution.
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.
High dynamic range image rendering with a Retinex-based adaptive filter.
Meylan, Laurence; Süsstrunk, Sabine
2006-09-01
We propose a new method to render high dynamic range images that models global and local adaptation of the human visual system. Our method is based on the center-surround Retinex model. The novelties of our method is first to use an adaptive filter, whose shape follows the image high-contrast edges, thus reducing halo artifacts common to other methods. Second, only the luminance channel is processed, which is defined by the first component of a principal component analysis. Principal component analysis provides orthogonality between channels and thus reduces the chromatic changes caused by the modification of luminance. We show that our method efficiently renders high dynamic range images and we compare our results with the current state of the art. PMID:16948325
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. PMID:27212938
Behavioral and neural Darwinism: selectionist function and mechanism in adaptive behavior dynamics.
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.
CARBON DYNAMICS OF THE CONSERVATION AND WETLAND RESERVE PROGRAMS
Data from the Conservation (CRP) and Wetland (WRP) Reserve Programs were analyzed to quantify the carbon (C) dynamics of associated cropland converted to grassland or forestland. Land-area enrollments were multiplied by grassland- and forestland-C densities to calculate C pools a...
Mississippi Curriculum Framework for Family Dynamics. Secondary Programs.
ERIC Educational Resources Information Center
Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.
This document, which reflects Mississippi's statutory requirement that instructional programs be based on core curricula and performance-based assessment, contains outlines of the instructional units required in local instructional management plans and daily lesson plans for family dynamics. The course uses skills in critical thinking, decision…
Dynamic Programming Algorithm vs. Genetic Algorithm: Which is Faster?
NASA Astrophysics Data System (ADS)
Petković, Dušan
The article compares two different approaches for the optimization problem of large join queries (LJQs). Almost all commercial database systems use a form of the dynamic programming algorithm to solve the ordering of join operations for large join queries, i.e. joins with more than dozen join operations. The property of the dynamic programming algorithm is that the execution time increases significantly in the case, where the number of join operations in a query is large. Genetic algorithms (GAs), as a data mining technique, have been shown as a promising technique in solving the ordering of join operations in LJQs. Using the existing implementation of GA, we compare the dynamic programming algorithm implemented in commercial database systems with the corresponding GA module. Our results show that the use of a genetic algorithm is a better solution for optimization of large join queries, i.e., that such a technique outperforms the implementations of the dynamic programming algorithm in conventional query optimization components for very large join queries.
Differentially Private Histogram Publication For Dynamic Datasets: An Adaptive Sampling Approach
Li, Haoran; Jiang, Xiaoqian; Xiong, Li; Liu, Jinfei
2016-01-01
Differential privacy has recently become a de facto standard for private statistical data release. Many algorithms have been proposed to generate differentially private histograms or synthetic data. However, most of them focus on “one-time” release of a static dataset and do not adequately address the increasing need of releasing series of dynamic datasets in real time. A straightforward application of existing histogram methods on each snapshot of such dynamic datasets will incur high accumulated error due to the composibility of differential privacy and correlations or overlapping users between the snapshots. In this paper, we address the problem of releasing series of dynamic datasets in real time with differential privacy, using a novel adaptive distance-based sampling approach. Our first method, DSFT, uses a fixed distance threshold and releases a differentially private histogram only when the current snapshot is sufficiently different from the previous one, i.e., with a distance greater than a predefined threshold. Our second method, DSAT, further improves DSFT and uses a dynamic threshold adaptively adjusted by a feedback control mechanism to capture the data dynamics. Extensive experiments on real and synthetic datasets demonstrate that our approach achieves better utility than baseline methods and existing state-of-the-art methods. PMID:26973795
Fournier-Level, Alexandre; Perry, Emily O; Wang, Jonathan A; Braun, Peter T; Migneault, Andrew; Cooper, Martha D; Metcalf, C Jessica E; Schmitt, Johanna
2016-05-17
Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico "resurrection experiments" showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation. PMID:27140640
An adaptive mesh finite volume method for the Euler equations of gas dynamics
NASA Astrophysics Data System (ADS)
Mungkasi, Sudi
2016-06-01
The Euler equations have been used to model gas dynamics for decades. They consist of mathematical equations for the conservation of mass, momentum, and energy of the gas. For a large time value, the solution may contain discontinuities, even when the initial condition is smooth. A standard finite volume numerical method is not able to give accurate solutions to the Euler equations around discontinuities. Therefore we solve the Euler equations using an adaptive mesh finite volume method. In this paper, we present a new construction of the adaptive mesh finite volume method with an efficient computation of the refinement indicator. The adaptive method takes action automatically at around places having inaccurate solutions. Inaccurate solutions are reconstructed to reduce the error by refining the mesh locally up to a certain level. On the other hand, if the solution is already accurate, then the mesh is coarsened up to another certain level to minimize computational efforts. We implement the numerical entropy production as the mesh refinement indicator. As a test problem, we take the Sod shock tube problem. Numerical results show that the adaptive method is more promising than the standard one in solving the Euler equations of gas dynamics.
Altered temporal dynamics of neural adaptation in the aging human auditory cortex.
Herrmann, Björn; Henry, Molly J; Johnsrude, Ingrid S; Obleser, Jonas
2016-09-01
Neural response adaptation plays an important role in perception and cognition. Here, we used electroencephalography to investigate how aging affects the temporal dynamics of neural adaptation in human auditory cortex. Younger (18-31 years) and older (51-70 years) normal hearing adults listened to tone sequences with varying onset-to-onset intervals. Our results show long-lasting neural adaptation such that the response to a particular tone is a nonlinear function of the extended temporal history of sound events. Most important, aging is associated with multiple changes in auditory cortex; older adults exhibit larger and less variable response magnitudes, a larger dynamic response range, and a reduced sensitivity to temporal context. Computational modeling suggests that reduced adaptation recovery times underlie these changes in the aging auditory cortex and that the extended temporal stimulation has less influence on the neural response to the current sound in older compared with younger individuals. Our human electroencephalography results critically narrow the gap to animal electrophysiology work suggesting a compensatory release from cortical inhibition accompanying hearing loss and aging. PMID:27459921
NASA Astrophysics Data System (ADS)
Li, Xiaofeng; Xiang, Suying; Zhu, Pengfei; Wu, Min
2015-12-01
In order to avoid the inherent deficiencies of the traditional BP neural network, such as slow convergence speed, that easily leading to local minima, poor generalization ability and difficulty in determining the network structure, the dynamic self-adaptive learning algorithm of the BP neural network is put forward to improve the function of the BP neural network. The new algorithm combines the merit of principal component analysis, particle swarm optimization, correlation analysis and self-adaptive model, hence can effectively solve the problems of selecting structural parameters, initial connection weights and thresholds and learning rates of the BP neural network. This new algorithm not only reduces the human intervention, optimizes the topological structures of BP neural networks and improves the network generalization ability, but also accelerates the convergence speed of a network, avoids trapping into local minima, and enhances network adaptation ability and prediction ability. The dynamic self-adaptive learning algorithm of the BP neural network is used to forecast the total retail sale of consumer goods of Sichuan Province, China. Empirical results indicate that the new algorithm is superior to the traditional BP network algorithm in predicting accuracy and time consumption, which shows the feasibility and effectiveness of the new algorithm.
[Dynamic structure of the cardiac rhythm in the process of adapting to high-altitude hypoxia].
Shukurov, F A; Nidekker, I G
1981-01-01
On the basis of dynamic series of RR intervals of electrocardiograms of healthy male test subjects exposed for a different period of time to high altitude hypoxia, autoregression clouds were built. The patterns of distribution thus obtained were compared with physical work capacity of the test subjects. It is suggested that when selecting people to work actively at high altitudes autoregression clouds can be used as quantitative estimates of their health state and as predictions of potential adaptation failures.
Dynamic analysis of spur gears using computer program DANST
NASA Technical Reports Server (NTRS)
Oswald, Fred B.; Lin, Hsiang H.; Liou, Chuen-Huei; Valco, Mark J.
1993-01-01
DANST is a computer program for static and dynamic analysis of spur gear systems. The program can be used for parametric studies to predict the effect on dynamic load and tooth bending stress of spur gears due to operating speed, torque, stiffness, damping, inertia, and tooth profile. DANST performs geometric modeling and dynamic analysis for low- or high-contact-ratio spur gears. DANST can simulate gear systems with contact ratio ranging from one to three. It was designed to be easy to use, and it is extensively documented by comments in the source code. This report describes the installation and use of DANST. It covers input data requirements and presents examples. The report also compares DANST predictions for gear tooth loads and bending stress to experimental and finite element results.
Dynamic analysis of spur gears using computer program DANST
Oswald, F.B.; Lin, H.H.; Liou, Chuenheui; Valco, M.J.
1993-06-01
DANST is a computer program for static and dynamic analysis of spur gear systems. The program can be used for parametric studies to predict the effect on dynamic load and tooth bending stress of spur gears due to operating speed, torque, stiffness, damping, inertia, and tooth profile. DANST performs geometric modeling and dynamic analysis for low- or high-contact-ratio spur gears. DANST can simulate gear systems with contact ratio ranging from one to three. It was designed to be easy to use, and it is extensively documented by comments in the source code. This report describes the installation and use of DANST. It covers input data requirements and presents examples. The report also compares DANST predictions for gear tooth loads and bending stress to experimental and finite element results. 14 refs.
NASA Astrophysics Data System (ADS)
Pathak, Anand; Sinha, Sitabhra
2015-09-01
Many complex systems can be represented as networks of dynamical elements whose states evolve in response to interactions with neighboring elements, noise and external stimuli. The collective behavior of such systems can exhibit remarkable ordering phenomena such as chimera order corresponding to coexistence of ordered and disordered regions. Often, the interactions in such systems can also evolve over time responding to changes in the dynamical states of the elements. Link adaptation inspired by Hebbian learning, the dominant paradigm for neuronal plasticity, has been earlier shown to result in structural balance by removing any initial frustration in a system that arises through conflicting interactions. Here we show that the rate of the adaptive dynamics for the interactions is crucial in deciding the emergence of different ordering behavior (including chimera) and frustration in networks of Ising spins. In particular, we observe that small changes in the link adaptation rate about a critical value result in the system exhibiting radically different energy landscapes, viz., smooth landscape corresponding to balanced systems seen for fast learning, and rugged landscapes corresponding to frustrated systems seen for slow learning.
Evolution dynamics of a model for gene duplication under adaptive conflict
NASA Astrophysics Data System (ADS)
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.
On the global dynamics of adaptive systems - A study of an elementary example
NASA Technical Reports Server (NTRS)
Espana, Martin D.; Praly, Laurent
1993-01-01
The inherent nonlinear character of adaptive systems poses serious theoretical problems for the analysis of their dynamics. On the other hand, the importance of their dynamic behavior is directly related to the practical interest in predicting such undesirable phenomena as nonlinear oscillations, abrupt transients, intermittence or a high sensitivity with respect to initial conditions. A geometrical/qualitative description of the phase portrait of a discrete-time adaptive system with unmodeled disturbances is given. For this, the motions in the phase space are referred to normally hyperbolic (structurally stable) locally invariant sets. The study is complemented with a local stability analysis of the equilibrium point and periodic solutions. The critical character of adaptive systems under rather usual working conditions is discussed. Special emphasis is put on the causes leading to intermittence. A geometric interpretation of the effects of some commonly used palliatives to this problem is given. The 'dead-zone' approach is studied in more detail. The predicted dynamics are compared with simulation results.
Demonstrating the impact of flood adaptation using an online dynamic flood mapper
NASA Astrophysics Data System (ADS)
Orton, P. M.; MacManus, K.; Doxsey-Whitfield, E.; Yetman, G.; Fisher, K.; Sanderson, E. W.; Giampieri, M.; Blumberg, A. F.
2015-12-01
Municipalities across the nation are weighing the value of coastal natural and nature-based features (NNBF) for flood risk reduction and the many ecosystem services they provide, yet there is limited quantitative information available to help make these decisions. Here, we describe a new "dynamic" flood mapping web-tool that demonstrates the modeled effects of NNBF on flood hazard zones for the highly populated areas surrounding Jamaica Bay, New York City. The tool also provides information on damages from flooding as well as cost-benefit analyses for NNBF adaptations for the bay. The project researchers are involved with development of a Jamaica Bay Coastal Master Plan, and the mapper will play an important role for increasing the public understanding of adaptation options. More broadly, dynamic flood mappers have many more possibilities than "static" mappers that simply add sea level rise onto pre-defined flood levels and bathtub them over flood plains. Dynamic modeling can enable inclusion of the response of coastal systems, imposed human adaptation, as well as flooding by surge, tide and precipitation.
Solution-Adaptive Program for Computing 2D/Axi Viscous Flow
NASA Technical Reports Server (NTRS)
Wood, William A.
2003-01-01
A computer program solves the Navier- Stokes equations governing the flow of a viscous, compressible fluid in an axisymmetric or two-dimensional (2D) setting. To obtain solutions more accurate than those generated by prior such programs that utilize regular and/or fixed computational meshes, this program utilizes unstructured (that is, irregular triangular) computational meshes that are automatically adapted to solutions. The adaptation can refine to regions of high change in gradient or can be driven by a novel residual minimization technique. Starting from an initial mesh and a corresponding data structure, the adaptation of the mesh is controlled by use of minimization functional. Other improvements over prior such programs include the following: (1) Boundary conditions are imposed weakly; that is, following initial specification of solution values at boundary nodes, these values are relaxed in time by means of the same formulations as those used for interior nodes. (2) Eigenvalues are limited in order to suppress expansion shocks. (3) An upwind fluctuation-splitting distribution scheme applied to inviscid flux requires fewer operations and produces less artificial dissipation than does a finite-volume scheme, leading to greater accuracy of solutions.
ERIC Educational Resources Information Center
Kumar, Swapna; Ritzhaupt, Albert D.
2014-01-01
A cohort-based online professional doctorate program that consisted of both online coursework and research activities was designed using Garrison et al's community of inquiry (CoI) framework. The evaluation of the program proved a challenge because all existing CoI assessment methods in the past have dealt with online courses, not with online…
Wardill, Trevor J.; O'Kane, Cahir J.; de Polavieja, Gonzalo G.; Juusola, Mikko
2009-01-01
Because of the limited processing capacity of eyes, retinal networks must adapt constantly to best present the ever changing visual world to the brain. However, we still know little about how adaptation in retinal networks shapes neural encoding of changing information. To study this question, we recorded voltage responses from photoreceptors (R1–R6) and their output neurons (LMCs) in the Drosophila eye to repeated patterns of contrast values, collected from natural scenes. By analyzing the continuous photoreceptor-to-LMC transformations of these graded-potential neurons, we show that the efficiency of coding is dynamically improved by adaptation. In particular, adaptation enhances both the frequency and amplitude distribution of LMC output by improving sensitivity to under-represented signals within seconds. Moreover, the signal-to-noise ratio of LMC output increases in the same time scale. We suggest that these coding properties can be used to study network adaptation using the genetic tools in Drosophila, as shown in a companion paper (Part II). PMID:19180196
Spike-Threshold Adaptation Predicted by Membrane Potential Dynamics In Vivo
Fontaine, Bertrand; Peña, José Luis; Brette, Romain
2014-01-01
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. PMID:24722397
Ogbunugafor, C Brandon; Wylie, C Scott; Diakite, Ibrahim; Weinreich, Daniel M; Hartl, Daniel L
2016-01-01
The adaptive landscape analogy has found practical use in recent years, as many have explored how their understanding can inform therapeutic strategies that subvert the evolution of drug resistance. A major barrier to applications of these concepts is a lack of detail concerning how the environment affects adaptive landscape topography, and consequently, the outcome of drug treatment. Here we combine empirical data, evolutionary theory, and computer simulations towards dissecting adaptive landscape by environment interactions for the evolution of drug resistance in two dimensions-drug concentration and drug type. We do so by studying the resistance mediated by Plasmodium falciparum dihydrofolate reductase (DHFR) to two related inhibitors-pyrimethamine and cycloguanil-across a breadth of drug concentrations. We first examine whether the adaptive landscapes for the two drugs are consistent with common definitions of cross-resistance. We then reconstruct all accessible pathways across the landscape, observing how their structure changes with drug environment. We offer a mechanism for non-linearity in the topography of accessible pathways by calculating of the interaction between mutation effects and drug environment, which reveals rampant patterns of epistasis. We then simulate evolution in several different drug environments to observe how these individual mutation effects (and patterns of epistasis) influence paths taken at evolutionary "forks in the road" that dictate adaptive dynamics in silico. In doing so, we reveal how classic metrics like the IC50 and minimal inhibitory concentration (MIC) are dubious proxies for understanding how evolution will occur across drug environments. We also consider how the findings reveal ambiguities in the cross-resistance concept, as subtle differences in adaptive landscape topography between otherwise equivalent drugs can drive drastically different evolutionary outcomes. Summarizing, we discuss the results with regards to their
Ogbunugafor, C. Brandon; Wylie, C. Scott; Diakite, Ibrahim; Weinreich, Daniel M.; Hartl, Daniel L.
2016-01-01
The adaptive landscape analogy has found practical use in recent years, as many have explored how their understanding can inform therapeutic strategies that subvert the evolution of drug resistance. A major barrier to applications of these concepts is a lack of detail concerning how the environment affects adaptive landscape topography, and consequently, the outcome of drug treatment. Here we combine empirical data, evolutionary theory, and computer simulations towards dissecting adaptive landscape by environment interactions for the evolution of drug resistance in two dimensions—drug concentration and drug type. We do so by studying the resistance mediated by Plasmodium falciparum dihydrofolate reductase (DHFR) to two related inhibitors—pyrimethamine and cycloguanil—across a breadth of drug concentrations. We first examine whether the adaptive landscapes for the two drugs are consistent with common definitions of cross-resistance. We then reconstruct all accessible pathways across the landscape, observing how their structure changes with drug environment. We offer a mechanism for non-linearity in the topography of accessible pathways by calculating of the interaction between mutation effects and drug environment, which reveals rampant patterns of epistasis. We then simulate evolution in several different drug environments to observe how these individual mutation effects (and patterns of epistasis) influence paths taken at evolutionary “forks in the road” that dictate adaptive dynamics in silico. In doing so, we reveal how classic metrics like the IC50 and minimal inhibitory concentration (MIC) are dubious proxies for understanding how evolution will occur across drug environments. We also consider how the findings reveal ambiguities in the cross-resistance concept, as subtle differences in adaptive landscape topography between otherwise equivalent drugs can drive drastically different evolutionary outcomes. Summarizing, we discuss the results with
The dynamics of the Π1 colour mechanism: further evidence for two sites of adaptation
Augenstein, E. J.; Pugh, E. N.
1977-01-01
1. The visual pathway that determines Stiles's Π1 colour mechanism was isolated by the auxiliary field technique and studied under dynamic conditions of light adaptation and recovery by threshold measurements. 2. The time courses of adaptation to Π1-equated short wave-length (μ ≤ 500 nm) and long wave-length (μ ≥ 550 nm) fields are very distinct: a large and relatively long-enduring transient threshold elevation occurs at the onset of the long wave-length, but not of the short wave-length fields. 3. Similarly, the time courses of recovery from Π1-equated long and short wave-length fields are quite distinctive: a large and relatively long enduring transient (`transient tritanopia') occurs at the offset of the long wave-length, but not of the short wave-length fields. 4. The wave-lengths of the fields which cause the adaptation transients coincide with those shown previously (Pugh, 1976) to combine non-additively with μ = 430 nm fields in effecting Π1 adaptation. The failure of the time course of Π1 adaptation to be spectrally `univariant' combines with the failures of field-additivity to demonstrate that signals from the long and/or middle wave-length sensitive cones affect the adaptation state of the Π1 pathway. 5. The adaptation transients are not observed in the pathways that determine Π4 and Π5. Thus, instantaneous signals from the middle and/or long wave-length sensitive cones are not the cause of the transients. Rather the cause must lie in the path by which those cones transmit their signals to the Π1 pathway or in the Π1 pathway itself. 6. The off-transient can be diminished by adding an adequately intense short wave-length field to a long wave-length field that would normally cause it. The Π1 pathway must receive chromatically opponent signals. PMID:592192
Sandovici, Ionel; Hoelle, Katharina; Angiolini, Emily; Constância, Miguel
2012-07-01
The placenta is a transient organ found in eutherian mammals that evolved primarily to provide nutrients for the developing fetus. The placenta exchanges a wide array of nutrients, endocrine signals, cytokines and growth factors with the mother and the fetus, thereby regulating intrauterine development. Recent studies show that the placenta is not just a passive organ mediating maternal-fetal exchange. It can adapt its capacity to supply nutrients in response to intrinsic and extrinsic variations in the maternal-fetal environment. These dynamic adaptations are thought to occur to maximize fetal growth and viability at birth in the prevailing conditions in utero. However, some of these adaptations may also affect the development of individual fetal tissues, with patho-physiological consequences long after birth. Here, this review summarizes current knowledge on the causes, possible mechanisms and consequences of placental adaptive responses, with a focus on the regulation of transporter-mediated processes for nutrients. This review also highlights the emerging roles that imprinted genes and epigenetic mechanisms of gene regulation may play in placental adaptations to the maternal-fetal environment.
Consequences of adaptive behaviour for the structure and dynamics of food webs.
Valdovinos, Fernanda S; Ramos-Jiliberto, Rodrigo; Garay-Narváez, Leslie; Urbani, Pasquinell; Dunne, Jennifer A
2010-12-01
Species coexistence within ecosystems and the stability of patterns of temporal changes in population sizes are central topics in ecological theory. In the last decade, adaptive behaviour has been proposed as a mechanism of population stabilization. In particular, widely distributed adaptive trophic behaviour (ATB), the fitness-enhancing changes in individuals' feeding-related traits due to variation in their trophic environment, may play a key role in modulating the dynamics of feeding relationships within natural communities. In this article, we review and synthesize models and results from theoretical research dealing with the consequences of ATB on the structure and dynamics of complex food webs. We discuss current approaches, point out limitations, and consider questions ripe for future research. In spite of some differences in the modelling and analytic approaches, there are points of convergence: (1) ATB promotes the complex structure of ecological networks, (2) ATB increases the stability of their dynamics, (3) ATB reverses May's negative complexity-stability relationship, and (4) ATB provides resilience and resistance of networks against perturbations. Current knowledge supports ATB as an essential ingredient for models of community dynamics, and future research that incorporates ATB will be well positioned to address questions important for basic ecological research and its applications.
Blamey, Peter J
2005-01-01
Adaptive dynamic range optimization (ADRO) is an amplification strategy that uses digital signal processing techniques to improve the audibility, comfort, and intelligibility of sounds for people who use cochlear implants and/or hearing aids. The strategy uses statistical analysis to select the most information-rich section of the input dynamic range in multiple-frequency channels. Fuzzy logic rules control the gain in each frequency channel so that the selected section of the dynamic range is presented at an audible and comfortable level. The ADRO processing thus adaptively optimizes the dynamic range of the signal in multiple-frequency channels. Clinical studies show that ADRO can be fitted easily to all degrees of hearing loss for hearing aids and cochlear implants in a direct and intuitive manner, taking the preferences of the listener into account. The result is high acceptance by new and experienced hearing aid users and strong preferences for ADRO compared with alternative amplification strategies. The ADRO processing is particularly well suited to bimodal and hybrid stimulation which combine electric and acoustic stimulation in opposite ears or in the same ear, respectively.
Blamey, Peter J.
2005-01-01
Adaptive dynamic range optimization (ADRO) is an amplification strategy that uses digital signal processing techniques to improve the audibility, comfort, and intelligibility of sounds for people who use cochlear implants and/or hearing aids. The strategy uses statistical analysis to select the most information-rich section of the input dynamic range in multiple-frequency channels. Fuzzy logic rules control the gain in each frequency channel so that the selected section of the dynamic range is presented at an audible and comfortable level. The ADRO processing thus adaptively optimizes the dynamic range of the signal in multiple-frequency channels. Clinical studies show that ADRO can be fitted easily to all degrees of hearing loss for hearing aids and cochlear implants in a direct and intuitive manner, taking the preferences of the listener into account. The result is high acceptance by new and experienced hearing aid users and strong preferences for ADRO compared with alternative amplification strategies. The ADRO processing is particularly well suited to bimodal and hybrid stimulation which combine electric and acoustic stimulation in opposite ears or in the same ear, respectively. PMID:16012705
NASA Astrophysics Data System (ADS)
Pathak, Harshavardhana S.; Shukla, Ratnesh K.
2016-08-01
A high-order adaptive finite-volume method is presented for simulating inviscid compressible flows on time-dependent redistributed grids. The method achieves dynamic adaptation through a combination of time-dependent mesh node clustering in regions characterized by strong solution gradients and an optimal selection of the order of accuracy and the associated reconstruction stencil in a conservative finite-volume framework. This combined approach maximizes spatial resolution in discontinuous regions that require low-order approximations for oscillation-free shock capturing. Over smooth regions, high-order discretization through finite-volume WENO schemes minimizes numerical dissipation and provides excellent resolution of intricate flow features. The method including the moving mesh equations and the compressible flow solver is formulated entirely on a transformed time-independent computational domain discretized using a simple uniform Cartesian mesh. Approximations for the metric terms that enforce discrete geometric conservation law while preserving the fourth-order accuracy of the two-point Gaussian quadrature rule are developed. Spurious Cartesian grid induced shock instabilities such as carbuncles that feature in a local one-dimensional contact capturing treatment along the cell face normals are effectively eliminated through upwind flux calculation using a rotated Hartex-Lax-van Leer contact resolving (HLLC) approximate Riemann solver for the Euler equations in generalized coordinates. Numerical experiments with the fifth and ninth-order WENO reconstructions at the two-point Gaussian quadrature nodes, over a range of challenging test cases, indicate that the redistributed mesh effectively adapts to the dynamic flow gradients thereby improving the solution accuracy substantially even when the initial starting mesh is non-adaptive. The high adaptivity combined with the fifth and especially the ninth-order WENO reconstruction allows remarkably sharp capture of
Cultural adaptation process for international dissemination of the strengthening families program.
Kumpfer, Karol L; Pinyuchon, Methinin; Teixeira de Melo, Ana; Whiteside, Henry O
2008-06-01
The Strengthening Families Program (SFP) is an evidence-based family skills training intervention developed and found efficacious for substance abuse prevention by U.S researchers in the 1980s. In the 1990s, a cultural adaptation process was developed to transport SFP for effectiveness trials with diverse populations (African, Hispanic, Asian, Pacific Islander, and Native American). Since 2003, SFP has been culturally adapted for use in 17 countries. This article reviews the SFP theory and research and a recommended cultural adaptation process. Challenges in international dissemination of evidence-based programs (EBPs) are discussed based on the results of U.N. and U.S. governmental initiatives to transport EBP family interventions to developing countries. The technology transfer and quality assurance system are described, including the language translation and cultural adaptation process for materials development, staff training, and on-site and online Web-based supervision and technical assistance and evaluation services to assure quality implementation and process evaluation feedback for improvements.
Johnson-Jennings, Michelle; Baumann, Ana A.; Proctor, Enola
2015-01-01
Introduction Diabetes disproportionately affects underserved racial/ethnic groups in the United States. Diabetes prevention interventions positively influence health; however, further evaluation is necessary to determine what role culture plays in effective programming. We report on the status of research that examines cultural adaptations of diabetes prevention programs. Methods We conducted database searches in March and April 2014. We included studies that were conducted in the United States and that focused on diabetes prevention among African Americans, American Indians/Alaska Natives, Asian Americans/Pacific Islanders, and Latinos. Results A total of 58 studies were identified for review; 29 were excluded from evaluation. Few adaptations referenced or followed recommendations for cultural adaptation nor did they justify the content modifications by providing a rationale or evidence. Cultural elements unique to racial/ethnic populations were not assessed. Conclusion Future cultural adaptations should use recommended processes to ensure that culture’s role in diabetes prevention–related behavioral changes contributes to research. PMID:25950567
Woo, Hyung Jun; Reifman, Jaques
2014-01-01
We describe a stochastic virus evolution model representing genomic diversification and within-host selection during experimental serial passages under cell culture or live-host conditions. The model incorporates realistic descriptions of the virus genotypes in nucleotide and amino acid sequence spaces, as well as their diversification from error-prone replications. It quantitatively considers factors such as target cell number, bottleneck size, passage period, infection and cell death rates, and the replication rate of different genotypes, allowing for systematic examinations of how their changes affect the evolutionary dynamics of viruses during passages. The relative probability for a viral population to achieve adaptation under a new host environment, quantified by the rate with which a target sequence frequency rises above 50%, was found to be most sensitive to factors related to sequence structure (distance from the wild type to the target) and selection strength (host cell number and bottleneck size). For parameter values representative of RNA viruses, the likelihood of observing adaptations during passages became negligible as the required number of mutations rose above two amino acid sites. We modeled the specific adaptation process of influenza A H5N1 viruses in mammalian hosts by simulating the evolutionary dynamics of H5 strains under the fitness landscape inferred from multiple sequence alignments of H3 proteins. In light of comparisons with experimental findings, we observed that the evolutionary dynamics of adaptation is strongly affected not only by the tendency toward increasing fitness values but also by the accessibility of pathways between genotypes constrained by the genetic code.
Bikard, David; Marraffini, Luciano A
2012-02-01
Bacteria are constantly challenged by bacteriophages (viruses that infect bacteria), the most abundant microorganism on earth. Bacteria have evolved a variety of immunity mechanisms to resist bacteriophage infection. In response, bacteriophages can evolve counter-resistance mechanisms and launch a 'virus versus host' evolutionary arms race. In this context, rapid evolution is fundamental for the survival of the bacterial cell. Programmed genetic variation mechanisms at loci involved in immunity against bacteriophages generate diversity at a much faster rate than random point mutation and enable bacteria to quickly adapt and repel infection. Diversity-generating retroelements (DGRs) and phase variation mechanisms enhance the generic (innate) immune response against bacteriophages. On the other hand, the integration of small bacteriophage sequences in CRISPR loci provide bacteria with a virus-specific and sequence-specific adaptive immune response. Therefore, although using different molecular mechanisms, both prokaryotes and higher organisms rely on programmed genetic variation to increase genetic diversity and fight rapidly evolving infectious agents.
Architecture-Adaptive Computing Environment: A Tool for Teaching Parallel Programming
NASA Technical Reports Server (NTRS)
Dorband, John E.; Aburdene, Maurice F.
2002-01-01
Recently, networked and cluster computation have become very popular. This paper is an introduction to a new C based parallel language for architecture-adaptive programming, aCe C. The primary purpose of aCe (Architecture-adaptive Computing Environment) is to encourage programmers to implement applications on parallel architectures by providing them the assurance that future architectures will be able to run their applications with a minimum of modification. A secondary purpose is to encourage computer architects to develop new types of architectures by providing an easily implemented software development environment and a library of test applications. This new language should be an ideal tool to teach parallel programming. In this paper, we will focus on some fundamental features of aCe C.
NASA Astrophysics Data System (ADS)
Wu, Xia; Wu, Genhua
2014-08-01
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 Ag61 cluster is found to be stacking-fault face-centered cubic, whose energy is lower than that of previously obtained icosahedron.
Pairwise adaptive thermostats for improved accuracy and stability in dissipative particle dynamics
NASA Astrophysics Data System (ADS)
Leimkuhler, Benedict; Shang, Xiaocheng
2016-11-01
We examine the formulation and numerical treatment of dissipative particle dynamics (DPD) and momentum-conserving molecular dynamics. We show that it is possible to improve both the accuracy and the stability of DPD by employing a pairwise adaptive Langevin thermostat that precisely matches the dynamical characteristics of DPD simulations (e.g., autocorrelation functions) while automatically correcting thermodynamic averages using a negative feedback loop. In the low friction regime, it is possible to replace DPD by a simpler momentum-conserving variant of the Nosé-Hoover-Langevin method based on thermostatting only pairwise interactions; we show that this method has an extra order of accuracy for an important class of observables (a superconvergence result), while also allowing larger timesteps than alternatives. All the methods mentioned in the article are easily implemented. Numerical experiments are performed in both equilibrium and nonequilibrium settings; using Lees-Edwards boundary conditions to induce shear flow.
Grand-Canonical Adaptive Resolution Centroid Molecular Dynamics: Implementation and application
NASA Astrophysics Data System (ADS)
Agarwal, Animesh; Delle Site, Luigi
2016-09-01
We have implemented the Centroid Molecular Dynamics scheme (CMD) into the Grand Canonical-like version of the Adaptive Resolution Simulation Molecular Dynamics (GC-AdResS) method. We have tested the implementation on two different systems, liquid parahydrogen at extreme thermodynamic conditions and liquid water at ambient conditions; the reproduction of structural as well as dynamical results of reference systems are highly satisfactory. The capability of performing GC-AdResS CMD simulations allows for the treatment of a system characterized by some quantum features and open boundaries. This latter characteristic not only is of computational convenience, allowing for equivalent results of much larger and computationally more expensive systems, but also suggests a tool of analysis so far not explored, that is the unambiguous identification of the essential degrees of freedom required for a given property.
Tone reproduction for high-dynamic range imaging based on adaptive filtering
NASA Astrophysics Data System (ADS)
Ha, Changwoo; Lee, Joohyun; Jeong, Jechang
2014-03-01
A tone reproduction algorithm with enhanced contrast of high-dynamic range images on conventional low-dynamic range display devices is presented. The proposed algorithm consists mainly of block-based parameter estimation, a characteristic-based luminance adjustment, and an adaptive Gaussian filter using minimum description length. Instead of relying only on the reduction of the dynamic range, a characteristic-based luminance adjustment process modifies the luminance values. The Gaussian-filtered luminance value is obtained from appropriate value of variance, and the contrast is then enhanced through the use of a relation between the adjusted luminance and Gaussian-filtered luminance values. In the final tone-reproduction process, the proposed algorithm combines color and luminance components in order to preserve the color consistency. The experimental results demonstrate that the proposed algorithm achieves a good subjective quality while enhancing the contrast of the image details.
NASA Astrophysics Data System (ADS)
Yakunin, Alexander N.; Scherbakov, Yury N.
1994-02-01
The absence of satisfactory criteria for discrete model parameters choice during computer modeling of thermal processes of laser-biotissue interaction may be the premier sign for the accuracy of the numerical results obtained. The approach realizing the new concept of direct automatical adaptive grid construction is suggested. The intellectual program provides high calculation accuracy and is simple in practical usage so that a physician receives the ability to prescribe treatment without any assistance of a specialist in mathematical modeling.
Dynamic Programming for Structured Continuous Markov Decision Problems
NASA Technical Reports Server (NTRS)
Dearden, Richard; Meuleau, Nicholas; Washington, Richard; Feng, Zhengzhu
2004-01-01
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamically partitioned into regions where the value function is the same throughout the region. We first describe the algorithm for piecewise constant representations. We then extend it to piecewise linear representations, using techniques from POMDPs to represent and reason about linear surfaces efficiently. We show that for complex, structured problems, our approach exploits the natural structure so that optimal solutions can be computed efficiently.
Kim, D.; Ghanem, R.
1994-12-31
Multigrid solution technique to solve a material nonlinear problem in a visual programming environment using the finite element method is discussed. The nonlinear equation of equilibrium is linearized to incremental form using Newton-Rapson technique, then multigrid solution technique is used to solve linear equations at each Newton-Rapson step. In the process, adaptive mesh refinement, which is based on the bisection of a pair of triangles, is used to form grid hierarchy for multigrid iteration. The solution process is implemented in a visual programming environment with distributed computing capability, which enables more intuitive understanding of solution process, and more effective use of resources.
Outcomes of a type 2 diabetes education program adapted to the cultural contexts of Saudi women
Al-Bannay, Hana R.; Jongbloed, Lyn E.; Jarus, Tal; Alabdulwahab, Sami S.; Khoja, Tawfik A.; Dean, Elizabeth
2015-01-01
Objective: To explore the outcomes of a pilot intervention of a type 2 diabetes (T2D) education program, based on international standards, and adapted to the cultural and religious contexts of Saudi women. Methods: This study is an experiment of a pilot intervention carried out between August 2011 and January 2012 at the primary health clinics in Dammam. Women at risk of or diagnosed with T2D (N=35 including dropouts) were assigned to one of 2 groups; an intervention group participated in a pilot intervention of T2D education program, based on international standards and tailored to their cultural and religious contexts; and a usual care group received the usual care for diabetes in Saudi Arabia. Outcomes included blood glucose, body composition, 6-minute walk distance, life satisfaction, quality of life, and diabetes knowledge. The intervention group participated in a focus group of their program experience. Data analysis was based on mixed methods. Results: Based on 95% confidence interval comparisons, improvements were noted in blood sugar, 6-minute walk distance, quality of life, and diabetes knowledge in participants of the intervention group. They also reported improvements in lifestyle-related health behaviors after the education program. Conclusion: Saudi women may benefit from a T2D education program based on international standards and adapted to their cultural and religious contexts. PMID:26108595
Developmental cascade effects of the New Beginnings Program on adolescent adaptation outcomes.
McClain, Darya Bonds; Wolchik, Sharlene A; Winslow, Emily; Tein, Jenn-Yun; Sandler, Irwin N; Millsap, Roger E
2010-11-01
Using data from a 6-year longitudinal follow-up sample of 240 youth who participated in a randomized experimental trial of a preventive intervention for divorced families with children ages 9-12, the current study tested alternative cascading pathways by which the intervention decreased symptoms of internalizing disorders, symptoms of externalizing disorders, substance use, and risky sexual behavior and increased self-esteem and academic performance in mid- to late adolescence (15-19 years old). It was hypothesized that the impact of the program on adolescent adaptation outcomes would be explained by progressive associations between program-induced changes in parenting and youth adaptation outcomes. The results supported a cascading model of program effects in which the program was related to increased mother-child relationship quality that was related to subsequent decreases in child internalizing problems, which then was related to subsequent increases in self-esteem and decreases in symptoms of internalizing disorders in adolescence. The results were also consistent with a model in which the program increased maternal effective discipline that was related to decreased child externalizing problems, which was related to subsequent decreases in symptoms of externalizing disorders, less substance use, and better academic performance in adolescence. There were no significant differences in the model based on level of baseline risk or adolescent gender. These results provide support for a cascading pathways model of child and adolescent development.
Developmental Cascade Effects of the New Beginnings Program on Adolescent Adaptation Outcomes
Bonds, Darya D.; Wolchik, Sharlene A.; Winslow, Emily; Tein, Jenn-Yun; Sandler, Irwin N.; Millsap, Roger E.
2010-01-01
Using data from a 6-year longitudinal follow-up sample of 240 youth who participated in a randomized experimental trial of a preventive intervention for divorced families with children ages 9–12, the current study tested alternative cascading pathways by which the intervention decreased symptoms of internalizing disorders, symptoms of externalizing disorders, substance use, and risky sexual behavior, and increased self-esteem and academic performance in mid-to late-adolescence (15–19 years old). It was hypothesized that the impact of the program on adolescent adaptation outcomes would be explained by progressive associations between program-induced changes in parenting and youth adaptation outcomes. The results supported a cascading model of program effects in which the program was related to increased mother-child relationship quality, which was related to subsequent decreases in child internalizing problems, which then was related to subsequent increases in self-esteem and decreases in symptoms of internalizing disorders in adolescence. The results also were consistent with a model in which the program was related to increased maternal effective discipline, which was related to subsequent decreases in child externalizing problems, which then was related to subsequent decreases in symptoms of externalizing disorders, less substance use and better academic performance in adolescence. There were no significant differences in the model based on level of baseline risk or adolescent gender. These results provide support for a cascading pathways model of child and adolescent development. PMID:20883581
Taylor, Catherine R.; DiPietro, Natalie A.
2012-01-01
Objective. To develop and validate the Assessment, Development, Assurance Pharmacist's Tool (ADAPT), an instrument for pharmacists and student pharmacists to use in developing and implementing health promotion programs. Methods. The 36-item ADAPT instrument was developed using the framework of public health's 3 core functions (assessment, policy development, and assurance) and 10 essential services. The tool's content and usage was assessed and conducted through peer-review and initial validity testing processes. Results. Over 20 faculty members, preceptors, and student pharmacists at 5 institutions involved in planning and implementing health promotion initiatives reviewed the instrument and conducted validity testing. The instrument took approximately 15 minutes to complete and the findings resulted in changes and improvements to elements of the programs evaluated. Conclusion. The ADAPT instrument fills a need to more effectively plan, develop, implement, and evaluate pharmacist-directed public health programs that are evidence-based, high-quality, and compliant with laws and regulations and facilitates documentation of pharmacists’ contributions to public health. PMID:22412211
Schlüter, Lothar; Lohbeck, Kai T; Gröger, Joachim P; Riebesell, Ulf; Reusch, Thorsten B H
2016-07-01
Marine phytoplankton may adapt to ocean change, such as acidification or warming, because of their large population sizes and short generation times. Long-term adaptation to novel environments is a dynamic process, and phenotypic change can take place thousands of generations after exposure to novel conditions. We conducted a long-term evolution experiment (4 years = 2100 generations), starting with a single clone of the abundant and widespread coccolithophore Emiliania huxleyi exposed to three different CO2 levels simulating ocean acidification (OA). Growth rates as a proxy for Darwinian fitness increased only moderately under both levels of OA [+3.4% and +4.8%, respectively, at 1100 and 2200 μatm partial pressure of CO2 (Pco2)] relative to control treatments (ambient CO2, 400 μatm). Long-term adaptation to OA was complex, and initial phenotypic responses of ecologically important traits were later reverted. The biogeochemically important trait of calcification, in particular, that had initially been restored within the first year of evolution was later reduced to levels lower than the performance of nonadapted populations under OA. Calcification was not constitutively lost but returned to control treatment levels when high CO2-adapted isolates were transferred back to present-day control CO2 conditions. Selection under elevated CO2 exacerbated a general decrease of cell sizes under long-term laboratory evolution. Our results show that phytoplankton may evolve complex phenotypic plasticity that can affect biogeochemically important traits, such as calcification. Adaptive evolution may play out over longer time scales (>1 year) in an unforeseen way under future ocean conditions that cannot be predicted from initial adaptation responses. PMID:27419227
Schlüter, Lothar; Lohbeck, Kai T; Gröger, Joachim P; Riebesell, Ulf; Reusch, Thorsten B H
2016-07-01
Marine phytoplankton may adapt to ocean change, such as acidification or warming, because of their large population sizes and short generation times. Long-term adaptation to novel environments is a dynamic process, and phenotypic change can take place thousands of generations after exposure to novel conditions. We conducted a long-term evolution experiment (4 years = 2100 generations), starting with a single clone of the abundant and widespread coccolithophore Emiliania huxleyi exposed to three different CO2 levels simulating ocean acidification (OA). Growth rates as a proxy for Darwinian fitness increased only moderately under both levels of OA [+3.4% and +4.8%, respectively, at 1100 and 2200 μatm partial pressure of CO2 (Pco2)] relative to control treatments (ambient CO2, 400 μatm). Long-term adaptation to OA was complex, and initial phenotypic responses of ecologically important traits were later reverted. The biogeochemically important trait of calcification, in particular, that had initially been restored within the first year of evolution was later reduced to levels lower than the performance of nonadapted populations under OA. Calcification was not constitutively lost but returned to control treatment levels when high CO2-adapted isolates were transferred back to present-day control CO2 conditions. Selection under elevated CO2 exacerbated a general decrease of cell sizes under long-term laboratory evolution. Our results show that phytoplankton may evolve complex phenotypic plasticity that can affect biogeochemically important traits, such as calcification. Adaptive evolution may play out over longer time scales (>1 year) in an unforeseen way under future ocean conditions that cannot be predicted from initial adaptation responses.
Adaptive feedback potential in dynamic stability during disturbed walking in the elderly.
Bierbaum, Stefanie; Peper, Andreas; Karamanidis, Kiros; Arampatzis, Adamantios
2011-07-01
After perturbation of the gait, feedback information may help regaining balance adequately, but it remains unknown whether adaptive feedback responses are possible after repetitive and unexpected perturbations during gait and if there are age-related differences. Prior experience may contribute to improved reactive behavior. Fourteen old (59-73 yrs) and fourteen young (22-31 yrs) males walked on a walkway which included one covered element. By exchanging this element participants either stepped on hard surface or unexpectedly on soft surface which caused a perturbation in gait. The gait protocol contained 5 unexpected soft trials to quantify the reactive adaptation. Each soft trial was followed by 4-8 hard trials to generate a wash-out effect. The dynamic stability was investigated by using the margin of stability (MoS), which was calculated as the difference between the anterior boundary of the base of support and the extrapolated position of the center of mass in the anterior-posterior direction. MoS at recovery leg touchdown were significantly lower in the unexpected soft trials compared to the baseline, indicating a less stable posture. However, MoS increased (p<0.05) in both groups within the disturbed trials, indicating feedback adaptive improvements. Young and old participants showed differences in the handling of the perturbation in the course of several trials. The magnitude of the reactive adaptation after the fifth unexpected perturbation was significantly different compared to the first unexpected perturbation (old: 49±30%; young: 77±40%), showing a tendency (p=0.065) for higher values in the young participants. Old individuals maintain the ability to adapt to feedback controlled perturbations. However, the locomotor behavior is more conservative compared to the young ones, leading to disadvantages in the reactive adaptation during disturbed walking.
Schlüter, Lothar; Lohbeck, Kai T.; Gröger, Joachim P.; Riebesell, Ulf; Reusch, Thorsten B. H.
2016-01-01
Marine phytoplankton may adapt to ocean change, such as acidification or warming, because of their large population sizes and short generation times. Long-term adaptation to novel environments is a dynamic process, and phenotypic change can take place thousands of generations after exposure to novel conditions. We conducted a long-term evolution experiment (4 years = 2100 generations), starting with a single clone of the abundant and widespread coccolithophore Emiliania huxleyi exposed to three different CO2 levels simulating ocean acidification (OA). Growth rates as a proxy for Darwinian fitness increased only moderately under both levels of OA [+3.4% and +4.8%, respectively, at 1100 and 2200 μatm partial pressure of CO2 (Pco2)] relative to control treatments (ambient CO2, 400 μatm). Long-term adaptation to OA was complex, and initial phenotypic responses of ecologically important traits were later reverted. The biogeochemically important trait of calcification, in particular, that had initially been restored within the first year of evolution was later reduced to levels lower than the performance of nonadapted populations under OA. Calcification was not constitutively lost but returned to control treatment levels when high CO2–adapted isolates were transferred back to present-day control CO2 conditions. Selection under elevated CO2 exacerbated a general decrease of cell sizes under long-term laboratory evolution. Our results show that phytoplankton may evolve complex phenotypic plasticity that can affect biogeochemically important traits, such as calcification. Adaptive evolution may play out over longer time scales (>1 year) in an unforeseen way under future ocean conditions that cannot be predicted from initial adaptation responses. PMID:27419227
Dynamic modulation of innate immunity programming and memory.
Yuan, Ruoxi; Li, Liwu
2016-01-01
Recent progress harkens back to the old theme of immune memory, except this time in the area of innate immunity, to which traditional paradigm only prescribes a rudimentary first-line defense function with no memory. However, both in vitro and in vivo studies reveal that innate leukocytes may adopt distinct activation states such as priming, tolerance, and exhaustion, depending upon the history of prior challenges. The dynamic programming and potential memory of innate leukocytes may have far-reaching consequences in health and disease. This review aims to provide some salient features of innate programing and memory, patho-physiological consequences, underlying mechanisms, and current pressing issues. PMID:26740103
Satellite-tracking and earth-dynamics research programs
NASA Technical Reports Server (NTRS)
Weiffenbach, G. C.
1973-01-01
The following activities in Smithsonian Astrophysical Observatory's (SAO) earth-dynamics programs are covered: (1) satellite-tracking network operations; (2) satellite geodesy and geophysics programs; (3) atmospheric research. Approximately 46,000 successful range measurements were acquired by the SAO laser stations in Peru, South Africa, Brazil, and Arizona. The Peole satellite-tracking campaign conducted in conjunction with the Centre National d'Etudes Spatiales was completed in August 1973. The SAO network obtained 4482 validated returns of 310 arcs of Peole. These data are of particular value for obtaining more accurate gravity-field and zonal-harmonics coefficients.
Overview of the solar dynamic ground test demonstration program
NASA Technical Reports Server (NTRS)
Shaltens, Richard K.; Boyle, Robert V.
1993-01-01
The Solar Dynamic (SD) Ground Test Demonstration (GTD) program demonstrates the availability of SD technologies in a simulated space environment at the NASA Lewis Research Center (LeRC) vacuum facility. An aerospace industry/ government team is working together to design, fabricate, build, and test a complete SD system. This paper reviews the goals and status of the SD GTD program. A description of the SD system includes key design features of the system, subsystems, and components as reported at the Critical Design Review (CDR).
Synthesizing Dynamic Programming Algorithms from Linear Temporal Logic Formulae
NASA Technical Reports Server (NTRS)
Rosu, Grigore; Havelund, Klaus
2001-01-01
The problem of testing a linear temporal logic (LTL) formula on a finite execution trace of events, generated by an executing program, occurs naturally in runtime analysis of software. We present an algorithm which takes an LTL formula and generates an efficient dynamic programming algorithm. The generated algorithm tests whether the LTL formula is satisfied by a finite trace of events given as input. The generated algorithm runs in linear time, its constant depending on the size of the LTL formula. The memory needed is constant, also depending on the size of the formula.
Adaptive modeling, identification, and control of dynamic structural systems. I. Theory
Safak, Erdal
1989-01-01
A concise review of the theory of adaptive modeling, identification, and control of dynamic structural systems based on discrete-time recordings is presented. Adaptive methods have four major advantages over the classical methods: (1) Removal of the noise from the signal is done over the whole frequency band; (2) time-varying characteristics of systems can be tracked; (3) systems with unknown characteristics can be controlled; and (4) a small segment of the data is needed during the computations. Included in the paper are the discrete-time representation of single-input single-output (SISO) systems, models for SISO systems with noise, the concept of stochastic approximation, recursive prediction error method (RPEM) for system identification, and the adaptive control. Guidelines for model selection and model validation and the computational aspects of the method are also discussed in the paper. The present paper is the first of two companion papers. The theory given in the paper is limited to that which is necessary to follow the examples for applications in structural dynamics presented in the second paper.
GLOBEC (Global Ocean Ecosystems Dynamics: Northwest Atlantic program
NASA Technical Reports Server (NTRS)
1991-01-01
The specific objective of the meeting was to plan an experiment in the Northwestern Atlantic to study the marine ecosystem and its role, together with that of climate and physical dynamics, in determining fisheries recruitment. The underlying focus of the GLOBEC initiative is to understand the marine ecosystem as it related to marine living resources and to understand how fluctuation in these resources are driven by climate change and exploitation. In this sense the goal is a solid scientific program to provide basic information concerning major fisheries stocks and the environment that sustains them. The plan is to attempt to reach this understanding through a multidisciplinary program that brings to bear new techniques as disparate as numerical fluid dynamic models of ocean circulation, molecular biology and modern acoustic imaging. The effort will also make use of the massive historical data sets on fisheries and the state of the climate in a coordinated manner.
Satellite-tracking and Earth dynamics research programs
NASA Technical Reports Server (NTRS)
1982-01-01
The activities carried out by the Smithsonian Astrophysical Observatory (SAO) are described. The SAO network continued to track LAGEOS at highest priority for polar motion and Earth rotation studies, and for other geophysical investigations, including crustal dynamics, Earth and ocean tides, and the general development of precision orbit determination. The network performed regular tracking of several other retroreflector satellites including GEOS-1, GEOS-3, BE-C, and Starlette for refined determinations of station coordinates and the Earth's gravity field and for studies of solid Earth dynamics. A major program in laser upgrading continued to improve ranging accuracy and data yield. This program includes an increase in pulse repetition rate from 8 ppm to 30 ppm, a reduction in laser pulse width from 6 nsec to 2 to 3 nsec, improvements in the photoreceiver and the electronics to improve daylight ranging, and an analog pulse detection system to improve range noise and accuracy. Data processing hardware and software are discussed.
A dynamic programming algorithm for finding alternative RNA secondary structures.
Williams, A L; Tinoco, I
1986-01-10
Dynamic programming algorithms that predict RNA secondary structure by minimizing the free energy have had one important limitation. They were able to predict only one optimal structure. Given the uncertainties of the thermodynamic data and the effects of proteins and other environmental factors on structure, the optimal structure predicted by these methods may not have biological significance. We present a dynamic programming algorithm that can determine optimal and suboptimal secondary structures for an RNA. The power and utility of the method is demonstrated in the folding of the intervening sequence of the rRNA of Tetrahymena. By first identifying the major secondary structures corresponding to the lowest free energy minima, a secondary structure of possible biological significance is derived.
Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart
2011-01-01
We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the "model-free" variational analysis (VA)-based image enhancement approach and the "model-based" descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations.
Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart
2011-01-01
We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the “model-free” variational analysis (VA)-based image enhancement approach and the “model-based” descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations. PMID:22163859
Rojnuckarin, A; Livesay, D R; Subramaniam, S
2000-08-01
We discuss here the implementation of the Weighted Ensemble Brownian (WEB) dynamics algorithm of Huber and Kim in the University of Houston Brownian Dynamics (UHBD) suite of programs and its application to bimolecular association problems. WEB dynamics is a biased Brownian dynamics (BD) algorithm that is more efficient than the standard Northrup-Allison-McCammon (NAM) method in cases where reaction events are infrequent because of intervening free energy barriers. Test cases reported here include the Smoluchowski rate for association of spheres, the association of the enzyme copper-zinc superoxide dismutase with superoxide anion, and the binding of the superpotent sweetener N-(p-cyanophenyl)-N'-(diphenylmethyl)-guanidinium acetic acid to a monoclonal antibody fragment, NC6.8. Our results show that the WEB dynamics algorithm is a superior simulation method for enzyme-substrate reaction encounters with large free energy barriers.
NASA Technical Reports Server (NTRS)
Burgin, G. H.; Owens, A. J.
1975-01-01
A detailed description is presented of the computer programs in order to provide an understanding of the mathematical and geometrical relationships as implemented in the programs. The individual sbbroutines and their underlying mathematical relationships are described, and the required input data and the output provided by the program are explained. The relationship of the adaptive maneuvering logic program with the program to drive the differential maneuvering simulator is discussed.
Application of dynamic programming to control khuzestan water resources system
Jamshidi, M.; Heidari, M.
1977-01-01
An approximate optimization technique based on discrete dynamic programming called discrete differential dynamic programming (DDDP), is employed to obtain the near optimal operation policies of a water resources system in the Khuzestan Province of Iran. The technique makes use of an initial nominal state trajectory for each state variable, and forms corridors around the trajectories. These corridors represent a set of subdomains of the entire feasible domain. Starting with such a set of nominal state trajectories, improvements in objective function are sought within the corridors formed around them. This leads to a set of new nominal trajectories upon which more improvements may be sought. Since optimization is confined to a set of subdomains, considerable savings in memory and computer time are achieved over that of conventional dynamic programming. The Kuzestan water resources system considered in this study is located in southwest Iran, and consists of two rivers, three reservoirs, three hydropower plants, and three irrigable areas. Data and cost benefit functions for the analysis were obtained either from the historical records or from similar studies. ?? 1977.
Experience with automatic, dynamic load balancing and adaptive finite element computation
Wheat, S.R.; Devine, K.D.; Maccabe, A.B.
1993-10-01
Distributed memory, Massively Parallel (MP), MIMD technology has enabled the development of applications requiring computational resources previously unobtainable. Structural mechanics and fluid dynamics applications, for example, are often solved by finite element methods (FEMs) requiring, millions of degrees of freedom to accurately simulate physical phenomenon. Adaptive methods, which automatically refine or coarsen meshes and vary the order of accuracy of the numerical solution, offer greater robustness and computational efficiency than traditional FEMs by reducing the amount of computation required away from physical structures such as shock waves and boundary layers. On MP computers, FEMs frequently result in distributed processor load imbalances. To overcome load imbalance, many MP FEMs use static load balancing as a preprocessor to the finite element calculation. Adaptive methods complicate the load imbalance problem since the work per element is not uniform across the solution domain and changes as the computation proceeds. Therefore, dynamic load balancing is required to maintain global load balance. We describe a dynamic, fine-grained, element-based data migration system that maintains global load balance and is effective in the presence of changing work loads. Global load balance is achieved by overlapping neighborhoods of processors, where each neighborhood performs local load balancing. The method utilizes an automatic element management system library to which a programmer integrates the application`s computational description. The library`s flexibility supports a large class of finite element and finite difference based applications.
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. PMID:21956028
Mulkidjanian, Armen Y.; Shaitan, Konstantin V.; Engelhard, Martin; Klare, Johann P.; Steinhoff, Heinz-Jürgen
2015-01-01
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. PMID:26496122
Zhang, Yu; Prakash, Edmond C; Sung, Eric
2004-01-01
This paper presents a new physically-based 3D facial model based on anatomical knowledge which provides high fidelity for facial expression animation while optimizing the computation. Our facial model has a multilayer biomechanical structure, incorporating a physically-based approximation to facial skin tissue, a set of anatomically-motivated facial muscle actuators, and underlying skull structure. In contrast to existing mass-spring-damper (MSD) facial models, our dynamic skin model uses the nonlinear springs to directly simulate the nonlinear visco-elastic behavior of soft tissue and a new kind of edge repulsion spring is developed to prevent collapse of the skin model. Different types of muscle models have been developed to simulate distribution of the muscle force applied on the skin due to muscle contraction. The presence of the skull advantageously constrain the skin movements, resulting in more accurate facial deformation and also guides the interactive placement of facial muscles. The governing dynamics are computed using a local semi-implicit ODE solver. In the dynamic simulation, an adaptive refinement automatically adapts the local resolution at which potential inaccuracies are detected depending on local deformation. The method, in effect, ensures the required speedup by concentrating computational time only where needed while ensuring realistic behavior within a predefined error threshold. This mechanism allows more pleasing animation results to be produced at a reduced computational cost.
An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks
Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Zhang, Xuekun
2015-01-01
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. PMID:26633421
NASA Astrophysics Data System (ADS)
Gao, Shigen; Dong, Hairong; Lyu, Shihang; Ning, Bin
2016-07-01
This paper studies decentralised neural adaptive control of a class of interconnected nonlinear systems, each subsystem is in the presence of input saturation and external disturbance and has independent system order. Using a novel truncated adaptation design, dynamic surface control technique and minimal-learning-parameters algorithm, the proposed method circumvents the problems of 'explosion of complexity' and 'dimension curse' that exist in the traditional backstepping design. Comparing to the methodology that neural weights are online updated in the controllers, only one scalar needs to be updated in the controllers of each subsystem when dealing with unknown systematic dynamics. Radial basis function neural networks (NNs) are used in the online approximation of unknown systematic dynamics. It is proved using Lyapunov stability theory that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded. The tracking errors of each subsystems, the amplitude of NN approximation residuals and external disturbances can be attenuated to arbitrarily small by tuning proper design parameters. Simulation results are given to demonstrate the effectiveness of the proposed method.
An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks.
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.
An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks.
Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Zhang, Xuekun
2015-01-01
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. PMID:26633421
Turing pattern dynamics and adaptive discretization for a super-diffusive Lotka-Volterra model.
Bendahmane, Mostafa; Ruiz-Baier, Ricardo; Tian, Canrong
2016-05-01
In this paper we analyze the effects of introducing the fractional-in-space operator into a Lotka-Volterra competitive model describing population super-diffusion. First, we study how cross super-diffusion influences the formation of spatial patterns: a linear stability analysis is carried out, showing that cross super-diffusion triggers Turing instabilities, whereas classical (self) super-diffusion does not. In addition we perform a weakly nonlinear analysis yielding a system of amplitude equations, whose study shows the stability of Turing steady states. A second goal of this contribution is to propose a fully adaptive multiresolution finite volume method that employs shifted Grünwald gradient approximations, and which is tailored for a larger class of systems involving fractional diffusion operators. The scheme is aimed at efficient dynamic mesh adaptation and substantial savings in computational burden. A numerical simulation of the model was performed near the instability boundaries, confirming the behavior predicted by our analysis.
Turing pattern dynamics and adaptive discretization for a super-diffusive Lotka-Volterra model.
Bendahmane, Mostafa; Ruiz-Baier, Ricardo; Tian, Canrong
2016-05-01
In this paper we analyze the effects of introducing the fractional-in-space operator into a Lotka-Volterra competitive model describing population super-diffusion. First, we study how cross super-diffusion influences the formation of spatial patterns: a linear stability analysis is carried out, showing that cross super-diffusion triggers Turing instabilities, whereas classical (self) super-diffusion does not. In addition we perform a weakly nonlinear analysis yielding a system of amplitude equations, whose study shows the stability of Turing steady states. A second goal of this contribution is to propose a fully adaptive multiresolution finite volume method that employs shifted Grünwald gradient approximations, and which is tailored for a larger class of systems involving fractional diffusion operators. The scheme is aimed at efficient dynamic mesh adaptation and substantial savings in computational burden. A numerical simulation of the model was performed near the instability boundaries, confirming the behavior predicted by our analysis. PMID:26219250
NASA Technical Reports Server (NTRS)
Feng, Hui-Yu; VanderWijngaart, Rob; Biswas, Rupak; Biegel, Bryan (Technical Monitor)
2001-01-01
We describe the design of a new method for the measurement of the performance of modern computer systems when solving scientific problems featuring irregular, dynamic memory accesses. The method involves the solution of a stylized heat transfer problem on an unstructured, adaptive grid. A Spectral Element Method (SEM) with an adaptive, nonconforming mesh is selected to discretize the transport equation. The relatively high order of the SEM lowers the fraction of wall clock time spent on inter-processor communication, which eases the load balancing task and allows us to concentrate on the memory accesses. The benchmark is designed to be three-dimensional. Parallelization and load balance issues of a reference implementation will be described in detail in future reports.
Xu, Haojie; Lu, Yunfeng; Zhu, Shanan
2014-01-01
It is of significance to assess the dynamic spectral causality among physiological signals. Several practical estimators adapted from spectral Granger causality have been exploited to track dynamic causality based on the framework of time-varying multivariate autoregressive (tvMVAR) models. The non-zero covariance of the model’s residuals has been used to describe the instantaneous effect phenomenon in some causality estimators. However, for the situations with Gaussian residuals in some autoregressive models, it is challenging to distinguish the directed instantaneous causality if the sufficient prior information about the “causal ordering” is missing. Here, we propose a new algorithm to assess the time-varying causal ordering of tvMVAR model under the assumption that the signals follow the same acyclic causal ordering for all time lags and to estimate the instantaneous effect factor (IEF) value in order to track the dynamic directed instantaneous connectivity. The time-lagged adaptive directed transfer function (ADTF) is also estimated to assess the lagged causality after removing the instantaneous effect. In the present study, we firstly investigated the performance of the causal-ordering estimation algorithm and the accuracy of IEF value. Then, we presented the results of IEF and time-lagged ADTF method by comparing with the conventional ADTF method through simulations of various propagation models. Statistical analysis results suggest that the new algorithm could accurately estimate the causal ordering and give a good estimation of the IEF values in the Gaussian residual conditions. Meanwhile, the time-lagged ADTF approach is also more accurate in estimating the time-lagged dynamic interactions in a complex nervous system after extracting the instantaneous effect. In addition to the simulation studies, we applied the proposed method to estimate the dynamic spectral causality on real visual evoked potential (VEP) data in a human subject. Its usefulness in
Adapting Animal-Assisted Therapy Trials to Prison-Based Animal Programs.
Allison, Molly; Ramaswamy, Megha
2016-09-01
Prison-based animal programs have shown promise when it comes to increased sociability, responsibility, and levels of patience for inmates who participate in these programs. Yet there remains a dearth of scientific research that demonstrates the impact of prison-based animal programs on inmates' physical and mental health. Trials of animal-assisted therapy interventions, a form of human-animal interaction therapy most often used with populations affected by depression/anxiety, mental illness, and trauma, may provide models of how prison-based animal program research can have widespread implementation in jail and prison settings, whose populations have high rates of mental health problems. This paper reviews the components of prison-based animal programs most commonly practiced in prisons today, presents five animal-assisted therapy case studies, evaluates them based on their adaptability to prison-based animal programs, and discusses the institutional constraints that act as barriers for rigorous prison-based animal program research implementation. This paper can serve to inform the development of a research approach to animal-assisted therapy that nurses and other public health researchers can use in working with correctional populations. PMID:27302852
Adapting Animal-Assisted Therapy Trials to Prison-Based Animal Programs.
Allison, Molly; Ramaswamy, Megha
2016-09-01
Prison-based animal programs have shown promise when it comes to increased sociability, responsibility, and levels of patience for inmates who participate in these programs. Yet there remains a dearth of scientific research that demonstrates the impact of prison-based animal programs on inmates' physical and mental health. Trials of animal-assisted therapy interventions, a form of human-animal interaction therapy most often used with populations affected by depression/anxiety, mental illness, and trauma, may provide models of how prison-based animal program research can have widespread implementation in jail and prison settings, whose populations have high rates of mental health problems. This paper reviews the components of prison-based animal programs most commonly practiced in prisons today, presents five animal-assisted therapy case studies, evaluates them based on their adaptability to prison-based animal programs, and discusses the institutional constraints that act as barriers for rigorous prison-based animal program research implementation. This paper can serve to inform the development of a research approach to animal-assisted therapy that nurses and other public health researchers can use in working with correctional populations.
Aperiodic dynamics in a deterministic adaptive network model of attitude formation in social groups
NASA Astrophysics Data System (ADS)
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
NASA Technical Reports Server (NTRS)
Everhart, J. L.
1983-01-01
A program called FLEXWAL for calculating wall modifications for solid, adaptive-wall wind tunnels is presented. The method used is the iterative technique of NASA TP-2081 and is applicable to subsonic and transonic test conditions. The program usage, program listing, and a sample case are given.
Adaptive uniform grayscale coded aperture design for high dynamic range compressive spectral imaging
NASA Astrophysics Data System (ADS)
Diaz, Nelson; Rueda, Hoover; Arguello, Henry
2016-05-01
Imaging spectroscopy is an important area with many applications in surveillance, agriculture and medicine. The disadvantage of conventional spectroscopy techniques is that they collect the whole datacube. In contrast, compressive spectral imaging systems capture snapshot compressive projections, which are the input of reconstruction algorithms to yield the underlying datacube. Common compressive spectral imagers use coded apertures to perform the coded projections. The coded apertures are the key elements in these imagers since they define the sensing matrix of the system. The proper design of the coded aperture entries leads to a good quality in the reconstruction. In addition, the compressive measurements are prone to saturation due to the limited dynamic range of the sensor, hence the design of coded apertures must consider saturation. The saturation errors in compressive measurements are unbounded and compressive sensing recovery algorithms only provide solutions for bounded noise or bounded with high probability. In this paper it is proposed the design of uniform adaptive grayscale coded apertures (UAGCA) to improve the dynamic range of the estimated spectral images by reducing the saturation levels. The saturation is attenuated between snapshots using an adaptive filter which updates the entries of the grayscale coded aperture based on the previous snapshots. The coded apertures are optimized in terms of transmittance and number of grayscale levels. The advantage of the proposed method is the efficient use of the dynamic range of the image sensor. Extensive simulations show improvements in the image reconstruction of the proposed method compared with grayscale coded apertures (UGCA) and adaptive block-unblock coded apertures (ABCA) in up to 10 dB.
NASA Astrophysics Data System (ADS)
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.
The Adaptively Biased Molecular Dynamics method revisited: New capabilities and an application
NASA Astrophysics Data System (ADS)
Moradi, Mahmoud; Babin, Volodymyr; Roland, Christopher; Sagui, Celeste
2015-09-01
The free energy is perhaps one of the most important quantity required for describing biomolecular systems at equilibrium. Unfortunately, accurate and reliable free energies are notoriously difficult to calculate. To address this issue, we previously developed the Adaptively Biased Molecular Dynamics (ABMD) method for accurate calculation of rugged free energy surfaces (FES). Here, we briefly review the workings of the ABMD method with an emphasis on recent software additions, along with a short summary of a selected ABMD application based on the B-to-Z DNA transition. The ABMD method, along with current extensions, is currently implemented in the AMBER (ver.10-14) software package.
An adaptive Newton-method based on a dynamical systems approach
NASA Astrophysics Data System (ADS)
Amrein, Mario; Wihler, Thomas P.
2014-09-01
The traditional Newton method for solving nonlinear operator equations in Banach spaces is discussed within the context of the continuous Newton method. This setting makes it possible to interpret the Newton method as a discrete dynamical system and thereby to cast it in the framework of an adaptive step size control procedure. In so doing, our goal is to reduce the chaotic behavior of the original method without losing its quadratic convergence property close to the roots. The performance of the modified scheme is illustrated with various examples from algebraic and differential equations.
2008-01-01
Background Natural selection and genetic drift are major forces responsible for temporal genetic changes in populations. Furthermore, these evolutionary forces may interact with each other. Here we study the impact of an ongoing adaptive process at the molecular genetic level by analyzing the temporal genetic changes throughout 40 generations of adaptation to a common laboratory environment. Specifically, genetic variability, population differentiation and demographic structure were compared in two replicated groups of Drosophila subobscura populations recently sampled from different wild sources. Results We found evidence for a decline in genetic variability through time, along with an increase in genetic differentiation between all populations studied. The observed decline in genetic variability was higher during the first 14 generations of laboratory adaptation. The two groups of replicated populations showed overall similarity in variability patterns. Our results also revealed changing demographic structure of the populations during laboratory evolution, with lower effective population sizes in the early phase of the adaptive process. One of the ten microsatellites analyzed showed a clearly distinct temporal pattern of allele frequency change, suggesting the occurrence of positive selection affecting the region around that particular locus. Conclusion Genetic drift was responsible for most of the divergence and loss of variability between and within replicates, with most changes occurring during the first generations of laboratory adaptation. We also found evidence suggesting a selective sweep, despite the low number of molecular markers analyzed. Overall, there was a similarity of evolutionary dynamics at the molecular level in our laboratory populations, despite distinct genetic backgrounds and some differences in phenotypic evolution. PMID:18302790
Fast and intuitive programming of adaptive laser cutting of lace enabled by machine vision
NASA Astrophysics Data System (ADS)
Vaamonde, Iago; Souto-López, Álvaro; García-Díaz, Antón
2015-07-01
A machine vision system has been developed, validated, and integrated in a commercial laser robot cell. It permits an offline graphical programming of laser cutting of lace. The user interface allows loading CAD designs and aligning them with images of lace pieces. Different thread widths are discriminated to generate proper cutting program templates. During online operation, the system aligns CAD models of pieces and lace images, pre-checks quality of lace cuts and adapts laser parameters to thread widths. For pieces detected with the required quality, the program template is adjusted by transforming the coordinates of every trajectory point. A low-cost lace feeding system was also developed for demonstration of full process automation.
Poirier, Josée; Bennett, Wendy L; Jerome, Gerald J; Shah, Nina G; Lazo, Mariana; Yeh, Hsin-Chieh; Clark, Jeanne M
2016-01-01
Background The benefits of physical activity are well documented, but scalable programs to promote activity are needed. Interventions that assign tailored and dynamically adjusting goals could effect significant increases in physical activity but have not yet been implemented at scale. Objective Our aim was to examine the effectiveness of an open access, Internet-based walking program that assigns daily step goals tailored to each participant. Methods A two-arm, pragmatic randomized controlled trial compared the intervention to no treatment. Participants were recruited from a workplace setting and randomized to a no-treatment control (n=133) or to treatment (n=132). Treatment participants received a free wireless activity tracker and enrolled in the walking program, Walkadoo. Assessments were fully automated: activity tracker recorded primary outcomes (steps) without intervention by the participant or investigators. The two arms were compared on change in steps per day from baseline to follow-up (after 6 weeks of treatment) using a two-tailed independent samples t test. Results Participants (N=265) were 66.0% (175/265) female with an average age of 39.9 years. Over half of the participants (142/265, 53.6%) were sedentary (<5000 steps/day) and 44.9% (119/265) were low to somewhat active (5000-9999 steps/day). The intervention group significantly increased their steps by 970 steps/day over control (P<.001), with treatment effects observed in sedentary (P=.04) and low-to-somewhat active (P=.004) participants alike. Conclusions The program is effective in increasing daily steps. Participants benefited from the program regardless of their initial activity level. A tailored, adaptive approach using wireless activity trackers is realistically implementable and scalable. Trial Registration Clinicaltrials.gov NCT02229409, https://clinicaltrials.gov/ct2/show/NCT02229409 (Archived by WebCite at http://www.webcitation.org/6eiWCvBYe) PMID:26860434
Robust adaptive control of spacecraft proximity maneuvers under dynamic coupling and uncertainty
NASA Astrophysics Data System (ADS)
Sun, Liang; Huo, Wei
2015-11-01
This paper provides a solution for the position tracking and attitude synchronization problem of the close proximity phase in spacecraft rendezvous and docking. The chaser spacecraft must be driven to a certain fixed position along the docking port direction of the target spacecraft, while the attitude of the two spacecraft must be synchronized for subsequent docking operations. The kinematics and dynamics for relative position and relative attitude are modeled considering dynamic coupling, parametric uncertainties and external disturbances. The relative motion model has a new form with a novel definition of the unknown parameters. An original robust adaptive control method is developed for the concerned problem, and a proof of the asymptotic stability is given for the six degrees of freedom closed-loop system. A numerical example is displayed in simulation to verify the theoretical results.
NASA Astrophysics Data System (ADS)
Wang, Tong; Ding, Yongsheng; Zhang, Lei; Hao, Kuangrong
2016-08-01
This paper considered the synchronisation of continuous complex dynamical networks with discrete-time communications and delayed nodes. The nodes in the dynamical networks act in the continuous manner, while the communications between nodes are discrete-time; that is, they communicate with others only at discrete time instants. The communication intervals in communication period can be uncertain and variable. By using a piecewise Lyapunov-Krasovskii function to govern the characteristics of the discrete communication instants, we investigate the adaptive feedback synchronisation and a criterion is derived to guarantee the existence of the desired controllers. The globally exponential synchronisation can be achieved by the controllers under the updating laws. Finally, two numerical examples including globally coupled network and nearest-neighbour coupled networks are presented to demonstrate the validity and effectiveness of the proposed control scheme.
Adaptive pulsed laser line extraction for terrain reconstruction using a dynamic vision sensor.
Brandli, Christian; Mantel, Thomas A; Hutter, Marco; Höpflinger, Markus A; Berner, Raphael; Siegwart, Roland; Delbruck, Tobi
2013-01-01
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 (DVS) 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 500 Hz were achieved using a line laser of 3 mW at a distance of 45 cm 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 2 mm. PMID:24478619
Adaptive coded spreading OFDM signal for dynamic-λ optical access network
NASA Astrophysics Data System (ADS)
Liu, Bo; Zhang, Lijia; Xin, Xiangjun
2015-12-01
This paper proposes and experimentally demonstrates a novel adaptive coded spreading (ACS) orthogonal frequency division multiplexing (OFDM) signal for dynamic distributed optical ring-based access network. The wavelength can be assigned to different remote nodes (RNs) according to the traffic demand of optical network unit (ONU). The ACS can provide dynamic spreading gain to different signals according to the split ratio or transmission length, which offers flexible power budget for the network. A 10×13.12 Gb/s OFDM access with ACS is successfully demonstrated over two RNs and 120 km transmission in the experiment. The demonstrated method may be viewed as one promising for future optical metro access network.
Adaptive pulsed laser line extraction for terrain reconstruction using a dynamic vision sensor.
Brandli, Christian; Mantel, Thomas A; Hutter, Marco; Höpflinger, Markus A; Berner, Raphael; Siegwart, Roland; Delbruck, Tobi
2013-01-01
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 (DVS) 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 500 Hz were achieved using a line laser of 3 mW at a distance of 45 cm 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 2 mm.
Ma, Cheng; Xu, Xiao; Liu, Yan; Wang, Lihong V.
2014-01-01
The ability to steer and focus light inside scattering media has long been sought for a multitude of applications. To form optical foci inside scattering media, the only feasible strategy at present is to guide photons by using either implanted1 or virtual2–4 guide stars, which can be inconvenient and limits potential applications. Here, we report a scheme for focusing light inside scattering media by employing intrinsic dynamics as guide stars. By time-reversing the perturbed component of the scattered light adaptively, we show that it is possible to focus light to the origin of the perturbation. Using the approach, we demonstrate non-invasive dynamic light focusing onto moving targets and imaging of a time-variant object obscured by highly scattering media. Anticipated applications include imaging and photoablation of angiogenic vessels in tumours as well as other biomedical uses. PMID:25530797
Adaptive pulsed laser line extraction for terrain reconstruction using a dynamic vision sensor
Brandli, Christian; Mantel, Thomas A.; Hutter, Marco; Höpflinger, Markus A.; Berner, Raphael; Siegwart, Roland; Delbruck, Tobi
2014-01-01
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 (DVS) 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 500 Hz were achieved using a line laser of 3 mW at a distance of 45 cm 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 2 mm. PMID:24478619
Duster, A; Garza, C; Lin, H
2016-01-01
Combined quantum mechanics/molecular mechanics (QM/MM) plays an important role in multiscale simulations of biological systems including enzymes. The adaptive-partitioning (AP) schemes surpass the conventional QM/MM methods in that they allow the on-the-fly, smooth exchange of particles between QM and MM subsystems in molecular dynamics simulations, leading to a seamless and dynamic integration of the QM and MM realms. Originally developed for simulating ion solvation in bulk solutions, the AP schemes have recently been extended to the treatment of proteins, fostering applications in the simulations of enzymes. The present contribution provides a detailed account of the AP schemes. We delineate the background of the algorithms and their parallel implementation, as well as offer practical advice and examples for their applications in the simulations of biological systems. PMID:27498644
ERIC Educational Resources Information Center
Antonakopoulou, Efi
2013-01-01
There is no evidence in the literature for direct comparison of the sociocultural adaptation brought by the participation of U.S. students in education abroad programs of different lengths. This study attempts to address this gap by comparing the sociocultural adaptation of education abroad students that results from their participation in both…
On-line upgrade of program modules using AdaPT
NASA Technical Reports Server (NTRS)
Waldrop, Raymond S.; Volz, Richard A.; Smith, Gary W.; Goldsack, Stephen J.; Holzbach-Valero, A. A.
1993-01-01
One purpose of our research is the investigation of the effectiveness and expressiveness of AdaPT, a set of language extensions to Ada 83, for distributed systems. As a part of that effort, we are now investigating the subject of replacing, e.g. upgrading, software modules while the software system remains in operation. The AdaPT language extensions provide a good basis for this investigation for several reasons: they include the concept of specific, self-contained program modules which can be manipulated; support for program configuration is included in the language; and although the discussion will be in terms of the AdaPT language, the AdaPT to Ada 83 conversion methodology being developed as another part of this project will provide a basis for the application of our findings to Ada 83 and Ada 9X systems. The purpose of this investigation is to explore the basic mechanisms of the replacement process. With this purpose in mind, we will avoid including issues whose presence would obscure these basic mechanisms by introducing additional, unrelated concerns. Thus, while replacement in the presence of real-time deadlines, heterogeneous systems, and unreliable networks is certainly a topic of interest, we will first gain an understanding of the basic processes in the absence of such concerns. The extension of the replacement process to more complex situations can be made later. A previous report established an overview of the module replacement problem, a taxonomy of the various aspects of the replacement process, and a solution to one case in the replacement taxonomy. This report provides solutions to additional cases in the replacement process taxonomy: replacement of partitions with state and replacement of nodes. The solutions presented here establish the basic principles for module replacement. Extension of these solutions to other more complicated cases in the replacement taxonomy is direct, though requiring substantial work beyond the available funding.
Dynamics of a wellness program: a conservation of resources perspective.
Kim, Sung Doo; Hollensbe, Elaine C; Schwoerer, Catherine E; Halbesleben, Jonathon R B
2015-01-01
We leverage conservation of resources theory to explain possible dynamics through which a holistic wellness program results in positive longer-term outcomes. Specifically, we hypothesize that wellness self-efficacy at the end of a wellness program will create a positive resource gain spiral, increasing psychological availability (a sense of having cognitive, physical, and emotional resources to engage oneself) 6 months later, and career satisfaction, 1 year later. To test these hypotheses, using a time-lagged with control group design, we gathered questionnaire data from 160 Episcopal priests who participated in a 10-day off-site wellness program. We developed a scale measuring self-efficacy in the 4 wellness areas the program was designed to improve: physical, spiritual, financial, and vocational. Our findings provide evidence from a field setting of a relatively untested tenet of conservation of resources theory, resource gain spirals. The wellness program that we studied served as an opportunity for participants to gain new resources in the form of wellness self-efficacy, which in turn helped participants experience positive outcomes over time. We discuss theoretical and practical implications of the findings. PMID:25151464
Tu, Jia-Ying; Hsiao, Wei-De; Chen, Chih-Ying
2014-01-01
Testing techniques of dynamically substructured systems dissects an entire engineering system into parts. Components can be tested via numerical simulation or physical experiments and run synchronously. Additional actuator systems, which interface numerical and physical parts, are required within the physical substructure. A high-quality controller, which is designed to cancel unwanted dynamics introduced by the actuators, is important in order to synchronize the numerical and physical outputs and ensure successful tests. An adaptive forward prediction (AFP) algorithm based on delay compensation concepts has been proposed to deal with substructuring control issues. Although the settling performance and numerical conditions of the AFP controller are improved using new direct-compensation and singular value decomposition methods, the experimental results show that a linear dynamics-based controller still outperforms the AFP controller. Based on experimental observations, the least-squares fitting technique, effectiveness of the AFP compensation and differences between delay and ordinary differential equations are discussed herein, in order to reflect the fundamental issues of actuator modelling in relevant literature and, more specifically, to show that the actuator and numerical substructure are heterogeneous dynamic components and should not be collectively modelled as a homogeneous delay differential equation. PMID:25104902
Lin, Hui; Gao, Jian; Mei, Qing; He, Yunbo; Liu, Junxiu; Wang, Xingjin
2016-04-01
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. PMID:27137056
Lenski, R E; Travisano, M
1994-01-01
We followed evolutionary change in 12 populations of Escherichia coli propagated for 10,000 generations in identical environments. Both morphology (cell size) and fitness (measured in competition with the ancestor) evolved rapidly for the first 2000 generations or so after the populations were introduced into the experimental environment, but both were nearly static for the last 5000 generations. Although evolving in identical environments, the replicate populations diverged significantly from one another in both morphology and mean fitness. The divergence in mean fitness was sustained and implies that the populations have approached different fitness peaks of unequal height in the adaptive landscape. Although the experimental time scale and environment were microevolutionary in scope, our experiments were designed to address questions concerning the origin as well as the fate of genetic and phenotypic novelties, the repeatability of adaptation, the diversification of lineages, and thus the causes and consequences of the uniqueness of evolutionary history. In fact, we observed several hallmarks of macroevolutionary dynamics, including periods of rapid evolution and stasis, altered functional relationships between traits, and concordance of anagenetic and cladogenetic trends. Our results support a Wrightian interpretation, in which chance events (mutation and drift) play an important role in adaptive evolution, as do the complex genetic interactions that underlie the structure of organisms. PMID:8041701
Dynamic dendritic compartmentalization underlies stimulus-specific adaptation in an insect neuron.
Prešern, Janez; Triblehorn, Jeffrey D; Schul, Johannes
2015-06-01
In many neural systems, repeated stimulation leads to stimulus-specific adaptation (SSA), with responses to repeated signals being reduced while responses to novel stimuli remain unaffected. The underlying mechanisms of SSA remain mostly hypothetical. One hypothesis is that dendritic processes generate SSA. Evidence for such a mechanism was recently described in an insect auditory interneuron (TN-1 in Neoconocephalus triops). Afferents, tuned to different frequencies, connect with different parts of the TN-1 dendrite. The specific adaptation of these inputs relies on calcium and sodium accumulation within the dendrite, with calcium having a transient and sodium a tonic effect. Using imaging techniques, we tested here whether the accumulation of these ions remained limited to the stimulated parts of the dendrite. Stimulation with a fast pulse rate, which results in strong adaptation, elicited a transient dendritic calcium signal. In contrast, the sodium signal was tonic, remaining high during the fast pulse rate stimulus. These time courses followed the predictions from the previous pharmacological experiments. The peak positions of the calcium and sodium signals differed with the carrier frequency of the stimulus; at 15 kHz, peak locations were significantly more rostral than at 40 kHz. This matched the predictions made from neuroanatomical data. Our findings confirm that excitatory postsynaptic potentials rather than spiking cause the increase of dendritic calcium and sodium concentrations and that these increases remain limited to the stimulated parts of the dendrite. This supports the hypothesis of "dynamic dendritic compartmentalization" underlying SSA in this auditory interneuron. PMID:25878158
Dynamical consequences of adaptation of the growth rates in a system of three competing populations
NASA Astrophysics Data System (ADS)
Dimitrova, Zlatinka I.; Vitanov, Nikolay K.
2001-09-01
We investigate the nonlinear dynamics of a system of populations competing for the same limited resource for the case where each of the populations adapts its growth rate to the total number of individuals in all populations. We consider regions of parameter space where chaotic motion of the Shilnikov kind exists and present results for two characteristic values of the growth ratio adaptation factor r*: r* = -0.15 and 5. Negative r* can lead to vanishing of regions of chaotic motion and to a stabilization of a fixed point of the studied model system of differential equations. Positive r* lead to changes of the shape of the bifurcation diagrams in comparison with the bifurcation diagrams for the case without adaptation. For the case r* = 5 we observe transition to chaos by period-doubling bifurcations, windows of periodic motion between the regions of chaotic motion and a region of transient chaos after the last window of periodic motion. The Lyapunov dimension for the chaotic attractors is close to two and the Lyapunov spectrum has a structure which allows a topological analysis of the attractors of the investigated system.
Exploiting the Adaptation Dynamics to Predict the Distribution of Beneficial Fitness Effects.
John, Sona; Seetharaman, Sarada
2016-01-01
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. PMID:26990188
Dynamically adaptive mesh refinement technique for image reconstruction in optical tomography.
Soloviev, Vadim Y; Krasnosselskaia, Lada V
2006-04-20
A novel adaptive mesh technique is introduced for problems of image reconstruction in luminescence optical tomography. A dynamical adaptation of the three-dimensional scheme based on the finite-volume formulation reduces computational time and balances the ill-posed nature of the inverse problem. The arbitrary shape of the bounding surface is handled by an additional refinement of computational cells on the boundary. Dynamical shrinking of the search volume is introduced to improve computational performance and accuracy while locating the luminescence target. Light propagation in the medium is modeled by the telegraph equation, and the image-reconstruction algorithm is derived from the Fredholm integral equation of the first kind. Stability and computational efficiency of the introduced method are demonstrated for image reconstruction of one and two spherical luminescent objects embedded within a breastlike tissue phantom. Experimental measurements are simulated by the solution of the forward problem on a grid of 5x5 light guides attached to the surface of the phantom.
Exploiting the Adaptation Dynamics to Predict the Distribution of Beneficial Fitness Effects
2016-01-01
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. PMID:26990188
NASA Technical Reports Server (NTRS)
Tesar, Delbert; Tosunoglu, Sabri; Lin, Shyng-Her
1990-01-01
Research results on general serial robotic manipulators modeled with structural compliances are presented. Two compliant manipulator modeling approaches, distributed and lumped parameter models, are used in this study. System dynamic equations for both compliant models are derived by using the first and second order influence coefficients. Also, the properties of compliant manipulator system dynamics are investigated. One of the properties, which is defined as inaccessibility of vibratory modes, is shown to display a distinct character associated with compliant manipulators. This property indicates the impact of robot geometry on the control of structural oscillations. Example studies are provided to illustrate the physical interpretation of inaccessibility of vibratory modes. Two types of controllers are designed for compliant manipulators modeled by either lumped or distributed parameter techniques. In order to maintain the generality of the results, neither linearization is introduced. Example simulations are given to demonstrate the controller performance. The second type controller is also built for general serial robot arms and is adaptive in nature which can estimate uncertain payload parameters on-line and simultaneously maintain trajectory tracking properties. The relation between manipulator motion tracking capability and convergence of parameter estimation properties is discussed through example case studies. The effect of control input update delays on adaptive controller performance is also studied.
The Glen Canyon Dam adaptive management program: progress and immediate challenges
Hamill, John F.; Melis, Theodore S.; Boon, Philip J.; Raven, Paul J.
2012-01-01
Adaptive management emerged as an important resource management strategy for major river systems in the United States (US) in the early 1990s. The Glen Canyon Dam Adaptive Management Program (‘the Program’) was formally established in 1997 to fulfill a statutory requirement in the 1992 Grand Canyon Protection Act (GCPA). The GCPA aimed to improve natural resource conditions in the Colorado River corridor in the Glen Canyon National Recreation Area and Grand Canyon National Park, Arizona that were affected by the Glen Canyon dam. The Program achieves this by using science and a variety of stakeholder perspectives to inform decisions about dam operations. Since the Program started the ecosystem is now much better understood and several biological and physical improvements have been achieved. These improvements include: (i) an estimated 50% increase in the adult population of endangered humpback chub (Gila cypha) between 2001 and 2008, following previous decline; (ii) a 90% decrease in non-native rainbow trout (Oncorhynchus mykiss), which are known to compete with and prey on native fish, as a result of removal experiments; and (iii) the widespread reappearance of sandbars in response to an experimental high-flow release of dam water in March 2008.Although substantial progress has been made, the Program faces several immediate challenges. These include: (i) defining specific, measurable objectives and desired future conditions for important natural, cultural and recreational attributes to inform science and management decisions; (ii) implementing structural and operational changes to improve collaboration among stakeholders; (iii) establishing a long-term experimental programme and management plan; and (iv) securing long-term funding for monitoring programmes to assess ecosystem and other responses to management actions. Addressing these challenges and building on recent progress will require strong and consistent leadership from the US Department of the Interior
The Glen Canyon Dam Adaptive Management Program: An experiment in science-based resource management
NASA Astrophysics Data System (ADS)
kaplinski, m
2001-12-01
In 1996, Glen Canyon Dam Adaptive Management (GCDAMP) program was established to provide input on Glen Canyon Dam operations and their affect on the Colorado Ecosystem in Grand Canyon. The GCDAMP is a bold experiment in federal resource management that features a governing partnership with all relevant stakeholders sitting at the same table. It is a complicated, difficult process where stakeholder-derived management actions must balance resource protection with water and power delivery compacts, the Endangered Species Act, the National Historical Preservation Act, the Grand Canyon Protection Act, National Park Service Policy, and other stakeholder concerns. The program consists of four entities: the Adaptive Management Workgroup (AMWG), the Technical Workgroup (TWG), the Grand Canyon Monitoring and Research Center (GCMRC), and independent review panels. The AMWG and TWG are federal advisory committees that consists of federal and state resource managers, Native American tribes, power, environmental and recreation interests. The AMWG is develops, evaluates and recommends alternative dam operations to the Secretary. The TWG translates AMWG policy and goals into management objectives and information needs, provides questions that serve as the basis for long-term monitoring and research activities, interprets research results from the GCMRC, and prepares reports as required for the AMWG. The GCMRC is an independent science center that is responsible for all GCDAMP monitoring and research activities. The GCMRC utilizes proposal requests with external peer review and an in-house staff that directs and synthesizes monitoring and research results. The GCMRC meets regularly with the TWG and AMWG and provides scientific information on the consequences of GCDAMP actions. Independent review panels consist of external peer review panels that provide reviews of scientific activities and the program in general, technical advice to the GCMRC, TWG and AMWG, and play a critical
Learning from adaptive neural dynamic surface control of strict-feedback systems.
Wang, Min; Wang, Cong
2015-06-01
Learning plays an essential role in autonomous control systems. However, how to achieve learning in the nonstationary environment for nonlinear systems is a challenging problem. In this paper, we present learning method for a class of n th-order strict-feedback systems by adaptive dynamic surface control (DSC) technology, which achieves the human-like ability of learning by doing and doing with learned knowledge. To achieve the learning, this paper first proposes stable adaptive DSC with auxiliary first-order filters, which ensures the boundedness of all the signals in the closed-loop system and the convergence of tracking errors in a finite time. With the help of DSC, the derivative of the filter output variable is used as the neural network (NN) input instead of traditional intermediate variables. As a result, the proposed adaptive DSC method reduces greatly the dimension of NN inputs, especially for high-order systems. After the stable DSC design, we decompose the stable closed-loop system into a series of linear time-varying perturbed subsystems. Using a recursive design, the recurrent property of NN input variables is easily verified since the complexity is overcome using DSC. Subsequently, the partial persistent excitation condition of the radial basis function NN is satisfied. By combining a state transformation, accurate approximations of the closed-loop system dynamics are recursively achieved in a local region along recurrent orbits. Then, the learning control method using the learned knowledge is proposed to achieve the closed-loop stability and the improved control performance. Simulation studies are performed to demonstrate the proposed scheme can not only reuse the learned knowledge to achieve the better control performance with the faster tracking convergence rate and the smaller tracking error but also greatly alleviate the computational burden because of reducing the number and complexity of NN input variables.
Musical structure analysis using similarity matrix and dynamic programming
NASA Astrophysics Data System (ADS)
Shiu, Yu; Jeong, Hong; Kuo, C.-C. Jay
2005-10-01
Automatic music segmentation and structure analysis from audio waveforms based on a three-level hierarchy is examined in this research, where the three-level hierarchy includes notes, measures and parts. The pitch class profile (PCP) feature is first extracted at the note level. Then, a similarity matrix is constructed at the measure level, where a dynamic time warping (DTW) technique is used to enhance the similarity computation by taking the temporal distortion of similar audio segments into account. By processing the similarity matrix, we can obtain a coarse-grain music segmentation result. Finally, dynamic programming is applied to the coarse-grain segments so that a song can be decomposed into several major parts such as intro, verse, chorus, bridge and outro. The performance of the proposed music structure analysis system is demonstrated for pop and rock music.
Censored-Data Correlation and Principal Component Dynamic Programming
NASA Astrophysics Data System (ADS)
Saad, Maarouf; Turgeon, Andre; Stedinger, Jery R.
1992-08-01
A principal component stochastic dynamic programming algorithm for stochastic multireservoir hydropower system operation optimization was proposed by Saad and Turgeon (1988). The dimension of the state space of the system is reduced by using only the major principal components of the system's state as determined by a principal component analysis of the results of a deterministic optimization. A significant refinement of the procedure is to employ censored-data principal component analysis. The more sophisticated statistical analysis provides a better model of the full dynamic range of the reservoir system's state, explains more observed variability of the reservoir volumes, and provides more accurate estimates of the statistical description's parameters. In an example presented of a four-reservoir system, the first component of the censored-data principal component analysis, for a given month, explained all but 7% of the uncensored system's variability, whereas the standard analysis for the same month left 12% of the observed system's variability unexplained.
A biologically inspired neural network for dynamic programming.
Francelin Romero, R A; Kacpryzk, J; Gomide, F
2001-12-01
An artificial neural network with a two-layer feedback topology and generalized recurrent neurons, for solving nonlinear discrete dynamic optimization problems, is developed. A direct method to assign the weights of neural networks is presented. The method is based on Bellmann's Optimality Principle and on the interchange of information which occurs during the synaptic chemical processing among neurons. The neural network based algorithm is an advantageous approach for dynamic programming due to the inherent parallelism of the neural networks; further it reduces the severity of computational problems that can occur in methods like conventional methods. Some illustrative application examples are presented to show how this approach works out including the shortest path and fuzzy decision making problems. PMID:11852439
A biologically inspired neural network for dynamic programming.
Francelin Romero, R A; Kacpryzk, J; Gomide, F
2001-12-01
An artificial neural network with a two-layer feedback topology and generalized recurrent neurons, for solving nonlinear discrete dynamic optimization problems, is developed. A direct method to assign the weights of neural networks is presented. The method is based on Bellmann's Optimality Principle and on the interchange of information which occurs during the synaptic chemical processing among neurons. The neural network based algorithm is an advantageous approach for dynamic programming due to the inherent parallelism of the neural networks; further it reduces the severity of computational problems that can occur in methods like conventional methods. Some illustrative application examples are presented to show how this approach works out including the shortest path and fuzzy decision making problems.
Adapting a multifaceted U.S. HIV prevention education program for girls in Ghana.
Fiscian, Vivian Sarpomaa; Obeng, E Kwame; Goldstein, Karen; Shea, Judy A; Turner, Barbara J
2009-02-01
We adapted a U.S. HIV prevention program to address knowledge gaps and cultural pressures that increase the risk of infection in adolescent Ghanaian girls. The theory-based nine-module HIV prevention program combines didactics and games, an interactive computer program about sugar daddies, and tie-and-dye training to demonstrate an economic alternative to transactional sex. The abstinence-based study was conducted in a church-affiliated junior secondary school in Nsawam, Ghana. Of 61 subjects aged 10-14 in the prevention program, over two thirds were very worried about becoming HIV infected. A pre-post evaluation of the intervention showed significant gains in three domains: HIV knowledge (p = .001) and self efficacy to discuss HIV and sex with men (p < .001) and with boys (p < .001). Responses to items about social norms of HIV risk behavior were also somewhat improved (p = .09). Subjects rated most program features highly. Although short-term knowledge and self-efficacy to address HIV improved significantly, longer term research is needed to address cultural and economic factors placing young women at risk of HIV infection.
Adaptation of an Alcohol and HIV School-Based Prevention Program for Teens
Springer, Carolyn; Leu, Cheng-Shiun; Ghosh, Shivnath; Sharma, Sunil Kumar; Rapkin, Bruce
2010-01-01
Given the current status of HIV infection in youth in India, developing and implementing HIV education and prevention interventions is critical. The goal for School-based Teenage Education Program (STEP) was to demonstrate that a HIV/AIDS and alcohol abuse educational program built with specific cultural, linguistic, and community-specific characteristics could be effective. Utilizing the Train-the-Trainer model, the instructors (17–21 years) were trained to present the 10 session manualized program to primarily rural and tribal youth aged 13–16 years in 23 schools (N = 1,421) in the northern state of Himachal Pradesh in India. The intervention had a greater impact on girls; girls evidenced greater communication skills and a trend towards greater self efficacy and reduced risk taking behavior. The STEP has been successfully adapted by the community organizations that were involved in coordinating the program at the local level. Their intention to continue STEP beyond extra funding shows that utilizing the local community in designing, implementing and evaluating programs promotes ownership and sustainability. PMID:20589528
NASA Technical Reports Server (NTRS)
Carey, L. D.; Petersen, W. A.; Deierling, W.; Roeder, W. P.
2009-01-01
A new weather radar is being acquired for use in support of America s space program at Cape Canaveral Air Force Station, NASA Kennedy Space Center, and Patrick AFB on the east coast of central Florida. This new radar replaces the modified WSR-74C at Patrick AFB that has been in use since 1984. The new radar is a Radtec TDR 43-250, which has Doppler and dual polarization capability. A new fixed scan strategy was designed to best support the space program. The fixed scan strategy represents a complex compromise between many competing factors and relies on climatological heights of various temperatures that are important for improved lightning forecasting and evaluation of Lightning Launch Commit Criteria (LCC), which are the weather rules to avoid lightning strikes to in-flight rockets. The 0 C to -20 C layer is vital since most generation of electric charge occurs within it and so it is critical in evaluating Lightning LCC and in forecasting lightning. These are two of the most important duties of 45 WS. While the fixed scan strategy that covers most of the climatological variation of the 0 C to -20 C levels with high resolution ensures that these critical temperatures are well covered most of the time, it also means that on any particular day the radar is spending precious time scanning at angles covering less important heights. The goal of this project is to develop a user-friendly, Interactive Data Language (IDL) computer program that will automatically generate optimized radar scan strategies that adapt to user input of the temperature profile and other important parameters. By using only the required scan angles output by the temperature profile adaptive scan strategy program, faster update times for volume scans and/or collection of more samples per gate for better data quality is possible, while maintaining high resolution at the critical temperature levels. The temperature profile adaptive technique will also take into account earth curvature and refraction
Segal, Ava D; Orendurff, Michael S; Czerniecki, Joseph M; Shofer, Jane B; Klute, Glenn K
2010-10-19
Lower limb amputees have decreased balance during daily ambulation compared to nonamputees. An optimally compliant torsion adapter, which enables transverse plane rotation at the socket-pylon junction may reduce limb asymmetries and improve comfort leading to increased confidence and stability during gait. The purpose of this study was to determine if the presence of a torsion adapter affects amputee sensitivity to local perturbations (local dynamic stability) during straight-line walking and during a turning task. Ten unilateral transtibial amputees were fit with a torsion and rigid adapter in random order and blinded to the condition. After a 3-week acclimation period, kinematic data were collected while subjects walked in a straight-line on a treadmill and around a 1-m radius circular path at constant speed. Maximum finite-time Lyapunov exponents (λ), an estimator of local dynamic stability, were calculated for the amputee's sagittal plane hip, knee and ankle angles for each condition. The prosthetic limb λ was greater during a turn compared to straight-line walking, suggesting amputees are less stable while turning. There were no statistically significant differences found in λ between adapters during both walking conditions, suggesting the torsion adapter had no effect on amputee stability; however, high inter-subject variability due to the examined population and turning task may have masked a small decrease in prosthetic limb hip and knee stability for the torsion adapter during straight-line gait. Therefore, the torsion adapter's added degree of freedom may have a small adverse effect on prosthetic limb stability during straight-line walking and no effect on turning.
NASA Astrophysics Data System (ADS)
Kartiwa, Iwa; Jung, Sang-Min; Hong, Moon-Ki; Han, Sang-Kook
2014-03-01
In this paper, we propose a novel fast adaptive approach that was applied to an OFDM-PON 20-km single fiber loopback transmission system to improve channel performance in term of stabilized BER below 2 × 10-3 and higher throughput beyond 10 Gb/s. The upstream transmission is performed through light source-seeded modulation using 1-GHz RSOA at the ONU. Experimental results indicated that the dynamic rate adaptation algorithm based on greedy Levin-Campello could be an effective solution to mitigate channel instability and data rate degradation caused by the Rayleigh back scattering effect and inefficient resource subcarrier allocation.
Dynamic Program Phase Detection in Distributed Shared-Memory Multiprocessors
Ipek, E; Martinez, J F; de Supinski, B R; McKee, S A; Schulz, M
2006-03-06
We present a novel hardware mechanism for dynamic program phase detection in distributed shared-memory (DSM) multiprocessors. We show that successful hardware mechanisms for phase detection in uniprocessors do not necessarily work well in DSM systems, since they lack the ability to incorporate the parallel application's global execution information and memory access behavior based on data distribution. We then propose a hardware extension to a well-known uniprocessor mechanism that significantly improves phase detection in the context of DSM multiprocessors. The resulting mechanism is modest in size and complexity, and is transparent to the parallel application.
Dynamic programming and graph algorithms in computer vision.
Felzenszwalb, Pedro F; Zabih, Ramin
2011-04-01
Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting since, by carefully exploiting problem structure, they often provide nontrivial guarantees concerning solution quality. In this paper, we review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo, the mid-level problem of interactive object segmentation, and the high-level problem of model-based recognition.
Parallel solution of sparse one-dimensional dynamic programming problems
NASA Technical Reports Server (NTRS)
Nicol, David M.
1989-01-01
Parallel computation offers the potential for quickly solving large computational problems. However, it is often a non-trivial task to effectively use parallel computers. Solution methods must sometimes be reformulated to exploit parallelism; the reformulations are often more complex than their slower serial counterparts. We illustrate these points by studying the parallelization of sparse one-dimensional dynamic programming problems, those which do not obviously admit substantial parallelization. We propose a new method for parallelizing such problems, develop analytic models which help us to identify problems which parallelize well, and compare the performance of our algorithm with existing algorithms on a multiprocessor.
Aligning transcript of historical documents using dynamic programming
NASA Astrophysics Data System (ADS)
Rabaev, Irina; Cohen, Rafi; El-Sana, Jihad; Kedem, Klara
2015-01-01
We present a simple and accurate approach for aligning historical documents with their corresponding transcription. First, a representative of each letter in the historical document is cropped. Then, the transcription is transformed to synthetic word images by representing the letters in the transcription by the cropped letters. These synthetic word images are aligned to groups of connected components in the original text, along each line, using dynamic programming. For measuring image similarities we experimented with a variety of feature extraction and matching methods. The presented alignment algorithm was tested on two historical datasets and provided excellent results.
GEODYN: A geological formation/drillstring dynamics computer program
Baird, J.A.; Caskey, B.C.; Stone, C.M.; Tinianow, M.A.
1984-09-01
This paper describes the initial development phase of a finite element computer program, GEODYN, capable of simulating the three-dimensional transient dynamic response of a polycrystalline diamond compact (PDC) bit interacting with a non-uniform formation. The ability of GEODYN to simulate response variations attributable to hole size, hole bottom surface shapes, and formation material non-uniformities is demonstrated. Planned developmental phases will address the detailed response of a bottom-hole assembly (BHA), a drill ahead (rock penetration and removal) simulation, and ultimately, the response of the entire string.
GEOGYN - a geological formation/drill string dynamics computer program
Caskey, B.
1984-09-16
This paper describes the initial development phase of a finite element computer program, GEODYN, capable of simulating the three-dimensional transient, dynamic response of a polycrystalline diamond compact (PDC) bit interacting with a non-uniform formation. The ability of GEODYN to simulate response variations attributable to hole size, hole bottom surface shapes, and formation material non-uniformities is demonstrated. Planned developmental phases will address the detailed response of a bottom-hole assembly (BHA), a drill ahead (rock penetration and removal) simulation, and ultimately, the response of the entire string.
Dynamics of the public concern and risk communication program implementation.
Zaryabova, Victoria; Israel, Michel
2015-09-01
The public concern about electromagnetic field (EMF) exposure varies due to different reasons. A part of them are connected with the better and higher quality of information that people receive from science, media, Internet, social networks, industry, but others are based on good communication programs performed by the responsible institutions, administration and persons. Especially, in Bulgaria, public concern follows interesting changes, some of them in correlation with the European processes of concern, but others following the economic and political processes in the country. Here, we analyze the dynamics of the public concern over the last 10 years. Our explanation of the decrease of the people's complaints against EMF exposure from base stations for mobile communication is as a result of our risk communication program that is in implementation for >10 years.
The Role of Clonal Interference in the Evolutionary Dynamics of Plasmid-Host Adaptation
Hughes, Julie M.; Lohman, Brian K.; Deckert, Gail E.; Nichols, Eric P.; Settles, Matt; Abdo, Zaid; Top, Eva M.
2012-01-01
ABSTRACT Promiscuous plasmids replicate in a wide range of bacteria and therefore play a key role in the dissemination of various host-beneficial traits, including antibiotic resistance. Despite the medical relevance, little is known about the evolutionary dynamics through which drug resistance plasmids adapt to new hosts and thereby persist in the absence of antibiotics. We previously showed that the incompatibility group P-1 (IncP-1) minireplicon pMS0506 drastically improved its stability in novel host Shewanella oneidensis MR-1 after 1,000 generations under antibiotic selection for the plasmid. The only mutations found were those affecting the N terminus of the plasmid replication initiation protein TrfA1. Our aim in this study was to gain insight into the dynamics of plasmid evolution. Changes in stability and genotype frequencies of pMS0506 were monitored in evolving populations of MR-1 (pMS0506). Genotypes were determined by sequencing trfA1 amplicons from individual clones and by 454 pyrosequencing of whole plasmids from entire populations. Stability of pMS0506 drastically improved by generation 200. Many evolved plasmid genotypes with point mutations as well as in-frame and frameshift deletions and duplications in trfA1 were observed in all lineages with both sequencing methods. Strikingly, multiple genotypes were simultaneously present at high frequencies (>10%) in each population. Their relative abundances changed over time, but after 1,000 generations only one or two genotypes dominated the populations. This suggests that hosts with different plasmid genotypes were competing with each other, thus affecting the evolutionary trajectory. Plasmids can thus rapidly improve their stability, and clonal interference plays a significant role in plasmid-host adaptation dynamics. PMID:22761390
Computational Fluid Dynamics Program at NASA Ames Research Center
NASA Technical Reports Server (NTRS)
Holst, Terry L.
1989-01-01
The Computational Fluid Dynamics (CFD) Program at NASA Ames Research Center is reviewed and discussed. The technical elements of the CFD Program are listed and briefly discussed. These elements include algorithm research, research and pilot code development, scientific visualization, advanced surface representation, volume grid generation, and numerical optimization. Next, the discipline of CFD is briefly discussed and related to other areas of research at NASA Ames including experimental fluid dynamics, computer science research, computational chemistry, and numerical aerodynamic simulation. These areas combine with CFD to form a larger area of research, which might collectively be called computational technology. The ultimate goal of computational technology research at NASA Ames is to increase the physical understanding of the world in which we live, solve problems of national importance, and increase the technical capabilities of the aerospace community. Next, the major programs at NASA Ames that either use CFD technology or perform research in CFD are listed and discussed. Briefly, this list includes turbulent/transition physics and modeling, high-speed real gas flows, interdisciplinary research, turbomachinery demonstration computations, complete aircraft aerodynamics, rotorcraft applications, powered lift flows, high alpha flows, multiple body aerodynamics, and incompressible flow applications. Some of the individual problems actively being worked in each of these areas is listed to help define the breadth or extent of CFD involvement in each of these major programs. State-of-the-art examples of various CFD applications are presented to highlight most of these areas. The main emphasis of this portion of the presentation is on examples which will not otherwise be treated at this conference by the individual presentations. Finally, a list of principal current limitations and expected future directions is given.
André, G; Engel, B; Berentsen, P B M; Vellinga, Th V; Lansink, A G J M Oude
2011-09-01
Automation and use of robots are increasingly being used within dairy farming and result in large amounts of real time data. This information provides a base for the new management concept of precision livestock farming. From 2003 to 2006, time series of herd mean daily milk yield were collected on 6 experimental research farms in the Netherlands. These time series were analyzed with an adaptive dynamic model following a Bayesian method to quantify the effect of heat stress. The effect of heat stress was quantified in terms of critical temperature above which heat stress occurred, duration of heat stress periods, and resulting loss in milk yield. In addition, dynamic changes in level and trend were monitored, including the estimation of a weekly pattern. Monitoring comprised detection of potential outliers and other deteriorations. The adaptive dynamic model fitted the data well; the root mean squared error of the forecasts ranged from 0.55 to 0.99 kg of milk/d. The percentages of potential outliers and signals for deteriorations ranged from 5.5 to 9.7%. The Bayesian procedure for time series analysis and monitoring provided a useful tool for process control. Online estimates (based on past and present only) and retrospective estimates (determined afterward from all data) of level and trend in daily milk yield showed an almost yearly cycle that was in agreement with the calving pattern: most cows calved in winter and early spring versus summer and autumn. Estimated weekly patterns in terms of weekday effects could be related to specific management actions, such as change of pasture during grazing. For the effect of heat stress, the mean estimated critical temperature above which heat stress was expected was 17.8±0.56°C. The estimated duration of the heat stress periods was 5.5±1.03 d, and the estimated loss was 31.4±12.2 kg of milk/cow per year. Farm-specific estimates are helpful to identify management factors like grazing, housing and feeding, that affect the
2011-01-01
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 by cerebral palsy may be
The adaptive dynamics of Lotka-Volterra systems with trade-offs.
Bowers, Roger G; White, Andrew
2002-02-01
We analyse the adaptive dynamics of a generalised type of Lotka-Volterra model subject to an explicit trade-off between two parameters. A simple expression for the fitness of a mutant strategy in an environment determined by the established, resident strategy is obtained leading to general results for the position of the evolutionary singular strategy and the associated second-order partial derivatives of the mutant fitness with respect to the mutant and resident strategies. Combinations of these results can be used to determine the evolutionary behaviour of the system. The theory is motivated by an example of prey evolution in a predator-prey system in which results show that only (non-EUS) evolutionary repellor dynamics, where evolution is directed away from a singular strategy, or dynamics where the singular strategy is an evolutionary attractor, are possible. Moreover, the general theory can be used to show that these results are the only possibility for all Lotka-Volterra systems in which aside from the trade-offs all parameters are independent and in which the interaction terms are of quadratic order or less. The applicability of the theory is highlighted by examining the evolution of an intermediate predator in a tri-trophic model.
Robust dynamic sliding-mode control using adaptive RENN for magnetic levitation system.
Lin, Faa-Jeng; Chen, Syuan-Yi; Shyu, Kuo-Kai
2009-06-01
In this paper, a robust dynamic sliding mode control system (RDSMC) using a recurrent Elman neural network (RENN) is proposed to control the position of a levitated object of a magnetic levitation system considering the uncertainties. First, a dynamic model of the magnetic levitation system is derived. Then, a proportional-integral-derivative (PID)-type sliding-mode control system (SMC) is adopted for tracking of the reference trajectories. Moreover, a new PID-type dynamic sliding-mode control system (DSMC) is proposed to reduce the chattering phenomenon. However, due to the hardware being limited and the uncertainty bound being unknown of the switching function for the DSMC, an RDSMC is proposed to improve the control performance and further increase the robustness of the magnetic levitation system. In the RDSMC, an RENN estimator is used to estimate an unknown nonlinear function of lumped uncertainty online and replace the switching function in the hitting control of the DSMC directly. The adaptive learning algorithms that trained the parameters of the RENN online are derived using Lyapunov stability theorem. Furthermore, a robust compensator is proposed to confront the uncertainties including approximation error, optimal parameter vectors, and higher order terms in Taylor series. Finally, some experimental results of tracking the various periodic trajectories demonstrate the validity of the proposed RDSMC for practical applications. PMID:19423437
Data-based virtual unmodeled dynamics driven multivariable nonlinear adaptive switching control.
Chai, Tianyou; Zhang, Yajun; Wang, Hong; Su, Chun-Yi; Sun, Jing
2011-12-01
For a complex industrial system, its multivariable and nonlinear nature generally make it very difficult, if not impossible, to obtain an accurate model, especially when the model structure is unknown. The control of this class of complex systems is difficult to handle by the traditional controller designs around their operating points. This paper, however, explores the concepts of controller-driven model and virtual unmodeled dynamics to propose a new design framework. The design consists of two controllers with distinct functions. First, using input and output data, a self-tuning controller is constructed based on a linear controller-driven model. Then the output signals of the controller-driven model are compared with the true outputs of the system to produce so-called virtual unmodeled dynamics. Based on the compensator of the virtual unmodeled dynamics, the second controller based on a nonlinear controller-driven model is proposed. Those two controllers are integrated by an adaptive switching control algorithm to take advantage of their complementary features: one offers stabilization function and another provides improved performance. The conditions on the stability and convergence of the closed-loop system are analyzed. Both simulation and experimental tests on a heavily coupled nonlinear twin-tank system are carried out to confirm the effectiveness of the proposed method.
Steiner, Christopher F; Stockwell, Richard D; Tadros, Monica; Shaman, Laith; Patel, Komal; Khraizat, Laila
2016-03-16
Prior ecological research has shown that spatial processes can enhance the temporal stability of populations in fluctuating environments. Less explored is the effect of dispersal on rapid adaptation and its concomitant impact on population dynamics. For asexually reproducing populations, theory predicts that dispersal in fluctuating environments can facilitate asynchrony among clones and enhance stability by reducing temporal variability of total population abundance. This effect is predicted when clones exhibit heritable variation in environmental optima and when fluctuations occur asynchronously among patches. We tested this in the field using artificial ponds and metapopulations composed of a diverse assemblage of Daphnia pulex clones. We directly manipulated dispersal presence/absence and environmental fluctuations in the form of nutrient pulses. Consistent with predictions, dispersal enhanced temporal asynchrony among clones in the presence of nutrient pulses; this in turn stabilized population dynamics. This effect only emerged when patches experienced spatially asynchronous nutrient pulses (dispersal had no effect when patches were synchronously pulsed). Clonal asynchrony was driven by strong positive selection for a single clone that exhibited a performance advantage under conditions of low resource availability. Our work highlights the importance of dispersal as a driver of eco-evolutionary dynamics and population stability in variable environments.
Inference for optimal dynamic treatment regimes using an adaptive m-out-of-n bootstrap scheme.
Chakraborty, Bibhas; Laber, Eric B; Zhao, Yingqi
2013-09-01
A dynamic treatment regime consists of a set of decision rules that dictate how to individualize treatment to patients based on available treatment and covariate history. A common method for estimating an optimal dynamic treatment regime from data is Q-learning which involves nonsmooth operations of the data. This nonsmoothness causes standard asymptotic approaches for inference like the bootstrap or Taylor series arguments to breakdown if applied without correction. Here, we consider the m-out-of-n bootstrap for constructing confidence intervals for the parameters indexing the optimal dynamic regime. We propose an adaptive choice of m and show that it produces asymptotically correct confidence sets under fixed alternatives. Furthermore, the proposed method has the advantage of being conceptually and computationally much simple than competing methods possessing this same theoretical property. We provide an extensive simulation study to compare the proposed method with currently available inference procedures. The results suggest that the proposed method delivers nominal coverage while being less conservative than alternatives. The proposed methods are implemented in the qLearn R-package and have been made available on the Comprehensive R-Archive Network (http://cran.r-project.org/). Analysis of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study is used as an illustrative example.
Evaluation of Electric Power Procurement Strategies by Stochastic Dynamic Programming
NASA Astrophysics Data System (ADS)
Saisho, Yuichi; Hayashi, Taketo; Fujii, Yasumasa; Yamaji, Kenji
In deregulated electricity markets, the role of a distribution company is to purchase electricity from the wholesale electricity market at randomly fluctuating prices and to provide it to its customers at a given fixed price. Therefore the company has to take risk stemming from the uncertainties of electricity prices and/or demand fluctuation instead of the customers. The way to avoid the risk is to make a bilateral contact with generating companies or install its own power generation facility. This entails the necessity to develop a certain method to make an optimal strategy for electric power procurement. In such a circumstance, this research has the purpose for proposing a mathematical method based on stochastic dynamic programming and additionally considering the characteristics of the start-up cost of electric power generation facility to evaluate strategies of combination of the bilateral contract and power auto-generation with its own facility for procuring electric power in deregulated electricity market. In the beginning we proposed two approaches to solve the stochastic dynamic programming, and they are a Monte Carlo simulation method and a finite difference method to derive the solution of a partial differential equation of the total procurement cost of electric power. Finally we discussed the influences of the price uncertainty on optimal strategies of power procurement.
Advantages and limitations of the spatially adaptive program SAPRO in clinical perimetry.
Fankhauser, F; Funkhouser, A; Kwasniewska, S
1986-05-01
The SAPRO program devised for the OCTOPUS 201 automated perimeter, consists of a number of program components. It is designed to be used on the Octopus 201 computer. In its measurement mode, it employs an algorithm which achieves high speed and efficiency. This is made possible by a threshold bracketing strategy which is simpler than the normal OCTOPUS bracketing. Moreover, three grids with test location distributions of increasing resolution are superimposed in succession on the whole or on part of the visual field to be analyzed. Out of the distribution of test locations, only those which fulfill a number of criteria are actually utilized. These criteria must be given and are adaptable to any given clinical problem. As a result, despite the high spatial resolution achieved, only a fraction of the test locations are utilized using SAPRO as compared with a program using a fixed pattern of test locations. The algorithm is thus able to imitate human intelligence, which tends to concentrate stimuli at places which appear to be relevant for the solution of a problem. The results of program SAPRO are disturbed by short- and long-term fluctuations. Their validity is limited, in a manner similar to that encountered in any other threshold determination procedure. A number of printout modes is available which are oriented towards an optimal understanding of the information contained in various examinations. These principles will be illustrated by one case of inactive disseminated chorioretinitis. PMID:3755124
Development of a School Adaptation Program for Elementary School Students with Hearing Impairment
Kim, Shin-Jeong; Kwon, Myung Soon
2015-01-01
Background and Objectives Although new technology of assistive listening device leads many hard of hearing children to be mainstreamed in public school programs, many clinicians and teachers still wonder whether the children are able to understand all instruction, access educational materials, and have social skills in the school. The purpose of this study is to develop a school adaptation program (SAP) for the hearing-impaired children who attend public elementary school. Subjects and Methods The theoretical framework of the SAP was a system model including microsystem, mesosystem, and macrosystem merged with Keller's ARCS theory. Results The SAP consisted of 10 sessions based on five categories (i.e., school life, activity in the class, relationship with friends, relationship with teacher, and school environments). For preliminary validity testing, the developed SAP was reviewed by sixteen elementary school teachers, using the evaluation questionnaire. The results of evaluation showed high average 3.60 (±0.52) points out of 4 while proving a reliable and valid school-based program. Conclusions The SAP indicated that it may serve as a practical and substantive program for hearing-impaired children in the public school in order to help them achieve better academic support and social integrations. PMID:26185788
ERIC Educational Resources Information Center
Kumpfer, Karol L.; Xie, Jing; O'Driscoll, Robert
2012-01-01
Background: Evidence-based programs (EBPs) targeting effective family skills are the most cost effective for improving adolescent behavioural health. Cochrane Reviews have found the "Strengthening Families Program" (SFP) to be the most effective substance abuse prevention intervention. Standardized cultural adaptation processes resulted in…
ERIC Educational Resources Information Center
Carvajal-Rodriguez, Antonio
2012-01-01
Mutate is a program developed for teaching purposes to impart a virtual laboratory class for undergraduate students of Genetics in Biology. The program emulates the so-called fluctuation test whose aim is to distinguish between spontaneous and adaptive mutation hypotheses in bacteria. The plan is to train students in certain key multidisciplinary…
ERIC Educational Resources Information Center
Iowa State Dept. of Natural Resources, Des Moines.
This document summarizes materials on aquatic education used by state programs. Emphasis is on materials developed by, or adapted for use with, programs in various states and territories. The 234 entries are categorized as activity books, brochures, newsletters, posters, videos, and other materials. Major subjects include fishing, boating and…
Digital computer program for generating dynamic turbofan engine models (DIGTEM)
NASA Technical Reports Server (NTRS)
Daniele, C. J.; Krosel, S. M.; Szuch, J. R.; Westerkamp, E. J.
1983-01-01
This report describes DIGTEM, a digital computer program that simulates two spool, two-stream turbofan engines. The turbofan engine model in DIGTEM contains steady-state performance maps for all of the components and has control volumes where continuity and energy balances are maintained. Rotor dynamics and duct momentum dynamics are also included. Altogether there are 16 state variables and state equations. DIGTEM features a backward-differnce integration scheme for integrating stiff systems. It trims the model equations to match a prescribed design point by calculating correction coefficients that balance out the dynamic equations. It uses the same coefficients at off-design points and iterates to a balanced engine condition. Transients can also be run. They are generated by defining controls as a function of time (open-loop control) in a user-written subroutine (TMRSP). DIGTEM has run on the IBM 370/3033 computer using implicit integration with time steps ranging from 1.0 msec to 1.0 sec. DIGTEM is generalized in the aerothermodynamic treatment of components.
Dynamic Analysis of a Helicopter Rotor by Dymore Program
NASA Astrophysics Data System (ADS)
Doğan, Vedat; Kırca, Mesut
The dynamic behavior of hingeless and bearingless blades of a light commercial helicopter which has been under design process at ITU (İstanbul Technical University, Rotorcraft Research and Development Centre) is investigated. Since the helicopter rotor consists of several parts connected to each other by joints and hinges; rotors in general can be considered as an assembly of the rigid and elastic parts. Dynamics of rotor system in rotation is complicated due to coupling of elastic forces (bending, torsion and tension), inertial forces, control and aerodynamic forces on the rotor blades. In this study, the dynamic behavior of the rotor for a real helicopter design project is analyzed by using DYMORE. Blades are modeled as elastic beams, hub as a rigid body, torque tubes as rigid bodies, control links as rigid bodies plus springs and several joints. Geometric and material cross-sectional properties of blades (Stiffness-Matrix and Mass-Matrix) are calculated by using VABS programs on a CATIA model. Natural frequencies and natural modes of the rotating (and non-rotating) blades are obtained by using DYMORE. Fan-Plots which show the variation of the natural frequencies for different modes (Lead-Lag, Flapping, Feathering, etc.) vs. rotor RPM are presented.
Dynamic recurrent neural networks for stable adaptive control of wing rock motion
NASA Astrophysics Data System (ADS)
Kooi, Steven Boon-Lam
Wing rock is a self-sustaining limit cycle oscillation (LCO) which occurs as the result of nonlinear coupling between the dynamic response of the aircraft and the unsteady aerodynamic forces. In this thesis, dynamic recurrent RBF (Radial Basis Function) network control methodology is proposed to control the wing rock motion. The concept based on the properties of the Presiach hysteresis model is used in the design of dynamic neural networks. The structure and memory mechanism in the Preisach model is analogous to the parallel connectivity and memory formation in the RBF neural networks. The proposed dynamic recurrent neural network has a feature for adding or pruning the neurons in the hidden layer according to the growth criteria based on the properties of ensemble average memory formation of the Preisach model. The recurrent feature of the RBF network deals with the dynamic nonlinearities and endowed temporal memories of the hysteresis model. The control of wing rock is a tracking problem, the trajectory starts from non-zero initial conditions and it tends to zero as time goes to infinity. In the proposed neural control structure, the recurrent dynamic RBF network performs identification process in order to approximate the unknown non-linearities of the physical system based on the input-output data obtained from the wing rock phenomenon. The design of the RBF networks together with the network controllers are carried out in discrete time domain. The recurrent RBF networks employ two separate adaptation schemes where the RBF's centre and width are adjusted by the Extended Kalman Filter in order to give a minimum networks size, while the outer networks layer weights are updated using the algorithm derived from Lyapunov stability analysis for the stable closed loop control. The issue of the robustness of the recurrent RBF networks is also addressed. The effectiveness of the proposed dynamic recurrent neural control methodology is demonstrated through simulations to
NASA Astrophysics Data System (ADS)
Patriarca, M.; Kuronen, A.; Robles, M.; Kaski, K.
2007-01-01
The study of crystal defects and the complex processes underlying their formation and time evolution has motivated the development of the program ALINE for interactive molecular dynamics experiments. This program couples a molecular dynamics code to a Graphical User Interface and runs on a UNIX-X11 Window System platform with the MOTIF library, which is contained in many standard Linux releases. ALINE is written in C, thus giving the user the possibility to modify the source code, and, at the same time, provides an effective and user-friendly framework for numerical experiments, in which the main parameters can be interactively varied and the system visualized in various ways. We illustrate the main features of the program through some examples of detection and dynamical tracking of point-defects, linear defects, and planar defects, such as stacking faults in lattice-mismatched heterostructures. Program summaryTitle of program:ALINE Catalogue identifier:ADYJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYJ_v1_0 Program obtainable from: CPC Program Library, Queen University of Belfast, N. Ireland Computer for which the program is designed and others on which it has been tested: Computers:DEC ALPHA 300, Intel i386 compatible computers, G4 Apple Computers Installations:Laboratory of Computational Engineering, Helsinki University of Technology, Helsinki, Finland Operating systems under which the program has been tested:True64 UNIX, Linux-i386, Mac OS X 10.3 and 10.4 Programming language used:Standard C and MOTIF libraries Memory required to execute with typical data:6 Mbytes but may be larger depending on the system size No. of lines in distributed program, including test data, etc.:16 901 No. of bytes in distributed program, including test data, etc.:449 559 Distribution format:tar.gz Nature of physical problem:Some phenomena involving defects take place inside three-dimensional crystals at times which can be hardly predicted. For this reason they are
NASA Astrophysics Data System (ADS)
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
Vencels, Juris; Delzanno, Gian Luca; Johnson, Alec; Peng, Ivy Bo; Laure, Erwin; Markidis, Stefano
2015-06-01
A spectral method for kinetic plasma simulations based on the expansion of the velocity distribution function in a variable number of Hermite polynomials is presented. The method is based on a set of non-linear equations that is solved to determine the coefficients of the Hermite expansion satisfying the Vlasov and Poisson equations. In this paper, we first show that this technique combines the fluid and kinetic approaches into one framework. Second, we present an adaptive strategy to increase and decrease the number of Hermite functions dynamically during the simulation. The technique is applied to the Landau damping and two-stream instabilitymore » test problems. Performance results show 21% and 47% saving of total simulation time in the Landau and two-stream instability test cases, respectively.« less
Dynamic Implicit 3D Adaptive Mesh Refinement for Non-Equilibrium Radiation Diffusion
Philip, Bobby; Wang, Zhen; Berrill, Mark A; Rodriguez Rodriguez, Manuel; Pernice, Michael
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 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 multiphysics systems: implicit time integration for efficient long term time integration of stiff multiphysics 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 linear solver convergence.
Shin, Hyun-Ho; Yoon, Woong-Sup
2008-07-01
An Adaptive-Spatial Decomposition parallel algorithm was developed to increase computation efficiency for molecular dynamics simulations of nano-fluids. Injection of a liquid argon jet with a scale of 17.6 molecular diameters was investigated. A solid annular platinum injector was also solved simultaneously with the liquid injectant by adopting a solid modeling technique which incorporates phantom atoms. The viscous heat was naturally discharged through the solids so the liquid boiling problem was avoided with no separate use of temperature controlling methods. Parametric investigations of injection speed, wall temperature, and injector length were made. A sudden pressure drop at the orifice exit causes flash boiling of the liquid departing the nozzle exit with strong evaporation on the surface of the liquids, while rendering a slender jet. The elevation of the injection speed and the wall temperature causes an activation of the surface evaporation concurrent with reduction in the jet breakup length and the drop size.
Adaptively biased molecular dynamics: An umbrella sampling method with a time-dependent potential
NASA Astrophysics Data System (ADS)
Babin, Volodymyr; Karpusenka, Vadzim; Moradi, Mahmoud; Roland, Christopher; Sagui, Celeste
We discuss an adaptively biased molecular dynamics (ABMD) method for the computation of a free energy surface for a set of reaction coordinates. The ABMD method belongs to the general category of umbrella sampling methods with an evolving biasing potential. It is characterized by a small number of control parameters and an O(t) numerical cost with simulation time t. The method naturally allows for extensions based on multiple walkers and replica exchange mechanism. The workings of the method are illustrated with a number of examples, including sugar puckering, and free energy landscapes for polymethionine and polyproline peptides, and for a short β-turn peptide. ABMD has been implemented into the latest version (Case et al., AMBER 10; University of California: San Francisco, 2008) of the AMBER software package and is freely available to the simulation community.
Luo, Shaohua
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.
Luo, Shaohua
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.
A Space-Time Adaptive Method for Simulating Complex Cardiac Dynamics
NASA Astrophysics Data System (ADS)
Cherry, E. M.; Greenside, H. S.; Henriquez, C. S.
2000-03-01
A new space-time adaptive mesh refinement algorithm (AMRA) is presented and analyzed which, by automatically adding and deleting local patches of higher-resolution Cartesian meshes, can simulate quantitatively accurate models of cardiac electrical dynamics efficiently in large domains. We find in two space dimensions that the AMRA is able to achieve a factor of 5 speedup and a factor of 5 reduction in memory while achieving the same accuracy compared to a code based on a uniform space-time mesh at the highest resolution of the AMRA method. We summarize applications of the code to the Luo-Rudy 1 cardiac model in large two- and three-dimensional domains and discuss the implications of our results for understanding the initiation of arrhythmias.
Vencels, Juris; Delzanno, Gian Luca; Johnson, Alec; Peng, Ivy Bo; Laure, Erwin; Markidis, Stefano
2015-06-01
A spectral method for kinetic plasma simulations based on the expansion of the velocity distribution function in a variable number of Hermite polynomials is presented. The method is based on a set of non-linear equations that is solved to determine the coefficients of the Hermite expansion satisfying the Vlasov and Poisson equations. In this paper, we first show that this technique combines the fluid and kinetic approaches into one framework. Second, we present an adaptive strategy to increase and decrease the number of Hermite functions dynamically during the simulation. The technique is applied to the Landau damping and two-stream instability test problems. Performance results show 21% and 47% saving of total simulation time in the Landau and two-stream instability test cases, respectively.
A parallel dynamic load balancing algorithm for 3-D adaptive unstructured grids
NASA Technical Reports Server (NTRS)
Vidwans, A.; Kallinderis, Y.; Venkatakrishnan, V.
1993-01-01
Adaptive local grid refinement and coarsening results in unequal distribution of workload among the processors of a parallel system. A novel method for balancing the load in cases of dynamically changing tetrahedral grids is developed. The approach employs local exchange of cells among processors in order to redistribute the load equally. An important part of the load balancing algorithm is the method employed by a processor to determine which cells within its subdomain are to be exchanged. Two such methods are presented and compared. The strategy for load balancing is based on the Divide-and-Conquer approach which leads to an efficient parallel algorithm. This method is implemented on a distributed-memory MIMD system.
On the optimal reconstruction and control of adaptive optical systems with mirror dynamics.
Correia, Carlos; Raynaud, Henri-François; Kulcsár, Caroline; Conan, Jean-Marc
2010-02-01
In adaptive optics (AO) the deformable mirror (DM) dynamics are usually neglected because, in general, the DM can be considered infinitely fast. Such assumption may no longer apply for the upcoming Extremely Large Telescopes (ELTs) with DM that are several meters in diameter with slow and/or resonant responses. For such systems an important challenge is to design an optimal regulator minimizing the variance of the residual phase. In this contribution, the general optimal minimum-variance (MV) solution to the full dynamical reconstruction and control problem of AO systems (AOSs) is established. It can be looked upon as the parent solution from which simpler (used hitherto) suboptimal solutions can be derived as special cases. These include either partial DM-dynamics-free solutions or solutions derived from the static minimum-variance reconstruction (where both atmospheric disturbance and DM dynamics are neglected altogether). Based on a continuous stochastic model of the disturbance, a state-space approach is developed that yields a fully optimal MV solution in the form of a discrete-time linear-quadratic-Gaussian (LQG) regulator design. From this LQG standpoint, the control-oriented state-space model allows one to (1) derive the optimal state-feedback linear regulator and (2) evaluate the performance of both the optimal and the sub-optimal solutions. Performance results are given for weakly damped second-order oscillatory DMs with large-amplitude resonant responses, in conditions representative of an ELT AO system. The highly energetic optical disturbance caused on the tip/tilt (TT) modes by the wind buffeting is considered. Results show that resonant responses are correctly handled with the MV regulator developed here. The use of sub-optimal regulators results in prohibitive performance losses in terms of residual variance; in addition, the closed-loop system may become unstable for resonant frequencies in the range of interest. PMID:20126246
Dynamics of the exponential integrate-and-fire model with slow currents and adaptation.
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. PMID:24443127
Subjective evaluation of H.265/HEVC based dynamic adaptive video streaming over HTTP (HEVC-DASH)
NASA Astrophysics Data System (ADS)
Irondi, Iheanyi; Wang, Qi; Grecos, Christos
2015-02-01
The Dynamic Adaptive Streaming over HTTP (DASH) standard is becoming increasingly popular for real-time adaptive HTTP streaming of internet video in response to unstable network conditions. Integration of DASH streaming techniques with the new H.265/HEVC video coding standard is a promising area of research. The performance of HEVC-DASH systems has been previously evaluated by a few researchers using objective metrics, however subjective evaluation would provide a better measure of the user's Quality of Experience (QoE) and overall performance of the system. This paper presents a subjective evaluation of an HEVC-DASH system implemented in a hardware testbed. Previous studies in this area have focused on using the current H.264/AVC (Advanced Video Coding) or H.264/SVC (Scalable Video Coding) codecs and moreover, there has been no established standard test procedure for the subjective evaluation of DASH adaptive streaming. In this paper, we define a test plan for HEVC-DASH with a carefully justified data set employing longer video sequences that would be sufficient to demonstrate the bitrate switching operations in response to various network condition patterns. We evaluate the end user's real-time QoE online by investigating the perceived impact of delay, different packet loss rates, fluctuating bandwidth, and the perceived quality of using different DASH video stream segment sizes on a video streaming session using different video sequences. The Mean Opinion Score (MOS) results give an insight into the performance of the system and expectation of the users. The results from this study show the impact of different network impairments and different video segments on users' QoE and further analysis and study may help in optimizing system performance.
The Dynamics of Cumulative Step Size Adaptation on the Ellipsoid Model.
Beyer, Hans-Georg; Hellwig, Michael
2016-01-01
The behavior of the [Formula: see text]-Evolution Strategy (ES) with cumulative step size adaptation (CSA) on the ellipsoid model is investigated using dynamic systems analysis. At first a nonlinear system of difference equations is derived that describes the mean value evolution of the ES. This system is successively simplified to finally allow for deriving closed-form solutions of the steady state behavior in the asymptotic limit case of large search space dimensions. It is shown that the system exhibits linear convergence order. The steady state mutation strength is calculated, and it is shown that compared to standard settings in [Formula: see text] self-adaptive ESs, the CSA control rule allows for an approximately [Formula: see text]-fold larger mutation strength. This explains the superior performance of the CSA in non-noisy environments. The results are used to derive a formula for the expected running time. Conclusions regarding the choice of the cumulation parameter c and the damping constant D are drawn.
Prusakov, V M; Prusakova, A V
2014-01-01
There was investigated the character of the adaptation processes in the population residing in conditions ofprolonged exposure to environmental pollution in the territory of the industrial cities of the Irkutsk region in order to identify the possible periodicity of their manifestations in the formation of the morbidity risk for the population of different age groups. Under conditions of prolonged exposure to air pollution and other adverse unfavorable factors of industrial cities in the population of all age groups long cyclic changes of adaptation processes in the body in the form of repeated 11-15-years cycles in which a period of relative destabilization of physiological functions with lowered resistance is replaced by the period with the state of elevated nonspecific resistance were established to be observed. Undulating changes of the dynamics of the relative risks of general morbidity should be considered in the assessment of the medical and environmental situation in the territory and making the managing decisions at the base on the data of public health monitoring.
TCP throughput adaptation in WiMax networks using replicator dynamics.
Anastasopoulos, Markos P; Petraki, Dionysia K; Kannan, Rajgopal; Vasilakos, Athanasios V
2010-06-01
The high-frequency segment (10-66 GHz) of the IEEE 802.16 standard seems promising for the implementation of wireless backhaul networks carrying large volumes of Internet traffic. In contrast to wireline backbone networks, where channel errors seldom occur, the TCP protocol in IEEE 802.16 Worldwide Interoperability for Microwave Access networks is conditioned exclusively by wireless channel impairments rather than by congestion. This renders a cross-layer design approach between the transport and physical layers more appropriate during fading periods. In this paper, an adaptive coding and modulation (ACM) scheme for TCP throughput maximization is presented. In the current approach, Internet traffic is modulated and coded employing an adaptive scheme that is mathematically equivalent to the replicator dynamics model. The stability of the proposed ACM scheme is proven, and the dependence of the speed of convergence on various physical-layer parameters is investigated. It is also shown that convergence to the strategy that maximizes TCP throughput may be further accelerated by increasing the amount of information from the physical layer. PMID:20083460
Pokallus, John W; Pauli, Jonathan N
2015-09-01
Community structure and interspecific interactions are particularly vulnerable to rapidly changing climatic regimes. Recent changes in both climate and vertebrate community assemblages have created a unique opportunity to examine the impacts of two dynamic forces on population regulation. We examined the effects of warming winter conditions and the reestablishment of a previously extirpated predator, the fisher (Martes pennanti), on regulatory mechanisms in a northern-adapted mammal, the porcupine (Erethizon dorsatum), along their southern range boundary. Using a long-term (17-year) capture-recapture data set, we (1) quantified the impacts of climate change and increased fisher predation on the survival of adult porcupines at their regional southern terminus, (2) assessed recruitment (via both adult fecundity and juvenile survival) of porcupines, and (3) modeled the relative importance of predation and winter conditions on the demography and population growth rate (λ). Severe winters and abundant predators interacted synergistically to reduce adult survivorship by as much as 44%, while expanding predator populations led to near reproductive failure among porcupines. Increasing predatory pressure, disruptions in this community module, and more frequent extreme winter weather events led to predicted extirpation within 50 years, whereas in the absence of predators, the population was viable. Our results provide a mechanistic understanding behind distributional shifts resulting from climate change and may be broadly relevant for predicting future distributional shifts in other northern-adapted mammalian species.
Stepanov, Serguei; Sánchez, Marcos Plata; Hernández, Eliseo Hernández
2016-09-10
Experimental investigations of the main noise sources that limit the sensitivity of the adaptive interferometric all-fiber sensors operating in the communication wavelength region are reported. Adaptive properties (i.e., the autostabilization of an optimal operation point of the interferometer) are enabled by the dynamic population grating recorded in a segment of the erbium-doped fiber (EDF) at milliwatt-scale cw power in the 1480-1560 nm spectral range. The utilized symmetric Sagnac configuration with low light internal reflections ensures reduced sensitivity of the sensor to phase noise of the laser, while intensity noise is reduced to an insignificant level by the balanced detection scheme. It is shown that the fluorescence from the erbium ions, excited by the counterpropagating waves recording the grating, increases the noise level from the fundamental shot noise approximately by a factor of 2-3 only. It is also shown that conventional communication distributed feedback (DFB) semiconductor lasers with megahertz linewidth are not suitable for high-sensitivity applications of such sensors. Because of inevitable backreflections from the output terminal devices (photodiodes, insulators, circulator), the above-mentioned fundamental noise level is increased by 2 orders of magnitude due to high phase noise of the DFB laser. PMID:27661369
Adaptive Neural Control of Pure-Feedback Nonlinear Time-Delay Systems via Dynamic Surface Technique.
Min Wang; Xiaoping Liu; Peng Shi
2011-12-01
This paper is concerned with robust stabilization problem for a class of nonaffine pure-feedback systems with unknown time-delay functions and perturbed uncertainties. Novel continuous packaged functions are introduced in advance to remove unknown nonlinear terms deduced from perturbed uncertainties and unknown time-delay functions, which avoids the functions with control law to be approximated by radial basis function (RBF) neural networks. This technique combining implicit function and mean value theorems overcomes the difficulty in controlling the nonaffine pure-feedback systems. Dynamic surface control (DSC) is used to avoid "the explosion of complexity" in the backstepping design. Design difficulties from unknown time-delay functions are overcome using the function separation technique, the Lyapunov-Krasovskii functionals, and the desirable property of hyperbolic tangent functions. RBF neural networks are employed to approximate desired virtual controls and desired practical control. Under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced significantly, and semiglobal uniform ultimate boundedness of all of the signals in the closed-loop system is guaranteed. Simulation studies are given to demonstrate the effectiveness of the proposed design scheme.
Adaptive robust stabilisation for a class of uncertain nonlinear time-delay dynamical systems
NASA Astrophysics Data System (ADS)
Wu, Hansheng
2013-02-01
The problem of adaptive robust stabilisation is considered for a class of uncertain nonlinear dynamical systems with multiple time-varying delays. It is assumed that the upper bounds of the nonlinear delayed state perturbations are unknown and that the time-varying delays are any non-negative continuous and bounded functions which do not require that their derivatives have to be less than one. In particular, it is only required that the nonlinear uncertainties, which can also include time-varying delays, are bounded in any non-negative nonlinear functions which are not required to be known for the system designer. For such a class of uncertain nonlinear time-delay systems, a new method is presented whereby a class of continuous memoryless adaptive robust state feedback controllers with a rather simpler structure is proposed. It is also shown that the solutions of uncertain nonlinear time-delay systems can be guaranteed to be uniformly exponentially convergent towards a ball which can be as small as desired. Finally, as an application, an uncertain nonlinear time-delay ecosystem with two competing species is given to demonstrate the validity of the results.
TCP throughput adaptation in WiMax networks using replicator dynamics.
Anastasopoulos, Markos P; Petraki, Dionysia K; Kannan, Rajgopal; Vasilakos, Athanasios V
2010-06-01
The high-frequency segment (10-66 GHz) of the IEEE 802.16 standard seems promising for the implementation of wireless backhaul networks carrying large volumes of Internet traffic. In contrast to wireline backbone networks, where channel errors seldom occur, the TCP protocol in IEEE 802.16 Worldwide Interoperability for Microwave Access networks is conditioned exclusively by wireless channel impairments rather than by congestion. This renders a cross-layer design approach between the transport and physical layers more appropriate during fading periods. In this paper, an adaptive coding and modulation (ACM) scheme for TCP throughput maximization is presented. In the current approach, Internet traffic is modulated and coded employing an adaptive scheme that is mathematically equivalent to the replicator dynamics model. The stability of the proposed ACM scheme is proven, and the dependence of the speed of convergence on various physical-layer parameters is investigated. It is also shown that convergence to the strategy that maximizes TCP throughput may be further accelerated by increasing the amount of information from the physical layer.
NASA Astrophysics Data System (ADS)
Kindermans, Pieter-Jan; Tangermann, Michael; Müller, Klaus-Robert; Schrauwen, Benjamin
2014-06-01
Objective. Most BCIs have to undergo a calibration session in which data is recorded to train decoders with machine learning. Only recently zero-training methods have become a subject of study. This work proposes a probabilistic framework for BCI applications which exploit event-related potentials (ERPs). For the example of a visual P300 speller we show how the framework harvests the structure suitable to solve the decoding task by (a) transfer learning, (b) unsupervised adaptation, (c) language model and (d) dynamic stopping. Approach. A simulation study compares the proposed probabilistic zero framework (using transfer learning and task structure) to a state-of-the-art supervised model on n = 22 subjects. The individual influence of the involved components (a)-(d) are investigated. Main results. Without any need for a calibration session, the probabilistic zero-training framework with inter-subject transfer learning shows excellent performance—competitive to a state-of-the-art supervised method using calibration. Its decoding quality is carried mainly by the effect of transfer learning in combination with continuous unsupervised adaptation. Significance. A high-performing zero-training BCI is within reach for one of the most popular BCI paradigms: ERP spelling. Recording calibration data for a supervised BCI would require valuable time which is lost for spelling. The time spent on calibration would allow a novel user to spell 29 symbols with our unsupervised approach. It could be of use for various clinical and non-clinical ERP-applications of BCI.
Micro-Level Adaptation, Macro-Level Selection, and the Dynamics of Market Partitioning.
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.
Micro-Level Adaptation, Macro-Level Selection, and the Dynamics of Market Partitioning
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. PMID:26656107
Perthame, Benoît; Gauduchon, Mathias
2010-09-01
Deterministic population models for adaptive dynamics are derived mathematically from individual-centred stochastic models in the limit of large populations. However, it is common that numerical simulations of both models fit poorly and give rather different behaviours in terms of evolution speeds and branching patterns. Stochastic simulations involve extinction phenomenon operating through demographic stochasticity, when the number of individual 'units' is small. Focusing on the class of integro-differential adaptive models, we include a similar notion in the deterministic formulations, a survival threshold, which allows phenotypical traits in the population to vanish when represented by few 'individuals'. Based on numerical simulations, we show that the survival threshold changes drastically the solution; (i) the evolution speed is much slower, (ii) the branching patterns are reduced continuously and (iii) these patterns are comparable to those obtained with stochastic simulations. The rescaled models can also be analysed theoretically. One can recover the concentration phenomena on well-separated Dirac masses through the constrained Hamilton-Jacobi equation in the limit of small mutations and large observation times. PMID:19734200
Analytic approach to co-evolving dynamics in complex networks: dissatisfied adaptive snowdrift game
NASA Astrophysics Data System (ADS)
Gräser, Oliver; Xu, Chen; Hui, P. M.
2011-08-01
We investigate the formulation of mean-field (MF) approaches for co-evolving dynamic model systems, focusing on the accuracy and validity of different schemes in closing MF equations. Within the context of a recently introduced co-evolutionary snowdrift game in which rational adaptive actions are driven by dissatisfaction in the payoff, we introduce a method to test the validity of closure schemes and analyse the shortcomings of previous schemes. A previous scheme suitable for adaptive epidemic models is shown to be invalid for the model studied here. A binomial-style closure scheme that significantly improves upon the previous schemes is introduced. Fixed-point analysis of the MF equations not only explains the numerical observed transition between a connected state with suppressed cooperation and a highly cooperative disconnected state, but also reveals a previously undetected connected state that exhibits the unusual behaviour of decreasing cooperation as the temptation for uncooperative action drops. We proposed a procedure for selecting proper initial conditions to realize the unusual state in numerical simulations. The effects of the mean number of connections that an agent carries are also studied.
Pokallus, John W; Pauli, Jonathan N
2015-09-01
Community structure and interspecific interactions are particularly vulnerable to rapidly changing climatic regimes. Recent changes in both climate and vertebrate community assemblages have created a unique opportunity to examine the impacts of two dynamic forces on population regulation. We examined the effects of warming winter conditions and the reestablishment of a previously extirpated predator, the fisher (Martes pennanti), on regulatory mechanisms in a northern-adapted mammal, the porcupine (Erethizon dorsatum), along their southern range boundary. Using a long-term (17-year) capture-recapture data set, we (1) quantified the impacts of climate change and increased fisher predation on the survival of adult porcupines at their regional southern terminus, (2) assessed recruitment (via both adult fecundity and juvenile survival) of porcupines, and (3) modeled the relative importance of predation and winter conditions on the demography and population growth rate (λ). Severe winters and abundant predators interacted synergistically to reduce adult survivorship by as much as 44%, while expanding predator populations led to near reproductive failure among porcupines. Increasing predatory pressure, disruptions in this community module, and more frequent extreme winter weather events led to predicted extirpation within 50 years, whereas in the absence of predators, the population was viable. Our results provide a mechanistic understanding behind distributional shifts resulting from climate change and may be broadly relevant for predicting future distributional shifts in other northern-adapted mammalian species. PMID:26552263
Grand-Canonical-like Molecular-Dynamics Simulations by Using an Adaptive-Resolution Technique
NASA Astrophysics Data System (ADS)
Wang, Han; Hartmann, Carsten; Schütte, Christof; Delle Site, Luigi
2013-01-01
In this work, we provide a detailed theoretical analysis, supported by numerical tests, of the reliability of the adaptive-resolution-simulation (AdResS) technique in sampling the grand-canonical ensemble. We demonstrate that the correct density and radial distribution functions in the hybrid region, where molecules change resolution, are two necessary conditions for considering the atomistic and coarse-grained regions in AdResS to be equivalent to subsystems of a full atomistic system with an accuracy up to the second order with respect to the probability distribution of the system. Moreover, we show that the work done by the thermostat and a thermodynamic force in the transition region is formally equivalent to balancing the chemical potential difference between the different resolutions. From these results follows the main conclusion that the atomistic region exchanges molecules with the coarse-grained region in a grand-canonical fashion with an accuracy up to (at least) second order. Numerical tests, for the relevant case of liquid water at ambient conditions, are carried out to strengthen the conclusions of the theoretical analysis. Finally, in order to show the computational convenience of AdResS as a grand-canonical setup, we compare our method to the insertion particle method in its most efficient computational implementation. This fruitful combination of theoretical principles and numerical evidence makes the adaptive-resolution technique a candidate for a natural, general, and efficient protocol for grand-canonical molecular dynamics for the case of large systems.
Stepanov, Serguei; Sánchez, Marcos Plata; Hernández, Eliseo Hernández
2016-09-10
Experimental investigations of the main noise sources that limit the sensitivity of the adaptive interferometric all-fiber sensors operating in the communication wavelength region are reported. Adaptive properties (i.e., the autostabilization of an optimal operation point of the interferometer) are enabled by the dynamic population grating recorded in a segment of the erbium-doped fiber (EDF) at milliwatt-scale cw power in the 1480-1560 nm spectral range. The utilized symmetric Sagnac configuration with low light internal reflections ensures reduced sensitivity of the sensor to phase noise of the laser, while intensity noise is reduced to an insignificant level by the balanced detection scheme. It is shown that the fluorescence from the erbium ions, excited by the counterpropagating waves recording the grating, increases the noise level from the fundamental shot noise approximately by a factor of 2-3 only. It is also shown that conventional communication distributed feedback (DFB) semiconductor lasers with megahertz linewidth are not suitable for high-sensitivity applications of such sensors. Because of inevitable backreflections from the output terminal devices (photodiodes, insulators, circulator), the above-mentioned fundamental noise level is increased by 2 orders of magnitude due to high phase noise of the DFB laser.
A simple computational principle predicts vocal adaptation dynamics across age and error size
Kelly, Conor W.; Sober, Samuel J.
2014-01-01
The brain uses sensory feedback to correct errors in behavior. Songbirds and humans acquire vocal behaviors by imitating the sounds produced by adults and rely on auditory feedback to correct vocal errors throughout their lifetimes. In both birds and humans, acoustic variability decreases steadily with age following the acquisition of vocal behavior. Prior studies in adults have shown that while sensory errors that fall within the limits of vocal variability evoke robust motor corrections, larger errors do not induce learning. Although such results suggest that younger animals, which have greater vocal variability, might correct large errors more readily than older individuals, it is unknown whether age-dependent changes in variability are accompanied by changes in the speed or magnitude of vocal error correction. We tested the hypothesis that auditory errors evoke greater vocal changes in younger animals and that a common computation determines how sensory information drives motor learning across different ages and error sizes. Consistent with our hypothesis, we found that in songbirds the speed and extent of error correction changes dramatically with age and that age-dependent differences in learning were predicted by a model in which the overlap between sensory errors and the distribution of prior sensory feedback determines the dynamics of adaptation. Our results suggest that the brain employs a simple and robust computational principle to calibrate the rate and magnitude of vocal adaptation across age-dependent changes in behavioral performance and in response to different sensory errors. PMID:25324740
Adaptation to environmental change is not a new concept. Humans have shown throughout history a capacity for adapting to different climates and environmental changes. Farmers, foresters, civil engineers, have all been forced to adapt to numerous challenges to overcome adversity...
Federal Register 2010, 2011, 2012, 2013, 2014
2012-03-30
... Dynamic Mobility Applications and Data Capture Management Programs; Notice of Public Meeting AGENCY: ITS... Data Capture and Management (DCM) and Dynamic Mobility Applications (DMA) programs in the Washington DC... to garner stakeholder feedback. About the Dynamic Mobility Application and Data Capture...
NASA Astrophysics Data System (ADS)
Irondi, Iheanyi; Wang, Qi; Grecos, Christos
2016-04-01
Adaptive video streaming using HTTP has become popular in recent years for commercial video delivery. The recent MPEG-DASH standard allows interoperability and adaptability between servers and clients from different vendors. The delivery of the MPD (Media Presentation Description) files in DASH and the DASH client behaviours are beyond the scope of the DASH standard. However, the different adaptation algorithms employed by the clients do affect the overall performance of the system and users' QoE (Quality of Experience), hence the need for research in this field. Moreover, standard DASH delivery is based on fixed segments of the video. However, there is no standard segment duration for DASH where various fixed segment durations have been employed by different commercial solutions and researchers with their own individual merits. Most recently, the use of variable segment duration in DASH has emerged but only a few preliminary studies without practical implementation exist. In addition, such a technique requires a DASH client to be aware of segment duration variations, and this requirement and the corresponding implications on the DASH system design have not been investigated. This paper proposes a segment-duration-aware bandwidth estimation and next-segment selection adaptation strategy for DASH. Firstly, an MPD file extension scheme to support variable segment duration is proposed and implemented in a realistic hardware testbed. The scheme is tested on a DASH client, and the tests and analysis have led to an insight on the time to download next segment and the buffer behaviour when fetching and switching between segments of different playback durations. Issues like sustained buffering when switching between segments of different durations and slow response to changing network conditions are highlighted and investigated. An enhanced adaptation algorithm is then proposed to accurately estimate the bandwidth and precisely determine the time to download the next
Real Time Updating Genetic Network Programming for Adapting to the Change of Stock Prices
NASA Astrophysics Data System (ADS)
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.