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 for auto-resilient video streaming
NASA Astrophysics Data System (ADS)
Zhao, Juan; Li, Xingmei; Wang, Wei; Wu, Guoping
2007-11-01
Wireless video transmission encounters higher error rate than in wired network, which introduces distortion into the error-sensitive compressed data, reducing the quality of the playback video. Therefore, to ensure the end-to-end quality, wireless video needs a transmission system including both efficient source coding scheme and transmission technology against the influence of the channel error. This paper tackles a dynamic programming algorithm for robust video streaming over error-prone channels. An auto-resilient multiple-description coding with optimized transmission strategy has been proposed. Further study is done on the computational complexity of rate-distortion optimized video streaming and a dynamic programming algorithm is considered. Experiment results show that video streaming with adaptive dynamic programming gains better playback video quality at the receiver when transmitted through error-prone mobile channel.
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. PMID:25794375
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. 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. PMID:25751878
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
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
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
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...
Dynamical Adaptation in Photoreceptors
Clark, Damon A.; Benichou, Raphael; Meister, Markus; Azeredo da Silveira, Rava
2013-01-01
Adaptation is at the heart of sensation and nowhere is it more salient than in early visual processing. Light adaptation in photoreceptors is doubly dynamical: it depends upon the temporal structure of the input and it affects the temporal structure of the response. We introduce a non-linear dynamical adaptation model of photoreceptors. It is simple enough that it can be solved exactly and simulated with ease; analytical and numerical approaches combined provide both intuition on the behavior of dynamical adaptation and quantitative results to be compared with data. Yet the model is rich enough to capture intricate phenomenology. First, we show that it reproduces the known phenomenology of light response and short-term adaptation. Second, we present new recordings and demonstrate that the model reproduces cone response with great precision. Third, we derive a number of predictions on the response of photoreceptors to sophisticated stimuli such as periodic inputs, various forms of flickering inputs, and natural inputs. In particular, we demonstrate that photoreceptors undergo rapid adaptation of response gain and time scale, over ∼ 300 ms—i. e., over the time scale of the response itself—and we confirm this prediction with data. For natural inputs, this fast adaptation can modulate the response gain more than tenfold and is hence physiologically relevant. PMID:24244119
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. 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. PMID:25910254
Kurrasch, Deborah M; Nevin, Linda M; Wong, Jinny S; Baier, Herwig; Ingraham, Holly A
2009-01-01
role for NSF in hypothalamic development, with mutant 5 days post-fertilization larvae exhibiting a stage-dependent loss of neuroendocrine transcripts and a corresponding accumulation of neuropeptides in the soma. Based on our collective findings, we speculate that neuroendocrine transcriptional programs adapt dynamically to both the supply and demand for neuropeptides to ensure adequate homeostatic responses. PMID:19549326
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
Adaptive dynamics of saturated polymorphisms.
Kisdi, Éva; Geritz, Stefan A H
2016-03-01
We study the joint adaptive dynamics of n scalar-valued strategies in ecosystems where n is the maximum number of coexisting strategies permitted by the (generalized) competitive exclusion principle. The adaptive dynamics of such saturated systems exhibits special characteristics, which we first demonstrate in a simple example of a host-pathogen-predator model. The main part of the paper characterizes the adaptive dynamics of saturated polymorphisms in general. In order to investigate convergence stability, we give a new sufficient condition for absolute stability of an arbitrary (not necessarily saturated) polymorphic singularity and show that saturated evolutionarily stable polymorphisms satisfy it. For the case [Formula: see text], we also introduce a method to construct different pairwise invasibility plots of the monomorphic population without changing the selection gradients of the saturated dimorphism. PMID:26676357
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.
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.
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
Dynamic Adaption of Vascular Morphology
Okkels, Fridolin; Jacobsen, Jens Christian Brings
2012-01-01
The structure of vascular networks adapts continuously to meet changes in demand of the surrounding tissue. Most of the known vascular adaptation mechanisms are based on local reactions to local stimuli such as pressure and flow, which in turn reflects influence from the surrounding tissue. Here we present a simple two-dimensional model in which, as an alternative approach, the tissue is modeled as a porous medium with intervening sharply defined flow channels. Based on simple, physiologically realistic assumptions, flow-channel structure adapts so as to reach a configuration in which all parts of the tissue are supplied. A set of model parameters uniquely determine the model dynamics, and we have identified the region of the best-performing model parameters (a global optimum). This region is surrounded in parameter space by less optimal model parameter values, and this separation is characterized by steep gradients in the related fitness landscape. Hence it appears that the optimal set of parameters tends to localize close to critical transition zones. Consequently, while the optimal solution is stable for modest parameter perturbations, larger perturbations may cause a profound and permanent shift in systems characteristics. We suggest that the system is driven toward a critical state as a consequence of the ongoing parameter optimization, mimicking an evolutionary pressure on the system. PMID:23060814
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.
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.
An Adaptive Superintendent Induction Program
ERIC Educational Resources Information Center
Brandon, Jim; Donlevy, Kent; Hanna, Paulette; Gereluk, Dianne; Patterson, Peggy; Rhyason, Kath
2014-01-01
This study examined a recently established induction program for new superintendents in the Canadian province of Alberta over a three-year period. In keeping with principles of design-based research data were collected from a variety of sources from the 26 new superintendents and their 25 mentors to assess and adjust programming through three…
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),…
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
Automated adaptive inference of phenomenological dynamical models
NASA Astrophysics Data System (ADS)
Daniels, Bryan C.; Nemenman, Ilya
2015-08-01
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.
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.
Dynamical Adaptation in Terrorist Cells/Networks
NASA Astrophysics Data System (ADS)
Hussain, D. M. Akbar; Ahmed, Zaki
Typical terrorist cells/networks have dynamical structure as they evolve or adapt to changes which may occur due to capturing or killing of a member of the cell/network. Analytical measures in graph theory like degree centrality, betweenness and closeness centralities are very common and have long history of their successful use in revealing the importance of various members of the network. However, modeling of covert, terrorist or criminal networks through social graph dose not really provide the hierarchical structure which exist in these networks as these networks are composed of leaders and followers etc. In this research we analyze and predict the most likely role a particular node can adapt once a member of the network is either killed or caught. The adaptation is based on computing Bayes posteriori probability of each node and the level of the said node in the network structure.
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.
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 synchronization and anticipatory dynamical systems
NASA Astrophysics Data System (ADS)
Yang, Ying-Jen; Chen, Chun-Chung; Lai, Pik-Yin; Chan, C. K.
2015-09-01
Many biological systems can sense periodical variations in a stimulus input and produce well-timed, anticipatory responses after the input is removed. Such systems show memory effects for retaining timing information in the stimulus and cannot be understood from traditional synchronization consideration of passive oscillatory systems. To understand this anticipatory phenomena, we consider oscillators built from excitable systems with the addition of an adaptive dynamics. With such systems, well-timed post-stimulus responses similar to those from experiments can be obtained. Furthermore, a well-known model of working memory is shown to possess similar anticipatory dynamics when the adaptive mechanism is identified with synaptic facilitation. The last finding suggests that this type of oscillator can be common in neuronal systems with plasticity.
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
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.
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. PMID:25529139
Mental workload dynamics in adaptive interface design
NASA Technical Reports Server (NTRS)
Hancock, Peter A.; Chignell, Mark H.
1988-01-01
In examining the role of time in mental workload, the authors present a different perspective from which to view the problem of assessment. Mental workload is plotted in three dimensions, whose axes represent effective time for action, perceived distance from desired goal state, level of effort required to achieve the time-constrained goal. This representation allows the generation of isodynamic workload contours that incorporate the factors of operator skill and equifinality of effort. An adaptive interface for dynamic task reallocation is described that uses this form of assessment to reconcile the joint aims of stable operator loading and acceptable primary task performance by the total system.
Direct adaptive control for nonlinear uncertain dynamical systems
NASA Astrophysics Data System (ADS)
Hayakawa, Tomohisa
In light of the complex and highly uncertain nature of dynamical systems requiring controls, it is not surprising that reliable system models for many high performance engineering and life science applications are unavailable. In the face of such high levels of system uncertainty, robust controllers may unnecessarily sacrifice system performance whereas adaptive controllers are clearly appropriate since they can tolerate far greater system uncertainty levels to improve system performance. In this dissertation, we develop a Lyapunov-based direct adaptive and neural adaptive control framework that addresses parametric uncertainty, unstructured uncertainty, disturbance rejection, amplitude and rate saturation constraints, and digital implementation issues. Specifically, we consider the following research topics; direct adaptive control for nonlinear uncertain systems with exogenous disturbances; robust adaptive control for nonlinear uncertain systems; adaptive control for nonlinear uncertain systems with actuator amplitude and rate saturation constraints; adaptive reduced-order dynamic compensation for nonlinear uncertain systems; direct adaptive control for nonlinear matrix second-order dynamical systems with state-dependent uncertainty; adaptive control for nonnegative and compartmental dynamical systems with applications to general anesthesia; direct adaptive control of nonnegative and compartmental dynamical systems with time delay; adaptive control for nonlinear nonnegative and compartmental dynamical systems with applications to clinical pharmacology; neural network adaptive control for nonlinear nonnegative dynamical systems; passivity-based neural network adaptive output feedback control for nonlinear nonnegative dynamical systems; neural network adaptive dynamic output feedback control for nonlinear nonnegative systems using tapped delay memory units; Lyapunov-based adaptive control framework for discrete-time nonlinear systems with exogenous disturbances
ADAPTIVE MULTILEVEL SPLITTING IN MOLECULAR DYNAMICS SIMULATIONS*
Aristoff, David; Lelièvre, Tony; Mayne, Christopher G.; Teo, Ivan
2014-01-01
Adaptive Multilevel Splitting (AMS) is a replica-based rare event sampling method that has been used successfully in high-dimensional stochastic simulations to identify trajectories across a high potential barrier separating one metastable state from another, and to estimate the probability of observing such a trajectory. An attractive feature of AMS is that, in the limit of a large number of replicas, it remains valid regardless of the choice of reaction coordinate used to characterize the trajectories. Previous studies have shown AMS to be accurate in Monte Carlo simulations. In this study, we extend the application of AMS to molecular dynamics simulations and demonstrate its effectiveness using a simple test system. Our conclusion paves the way for useful applications, such as molecular dynamics calculations of the characteristic time of drug dissociation from a protein target. PMID:26005670
Circuit dynamics of adaptive and maladaptive behaviour
Deisseroth, Karl
2014-01-01
The recent development of technologies for investigating specific components of intact biological systems has allowed elucidation of the neural circuitry underlying adaptive and maladaptive behaviours. Investigators are now able to observe and control, with high spatio-temporal resolution, structurally defined intact pathways along which electrical activity flows during and after the performance of complex behaviours. These investigations have revealed that control of projection-specific dynamics is well suited to modulating behavioural patterns that are relevant to a broad range of psychiatric diseases. Structural dynamics principles have emerged to provide diverse, unexpected and causal insights into the operation of intact and diseased nervous systems, linking form and function in the brain. PMID:24429629
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.
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
Adaptive dynamics for physiologically structured population models.
Durinx, Michel; Metz, J A J Hans; Meszéna, Géza
2008-05-01
We develop a systematic toolbox for analyzing the adaptive dynamics of multidimensional traits in physiologically structured population models with point equilibria (sensu Dieckmann et al. in Theor. Popul. Biol. 63:309-338, 2003). Firstly, we show how the canonical equation of adaptive dynamics (Dieckmann and Law in J. Math. Biol. 34:579-612, 1996), an approximation for the rate of evolutionary change in characters under directional selection, can be extended so as to apply to general physiologically structured population models with multiple birth states. Secondly, we show that the invasion fitness function (up to and including second order terms, in the distances of the trait vectors to the singularity) for a community of N coexisting types near an evolutionarily singular point has a rational form, which is model-independent in the following sense: the form depends on the strategies of the residents and the invader, and on the second order partial derivatives of the one-resident fitness function at the singular point. This normal form holds for Lotka-Volterra models as well as for physiologically structured population models with multiple birth states, in discrete as well as continuous time and can thus be considered universal for the evolutionary dynamics in the neighbourhood of singular points. Only in the case of one-dimensional trait spaces or when N = 1 can the normal form be reduced to a Taylor polynomial. Lastly we show, in the form of a stylized recipe, how these results can be combined into a systematic approach for the analysis of the (large) class of evolutionary models that satisfy the above restrictions. PMID:17943289
Opinion dynamics on an adaptive random network
NASA Astrophysics Data System (ADS)
Benczik, I. J.; Benczik, S. Z.; Schmittmann, B.; Zia, R. K. P.
2009-04-01
We revisit the classical model for voter dynamics in a two-party system with two basic modifications. In contrast to the original voter model studied in regular lattices, we implement the opinion formation process in a random network of agents in which interactions are no longer restricted by geographical distance. In addition, we incorporate the rapidly changing nature of the interpersonal relations in the model. At each time step, agents can update their relationships. This update is determined by their own opinion, and by their preference to make connections with individuals sharing the same opinion, or rather with opponents. In this way, the network is built in an adaptive manner, in the sense that its structure is correlated and evolves with the dynamics of the agents. The simplicity of the model allows us to examine several issues analytically. We establish criteria to determine whether consensus or polarization will be the outcome of the dynamics and on what time scales these states will be reached. In finite systems consensus is typical, while in infinite systems a disordered metastable state can emerge and persist for infinitely long time before consensus is reached.
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
Ultra-Low Power Dynamic Knob in Adaptive Compressed Sensing Towards Biosignal Dynamics.
Wang, Aosen; Lin, Feng; Jin, Zhanpeng; Xu, Wenyao
2016-06-01
Compressed sensing (CS) is an emerging sampling paradigm in data acquisition. Its integrated analog-to-information structure can perform simultaneous data sensing and compression with low-complexity hardware. To date, most of the existing CS implementations have a fixed architectural setup, which lacks flexibility and adaptivity for efficient dynamic data sensing. In this paper, we propose a dynamic knob (DK) design to effectively reconfigure the CS architecture by recognizing the biosignals. Specifically, the dynamic knob design is a template-based structure that comprises a supervised learning module and a look-up table module. We model the DK performance in a closed analytic form and optimize the design via a dynamic programming formulation. We present the design on a 130 nm process, with a 0.058 mm (2) fingerprint and a 187.88 nJ/event energy-consumption. Furthermore, we benchmark the design performance using a publicly available dataset. Given the energy constraint in wireless sensing, the adaptive CS architecture can consistently improve the signal reconstruction quality by more than 70%, compared with the traditional CS. The experimental results indicate that the ultra-low power dynamic knob can provide an effective adaptivity and improve the signal quality in compressed sensing towards biosignal dynamics. PMID:26800548
Adaptive Assessment of Student's Knowledge in Programming Courses
ERIC Educational Resources Information Center
Chatzopoulou, D. I.; Economides, A. A.
2010-01-01
This paper presents Programming Adaptive Testing (PAT), a Web-based adaptive testing system for assessing students' programming knowledge. PAT was used in two high school programming classes by 73 students. The question bank of PAT is composed of 443 questions. A question is classified in one out of three difficulty levels. In PAT, the levels of…
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.
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.
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.
Static and dynamic responses of an ultrathin adaptive secondary mirror
NASA Astrophysics Data System (ADS)
del Vecchio, Ciro; Brusa, Guido; Gallieni, Daniele; Lloyd-Hart, Michael; Davison, Warren B.
1999-09-01
We present the results of a compete set of static and dynamic runs of the FEA model of the MMT adaptive secondary. The thin mirror is the most delicate component of the MMT adaptive secondary unit, as it provides the deformable optical surface able to correct the incoming wavefront. The static performances are evaluated as a function of the various load cases arising form gravitational loads and from the forces deriving from the magnetic interactions between actuators. In addition, computations were performed to assess the dynamic response to the high bandwidth, adaptive correcting force.s In both cases, the performances of the adaptive mirror design are able to accommodate the severe specifications.
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.
Conservation program participation and adaptive rangeland decision-making
Technology Transfer Automated Retrieval System (TEKTRAN)
This paper analyzes rancher participation in conservation programs in the context of a social-ecological framework for adaptive rangeland management. We argue that conservation programs are best understood as one of many strategies of adaptively managing rangelands in ways that sustain livelihoods a...
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…
Dynamic mesh adaption for triangular and tetrahedral grids
NASA Technical Reports Server (NTRS)
Biswas, Rupak; Strawn, Roger
1993-01-01
The following topics are discussed: requirements for dynamic mesh adaption; linked-list data structure; edge-based data structure; adaptive-grid data structure; three types of element subdivision; mesh refinement; mesh coarsening; additional constraints for coarsening; anisotropic error indicator for edges; unstructured-grid Euler solver; inviscid 3-D wing; and mesh quality for solution-adaptive grids. The discussion is presented in viewgraph form.
Selecting, adapting, and sustaining programs in health care systems.
Zullig, Leah L; Bosworth, Hayden B
2015-01-01
Practitioners and researchers often design behavioral programs that are effective for a specific population or problem. Despite their success in a controlled setting, relatively few programs are scaled up and implemented in health care systems. Planning for scale-up is a critical, yet often overlooked, element in the process of program design. Equally as important is understanding how to select a program that has already been developed, and adapt and implement the program to meet specific organizational goals. This adaptation and implementation requires attention to organizational goals, available resources, and program cost. We assert that translational behavioral medicine necessitates expanding successful programs beyond a stand-alone research study. This paper describes key factors to consider when selecting, adapting, and sustaining programs for scale-up in large health care systems and applies the Knowledge to Action (KTA) Framework to a case study, illustrating knowledge creation and an action cycle of implementation and evaluation activities. PMID:25931825
Adaptation and dynamics of cat retinal ganglion cells
Enroth-Cugell, Christina; Shapley, R. M.
1973-01-01
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. PMID:4747229
Quantitative Adaptation Analytics for Assessing Dynamic Systems of Systems.
Gauthier, John H.; Miner, Nadine E.; Wilson, Michael L.; Le, Hai D.; Kao, Gio K; Melander, Darryl J.; Longsine, Dennis Earl; Vander Meer, Robert Charles,
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.
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.
Dynamics of adaptive agents with asymmetric information
NASA Astrophysics Data System (ADS)
DeMartino, Andrea; Galla, Tobias
2005-08-01
We apply path integral techniques to study the dynamics of agent-based models with asymmetric information structures. In particular, we devise a batch version of a model proposed originally by Berg et al (2001 Quantitative Finance 1 203), and convert the coupled multi-agent processes into an effective-agent problem from which the dynamical order parameters in ergodic regimes can be derived self-consistently together with the corresponding phase structure. Our dynamical study complements and extends the available static theory. Results are confirmed by numerical simulations.
Complexity and network dynamics in physiological adaptation: an integrated view.
Baffy, György; Loscalzo, Joseph
2014-05-28
Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of the operational characteristics, allowing us to propose an integrated framework of physiological adaptation from a complex network perspective. Applicability of this concept is illustrated by analyzing molecular and cellular mechanisms of adaptation in response to the pervasive challenge of obesity, a chronic condition resulting from sustained nutrient excess that prompts chaotic exploration for system stability associated with tradeoffs and a risk of adverse outcomes such as diabetes, cardiovascular disease, and cancer. Deconstruction of this complexity holds the promise of gaining novel insights into physiological adaptation in health and disease. PMID:24751342
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.
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...
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.
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.
Adapting Scheduling Programs for Educational Specifications.
ERIC Educational Resources Information Center
Glass, Thomas E.
1984-01-01
Planners of a new Arizona school used the district's existing computerized master scheduling program to identify instructional spaces needed. Total classroom needs by subject were translated into total square footage requirements. (MLF)
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…
Dynamic Programming Applications in Water Resources
NASA Astrophysics Data System (ADS)
Yakowitz, Sidney
1982-08-01
The central intention of this survey is to review dynamic programming models for water resource problems and to examine computational techniques which have been used to obtain solutions to these problems. Problem areas surveyed here include aqueduct design, irrigation system control, project development, water quality maintenance, and reservoir operations analysis. Computational considerations impose severe limitation on the scale of dynamic programming problems which can be solved. Inventive numerical techniques for implementing dynamic programming have been applied to water resource problems. Discrete dynamic programming, differential dynamic programming, state incremental dynamic programming, and Howard's policy iteration method are among the techniques reviewed. Attempts have been made to delineate the successful applications, and speculative ideas are offered toward attacking problems which have not been solved satisfactorily.
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.
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.
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…
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
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.
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.
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.
Boundary detection via dynamic programming
NASA Astrophysics Data System (ADS)
Udupa, Jayaram K.; Samarasekera, Supun; Barrett, William A.
1992-09-01
This paper reports a new method for detecting optimal boundaries in multidimensional scene data via dynamic programming (DP). In its current form the algorithm detects 2-D contours on slices and differs from other reported DP-based algorithms in an essential way in that it allows freedom in 2-D for finding optimal contour paths (as opposed to a single degree of freedom in the published methods). The method is being successfully used in segmenting object boundaries in a variety of medical applications including orbital volume from CT images (for craniofacial surgical planning), segmenting bone in MR images for kinematic analysis of the joints of the foot, segmenting the surface of the brain from the inner surface of the cranial vault, segmenting pituitary gland tumor for following the effect of a drug on the tumor, segmenting the boundaries of the heart in MR images, and segmenting the olfactory bulb for verifying hypotheses related to the size of this bulb in certain disease states.
Adaptive sampling program support for expedited site characterization
Johnson, R.
1993-10-01
Expedited site characterizations offer substantial savings in time and money when assessing hazardous waste sites. Key to some of these savings is the ability to adapt a sampling program to the ``real-time`` data generated by an expedited site characterization. This paper presents a two-prong approach to supporting adaptive sampling programs: a specialized object-oriented database/geographical information system for data fusion, management and display; and combined Bayesian/geostatistical methods for contamination extent estimation and sample location selection.
Modifications to the Flexible Spacecraft Dynamics Program
NASA Technical Reports Server (NTRS)
1980-01-01
Modifications to existing subroutines are briefly described and a detailed description of new subroutines is given. The capability to simulate the Dynamics Explorer-B control system new developed and the formulation for this addition is given. The program variables in new labelled COMMON blocks are described in detail and the modified input and output for the d Flexible Spacecraft Dynamics Program is described.
Content-adaptive ghost imaging of dynamic scenes.
Li, Ziwei; Suo, Jinli; Hu, Xuemei; Dai, Qionghai
2016-04-01
Limited by long acquisition time of 2D ghost imaging, current ghost imaging systems are so far inapplicable for dynamic scenes. However, it's been demonstrated that nature images are spatiotemporally redundant and the redundancy is scene dependent. Inspired by that, we propose a content-adaptive computational ghost imaging approach to achieve high reconstruction quality under a small number of measurements, and thus achieve ghost imaging of dynamic scenes. To utilize content-adaptive inter-frame redundancy, we put the reconstruction under an iterative reweighted optimization, with non-uniform weight computed from temporal-correlated frame sequences. The proposed approach can achieve dynamic imaging at 16fps with 64×64-pixel resolution. PMID:27137022
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
Dynamic analysis of neural encoding by point process adaptive filtering.
Eden, Uri T; Frank, Loren M; Barbieri, Riccardo; Solo, Victor; Brown, Emery N
2004-05-01
Neural receptive fields are dynamic in that with experience, neurons change their spiking responses to relevant stimuli. To understand how neural systems adapt their representations of biological information, analyses of receptive field plasticity from experimental measurements are crucial. Adaptive signal processing, the well-established engineering discipline for characterizing the temporal evolution of system parameters, suggests a framework for studying the plasticity of receptive fields. We use the Bayes' rule Chapman-Kolmogorov paradigm with a linear state equation and point process observation models to derive adaptive filters appropriate for estimation from neural spike trains. We derive point process filter analogues of the Kalman filter, recursive least squares, and steepest-descent algorithms and describe the properties of these new filters. We illustrate our algorithms in two simulated data examples. The first is a study of slow and rapid evolution of spatial receptive fields in hippocampal neurons. The second is an adaptive decoding study in which a signal is decoded from ensemble neural spiking activity as the receptive fields of the neurons in the ensemble evolve. Our results provide a paradigm for adaptive estimation for point process observations and suggest a practical approach for constructing filtering algorithms to track neural receptive field dynamics on a millisecond timescale. PMID:15070506
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.
Model-adaptive hybrid dynamic control for robotic assembly tasks
Austin, D.J.; McCarragher, B.J.
1999-10-01
A new task-level adaptive controller is presented for the hybrid dynamic control of robotic assembly tasks. Using a hybrid dynamic model of the assembly task, velocity constraints are derived from which satisfactory velocity commands are obtained. Due to modeling errors and parametric uncertainties, the velocity commands may be erroneous and may result in suboptimal performance. Task-level adaptive control schemes, based on the occurrence of discrete events, are used to change the model parameters from which the velocity commands are determined. Two adaptive schemes are presented: the first is based on intuitive reasoning about the vector spaces involved whereas the second uses a search region that is reduced with each iteration. For the first adaptation law, asymptotic convergence to the correct model parameters is proven except for one case. This weakness motivated the development of the second adaptation law, for which asymptotic convergence is proven in all cases. Automated control of a peg-in-hole assembly task is given as an example, and simulations and experiments for this task are presented. These results demonstrate the success of the method and also indicate properties for rapid convergence.
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.
Eco-evolutionary feedbacks, adaptive dynamics and evolutionary rescue theory
Ferriere, Regis; Legendre, Stéphane
2013-01-01
Adaptive dynamics theory has been devised to account for feedbacks between ecological and evolutionary processes. Doing so opens new dimensions to and raises new challenges about evolutionary rescue. Adaptive dynamics theory predicts that successive trait substitutions driven by eco-evolutionary feedbacks can gradually erode population size or growth rate, thus potentially raising the extinction risk. Even a single trait substitution can suffice to degrade population viability drastically at once and cause ‘evolutionary suicide’. In a changing environment, a population may track a viable evolutionary attractor that leads to evolutionary suicide, a phenomenon called ‘evolutionary trapping’. Evolutionary trapping and suicide are commonly observed in adaptive dynamics models in which the smooth variation of traits causes catastrophic changes in ecological state. In the face of trapping and suicide, evolutionary rescue requires that the population overcome evolutionary threats generated by the adaptive process itself. Evolutionary repellors play an important role in determining how variation in environmental conditions correlates with the occurrence of evolutionary trapping and suicide, and what evolutionary pathways rescue may follow. In contrast with standard predictions of evolutionary rescue theory, low genetic variation may attenuate the threat of evolutionary suicide and small population sizes may facilitate escape from evolutionary traps. PMID:23209163
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.
Cheung, Ying Kuen; Chakraborty, Bibhas; Davidson, Karina W
2015-06-01
Implementation study is an important tool for deploying state-of-the-art treatments from clinical efficacy studies into a treatment program, with the dual goals of learning about effectiveness of the treatments and improving the quality of care for patients enrolled into the program. In this article, we deal with the design of a treatment program of dynamic treatment regimens (DTRs) for patients with depression post-acute coronary syndrome. We introduce a novel adaptive randomization scheme for a sequential multiple assignment randomized trial of DTRs. Our approach adapts the randomization probabilities to favor treatment sequences having comparatively superior Q-functions used in Q-learning. The proposed approach addresses three main concerns of an implementation study: it allows incorporation of historical data or opinions, it includes randomization for learning purposes, and it aims to improve care via adaptation throughout the program. We demonstrate how to apply our method to design a depression treatment program using data from a previous study. By simulation, we illustrate that the inputs from historical data are important for the program performance measured by the expected outcomes of the enrollees, but also show that the adaptive randomization scheme is able to compensate poorly specified historical inputs by improving patient outcomes within a reasonable horizon. The simulation results also confirm that the proposed design allows efficient learning of the treatments by alleviating the curse of dimensionality. PMID:25354029
Dynamical singularities in adaptive delayed-feedback control.
Saito, Asaki; Konishi, Keiji
2011-09-01
We demonstrate the dynamical characteristics of adaptive delayed-feedback control systems, exploiting a discrete-time adaptive control method derived for carrying out detailed analysis. In particular, the systems exhibit singularities such as power-law decay of the distribution of transient times and almost zero finite-time Lyapunov exponents. We can explain these results by characterizing such systems as having (1) a Jacobian matrix with unity eigenvalue in the whole phase space, and (2) parameters approaching a stability boundary proven to be identical with that of (nonadaptive) delayed-feedback control. PMID:22060398
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.
Function-valued adaptive dynamics and the calculus of variations.
Parvinen, Kalle; Dieckmann, Ulf; Heino, Mikko
2006-01-01
Adaptive dynamics has been widely used to study the evolution of scalar-valued, and occasionally vector-valued, strategies in ecologically realistic models. In many ecological situations, however, evolving strategies are best described as function-valued, and thus infinite-dimensional, traits. So far, such evolution has only been studied sporadically, mostly based on quantitative genetics models with limited ecological realism. In this article we show how to apply the calculus of variations to find evolutionarily singular strategies of function-valued adaptive dynamics: such a strategy has to satisfy Euler's equation with environmental feedback. We also demonstrate how second-order derivatives can be used to investigate whether or not a function-valued singular strategy is evolutionarily stable. We illustrate our approach by presenting several worked examples. PMID:16012801
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.
Adaptive neural information processing with dynamical electrical synapses
Xiao, Lei; Zhang, Dan-ke; Li, Yuan-qing; Liang, Pei-ji; Wu, Si
2013-01-01
The present study investigates a potential computational role of dynamical electrical synapses in neural information process. Compared with chemical synapses, electrical synapses are more efficient in modulating the concerted activity of neurons. Based on the experimental data, we propose a phenomenological model for short-term facilitation of electrical synapses. The model satisfactorily reproduces the phenomenon that the neuronal correlation increases although the neuronal firing rates attenuate during the luminance adaptation. We explore how the stimulus information is encoded in parallel by firing rates and correlated activity of neurons, and find that dynamical electrical synapses mediate a transition from the firing rate code to the correlation one during the luminance adaptation. The latter encodes the stimulus information by using the concerted, but lower neuronal firing rate, and hence is economically more efficient. PMID:23596413
Effects of adaptive dynamical linking in networked games.
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. PMID:24229137
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.
The adaptive potential of maternal stress exposure in regulating population dynamics.
Sheriff, Michael J
2015-03-01
Ecologists, evolutionary biologists and biomedical researchers are investing great effort in understanding the impact maternal stress may have on offspring phenotypes. Bian et al. advance this field by providing evidence that density-induced maternal stress programs offspring phenotypes, resulting in direct consequences on their fitness and population dynamics, but doing so in a context-dependent manner. They suggest that intrinsic state alterations induced by maternal stress may be one ecological factor generating delayed density-dependent effects. This research highlights the connection between maternal stress and population dynamics, and the importance of understanding the adaptive potential of such effects in a context-dependent manner. PMID:26247815
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.
Vectorization of computer programs with applications to computational fluid dynamics
NASA Astrophysics Data System (ADS)
Gentzsch, W.
Techniques for adapting serial computer programs to the architecture of modern vector computers are presented and illustrated with examples, mainly from the field of computational fluid dynamics. The limitations of conventional computers are reviewed; the vector computers CRAY-1S and CDC-CYBER 205 are characterized; and chapters are devoted to vectorization of FORTRAN programs, sample-program vectorization on five different vector and parallel-architecture computers, restructuring of basic linear-algebra algorithms, iterative methods, vectorization of simple numerical algorithms, and fluid-dynamics vectorization on CRAY-1 (including an implicit beam and warming scheme, an implicit finite-difference method for laminar boundary-layer equations, the Galerkin method and a direct Monte Carlo simulation). Diagrams, charts, tables, and photographs are provided.
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…
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.
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
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
Computer program for flexible rotor dynamics analysis
NASA Technical Reports Server (NTRS)
Shen, F. A.
1974-01-01
Program analyzes general nonaxisymmetric and nonsynchronous transient and steady-state rotor dynamic performance of bending- and shear-wise flexible rotor-bearing system under various operating conditions. Program can be used as analytical study tool for general transient spin-speed and/or non-axisymmetric rotor motion.
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)
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 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.
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.
Dynamic data-driven sensor network adaptation for border control
NASA Astrophysics Data System (ADS)
Bein, Doina; Madan, Bharat B.; Phoha, Shashi; Rajtmajer, Sarah; Rish, Anna
2013-06-01
Given a specific scenario for the border control problem, we propose a dynamic data-driven adaptation of the associated sensor network via embedded software agents which make sensor network control, adaptation and collaboration decisions based on the contextual information value of competing data provided by different multi-modal sensors. We further propose the use of influence diagrams to guide data-driven decision making in selecting the appropriate action or course of actions which maximize a given utility function by designing a sensor embedded software agent that uses an influence diagram to make decisions about whether to engage or not engage higher level sensors for accurately detecting human presence in the region. The overarching goal of the sensor system is to increase the probability of target detection and classification and reduce the rate of false alarms. The proposed decision support software agent is validated experimentally on a laboratory testbed for multiple border control scenarios.
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
Development of a dynamically adaptive grid method for multidimensional problems
NASA Astrophysics Data System (ADS)
Holcomb, J. E.; Hindman, R. G.
1984-06-01
An approach to solution adaptive grid generation for use with finite difference techniques, previously demonstrated on model problems in one space dimension, has been extended to multidimensional problems. The method is based on the popular elliptic steady grid generators, but is 'dynamically' adaptive in the sense that a grid is maintained at all times satisfying the steady grid law driven by a solution-dependent source term. Testing has been carried out on Burgers' equation in one and two space dimensions. Results appear encouraging both for inviscid wave propagation cases and viscous boundary layer cases, suggesting that application to practical flow problems is now possible. In the course of the work, obstacles relating to grid correction, smoothing of the solution, and elliptic equation solvers have been largely overcome. Concern remains, however, about grid skewness, boundary layer resolution and the need for implicit integration methods. Also, the method in 3-D is expected to be very demanding of computer resources.
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.
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)
Piacentino, Michael R.; Berends, David C.; Zhang, David C.; Gudis, Eduardo
2013-05-01
Two of the biggest challenges in designing U×V vision systems are properly representing high dynamic range scene content using low dynamic range components and reducing camera motion blur. SRI's MASI-HDR (Motion Adaptive Signal Integration-High Dynamic Range) is a novel technique for generating blur-reduced video using multiple captures for each displayed frame while increasing the effective camera dynamic range by four bits or more. MASI-HDR processing thus provides high performance video from rapidly moving platforms in real-world conditions in low latency real time, enabling even the most demanding applications on air, ground and water.
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.
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
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.
Inter-limb interference during bimanual adaptation to dynamic environments
Casadio, Maura; Sanguineti, Vittorio; Squeri, Valentina; Masia, Lorenzo; Morasso, Pietro
2015-01-01
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
Hydrodynamics in adaptive resolution particle simulations: Multiparticle collision dynamics
NASA Astrophysics Data System (ADS)
Alekseeva, Uliana; Winkler, Roland G.; Sutmann, Godehard
2016-06-01
A new adaptive resolution technique for particle-based multi-level simulations of fluids is presented. In the approach, the representation of fluid and solvent particles is changed on the fly between an atomistic and a coarse-grained description. The present approach is based on a hybrid coupling of the multiparticle collision dynamics (MPC) method and molecular dynamics (MD), thereby coupling stochastic and deterministic particle-based methods. Hydrodynamics is examined by calculating velocity and current correlation functions for various mixed and coupled systems. We demonstrate that hydrodynamic properties of the mixed fluid are conserved by a suitable coupling of the two particle methods, and that the simulation results agree well with theoretical expectations.
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.
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.
Optimal spectral tracking--adapting to dynamic regime change.
Brittain, John-Stuart; Halliday, David M
2011-01-30
Real world data do not always obey the statistical restraints imposed upon them by sophisticated analysis techniques. In spectral analysis for instance, an ergodic process--the interchangeability of temporal for spatial averaging--is assumed for a repeat-trial design. Many evolutionary scenarios, such as learning and motor consolidation, do not conform to such linear behaviour and should be approached from a more flexible perspective. To this end we previously introduced the method of optimal spectral tracking (OST) in the study of trial-varying parameters. In this extension to our work we modify the OST routines to provide an adaptive implementation capable of reacting to dynamic transitions in the underlying system state. In so doing, we generalise our approach to characterise both slow-varying and rapid fluctuations in time-series, simultaneously providing a metric of system stability. The approach is first applied to a surrogate dataset and compared to both our original non-adaptive solution and spectrogram approaches. The adaptive OST is seen to display fast convergence and desirable statistical properties. All three approaches are then applied to a neurophysiological recording obtained during a study on anaesthetic monitoring. Local field potentials acquired from the posterior hypothalamic region of a deep brain stimulation patient undergoing anaesthesia were analysed. The characterisation of features such as response delay, time-to-peak and modulation brevity are considered. PMID:21115043
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.
Adaptation and Learning of Agents in Market Oriented Programming
NASA Astrophysics Data System (ADS)
Ishinishi, Masayuki; Namatame, Akira; Kita, Hajime
Market Oriented Programming (MOP) proposed by Wellman is a decentralized control method using auction machanism inspired by the market economy. It is applied to many problems such as network and computation resource allocation. Conventional MOP models are formulated based on the concept of ‘competitive market’ of economics which assumes that the market consists of sufficiently many and small agents. However, in realistic applications of MOP, number of agents is limited and their interdependency is not negligible. In this paper, MOP for interdependent agents is discussed. An oligopoly market model for MOP is introduced, and adaptation process of interdependent agents and its stability are discussed. Further, it is also demonstrated that selfish learning of adaptation coefficiency by each agent achieves stability of market through computer simulation.
Reconfigurable systems for sequence alignment and for general dynamic programming.
Jacobi, Ricardo P; Ayala-Rincón, Mauricio; Carvalho, Luis G A; Llanos, Carlos H; Hartenstein, Reiner W
2005-01-01
Reconfigurable systolic arrays can be adapted to efficiently resolve a wide spectrum of computational problems; parallelism is naturally explored in systolic arrays and reconfigurability allows for redefinition of the interconnections and operations even during run time (dynamically). We present a reconfigurable systolic architecture that can be applied for the efficient treatment of several dynamic programming methods for resolving well-known problems, such as global and local sequence alignment, approximate string matching and longest common subsequence. The dynamicity of the reconfigurability was found to be useful for practical applications in the construction of sequence alignments. A VHDL (VHSIC hardware description language) version of this new architecture was implemented on an APEX FPGA (Field programmable gate array). It would be several magnitudes faster than the software algorithm alternatives. PMID:16342039
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
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.
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
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.
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
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 (
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
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.
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.
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.
Dynamic adaptive learning for decision-making supporting systems
NASA Astrophysics Data System (ADS)
He, Haibo; Cao, Yuan; Chen, Sheng; Desai, Sachi; Hohil, Myron E.
2008-03-01
This paper proposes a novel adaptive learning method for data mining in support of decision-making systems. Due to the inherent characteristics of information ambiguity/uncertainty, high dimensionality and noisy in many homeland security and defense applications, such as surveillances, monitoring, net-centric battlefield, and others, it is critical to develop autonomous learning methods to efficiently learn useful information from raw data to help the decision making process. The proposed method is based on a dynamic learning principle in the feature spaces. Generally speaking, conventional approaches of learning from high dimensional data sets include various feature extraction (principal component analysis, wavelet transform, and others) and feature selection (embedded approach, wrapper approach, filter approach, and others) methods. However, very limited understandings of adaptive learning from different feature spaces have been achieved. We propose an integrative approach that takes advantages of feature selection and hypothesis ensemble techniques to achieve our goal. Based on the training data distributions, a feature score function is used to provide a measurement of the importance of different features for learning purpose. Then multiple hypotheses are iteratively developed in different feature spaces according to their learning capabilities. Unlike the pre-set iteration steps in many of the existing ensemble learning approaches, such as adaptive boosting (AdaBoost) method, the iterative learning process will automatically stop when the intelligent system can not provide a better understanding than a random guess in that particular subset of feature spaces. Finally, a voting algorithm is used to combine all the decisions from different hypotheses to provide the final prediction results. Simulation analyses of the proposed method on classification of different US military aircraft databases show the effectiveness of this method.
Community dynamics of cellulose-adapted thermophilic bacterial consortia.
Eichorst, Stephanie A; Varanasi, Patanjali; Stavila, Vatalie; Zemla, Marcin; Auer, Manfred; Singh, Seema; Simmons, Blake A; Singer, Steven W
2013-09-01
Enzymatic hydrolysis of cellulose is a key process in the global carbon cycle and the industrial conversion of biomass to biofuels. In natural environments, cellulose hydrolysis is predominately performed by microbial communities. However, detailed understanding of bacterial cellulose hydrolysis is primarily confined to a few model isolates. Developing models for cellulose hydrolysis by mixed microbial consortia will complement these isolate studies and may reveal new mechanisms for cellulose deconstruction. Microbial communities were adapted to microcrystalline cellulose under aerobic, thermophilic conditions using green waste compost as the inoculum to study cellulose hydrolysis in a microbial consortium. This adaptation selected for three dominant taxa--the Firmicutes, Bacteroidetes and Thermus. A high-resolution profile of community development during the enrichment demonstrated a community transition from Firmicutes to a novel Bacteroidetes population that clusters in the Chitinophagaceae family. A representative strain of this population, strain NYFB, was successfully isolated, and sequencing of a nearly full-length 16S rRNA gene demonstrated that it was only 86% identical compared with other validated strains in the phylum Bacteroidetes. Strain NYFB grew well on soluble polysaccharide substrates, but grew poorly on insoluble polysaccharide substrates. Similar communities were observed in companion thermophilic enrichments on insoluble wheat arabinoxylan, a hemicellulosic substrate, suggesting a common model for deconstruction of plant polysaccharides. Combining observations of community dynamics and the physiology of strain NYFB, a cooperative successional model for polysaccharide hydrolysis by the Firmicutes and Bacteroidetes in the thermophilic cellulolytic consortia is proposed. PMID:23763762
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.
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
iAPBS: a programming interface to Adaptive Poisson-Boltzmann Solver
Konecny, Robert; Baker, Nathan A.; McCammon, J. A.
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.
A new procedure for dynamic adaption of three-dimensional unstructured grids
NASA Technical Reports Server (NTRS)
Biswas, Rupak; Strawn, Roger
1993-01-01
A new procedure is presented for the simultaneous coarsening and refinement of three-dimensional unstructured tetrahedral meshes. This algorithm allows for localized grid adaption that is used to capture aerodynamic flow features such as vortices and shock waves in helicopter flowfield simulations. The mesh-adaption algorithm is implemented in the C programming language and uses a data structure consisting of a series of dynamically-allocated linked lists. These lists allow the mesh connectivity to be rapidly reconstructed when individual mesh points are added and/or deleted. The algorithm allows the mesh to change in an anisotropic manner in order to efficiently resolve directional flow features. The procedure has been successfully implemented on a single processor of a Cray Y-MP computer. Two sample cases are presented involving three-dimensional transonic flow. Computed results show good agreement with conventional structured-grid solutions for the Euler equations.
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.
Adaptive methods for nonlinear structural dynamics and crashworthiness analysis
NASA Technical Reports Server (NTRS)
Belytschko, Ted
1993-01-01
The objective is to describe three research thrusts in crashworthiness analysis: adaptivity; mixed time integration, or subcycling, in which different timesteps are used for different parts of the mesh in explicit methods; and methods for contact-impact which are highly vectorizable. The techniques are being developed to improve the accuracy of calculations, ease-of-use of crashworthiness programs, and the speed of calculations. The latter is still of importance because crashworthiness calculations are often made with models of 20,000 to 50,000 elements using explicit time integration and require on the order of 20 to 100 hours on current supercomputers. The methodologies are briefly reviewed and then some example calculations employing these methods are described. The methods are also of value to other nonlinear transient computations.
Dynamic skeletal muscle stimulation and its potential in bone adaptation
Qin, Y-X.; Lam, H.; Ferreri, S.; Rubin, C.
2016-01-01
To identify mechanotransductive signals for combating musculoskeletal deterioration, it is essential to determine the components and mechanisms critical to the anabolic processes of musculoskeletal tissues. It is hypothesized that the interaction between bone and muscle may depend on fluid exchange in these tissues by mechanical loading. It has been shown that intramedullary pressure (ImP) and low-level bone strain induced by muscle stimulation (MS) has the potential to mitigate bone loss induced by disuse osteopenia. Optimized MS signals, i.e., low-intensity and high frequency, may be critical in maintaining bone mass and mitigating muscle atrophy. The objectives for this review are to discuss the potential for MS to induce ImP and strains on bone, to regulate bone adaptation, and to identify optimized stimulation frequency in the loading regimen. The potential for MS to regulate blood and fluid flow will also be discussed. The results suggest that oscillatory MS regulates fluid dynamics with minimal mechanical strain in bone. The response was shown to be dependent on loading frequency, serving as a critical mediator in mitigating bone loss. A specific regimen of dynamic MS may be optimized in vivo to attenuate disuse osteopenia and serve as a biomechanical intervention in the clinical setting. PMID:20190376
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.
Simulation of dynamic processes with adaptive neural networks.
Tzanos, C. P.
1998-02-03
Many industrial processes are highly non-linear and complex. Their simulation with first-principle or conventional input-output correlation models is not satisfactory, either because the process physics is not well understood, or it is so complex that direct simulation is either not adequately accurate, or it requires excessive computation time, especially for on-line applications. Artificial intelligence techniques (neural networks, expert systems, fuzzy logic) or their combination with simple process-physics models can be effectively used for the simulation of such processes. Feedforward (static) neural networks (FNNs) can be used effectively to model steady-state processes. They have also been used to model dynamic (time-varying) processes by adding to the network input layer input nodes that represent values of input variables at previous time steps. The number of previous time steps is problem dependent and, in general, can be determined after extensive testing. This work demonstrates that for dynamic processes that do not vary fast with respect to the retraining time of the neural network, an adaptive feedforward neural network can be an effective simulator that is free of the complexities introduced by the use of input values at previous time steps.
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
Adaptive strategies in designing the simultaneous global drug development program.
Yuan, Zhilong; Chen, Gang; Huang, Qin
2016-01-01
Many methods have been proposed to account for the potential impact of ethnic/regional factors when extrapolating results from multiregional clinical trials (MRCTs) to targeted ethnic (TE) patients, i.e., "bridging." Most of them either focused on TE patients in the MRCT (i.e., internal bridging) or a separate local clinical trial (LCT) (i.e., external bridging). Huang et al. (2012) integrated both bridging concepts in their method for the Simultaneous Global Drug Development Program (SGDDP) which designs both the MRCT and the LCT prospectively and combines patients in both trials by ethnic origin, i.e., TE vs. non-TE (NTE). The weighted Z test was used to combine information from TE and NTE patients to test with statistical rigor whether a new treatment is effective in the TE population. Practically, the MRCT is often completed before the LCT. Thus to increase the power for the SGDDP and/or obtain more informative data in TE patients, we may use the final results from the MRCT to re-evaluate initial assumptions (e.g., effect sizes, variances, weight), and modify the LCT accordingly. We discuss various adaptive strategies for the LCT such as sample size reassessment, population enrichment, endpoint change, and dose adjustment. As an example, we extend a popular adaptive design method to re-estimate the sample size for the LCT, and illustrate it for a normally distributed endpoint. PMID:26098138
DEAN: A program for dynamic engine analysis
NASA Technical Reports Server (NTRS)
Sadler, G. G.; Melcher, K. J.
1985-01-01
The Dynamic Engine Analysis program, DEAN, is a FORTRAN code implemented on the IBM/370 mainframe at NASA Lewis Research Center for digital simulation of turbofan engine dynamics. DEAN is an interactive program which allows the user to simulate engine subsystems as well as a full engine systems with relative ease. The nonlinear first order ordinary differential equations which define the engine model may be solved by one of four integration schemes, a second order Runge-Kutta, a fourth order Runge-Kutta, an Adams Predictor-Corrector, or Gear's method for still systems. The numerical data generated by the model equations are displayed at specified intervals between which the user may choose to modify various parameters affecting the model equations and transient execution. Following the transient run, versatile graphics capabilities allow close examination of the data. DEAN's modeling procedure and capabilities are demonstrated by generating a model of simple compressor rig.
Velocity fluctuation analysis via dynamic programming
Schlossberg, D. J.; Gupta, D. K.; Fonck, R. J.; McKee, G. R.; Shafer, M. W.
2006-10-15
A new method of calculating one-dimensional velocity fluctuations from spatially resolved density fluctuation measurements is presented. The algorithm uses vector-matching methods of dynamic programming that match structures, such as turbulent fluctuations, in two data sets. The associated time delay between data sets is estimated by determining an optimal path to transform one vector to another. This time-delay-estimation (TDE) method establishes a new benchmark for velocity analysis by achieving higher sensitivity and frequency response than previously developed methods, such as time-resolved cross correlations and wavelets. TDE has been successfully applied to beam emission spectroscopy measurements of density fluctuations to obtain poloidal flow fluctuations associated with such phenomena as the geodesic acoustic mode. The dynamic programming algorithm should allow extension to high frequency velocity fluctuations associated with underlying electrostatic potential and resulting ExB fluctuations.
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
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.
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'…
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. PMID:21851473
Adaptive optics optical coherence tomography with dynamic retinal tracking
Kocaoglu, Omer P.; Ferguson, R. Daniel; Jonnal, Ravi S.; Liu, Zhuolin; Wang, Qiang; Hammer, Daniel X.; Miller, Donald T.
2014-01-01
Adaptive optics optical coherence tomography (AO-OCT) is a highly sensitive and noninvasive method for three dimensional imaging of the microscopic retina. Like all in vivo retinal imaging techniques, however, it suffers the effects of involuntary eye movements that occur even under normal fixation. In this study we investigated dynamic retinal tracking to measure and correct eye motion at KHz rates for AO-OCT imaging. A customized retina tracking module was integrated into the sample arm of the 2nd-generation Indiana AO-OCT system and images were acquired on three subjects. Analyses were developed based on temporal amplitude and spatial power spectra in conjunction with strip-wise registration to independently measure AO-OCT tracking performance. After optimization of the tracker parameters, the system was found to correct eye movements up to 100 Hz and reduce residual motion to 10 µm root mean square. Between session precision was 33 µm. Performance was limited by tracker-generated noise at high temporal frequencies. PMID:25071963
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.
Adaptive optics optical coherence tomography with dynamic retinal tracking.
Kocaoglu, Omer P; Ferguson, R Daniel; Jonnal, Ravi S; Liu, Zhuolin; Wang, Qiang; Hammer, Daniel X; Miller, Donald T
2014-07-01
Adaptive optics optical coherence tomography (AO-OCT) is a highly sensitive and noninvasive method for three dimensional imaging of the microscopic retina. Like all in vivo retinal imaging techniques, however, it suffers the effects of involuntary eye movements that occur even under normal fixation. In this study we investigated dynamic retinal tracking to measure and correct eye motion at KHz rates for AO-OCT imaging. A customized retina tracking module was integrated into the sample arm of the 2nd-generation Indiana AO-OCT system and images were acquired on three subjects. Analyses were developed based on temporal amplitude and spatial power spectra in conjunction with strip-wise registration to independently measure AO-OCT tracking performance. After optimization of the tracker parameters, the system was found to correct eye movements up to 100 Hz and reduce residual motion to 10 µm root mean square. Between session precision was 33 µm. Performance was limited by tracker-generated noise at high temporal frequencies. PMID:25071963
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,…
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
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.
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…
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.
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.
Adaptive fusion of infrared and visible images in dynamic scene
NASA Astrophysics Data System (ADS)
Yang, Guang; Yin, Yafeng; Man, Hong; Desai, Sachi
2011-11-01
Multiple modalities sensor fusion has been widely employed in various surveillance and military applications. A variety of image fusion techniques including PCA, wavelet, curvelet and HSV has been proposed in recent years to improve human visual perception for object detection. One of the main challenges for visible and infrared image fusion is to automatically determine an optimal fusion strategy for different input scenes along with an acceptable computational cost. This paper, we propose a fast and adaptive feature selection based image fusion method to obtain high a contrast image from visible and infrared sensors for targets detection. At first, fuzzy c-means clustering is applied on the infrared image to highlight possible hotspot regions, which will be considered as potential targets' locations. After that, the region surrounding the target area is segmented as the background regions. Then image fusion is locally applied on the selected target and background regions by computing different linear combination of color components from registered visible and infrared images. After obtaining different fused images, histogram distributions are computed on these local fusion images as the fusion feature set. The variance ratio which is based on Linear Discriminative Analysis (LDA) measure is employed to sort the feature set and the most discriminative one is selected for the whole image fusion. As the feature selection is performed over time, the process will dynamically determine the most suitable feature for the image fusion in different scenes. Experiment is conducted on the OSU Color-Thermal database, and TNO Human Factor dataset. The fusion results indicate that our proposed method achieved a competitive performance compared with other fusion algorithms at a relatively low computational cost.
Evaluation of dynamic programming among the existing stereo matching algorithms
NASA Astrophysics Data System (ADS)
Huat, Teo Chee; Manap, Nurulfajar bin Abd
2015-05-01
There are various types of existing stereo matching algorithms on image processing which applied on stereo vision images to get better results of disparity depth map. One of them is the dynamic programming method. On this research is to perform an evaluation on the performance between the dynamic programming with other existing method as comparison. The algorithm used on the dynamic programming is the global optimization which provides better process on stereo images like its accuracy and its computational efficiency compared to other existing stereo matching algorithms. The dynamic programming algorithm used on this research is the current method as its disparity estimates at a particular pixel and all the other pixels unlike the old methods which with scanline based of dynamic programming. There will be details on every existing methods presented on this paper with the comparison between the dynamic programming and the existing methods. This can propose the dynamic programming method to be used on many applications in image processing.
Automatic cone photoreceptor segmentation using graph theory and dynamic programming
Chiu, Stephanie J.; Lokhnygina, Yuliya; Dubis, Adam M.; Dubra, Alfredo; Carroll, Joseph; Izatt, Joseph A.; Farsiu, Sina
2013-01-01
Geometrical analysis of the photoreceptor mosaic can reveal subclinical ocular pathologies. In this paper, we describe a fully automatic algorithm to identify and segment photoreceptors in adaptive optics ophthalmoscope images of the photoreceptor mosaic. This method is an extension of our previously described closed contour segmentation framework based on graph theory and dynamic programming (GTDP). We validated the performance of the proposed algorithm by comparing it to the state-of-the-art technique on a large data set consisting of over 200,000 cones and posted the results online. We found that the GTDP method achieved a higher detection rate, decreasing the cone miss rate by over a factor of five. PMID:23761854
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.
Optimal caching algorithm based on dynamic programming
NASA Astrophysics Data System (ADS)
Guo, Changjie; Xiang, Zhe; Zhong, Yuzhuo; Long, Jidong
2001-07-01
With the dramatic growth of multimedia streams, the efficient distribution of stored videos has become a major concern. There are two basic caching strategies: the whole caching strategy and the caching strategy based on layered encoded video, the latter can satisfy the requirement of the highly heterogeneous access to the Internet. Conventional caching strategies assign each object a cache gain by calculating popularity or density popularity, and determine which videos and which layers should be cached. In this paper, we first investigate the delivery model of stored video based on proxy, and propose two novel caching algorithms, DPLayer (for layered encoded caching scheme) and DPWhole (for whole caching scheme) for multimedia proxy caching. The two algorithms are based on the resource allocation model of dynamic programming to select the optimal subset of objects to be cached in proxy. Simulation proved that our algorithms achieve better performance than other existing schemes. We also analyze the computational complexity and space complexity of the algorithms, and introduce a regulative parameter to compress the states space of the dynamic programming problem and reduce the complexity of algorithms.
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…
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
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.
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
Ingram, James N; Howard, Ian S; Flanagan, J Randall; Wolpert, Daniel M
2011-09-01
Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics
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
Dynamics modeling and adaptive control of flexible manipulators
NASA Technical Reports Server (NTRS)
Sasiadek, J. Z.
1991-01-01
An application of Model Reference Adaptive Control (MRAC) to the position and force control of flexible manipulators and robots is presented. A single-link flexible manipulator is analyzed. The problem was to develop a mathematical model of a flexible robot that is accurate. The objective is to show that the adaptive control works better than 'conventional' systems and is suitable for flexible structure control.
Robot trajectory planning via dynamic programming
Dohrmann, C.R.; Robinett, R.D.
1994-03-01
The method of dynamic programming is applied to three example problems dealing with robot trajectory planning. The first two examples involve end-effector tracking of a straight line with rest-to-rest motions of planar two-link and three-link rigid robots. These examples illustrate the usefulness of the method for producing smooth trajectories either in the presence or absence of joint redundancies. The last example demonstrates the use of the method for rest-to-rest maneuvers of a single-link manipulator with a flexible payload. Simulation results for this example display interesting symmetries that are characteristic of such maneuvers. Details concerning the implementation and computational aspects of the method are discussed.
Model-Free Dual Heuristic Dynamic Programming.
Ni, Zhen; He, Haibo; Zhong, Xiangnan; Prokhorov, Danil V
2015-08-01
Model-based dual heuristic dynamic programming (MB-DHP) is a popular approach in approximating optimal solutions in control problems. Yet, it usually requires offline training for the model network, and thus resulting in extra computational cost. In this brief, we propose a model-free DHP (MF-DHP) design based on finite-difference technique. In particular, we adopt multilayer perceptron with one hidden layer for both the action and the critic networks design, and use delayed objective functions to train both the action and the critic networks online over time. We test both the MF-DHP and MB-DHP approaches with a discrete time example and a continuous time example under the same parameter settings. Our simulation results demonstrate that the MF-DHP approach can obtain a control performance competitive with that of the traditional MB-DHP approach while requiring less computational resources. PMID:25955997
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. PMID
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.
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
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
Adaptive routing for dynamic on-body wireless sensor networks.
Maskooki, Arash; Soh, Cheong Boon; Gunawan, Erry; Low, Kay Soon
2015-03-01
Energy is scarce in mobile computing devices including wearable and implantable devices in a wireless body area network. In this paper, an adaptive routing protocol is developed and analyzed which minimizes the energy cost per bit of information by using the channel information to choose the best strategy to route data. In this approach, the source node will switch between direct and relayed communication based on the quality of the link and will use the relay only if the channel quality is below a certain threshold. The mathematical model is then validated through simulations which shows that the adaptive routing strategy can improve energy efficiency significantly compared with existing methods. PMID:24686306
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.
Free energy calculations from adaptive molecular dynamics simulations with adiabatic reweighting
NASA Astrophysics Data System (ADS)
Cao, Lingling; Stoltz, Gabriel; Lelièvre, Tony; Marinica, Mihai-Cosmin; Athènes, Manuel
2014-03-01
We propose an adiabatic reweighting algorithm for computing the free energy along an external parameter from adaptive molecular dynamics simulations. The adaptive bias is estimated using Bayes identity and information from all the sampled configurations. We apply the algorithm to a structural transition in a cluster and to the migration of a crystalline defect along a reaction coordinate. Compared to standard adaptive molecular dynamics, we observe an acceleration of convergence. With the aid of the algorithm, it is also possible to iteratively construct the free energy along the reaction coordinate without having to differentiate the gradient of the reaction coordinate or any biasing potential.
Dynamic Range Adaptation to Sound Level Statistics in the Auditory Nerve
Wen, Bo; Wang, Grace I.; Dean, Isabel; Delgutte, Bertrand
2009-01-01
The auditory system operates over a vast range of sound pressure levels (100–120 dB) with nearly constant discrimination ability across most of the range, well exceeding the dynamic range of most auditory neurons (20–40 dB). Dean et al. (Nat. Neurosci. 8:1684, 2005) have reported that the dynamic range of midbrain auditory neurons adapts to the distribution of sound levels in a continuous, dynamic stimulus by shifting towards the most frequently occurring level. Here we show that dynamic range adaptation, distinct from classic firing rate adaptation, also occurs in primary auditory neurons in anesthetized cats for tone and noise stimuli. Specifically, the range of sound levels over which firing rates of auditory-nerve (AN) fibers grows rapidly with level shifts nearly linearly with the most probable levels in a dynamic sound stimulus. This dynamic range adaptation was observed for fibers with all characteristic frequencies and spontaneous discharge rates. As in the midbrain, dynamic range adaptation improved the precision of level coding by the AN fiber population for the prevailing sound levels in the stimulus. However, dynamic range adaptation in the AN was weaker than in the midbrain, and not sufficient (0.25 dB/dB on average for broadband noise) to prevent a significant degradation of the precision of level coding by the AN population above 60 dB SPL. These findings suggest that adaptive processing of sound levels first occurs in the auditory periphery and is enhanced along the auditory pathway. PMID:19889991
Adaptive control of nonlinear systems using multistage dynamic neural networks
NASA Astrophysics Data System (ADS)
Gupta, Madan M.; Rao, Dandina H.
1992-11-01
In this paper we present a new architecture of neuron, called the dynamic neural unit (DNU). The topology of the proposed neuronal model embodies delay elements, feedforward and feedback signals weighted by the synaptic weights and a time-varying nonlinear activation function, and is thus different from the conventionally and assumed architecture of neurons. The learning algorithm for the proposed neuronal structure and the corresponding implementation scheme are presented. A multi-stage dynamic neural network is developed using the DNU as the basic processing element. The performance evaluation of the dynamic neural network is presented for nonlinear dynamic systems under various situations. The capabilities of the proposed neural network model not only account for the learning and control actions emulating some of the biological control functions, but also provide a promising parallel-distributed intelligent control scheme for large-scale complex dynamic systems.
ERIC Educational Resources Information Center
Keller, Mimi
An adaptive physical education program was implemented for two special classes of educable mentally retarded children, grades K-3 in California. Children from a regular kindergarten class also participated in the program. The program operated for 5 months, with children receiving motor skills training 40 minutes per day, 4 days per week. Analysis…
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…
A massively parallel adaptive finite element method with dynamic load balancing
Devine, K.D.; Flaherty, J.E.; Wheat, S.R.; Maccabe, A.B.
1993-05-01
We construct massively parallel, adaptive finite element methods for the solution of hyperbolic conservation laws in one and two dimensions. Spatial discretization is performed by a discontinuous Galerkin finite element method using a basis of piecewise Legendre polynomials. Temporal discretization utilizes a Runge-Kutta method. Dissipative fluxes and projection limiting prevent oscillations near solution discontinuities. The resulting method is of high order and may be parallelized efficiently on MIMD computers. We demonstrate parallel efficiency through computations on a 1024-processor nCUBE/2 hypercube. We also present results using adaptive p-refinement to reduce the computational cost of the method. We describe tiling, a dynamic, element-based data migration system. Tiling dynamically maintains global load balance in the adaptive method by overlapping neighborhoods of processors, where each neighborhood performs local load balancing. We demonstrate the effectiveness of the dynamic load balancing with adaptive p-refinement examples.
Arévalo, Orlando; Bornschlegl, Mona A; Eberhardt, Sven; Ernst, Udo; Pawelzik, Klaus; Fahle, Manfred
2013-01-01
In everyday life, humans interact with a dynamic environment often requiring rapid adaptation of visual perception and motor control. In particular, new visuo-motor mappings must be learned while old skills have to be kept, such that after adaptation, subjects may be able to quickly change between two different modes of generating movements ('dual-adaptation'). A fundamental question is how the adaptation schedule determines the acquisition speed of new skills. Given a fixed number of movements in two different environments, will dual-adaptation be faster if switches ('phase changes') between the environments occur more frequently? We investigated the dynamics of dual-adaptation under different training schedules in a virtual pointing experiment. Surprisingly, we found that acquisition speed of dual visuo-motor mappings in a pointing task is largely independent of the number of phase changes. Next, we studied the neuronal mechanisms underlying this result and other key phenomena of dual-adaptation by relating model simulations to experimental data. We propose a simple and yet biologically plausible neural model consisting of a spatial mapping from an input layer to a pointing angle which is subjected to a global gain modulation. Adaptation is performed by reinforcement learning on the model parameters. Despite its simplicity, the model provides a unifying account for a broad range of experimental data: It quantitatively reproduced the learning rates in dual-adaptation experiments for both direct effect, i.e. adaptation to prisms, and aftereffect, i.e. behavior after removal of prisms, and their independence on the number of phase changes. Several other phenomena, e.g. initial pointing errors that are far smaller than the induced optical shift, were also captured. Moreover, the underlying mechanisms, a local adaptation of a spatial mapping and a global adaptation of a gain factor, explained asymmetric spatial transfer and generalization of prism adaptation, as
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…
An adaptive compromise programming method for multi-objective path optimization
NASA Astrophysics Data System (ADS)
Li, Rongrong; Leung, Yee; Lin, Hui; Huang, Bo
2013-04-01
Network routing problems generally involve multiple objectives which may conflict one another. An effective way to solve such problems is to generate a set of Pareto-optimal solutions that is small enough to be handled by a decision maker and large enough to give an overview of all possible trade-offs among the conflicting objectives. To accomplish this, the present paper proposes an adaptive method based on compromise programming to assist decision makers in identifying Pareto-optimal paths, particularly for non-convex problems. This method can provide an unbiased approximation of the Pareto-optimal alternatives by adaptively changing the origin and direction of search in the objective space via the dynamic updating of the largest unexplored region till an appropriately structured Pareto front is captured. To demonstrate the efficacy of the proposed methodology, a case study is carried out for the transportation of dangerous goods in the road network of Hong Kong with the support of geographic information system. The experimental results confirm the effectiveness of the approach.
Adapting Physical Education: A Guide for Individualizing Physical Education Programs.
ERIC Educational Resources Information Center
Buckanavage, Robert, Ed.; And Others
Guidelines are presented for organizing programs and modifying activities in physical education programs for children with a wide range of physical and emotional disabilities. The guidelines should result in a program that allows students to work to their maximum potential within the framework of regular physical education classes. In planning the…
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.
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. PMID:26669825
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.
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…
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…
ERIC Educational Resources Information Center
McCabe, Kristen M.; Yeh, May; Garland, Ann F.; Lau, Anna S.; Chavez, Gloria
2005-01-01
The current manuscript describes the process of developing the GANA program, a version of PCIT that has been culturally adapted for Mexican American families. The adaptation process involved combining information from 1) clinical literature on Mexican American families, 2) empirical literature on barriers to treatment access and effectiveness, 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…
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…
Space station orbit design using dynamic programming
NASA Astrophysics Data System (ADS)
Lin, Kun-Peng; Luo, Ya-Zhong; Tang, Guo-Jin
2013-08-01
A space station orbit design mission is characterized by a long-duration and multi-step decision process. First, the long-duration design process is divided into multiple planning periods, each of which consists of five basic flight segments. Second, each planning period is modeled as a multi-step decision process, and the orbital altitude strategies of different flight segments have interaction effects on each other. Third, a dynamic programming method is used to optimize the total propellant consumption of a planning period while considering interaction effects. The step cost of each decision segment is the propellant for orbital-decay maintenance or lifting altitude, and is calculated by approximate analytical equations and combining a shooting iteration method. The proposed approach is demonstrated for a typical orbit design problem of a space station. The results show that the proposed approach can effectively optimize the design of altitude strategies, and can save considerable propellant consumption for the space station than previous public studies.
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.
Dynamic Nature of Noncoding RNA Regulation of Adaptive Immune Response
Curtale, Graziella; Citarella, Franca
2013-01-01
Immune response plays a fundamental role in protecting the organism from infections; however, dysregulation often occurs and can be detrimental for the organism, leading to a variety of immune-mediated diseases. Recently our understanding of the molecular and cellular networks regulating the immune response, and, in particular, adaptive immunity, has improved dramatically. For many years, much of the focus has been on the study of protein regulators; nevertheless, recent evidence points to a fundamental role for specific classes of noncoding RNAs (ncRNAs) in regulating development, activation and homeostasis of the immune system. Although microRNAs (miRNAs) are the most comprehensive and well-studied, a number of reports suggest the exciting possibility that long ncRNAs (lncRNAs) could mediate host response and immune function. Finally, evidence is also accumulating that suggests a role for miRNAs and other small ncRNAs in autocrine, paracrine and exocrine signaling events, thus highlighting an elaborate network of regulatory interactions mediated by different classes of ncRNAs during immune response. This review will explore the multifaceted roles of ncRNAs in the adaptive immune response. In particular, we will focus on the well-established role of miRNAs and on the emerging role of lncRNAs and circulating ncRNAs, which all make indispensable contributions to the understanding of the multilayered modulation of the adaptive immune response. PMID:23975170
Plant adaptation to dynamically changing environment: the shade avoidance response.
Ruberti, I; Sessa, G; Ciolfi, A; Possenti, M; Carabelli, M; Morelli, G
2012-01-01
The success of competitive interactions between plants determines the chance of survival of individuals and eventually of whole plant species. Shade-tolerant plants have adapted their photosynthesis to function optimally under low-light conditions. These plants are therefore capable of long-term survival under a canopy shade. In contrast, shade-avoiding plants adapt their growth to perceive maximum sunlight and therefore rapidly dominate gaps in a canopy. Daylight contains roughly equal proportions of red and far-red light, but within vegetation that ratio is lowered as a result of red absorption by photosynthetic pigments. This light quality change is perceived through the phytochrome system as an unambiguous signal of the proximity of neighbors resulting in a suite of developmental responses (termed the shade avoidance response) that, when successful, result in the overgrowth of those neighbors. Shoot elongation induced by low red/far-red light may confer high relative fitness in natural dense communities. However, since elongation is often achieved at the expense of leaf and root growth, shade avoidance may lead to reduction in crop plant productivity. Over the past decade, major progresses have been achieved in the understanding of the molecular basis of shade avoidance. However, uncovering the mechanisms underpinning plant response and adaptation to changes in the ratio of red to far-red light is key to design new strategies to precise modulate shade avoidance in time and space without impairing the overall crop ability to compete for light. PMID:21888962
Arévalo, Orlando; Bornschlegl, Mona A.; Eberhardt, Sven; Ernst, Udo; Pawelzik, Klaus; Fahle, Manfred
2013-01-01
In everyday life, humans interact with a dynamic environment often requiring rapid adaptation of visual perception and motor control. In particular, new visuo–motor mappings must be learned while old skills have to be kept, such that after adaptation, subjects may be able to quickly change between two different modes of generating movements (‘dual–adaptation’). A fundamental question is how the adaptation schedule determines the acquisition speed of new skills. Given a fixed number of movements in two different environments, will dual–adaptation be faster if switches (‘phase changes’) between the environments occur more frequently? We investigated the dynamics of dual–adaptation under different training schedules in a virtual pointing experiment. Surprisingly, we found that acquisition speed of dual visuo–motor mappings in a pointing task is largely independent of the number of phase changes. Next, we studied the neuronal mechanisms underlying this result and other key phenomena of dual–adaptation by relating model simulations to experimental data. We propose a simple and yet biologically plausible neural model consisting of a spatial mapping from an input layer to a pointing angle which is subjected to a global gain modulation. Adaptation is performed by reinforcement learning on the model parameters. Despite its simplicity, the model provides a unifying account for a broad range of experimental data: It quantitatively reproduced the learning rates in dual–adaptation experiments for both direct effect, i.e. adaptation to prisms, and aftereffect, i.e. behavior after removal of prisms, and their independence on the number of phase changes. Several other phenomena, e.g. initial pointing errors that are far smaller than the induced optical shift, were also captured. Moreover, the underlying mechanisms, a local adaptation of a spatial mapping and a global adaptation of a gain factor, explained asymmetric spatial transfer and generalization of
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.
Segmentation of Indus Texts: A Dynamic Programming Approach.
ERIC Educational Resources Information Center
Siromoney, Gift; Huq, Abdul
1988-01-01
Demonstrates how a dynamic programing algorithm can be developed to segment unusually long written inscriptions from the Indus Valley Civilization. Explains the problem of segmentation, discusses the dynamic programing algorithm used, and includes tables which illustrate the segmentation of the inscriptions. (GEA)
Stefanich, Charlotte A; Witmer, Julie M; Young, Bonnie D; Benson, LouAnn E; Penn, Cheryl A; Ammerman, Alice S; Garcia, Beverly A; Jilcott, Stephanie B; Etzel, Ruth A
2005-10-01
Southcentral Foundation's Traditions of the Heart program is an innovative cardiovascular disease prevention program for women designed to build on the strengths of the Alaska Native culture as a way to support and encourage positive lifestyle behaviors that focus on healthy eating, active living, stress management, and tobacco cessation. After conducting assessments of existing intervention programs and formative data collection, we adapted two existing programs, Native Nutrition Circles and A New Leaf... Choices for Healthy Living, to develop the Traditions of the Heart program. We implemented and evaluated a pilot intervention study to determine the program's acceptance among Alaska Native women. We used the evaluation results to further refine our study protocol. This article describes the adaptation of these programs to the cultural needs and strengths of Alaska Native women and the results of the formative evaluation used to improve the program design. The complete pilot study outcomes will be published separately. PMID:16210690
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.
Promising Practices, and Program Adaptations & Successes. Annual Report.
ERIC Educational Resources Information Center
Dianda, Marcella; Flaherty, John
Through its Metropolitan Educational Trends and Research Outcomes (METRO) Center, the Southwest Regional Laboratory (SWRL) helps school districts implement research-based programs for educationally disadvantaged students. The most prominent of these is Success for All, a nationally recognized school restructuring program. In 1992, SWRL made a…
[Development of an adapted leisure education program for persons with dementia].
Carbonneau, Hélène; Caron, Chantal D; Desrosiers, Johanne
2009-06-01
Leisure represents a positive way to keep relationships satisfactory between caregivers and a person with dementia. Adapted leisure education is a promising approach to assist the family to discover new ways to share good times with their relatives. This study aimed to develop an adapted leisure education program. It included an evaluation of the caregivers' needs, the program content development, and a pilot study to experiment with the content of the program. Three focus groups of dementia caregivers (n = 19) were conducted to investigate caregivers needs. Based on content analysis of these focus groups and a literature review, the content of the program was developed. The pilot study (n = 4) included a quasi-experimental trial and an implementation evaluation. This study led to the development of an adapted leisure education program that puts caregiver support in a new perspective, focusing on positive aspects rather than the burden of caregiving. PMID:19860971
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.
Adaptive optimal spectral range for dynamically changing scene
NASA Astrophysics Data System (ADS)
Pinsky, Ephi; Siman-tov, Avihay; Peles, David
2012-06-01
A novel multispectral video system that continuously optimizes both its spectral range channels and the exposure time of each channel autonomously, under dynamic scenes, varying from short range-clear scene to long range-poor visibility, is currently being developed. Transparency and contrast of high scattering medium of channels with spectral ranges in the near infrared is superior to the visible channels, particularly to the blue range. Longer wavelength spectral ranges that induce higher contrast are therefore favored. Images of 3 spectral channels are fused and displayed for (pseudo) color visualization, as an integrated high contrast video stream. In addition to the dynamic optimization of the spectral channels, optimal real-time exposure time is adjusted simultaneously and autonomously for each channel. A criterion of maximum average signal, derived dynamically from previous frames of the video stream is used (Patent Application - International Publication Number: WO2009/093110 A2, 30.07.2009). This configuration enables dynamic compatibility with the optimal exposure time of a dynamically changing scene. It also maximizes the signal to noise ratio and compensates each channel for the specified value of daylight reflections and sensors response for each spectral range. A possible implementation is a color video camera based on 4 synchronized, highly responsive, CCD imaging detectors, attached to a 4CCD dichroic prism and combined with a common, color corrected, lens. Principal Components Analysis (PCA) technique is then applied for real time "dimensional collapse" in color space, in order to select and fuse, for clear color visualization, the 3 most significant principal channels out of at least 4 characterized by high contrast and rich details in the image data.
Broom, Donald M
2006-01-01
The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and
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.
Trans-radial upper extremity amputees are capable of adapting to a novel dynamic environment.
Schabowsky, Christopher N; Dromerick, Alexander W; Holley, Rahsaan J; Monroe, Brian; Lum, Peter S
2008-07-01
This study investigated differences in adaptation to a novel dynamic environment between eight trans-radial upper extremity (UE) prosthetic users and eight naive, neurologically intact subjects. Participants held onto the handle of a robotic manipulandum and executed reaching movements within a horizontal plane following a pseudo-random sequence of targets. Curl field perturbations were imposed by the robot motors, and we compared the rate and quality of adaptation between the prosthetic and control subjects. Adaptation was quantitatively assessed by peak error, defined as the maximum orthogonal distance between an observed trajectory and an ideal straight trajectory. Initial exposure to the curl field resulted in large errors, and as the subjects adapted to the novel environment, the errors decreased. During the early phase of adaptation, group differences in the rate of motor adaptation were not significant. However, during late learning, both error magnitude and variability were larger in the prosthetic group. The quality of adaptation, as indicated by the magnitude of the aftereffects, was similar between groups. We conclude that in persons with trans-radial arm amputation, motor adaptation to curl fields during reaching is similar to unimpaired individuals. These findings are discussed in relation to mechanisms of motor adaptation, neural plasticity following an upper extremity amputation (UEA), and potential motor recovery therapies for prosthetic users. PMID:18443766
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
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.
Inverse dynamics of adaptive structures used as space cranes
NASA Technical Reports Server (NTRS)
Das, S. K.; Utku, S.; Wada, B. K.
1990-01-01
As a precursor to the real-time control of fast moving adaptive structures used as space cranes, a formulation is given for the flexibility induced motion relative to the nominal motion (i.e., the motion that assumes no flexibility) and for obtaining the open loop time varying driving forces. An algorithm is proposed for the computation of the relative motion and driving forces. The governing equations are given in matrix form with explicit functional dependencies. A simulator is developed to implement the algorithm on a digital computer. In the formulations, the distributed mass of the crane is lumped by two schemes, vz., 'trapezoidal' lumping and 'Simpson's rule' lumping. The effects of the mass lumping schemes are shown by simulator runs.
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
Dynamic analysis of naive adaptive brain-machine interfaces.
Kowalski, Kevin C; He, Bryan D; Srinivasan, Lakshminarayan
2013-09-01
The closed-loop operation of brain-machine interfaces (BMI) provides a context to discover foundational principles behind human-computer interaction, with emerging clinical applications to stroke, neuromuscular diseases, and trauma. In the canonical BMI, a user controls a prosthetic limb through neural signals that are recorded by electrodes and processed by a decoder into limb movements. In laboratory demonstrations with able-bodied test subjects, parameters of the decoder are commonly tuned using training data that include neural signals and corresponding overt arm movements. In the application of BMI to paralysis or amputation, arm movements are not feasible, and imagined movements create weaker, partially unrelated patterns of neural activity. BMI training must begin naive, without access to these prototypical methods for parameter initialization used in most laboratory BMI demonstrations. Naive adaptive BMI refer to a class of methods recently introduced to address this problem. We first identify the basic elements of existing approaches based on adaptive filtering and define a decoder, ReFIT-PPF to represent these existing approaches. We then present Joint RSE, a novel approach that logically extends prior approaches. Using recently developed human- and synthetic-subjects closed-loop BMI simulation platforms, we show that Joint RSE significantly outperforms ReFIT-PPF and nonadaptive (static) decoders. Control experiments demonstrate the critical role of jointly estimating neural parameters and user intent. In addition, we show that nonzero sensorimotor delay in the user significantly degrades ReFIT-PPF but not Joint RSE, owing to differences in the prior on intended velocity. Paradoxically, substantial differences in the nature of sensory feedback between these methods do not contribute to differences in performance between Joint RSE and ReFIT-PPF. Instead, BMI performance improvement is driven by machine learning, which outpaces rates of human learning in
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.
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. PMID:25287405
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…
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
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.
NASA Astrophysics Data System (ADS)
Bentaallah, Abderrahim; Massoum, Ahmed; Benhamida, Farid; Meroufel, Abdelkader
2012-03-01
This paper studies the nonlinear adaptive control of an induction motor with natural dynamic complete nonlinear observer. The aim of this work is to develop a nonlinear control law and adaptive performance for an asynchronous motor with two main objectives: to improve the continuation of trajectories and the stability, robustness to parametric variations and disturbances rejection. This control law will independently control the speed and flux into the machine by restricting supply. A complete nonlinear observer for dynamic nature ensuring closed loop stability of the entire control and observer has been developed. Several simulations have also been carried out to demonstrate system performance.
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.
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
Adapting Foreign Language Programs to New Educational Designs.
ERIC Educational Resources Information Center
Levy, Stephen L.
John Dewey High School, the first experimental non-graded school in New York City, is described in this article in terms of its educational philosophy and administrative procedures. With modular scheduling, five area resource centers, and innovative student evaluation procedures integrated into the program, the school views the concept of…
Adapting the Behavior Education Program for Preschool Settings
ERIC Educational Resources Information Center
Steed, Elizabeth A.
2011-01-01
Behavior Education Program (BEP) is the most researched targeted intervention that is used in schoolwide positive behavior intervention and supports (PBIS). It is a daily check-in and check-out system in which students receive extra attention for positive social behavior throughout their school day. This extra attention is intended to prevent…
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
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
A New Approach to Parallel Dynamic Partitioning for Adaptive Unstructured Meshes
NASA Technical Reports Server (NTRS)
Heber, Gerd; Biswas, Rupak; Gao, Guang R.
1999-01-01
Classical mesh partitioning algorithms were designed for rather static situations, and their straightforward application in a dynamical framework may lead to unsatisfactory results, e.g., excessive data migration among processors. Furthermore, special attention should be paid to their amenability to parallelization. In this paper, a novel parallel method for the dynamic partitioning of adaptive unstructured meshes is described. It is based on a linear representation of the mesh using self-avoiding walks.
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.
Voter dynamics on an adaptive network with finite average connectivity
NASA Astrophysics Data System (ADS)
Mukhopadhyay, Abhishek; Schmittmann, Beate
2009-03-01
We study a simple model for voter dynamics in a two-party system. The opinion formation process is implemented in a random network of agents in which interactions are not restricted by geographical distance. In addition, we incorporate the rapidly changing nature of the interpersonal relations in the model. At each time step, agents can update their relationships, so that there is no history dependence in the model. This update is determined by their own opinion, and by their preference to make connections with individuals sharing the same opinion and with opponents. Using simulations and analytic arguments, we determine the final steady states and the relaxation into these states for different system sizes. In contrast to earlier studies, the average connectivity (``degree'') of each agent is constant here, independent of the system size. This has significant consequences for the long-time behavior of the model.
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.
Ph.D. and Ed.D. Program Adaptations for College Teachers.
ERIC Educational Resources Information Center
Dressel, Paul L.; Guiste, Evelyn B.
The extent to which the Ph.D. and/or Ed.D. programs have been adapted to assist in preparing students for college teaching was surveyed. Of 309 universities, 122 responded, and of these, 72 had no adaptations. However, 50 universities indicated the availability, in at least one discipline or field, of modifications in the Ph.D. and/or Ed.D.…
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.
The evolutionary dynamics of influenza A virus adaptation to mammalian hosts
Bhatt, S.; Lam, T. T.; Lycett, S. J.; Leigh Brown, A. J.; Bowden, T. A.; Holmes, E. C.; Guan, Y.; Wood, J. L. N.; Brown, I. H.; Kellam, P.; Pybus, O. G.; Brown, Ian; Brookes, Sharon; Germundsson, Anna; Cook, Alex; Williamson, Susanna; Essen, Stephen; Garcon, Fanny; Gunn, George; Sanchez, Manuel; Marques, Diogo; Wood, James; Tucker, Dan; McCrone, Ian; Gog, Julia; Saenz, Roberto; Staff, Meg; Murcia, Pablo; Barclay, Wendy; Donnelly, Christl; Elderfield, Ruth A.; Kellam, Paul; Baillie, Greg; Coulter, Eve; Wieland, Barbara; Mastin, Alex; McCauley, John; Brown, Andy Leigh; Lycett, Sam; Woolhouse, Mark; Pybus, Oliver; Bhatt, Samir; Hayward, Andrew; Ishola, David; Archibald, Alan; Freeman, Tom; Charleston, Bryan; LeFevre, Eric; Bailey, Mick; Inman, Charlotte; Stokes, Chris; Chang, Kin Chow; Dunham, Stephen; White, Gavin; Nguyen-Van-Tam, Jonathan; Enstone, Joanne
2013-01-01
Few questions on infectious disease are more important than understanding how and why avian influenza A viruses successfully emerge in mammalian populations, yet little is known about the rate and nature of the virus’ genetic adaptation in new hosts. Here, we measure, for the first time, the genomic rate of adaptive evolution of swine influenza viruses (SwIV) that originated in birds. By using a curated dataset of more than 24 000 human and swine influenza gene sequences, including 41 newly characterized genomes, we reconstructed the adaptive dynamics of three major SwIV lineages (Eurasian, EA; classical swine, CS; triple reassortant, TR). We found that, following the transfer of the EA lineage from birds to swine in the late 1970s, EA virus genes have undergone substantially faster adaptive evolution than those of the CS lineage, which had circulated among swine for decades. Further, the adaptation rates of the EA lineage antigenic haemagglutinin and neuraminidase genes were unexpectedly high and similar to those observed in human influenza A. We show that the successful establishment of avian influenza viruses in swine is associated with raised adaptive evolution across the entire genome for many years after zoonosis, reflecting the contribution of multiple mutations to the coordinated optimization of viral fitness in a new environment. This dynamics is replicated independently in the polymerase genes of the TR lineage, which established in swine following separate transmission from non-swine hosts. PMID:23382435
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
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.
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.
Design implementation and control of MRAS error dynamics. [Model-Reference Adaptive System
NASA Technical Reports Server (NTRS)
Colburn, B. K.; Boland, J. S., III
1974-01-01
Use is made of linearized error characteristic equation for model-reference adaptive systems to determine a parameter adjustment rule for obtaining time-invariant error dynamics. Theoretical justification of error stability is given and an illustrative example included to demonstrate the utility of the proposed technique.
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.
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. PMID:26302525
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
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
Neural network-based adaptive dynamic surface control for permanent magnet synchronous motors.
Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Chen, Bing; Lin, Chong
2015-03-01
This brief considers the problem of neural networks (NNs)-based adaptive dynamic surface control (DSC) for permanent magnet synchronous motors (PMSMs) with parameter uncertainties and load torque disturbance. First, NNs are used to approximate the unknown and nonlinear functions of PMSM drive system and a novel adaptive DSC is constructed to avoid the explosion of complexity in the backstepping design. Next, under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced to only one, and the designed neural controllers structure is much simpler than some existing results in literature, which can guarantee that the tracking error converges to a small neighborhood of the origin. Then, simulations are given to illustrate the effectiveness and potential of the new design technique. PMID:25720014
TSS subsatellite attitude dynamics and control laws verification programs
NASA Technical Reports Server (NTRS)
Venditti, Floriano
1987-01-01
A dynamic model of the Tethered Satellite System (TSS) and of the relevant simulation program, developed in order to provide the dynamic analysis support for the design verification of the subsatellite attitude control, is presented. Special care was spent in the satellite attitude dynamic analysis and the model was specifically conceived to this aim. The way in which the simulation results can be utilized for the verification and testing of the attitude control is also presented.
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
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.
China's small town urbanization program: criticism and adaptation.
Tan, K C
1993-02-01
"China's 12,000 designated towns and more than 40,000 rural market towns have experienced a major transformation since the institution of rural reforms in the late 1970s. Rural industrialization based on the concept of 'leaving the soil but not the village, entering the factory but not the town' has contributed to the revitalization of many small towns. But this rural urbanization has also brought about a number of problems in the countryside, leading many to propose the adoption of the concept of 'leaving the soil and the village' as another basis of China's small town urbanization. This essay attempts to examine this transformation, particularly the recent criticism and adjustment made to the small town urbanization program." PMID:12318388
A rigorous model study of the adaptive dynamics of Mendelian diploids.
Collet, Pierre; Méléard, Sylvie; Metz, Johan A J
2013-09-01
Adaptive dynamics (AD) so far has been put on a rigorous footing only for clonal inheritance. We extend this to sexually reproducing diploids, although admittedly still under the restriction of an unstructured population with Lotka-Volterra-like dynamics and single locus genetics (as in Kimura's in Proc Natl Acad Sci USA 54: 731-736, 1965 infinite allele model). We prove under the usual smoothness assumptions, starting from a stochastic birth and death process model, that, when advantageous mutations are rare and mutational steps are not too large, the population behaves on the mutational time scale (the 'long' time scale of the literature on the genetical foundations of ESS theory) as a jump process moving between homozygous states (the trait substitution sequence of the adaptive dynamics literature). Essential technical ingredients are a rigorous estimate for the probability of invasion in a dynamic diploid population, a rigorous, geometric singular perturbation theory based, invasion implies substitution theorem, and the use of the Skorohod M 1 topology to arrive at a functional convergence result. In the small mutational steps limit this process in turn gives rise to a differential equation in allele or in phenotype space of a type referred to in the adaptive dynamics literature as 'canonical equation'. PMID:22821207
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.
Modeling human target reaching with an adaptive observer implemented with dynamic neural fields.
Fard, Farzaneh S; Hollensen, Paul; Heinke, Dietmar; Trappenberg, Thomas P
2015-12-01
Humans can point fairly accurately to memorized states when closing their eyes despite slow or even missing sensory feedback. It is also common that the arm dynamics changes during development or from injuries. We propose a biologically motivated implementation of an arm controller that includes an adaptive observer. Our implementation is based on the neural field framework, and we show how a path integration mechanism can be trained from few examples. Our results illustrate successful generalization of path integration with a dynamic neural field by which the robotic arm can move in arbitrary directions and velocities. Also, by adapting the strength of the motor effect the observer implicitly learns to compensate an image acquisition delay in the sensory system. Our dynamic implementation of an observer successfully guides the arm toward the target in the dark, and the model produces movements with a bell-shaped velocity profile, consistent with human behavior data. PMID:26559472
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…
NASA Astrophysics Data System (ADS)
Chiang, Y.; Chiang, W.; Sui, C.; Tung, C.; Ho, H.; Li, M.; Chan, S.; Climate Change Adaptation Technologies Program, National Science Council, Taiwan
2010-12-01
Climate changes adaptation needs innovative technological revolution on demand for transdisciplinary studies in various temporal and spatial scales. In our proposed program, a systematic and scientific framework will be developed to promote innovative adaptation technologies with respect to providing decision making information for government sectors, enhancing applicability of scientific research output, strengthening national research capabilities, and integrating both academic and non-academic resources. The objectives of this program are to identify key issues, required technologies, and scientific knowledge for climate change adaptations, and to build a transdisciplinary platform bridging science-supported technologies required by government sectors and demand-oriented scientific research conducted by academic communities. The approach proposed herein will be practiced in vulnerable regions, such as urban, rural, mountain, river basin, and coastal areas, which are particularly sensitive to climate change. The first phase of 3-year (2011~2013) work is to deploy framework and strategies of climate change impact assessment and adaptation measures between related government sectors and researchers from academic communities. The proposed framework involves three principle research groups, namely Environmental System, Vulnerability Assessment, and Risk Management and Adaptation Technology. The goal of the first group, Environmental System, is to combine climate change projections with enhanced scientific and environmental monitoring technologies for better adaptations to future scenarios in different social, economic, and environmental sectors to support adaptation measures planning and to reduce uncertainties on assessing vulnerability. The goal of the second group, Vulnerability Assessment, is to identify interfaces and information structures of climate change vulnerably issues and to develop protocol, models, and indices for vulnerability assessment. The goal of
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
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.
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.
Tabak, Rachel G; Sinclair, Kàimi A; Baumann, Ana A; Racette, Susan B; Sebert Kuhlmann, Anne; Johnson-Jennings, Michelle D; Brownson, Ross C
2015-12-01
The Diabetes Prevention Program (DPP) has been shown to prevent type 2 diabetes through lifestyle modification. The purpose of this study was to describe the literature on DPP translation, synthesizing studies using cultural adaptation and implementation research. A systematic search was conducted. Original studies evaluating DPP implementation and/or cultural adaptation were included. Data about cultural adaptation, implementation outcomes, and translation strategies was abstracted. A total of 44 were included, of which 15 reported cultural adaptations and 38 explored implementation. Many studies shortened the program length and reported a group format. The most commonly reported cultural adaptation (13 of 15) was with content. At the individual level, the most frequently assessed implementation outcome (n = 30) was adoption. Feasibility was most common (n = 32) at the organization level. The DPP is being tested in a variety of settings and populations, using numerous translational strategies and cultural adaptations. Implementation research that identifies, evaluates, and reports efforts to translate the DPP into practice is crucial. PMID:26622913
Parallel Molecular Dynamics Program for Molecules
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.
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
Development of a Programming Adapter for a Classified-Data Processor Device
PEREA,DOMINIC A.
2000-08-09
This summer, the author was tasked with the development of a design and prototype for a Programming Adapter (PA). This device must interface to a specialized cluster of computers at a US Air Force programming station. The PA is a command/response system capable of recognizing commands from a host Programming Computer (PC) generating a response to these commands according to design requirements. The PA must also route classified serial data between a programming station and any target devices on the PA without compromising the data. In this manner, classified data can pass through the adapter, but when data transfer is complete, the PA can be handled as an unclassified piece of hardware.
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.
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
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. PMID:23526141
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
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.
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.
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. PMID:27409319
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
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
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
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…
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…
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…
76 FR 584 - Glen Canyon Dam Adaptive Management Program Work Group (AMWG)
Federal Register 2010, 2011, 2012, 2013, 2014
2011-01-05
... Bureau of Reclamation Glen Canyon Dam Adaptive Management Program Work Group (AMWG) AGENCY: Bureau of... Management Work Group (AMWG), a technical work group (TWG), a Grand Canyon Monitoring and Research Center... addition, there will be updates from the Charter Ad Hoc Group and a follow up report on the work done...
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.…
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…
ERIC Educational Resources Information Center
Cramer, Kristine M.; Castro-Olivo, Sara
2016-01-01
Student self-reports of resiliency and social-emotional internalizing problems were examined to determine intervention effects of a culturally adapted social and emotional learning (SEL) program. Data were analyzed from 20 culturally and linguistically diverse high school students who participated in a school-based 12-lesson SEL intervention and…
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…
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.
A massively parallel adaptive finite element method with dynamic load balancing
Devine, K.D.; Flaherty, J.E.; Wheat, S.R.; Maccabe, A.B.
1993-12-31
The authors construct massively parallel adaptive finite element methods for the solution of hyperbolic conservation laws. Spatial discretization is performed by a discontinuous Galerkin finite element method using a basis of piecewise Legendre polynomials. Temporal discretization utilizes a Runge-Kutta method. Dissipative fluxes and projection limiting prevent oscillations near solution discontinuities. The resulting method is of high order and may be parallelized efficiently on MIMD computers. They demonstrate parallel efficiency through computations on a 1024-processor nCUBE/2 hypercube. They present results using adaptive p-refinement to reduce the computational cost of the method, and tiling, a dynamic, element-based data migration system that maintains global load balance of the adaptive method by overlapping neighborhoods of processors that each perform local balancing.
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.
Spacecraft Dynamics and Control Program at AFRPL
NASA Technical Reports Server (NTRS)
Das, A.; Slimak, L. K. S.; Schloegel, W. T.
1986-01-01
A number of future DOD and NASA spacecraft such as the space based radar will be not only an order of magnitude larger in dimension than the current spacecraft, but will exhibit extreme structural flexibility with very low structural vibration frequencies. Another class of spacecraft (such as the space defense platforms) will combine large physical size with extremely precise pointing requirement. Such problems require a total departure from the traditional methods of modeling and control system design of spacecraft where structural flexibility is treated as a secondary effect. With these problems in mind, the Air Force Rocket Propulsion Laboratory (AFRPL) initiated research to develop dynamics and control technology so as to enable the future large space structures (LSS). AFRPL's effort in this area can be subdivided into the following three overlapping areas: (1) ground experiments, (2) spacecraft modeling and control, and (3) sensors and actuators. Both the in-house and contractual efforts of the AFRPL in LSS are summarized.
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
Earthquake Rupture Dynamics using Adaptive Mesh Refinement and High-Order Accurate Numerical Methods
NASA Astrophysics Data System (ADS)
Kozdon, J. E.; Wilcox, L.
2013-12-01
Our goal is to develop scalable and adaptive (spatial and temporal) numerical methods for coupled, multiphysics problems using high-order accurate numerical methods. To do so, we are developing an opensource, parallel library known as bfam (available at http://bfam.in). The first application to be developed on top of bfam is an earthquake rupture dynamics solver using high-order discontinuous Galerkin methods and summation-by-parts finite difference methods. In earthquake rupture dynamics, wave propagation in the Earth's crust is coupled to frictional sliding on fault interfaces. This coupling is two-way, required the simultaneous simulation of both processes. The use of laboratory-measured friction parameters requires near-fault resolution that is 4-5 orders of magnitude higher than that needed to resolve the frequencies of interest in the volume. This, along with earlier simulations using a low-order, finite volume based adaptive mesh refinement framework, suggest that adaptive mesh refinement is ideally suited for this problem. The use of high-order methods is motivated by the high level of resolution required off the fault in earlier the low-order finite volume simulations; we believe this need for resolution is a result of the excessive numerical dissipation of low-order methods. In bfam spatial adaptivity is handled using the p4est library and temporal adaptivity will be accomplished through local time stepping. In this presentation we will present the guiding principles behind the library as well as verification of code against the Southern California Earthquake Center dynamic rupture code validation test problems.
Collective Fluctuations in the Dynamics of Adaptation and Other Traveling Waves.
Hallatschek, Oskar; Geyrhofer, Lukas
2016-03-01
The dynamics of adaptation are difficult to predict because it is highly stochastic even in large populations. The uncertainty emerges from random genetic drift arising in a vanguard of particularly fit individuals of the population. Several approaches have been developed to analyze the crucial role of genetic drift on the expected dynamics of adaptation, including the mean fitness of the entire population, or the fate of newly arising beneficial deleterious mutations. However, little is known about how genetic drift causes fluctuations to emerge on the population level, where it becomes palpable as variations in the adaptation speed and the fitness distribution. Yet these phenomena control the decay of genetic diversity and variability in evolution experiments and are key to a truly predictive understanding of evolutionary processes. Here, we show that correlations induced by these emergent fluctuations can be computed at any arbitrary order by a suitable choice of a dynamical constraint. The resulting linear equations exhibit fluctuation-induced terms that amplify short-distance correlations and suppress long-distance ones. These terms, which are in general not small, control the decay of genetic diversity and, for wave-tip dominated ("pulled") waves, lead to anticorrelations between the tip of the wave and the lagging bulk of the population. While it is natural to consider the process of adaptation as a branching random walk in fitness space subject to a constraint (due to finite resources), we show that other traveling wave phenomena in ecology and evolution likewise fall into this class of constrained branching random walks. Our methods, therefore, provide a systematic approach toward analyzing fluctuations in a wide range of population biological processes, such as adaptation, genetic meltdown, species invasions, or epidemics. PMID:26819246
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
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
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
Determining the Energetics of Small β-Sheet Peptides using Adaptive Steered Molecular Dynamics.
Bureau, Hailey R; Hershkovits, Eli; Quirk, Stephen; Hernandez, Rigoberto
2016-04-12
Mechanically driven unfolding is a useful computational tool for extracting the energetics and stretching pathway of peptides. In this work, two representative β-hairpin peptides, chignolin (PDB: 1UAO ) and trpzip1 (PDB: 1LE0 ), were investigated using an adaptive variant of the original steered molecular dynamics method called adaptive steered molecular dynamics (ASMD). The ASMD method makes it possible to perform energetic calculations on increasingly complex biological systems. Although the two peptides are similar in length and have similar secondary structures, their unfolding energetics are quite different. The hydrogen bonding profile and specific residue pair interaction energies provide insight into the differing stabilities of these peptides and reveal which of the pairs provides the most significant stabilization. PMID:26930270
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.
Symmetry-adapted non-equilibrium molecular dynamics of chiral carbon nanotubes under tensile loading
NASA Astrophysics Data System (ADS)
Aghaei, Amin; Dayal, Kaushik
2011-06-01
We report on non-equilibrium molecular dynamics calculations of chiral single-wall carbon nanotubes using the framework of Objective Structures. This enables us to adapt molecular dynamics to the symmetry of chiral nanotubes and efficiently simulate these systems with small unit cells. We outline the method and the adaptation of a conventional thermostat and barostat to this setting. We then apply the method in order to examine the behavior of nanotubes with various chiralities subject to a constant extensional strain rate. We examine the effects of temperature, strain rate, and pre-compression/pre-tension. We find a range of failure mechanisms, including the formation of Stone-Wales defects, the opening of voids, and the motion of atoms out of the cross-section.
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
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
Test application of Bayesian Programming: Adaptive water quality management under uncertainty
NASA Astrophysics Data System (ADS)
Harrison, Kenneth W.
2007-03-01
A new method, Bayesian Programming (BP), developed by Harrison [Harrison KW. Multi-stage decision-making under uncertainty and stochasticity: Bayesian Programming. Adv Water Resour, submitted for publication] is tested on a case study involving optimal adaptive management of a river basin. The case study considers anew the process of permitting pulp mills on the Athabasca River in Alberta, Canada. The problem has characteristics common to many environmental management problems. There is uncertainty in the water quality response to pollutant loadings that will not be completely resolved with monitoring and the resolution of this uncertainty is impeded by the stochastic behavior of the water quality system. A two-stage adaptive management process is optimized with BP. Based on monitoring data collected after implementation of the first-stage decision, the uncertainties are updated prior to the second decision stage using Bayesian analysis. The worth of this two-stage adaptive management approach to this problem and the worth of monitoring are evaluated. Conclusions are drawn on the general practicality of BP for adaptive management. Potential strategies are outlined for extending the BP approach to secure further benefits of adaptive management.
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.
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.
Static and Dynamic Responses of AN Adaptive Optics Ferrofluidic Mirror - Poster Paper
NASA Astrophysics Data System (ADS)
Seaman, A.; Cookson, C. J.; MacPherson, J. B.; Borra, E. F.; Ritcey, A. M.; Asselin, D.; Jerominek, H.; Thibault, S.; Campbell, M. C. W.
2008-01-01
Ferrofluidic mirrors can be used to improve images of structures at the rear of the eye and may be an effective, low cost solution for adaptive optics, perhaps allowing it to become widespread in clinical settings. We use a Hartmann-Shack wavefront reconstruction technique to study the static and dynamic responses of a ferrofluidic mirror. The displacement heights versus the current in the magnetic field actuators of the mirror have been measured, as well as actuator influence functions (including non-linearites). Finally, we also characterized the real-time dynamics of the mirror.
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
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.
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
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.
Stable indirect adaptive switching control for fuzzy dynamical systems based on T-S multiple models
NASA Astrophysics Data System (ADS)
Sofianos, Nikolaos A.; Boutalis, Yiannis S.
2013-08-01
A new indirect adaptive switching fuzzy control method for fuzzy dynamical systems, based on Takagi-Sugeno (T-S) multiple models is proposed in this article. Motivated by the fact that indirect adaptive control techniques suffer from poor transient response, especially when the initialisation of the estimation model is highly inaccurate and the region of uncertainty for the plant parameters is very large, we present a fuzzy control method that utilises the advantages of multiple models strategy. The dynamical system is expressed using the T-S method in order to cope with the nonlinearities. T-S adaptive multiple models of the system to be controlled are constructed using different initial estimations for the parameters while one feedback linearisation controller corresponds to each model according to a specified reference model. The controller to be applied is determined at every time instant by the model which best approximates the plant using a switching rule with a suitable performance index. Lyapunov stability theory is used in order to obtain the adaptive law for the multiple models parameters, ensuring the asymptotic stability of the system while a modification in this law keeps the control input away from singularities. Also, by introducing the next best controller logic, we avoid possible infeasibilities in the control signal. Simulation results are presented, indicating the effectiveness and the advantages of the proposed method.
Molecular dynamics modelling of mechanical properties of polymers for adaptive aerospace structures
NASA Astrophysics Data System (ADS)
Papanikolaou, Michail; Drikakis, Dimitris; Asproulis, Nikolaos
2015-02-01
The features of adaptive structures depend on the properties of the supporting materials. For example, morphing wing structures require wing skin materials, such as rubbers that can withstand the forces imposed by the internal mechanism while maintaining the required aerodynamic properties of the aircraft. In this study, Molecular Dynamics and Minimization simulations are being used to establish well-equilibrated models of Ethylene-Propylene-Diene Monomer (EPDM) elastomer systems and investigate their mechanical properties.
Satellite tracking and Earth dynamics research programs
NASA Technical Reports Server (NTRS)
Pearlman, M. R.
1984-01-01
Following an upgrading program, ranging performance capabilities of a satellite-tracking pulsed laser system were assessed in terms of range accuracy, range noise, data yield, and reliability. With a shorter laser pulse duration (2.5 to 3.0 NSEC) and a new analog pulse processing system, the systematic range errors were reduced to 3 to 5 cm and range noise was reduced to 5 to 16 cm and range noise was reduced to 5 to 15 cm on Starlette and BE-C, and 10 to 18 cm on LAGEOS. Maximum pulse repetition rate was increased to 30 pulses per minute and significant improvement was made in signal to noise ratio by installing a 3 A interference filter and by reducing the range gate window to 200 to 400 nsec. The solution to a problem involving leakage of a fraction of the laser oscillator pulse through the pulse chopper was outlined.
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.
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.
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.
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.
Papaleo, Elena; Riccardi, Laura; Villa, Chiara; Fantucci, Piercarlo; De Gioia, Luca
2006-08-01
Molecular dynamics simulations of representative mesophilic and psycrophilic elastases have been carried out at different temperatures to explore the molecular basis of cold adaptation inside a specific enzymatic family. The molecular dynamics trajectories have been compared and analyzed in terms of secondary structure, molecular flexibility, intramolecular and protein-solvent interactions, unravelling molecular features relevant to rationalize the efficient catalytic activity of psychrophilic elastases at low temperature. The comparative molecular dynamics investigation reveals that modulation of the number of protein-solvent interactions is not the evolutionary strategy followed by the psycrophilic elastase to enhance catalytic activity at low temperature. In addition, flexibility and solvent accessibility of the residues forming the catalytic triad and the specificity pocket are comparable in the cold- and warm-adapted enzymes. Instead, loop regions with different amino acid composition in the two enzymes, and clustered around the active site or the specificity pocket, are characterized by enhanced flexibility in the cold-adapted enzyme. Remarkably, the psycrophilic elastase is characterized by reduced flexibility, when compared to the mesophilic counterpart, in some scattered regions distant from the functional sites, in agreement with hypothesis suggesting that local rigidity in regions far from functional sites can be beneficial for the catalytic activity of psychrophilic enzymes. PMID:16920043
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.
Shuttle/Centaur G-prime composite adapters damage tolerance/repair test program
NASA Technical Reports Server (NTRS)
Sollars, Teresa A.
1987-01-01
The Space Shuttle/Centaur Composite Adapters Damage Tolerance/Repair Test program had as its goals the determination of probable and potentially critical defects or damages on the adapters' strength and stability, as well as the adequacy of repairs on significantly damaged areas and the generation of NDT data for the upgrading of acceptance criteria. Such rational accept/reject criteria and repair methods reduce both engineering liason costs and any unnecessary parts-scrapping. Successful 'damage tolerant' design ensures that degradations of strength and stability due to undetected defects or damage will not be catastrophic.
Path planning for complex terrain navigation via dynamic programming
Kwok, K.S.; Driessen, B.J.
1998-12-31
This work considers the problem of planning optimal paths for a mobile robot traversing complex terrain. In addition to the existing obstacles, locations in the terrain where the slope is too steep for the mobile robot to navigate safely without tipping over become mathematically equivalent to extra obstacles. To solve the optimal path problem, the authors use a dynamic programming approach. The dynamic programming approach utilized herein does not suffer the difficulties associated with spurious local minima that the artificial potential field approaches do. In fact, a globally optimal solution is guaranteed to be found if a feasible solution exists. The method is demonstrated on several complex examples including very complex terrains.
Mitesser, Oliver; Weissel, Norbert; Strohm, Erhard; Poethke, Hans-Joachim
2007-01-01
Background According to the classical model of Macevicz and Oster, annual eusocial insects should show a clear dichotomous "bang-bang" strategy of resource allocation; colony fitness is maximised when a period of pure colony growth (exclusive production of workers) is followed by a single reproductive period characterised by the exclusive production of sexuals. However, in several species graded investment strategies with a simultaneous production of workers and sexuals have been observed. Such deviations from the "bang-bang" strategy are usually interpreted as an adaptive (bet-hedging) response to environmental fluctuations such as variation in season length or food availability. To generate predictions about the optimal investment pattern of insect colonies in fluctuating environments, we slightly modified Macevicz and Oster's classical model of annual colony dynamics and used a dynamic programming approach nested into a recurrence procedure for the solution of the stochastic optimal control problem. Results 1) The optimal switching time between pure colony growth and the exclusive production of sexuals decreases with increasing environmental variance. 2) Yet, for reasonable levels of environmental fluctuations no deviation from the typical bang-bang strategy is predicted. 3) Model calculations for the halictid bee Lasioglossum malachurum reveal that bet-hedging is not likely to be the reason for the graded allocation into sexuals versus workers observed in this species. 4) When environmental variance reaches a critical level our model predicts an abrupt change from dichotomous behaviour to graded allocation strategies, but the transition between colony growth and production of sexuals is not necessarily monotonic. Both, the critical level of environmental variance as well as the characteristic pattern of resource allocation strongly depend on the type of function used to describe environmental fluctuations. Conclusion Up to now bet-hedging as an evolutionary
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
Anderson, Jill T; Geber, Monica A
2010-02-01
In heterogeneous landscapes, divergent selection can favor the evolution of locally adapted ecotypes, especially when interhabitat gene flow is minimal. However, if habitats differ in size or quality, source-sink dynamics can shape evolutionary trajectories. Upland and bottomland forests of the southeastern USA differ in water table depth, light availability, edaphic conditions, and plant community. We conducted a multiyear reciprocal transplant experiment to test whether Elliott's blueberry (Vaccinium elliottii) is locally adapted to these contrasting environments. Additionally, we exposed seedlings and cuttings to prolonged drought and flooding in the greenhouse to assess fitness responses to abiotic stress. Contrary to predictions of local adaptation, V. elliottii families exhibited significantly higher survivorship and growth in upland than in bottomland forests and under drought than flooded conditions, regardless of habitat of origin. Neutral population differentiation was minimal, suggesting widespread interhabitat migration. Population density, reproductive output, and genetic diversity were all significantly greater in uplands than in bottomlands. These disparities likely result in asymmetric gene flow from uplands to bottomlands. Thus, adaptation to a marginal habitat can be constrained by small populations, limited fitness, and immigration from a benign habitat. Our study highlights the importance of demography and genetic diversity in the evolution of local (mal)adaptation. PMID:19703223
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.
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
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.
Adaptive dynamic surface control for a class of MIMO nonlinear systems with actuator failures
NASA Astrophysics Data System (ADS)
Amezquita S., Kendrick; Yan, Lin; Butt, Waseem A.
2013-03-01
In this article, an adaptive dynamic surface control scheme for a class of MIMO nonlinear systems with actuator failures and uncertainties is presented. In the proposed control scheme, the dynamic changes and disturbances induced by actuator failures are detected and isolated by means of radial basis function neural networks, which also compensate system uncertainties that arise from the mismatch between nominal model and real plant. In the presence of unknown actuation functions, the effectiveness of the control scheme is guaranteed by imposing a structural condition on the actuation matrix. Moreover, the singularity problem that arises from the approximation of unknown actuation functions is circumvented, and thus the use parameter projection is avoided. In this work, the nominal plant is transformed into a suitable form via diffeomorphism. Dynamic surface control design technique is used to develop the control laws. The closed-loop signals are proven to be uniformly ultimately bounded through Lyapunov approach, and the output tracking error is shown to be bounded within a residual set which can be made arbitrarily small by appropriately tuning the controller parameters. Finally, the proposed adaptive control scheme effectiveness is verified by simulation of the longitudinal dynamics of a twin otter aircraft undergoing actuator failures.
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
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…
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...
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.
On-line replacement of program modules using AdaPT
NASA Technical Reports Server (NTRS)
Waldrop, Raymond S.; Volz, Richard A.; Smith, Gary W.; Holzbacher-Valero, A. A.; Goldsack, Stephen J.
1992-01-01
One purpose of our research is the investigation of the effectiveness and expressiveness of AdaPT(1), 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 extension provide a good basis for this investigation for several reasons: (1) they include the concept of specific, self-contained program modules which can be manipulated; (2) support for program configuration is included in the language; and (3) 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 systems. The purpose of this investigation is to explore the basic mechanisms to the replacement process. 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. This report will establish an overview of the on-line upgrade problem, and present a taxonomy of the various aspects of the replacement process.
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
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.
Dynamic analysis of spur gears using computer program DANST
NASA Technical Reports Server (NTRS)
Oswald, Fred B.; Lin, Hsiang Hsi; 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.
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
Hirashima, Masaya
2014-01-01
Adaptation of reaching movements to a novel dynamic environment is associated with changes in neuronal activity in the primary motor cortex (M1), suggesting that M1 neurons are part of the internal model. Here, we investigated whether such changes in neuronal activity, resulting from motor adaptation, were also accompanied by changes in human corticospinal excitability, which reflects M1 activity at a macroscopic level. Participants moved a cursor on a display using the right wrist joint from the starting position toward one of eight equally spaced peripheral targets. Motor-evoked potentials (MEPs) were elicited from the wrist muscles by transcranial magnetic stimulation delivered over the left M1 before and after adaptation to a clockwise velocity-dependent force field. We found that the MEP elicited even during the preparatory period exhibited a directional tuning property, and that the preferred direction shifted clockwise after adaptation to the force field. In a subsequent experiment, participants simultaneously adapted an identical wrist movement to two opposing force fields, each of which was associated with unimanual or bimanual contexts, and the MEP during the preparatory period was flexibly modulated, depending on the context. In contrast, such modulation of the MEP was not observed when participants tried to adapt to two opposing force fields that were each associated with a target color. These results suggest that the internal model formed in the M1 is retrieved flexibly even during the preparatory period, and that the MEP could be a very useful probe for evaluating the formation and retrieval of motor memory. PMID:25209281
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
NASA Astrophysics Data System (ADS)
Xiao, Xiong; Zhao, Shengkui; Ha Nguyen, Duc Hoang; Zhong, Xionghu; Jones, Douglas L.; Chng, Eng Siong; Li, Haizhou
2016-01-01
This paper investigates deep neural networks (DNN) based on nonlinear feature mapping and statistical linear feature adaptation approaches for reducing reverberation in speech signals. In the nonlinear feature mapping approach, DNN is trained from parallel clean/distorted speech corpus to map reverberant and noisy speech coefficients (such as log magnitude spectrum) to the underlying clean speech coefficients. The constraint imposed by dynamic features (i.e., the time derivatives of the speech coefficients) are used to enhance the smoothness of predicted coefficient trajectories in two ways. One is to obtain the enhanced speech coefficients with a least square estimation from the coefficients and dynamic features predicted by DNN. The other is to incorporate the constraint of dynamic features directly into the DNN training process using a sequential cost function. In the linear feature adaptation approach, a sparse linear transform, called cross transform, is used to transform multiple frames of speech coefficients to a new feature space. The transform is estimated to maximize the likelihood of the transformed coefficients given a model of clean speech coefficients. Unlike the DNN approach, no parallel corpus is used and no assumption on distortion types is made. The two approaches are evaluated on the REVERB Challenge 2014 tasks. Both speech enhancement and automatic speech recognition (ASR) results show that the DNN-based mappings significantly reduce the reverberation in speech and improve both speech quality and ASR performance. For the speech enhancement task, the proposed dynamic feature constraint help to improve cepstral distance, frequency-weighted segmental signal-to-noise ratio (SNR), and log likelihood ratio metrics while moderately degrades the speech-to-reverberation modulation energy ratio. In addition, the cross transform feature adaptation improves the ASR performance significantly for clean-condition trained acoustic models.
Translation, cultural adaptation and field-testing of the Thinking Healthy Program for Vietnam
2014-01-01
Background Depression and anxiety are prevalent among women in low- and lower-middle income countries who are pregnant or have recently given birth. There is promising evidence that culturally-adapted, evidence-informed, perinatal psycho-educational programs implemented in local communities are effective in reducing mental health problems. The Thinking Healthy Program (THP) has proved effective in Pakistan. The aims were to adapt the THP for rural Vietnam; establish the program’s comprehensibility, acceptability and salience for universal use, and investigate whether administration to small groups of women might be of equivalent effectiveness to administration in home visits to individual women. Methods The THP Handbook and Calendar were made available in English by the program developers and translated into Vietnamese. Cultural adaptation and field-testing were undertaken using WHO guidance. Field-testing of the four sessions of THP Module One was undertaken in weekly sessions with a small group in a rural commune and evaluated using baseline, process and endline surveys. Results The adapted Vietnamese version of the Thinking Healthy Program (THP-V) was found to be understandable, meaningful and relevant to pregnant women, and commune health centre and Women’s Union representatives in a rural district. It was delivered effectively by trained local facilitators. Role-play, brainstorming and small-group discussions to find shared solutions to common problems were appraised as helpful learning opportunities. Conclusions The THP-V is safe and comprehensible, acceptable and salient to pregnant women without mental health problems in rural Vietnam. Delivery in facilitated small groups provided valued opportunities for role-play rehearsal and shared problem solving. Local observers found the content and approach highly relevant to local needs and endorsed the approach as a mental health promotion strategy with potential for integration into local universal maternal
Domain-elongation NMR spectroscopy yields new insights into RNA dynamics and adaptive recognition.
Zhang, Qi; Al-Hashimi, Hashim M
2009-11-01
By simplifying the interpretation of nuclear magnetic resonance spin relaxation and residual dipolar couplings data, recent developments involving the elongation of RNA helices are providing new atomic insights into the dynamical properties that allow RNA structures to change functionally and adaptively. Domain elongation, in concert with spin relaxation measurements, has allowed the detailed characterization of a hierarchical network of local and collective motional modes occurring at nanosecond timescale that mirror the structural rearrangements that take place following adaptive recognition. The combination of domain elongation with residual dipolar coupling measurements has allowed the experimental three-dimensional visualization of very large amplitude rigid-body helix motions in HIV-1 transactivation response element (TAR) that trace out a highly choreographed trajectory in which the helices twist and bend in a correlated manner. The dynamic trajectory allows unbound TAR to sample many of its ligand bound conformations, indicating that adaptive recognition occurs by "conformational selection" rather than "induced fit." These studies suggest that intrinsic flexibility plays essential roles directing RNA conformational changes along specific pathways. PMID:19776156
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.
ERIC Educational Resources Information Center
Karakostas, A.; Demetriadis, S.
2011-01-01
Research on computer-supported collaborative learning (CSCL) has strongly emphasized the value of providing student support of either fixed (e.g. collaboration scripts) or dynamic form (e.g. adaptive supportive interventions). Currently, however, there is not sufficient evidence corroborating the potential of adaptive support methods to improve…
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.
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
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
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
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
NASA Astrophysics Data System (ADS)
Wang, Chenliang; Lin, Yan
2015-04-01
In this paper, an adaptive dynamic surface control scheme is proposed for a class of multi-input multi-output (MIMO) nonlinear time-varying systems. By fusing a bound estimation approach, a smooth function and a time-varying matrix factorisation, the obstacle caused by unknown time-varying parameters is circumvented. The proposed scheme is free of the problem of explosion of complexity and needs only one updated parameter at each design step. Moreover, all tracking errors can converge to predefined arbitrarily small residual sets with a prescribed convergence rate and maximum overshoot. Such features result in a simple adaptive controller which can be easily implemented in applications with less computational burden and satisfactory tracking performance. Simulation results are presented to illustrate the effectiveness of the proposed scheme.
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.
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
Xing, Dajun; Yeh, Chun-I; Gordon, James; Shapley, Robert M
2014-01-21
Darkness and brightness are very different perceptually. To understand the neural basis for the visual difference, we studied the dynamical states of populations of neurons in macaque primary visual cortex when a spatially uniform area (8° × 8°) of the visual field alternated between black and white. Darkness evoked sustained nerve-impulse spiking in primary visual cortex neurons, but bright stimuli evoked only a transient response. A peak in the local field potential (LFP) γ band (30-80 Hz) occurred during darkness; white-induced LFP fluctuations were of lower amplitude, peaking at 25 Hz. However, the sustained response to white in the evoked LFP was larger than for black. Together with the results on spiking, the LFP results imply that, throughout the stimulus period, bright fields evoked strong net sustained inhibition. Such cortical brightness adaptation can explain many perceptual phenomena: interocular speeding up of dark adaptation, tonic interocular suppression, and interocular masking. PMID:24398523
An adaptive model order reduction by proper snapshot selection for nonlinear dynamical problems
NASA Astrophysics Data System (ADS)
Nigro, P. S. B.; Anndif, M.; Teixeira, Y.; Pimenta, P. M.; Wriggers, P.
2016-04-01
Model Order Reduction (MOR) methods are employed in many fields of Engineering in order to reduce the processing time of complex computational simulations. A usual approach to achieve this is the application of Galerkin projection to generate representative subspaces (reduced spaces). However, when strong nonlinearities in a dynamical system are present and this technique is employed several times along the simulation, it can be very inefficient. This work proposes a new adaptive strategy, which ensures low computational cost and small error to deal with this problem. This work also presents a new method to select snapshots named Proper Snapshot Selection (PSS). The objective of the PSS is to obtain a good balance between accuracy and computational cost by improving the adaptive strategy through a better snapshot selection in real time (online analysis). With this method, it is possible a substantial reduction of the subspace, keeping the quality of the model without the use of the Proper Orthogonal Decomposition (POD).
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
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
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.
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.
Dynamic optical aberration correction with adaptive coded apertures techniques in conformal imaging
NASA Astrophysics Data System (ADS)
Li, Yan; Hu, Bin; Zhang, Pengbin; Zhang, Binglong
2015-02-01
Conformal imaging systems are confronted with dynamic aberration in optical design processing. In classical optical designs, for combination high requirements of field of view, optical speed, environmental adaption and imaging quality, further enhancements can be achieved only by the introduction of increased complexity of aberration corrector. In recent years of computational imaging, the adaptive coded apertures techniques which has several potential advantages over more traditional optical systems is particularly suitable for military infrared imaging systems. The merits of this new concept include low mass, volume and moments of inertia, potentially lower costs, graceful failure modes, steerable fields of regard with no macroscopic moving parts. Example application for conformal imaging system design where the elements of a set of binary coded aperture masks are applied are optimization designed is presented in this paper, simulation results show that the optical performance is closely related to the mask design and the reconstruction algorithm optimization. As a dynamic aberration corrector, a binary-amplitude mask located at the aperture stop is optimized to mitigate dynamic optical aberrations when the field of regard changes and allow sufficient information to be recorded by the detector for the recovery of a sharp image using digital image restoration in conformal optical system.
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
Blended particle methods with adaptive subspaces for filtering turbulent dynamical systems
NASA Astrophysics Data System (ADS)
Qi, Di; Majda, Andrew J.
2015-04-01
It is a major challenge throughout science and engineering to improve uncertain model predictions by utilizing noisy data sets from nature. Hybrid methods combining the advantages of traditional particle filters and the Kalman filter offer a promising direction for filtering or data assimilation in high dimensional turbulent dynamical systems. In this paper, blended particle filtering methods that exploit the physical structure of turbulent dynamical systems are developed. Non-Gaussian features of the dynamical system are captured adaptively in an evolving-in-time low dimensional subspace through particle methods, while at the same time statistics in the remaining portion of the phase space are amended by conditional Gaussian mixtures interacting with the particles. The importance of both using the adaptively evolving subspace and introducing conditional Gaussian statistics in the orthogonal part is illustrated here by simple examples. For practical implementation of the algorithms, finding the most probable distributions that characterize the statistics in the phase space as well as effective resampling strategies is discussed to handle realizability and stability issues. To test the performance of the blended algorithms, the forty dimensional Lorenz 96 system is utilized with a five dimensional subspace to run particles. The filters are tested extensively in various turbulent regimes with distinct statistics and with changing observation time frequency and both dense and sparse spatial observations. In real applications perfect dynamical models are always inaccessible considering the complexities in both modeling and computation of high dimensional turbulent system. The effects of model errors from imperfect modeling of the systems are also checked for these methods. The blended methods show uniformly high skill in both capturing non-Gaussian statistics and achieving accurate filtering results in various dynamical regimes with and without model errors.
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
Localized dynamic kinetic-energy-based models for stochastic coherent adaptive large eddy simulation
NASA Astrophysics Data System (ADS)
De Stefano, Giuliano; Vasilyev, Oleg V.; Goldstein, Daniel E.
2008-04-01
Stochastic coherent adaptive large eddy simulation (SCALES) is an extension of the large eddy simulation approach in which a wavelet filter-based dynamic grid adaptation strategy is employed to solve for the most "energetic" coherent structures in a turbulent field while modeling the effect of the less energetic background flow. In order to take full advantage of the ability of the method in simulating complex flows, the use of localized subgrid-scale models is required. In this paper, new local dynamic one-equation subgrid-scale models based on both eddy-viscosity and non-eddy-viscosity assumptions are proposed for SCALES. The models involve the definition of an additional field variable that represents the kinetic energy associated with the unresolved motions. This way, the energy transfer between resolved and residual flow structures is explicitly taken into account by the modeling procedure without an equilibrium assumption, as in the classical Smagorinsky approach. The wavelet-filtered incompressible Navier-Stokes equations for the velocity field, along with the additional evolution equation for the subgrid-scale kinetic energy variable, are numerically solved by means of the dynamically adaptive wavelet collocation solver. The proposed models are tested for freely decaying homogeneous turbulence at Reλ=72. It is shown that the SCALES results, obtained with less than 0.5% of the total nonadaptive computational nodes, closely match reference data from direct numerical simulation. In contrast to classical large eddy simulation, where the energetic small scales are poorly simulated, the agreement holds not only in terms of global statistical quantities but also in terms of spectral distribution of energy and, more importantly, enstrophy all the way down to the dissipative scales.
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.
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.
Adaptive dynamic load-balancing with irregular domain decomposition for particle simulations
NASA Astrophysics Data System (ADS)
Begau, Christoph; Sutmann, Godehard
2015-05-01
We present a flexible and fully adaptive dynamic load-balancing scheme, which is designed for particle simulations of three-dimensional systems with short ranged interactions. The method is based on domain decomposition with non-orthogonal non-convex domains, which are constructed based on a local repartitioning of computational work between neighbouring processors. Domains are dynamically adjusted in a flexible way under the condition that the original topology is not changed, i.e. neighbour relations between domains are retained, which guarantees a fixed communication pattern for each domain during a simulation. Extensions of this scheme are discussed and illustrated with examples, which generalise the communication patterns and do not fully restrict data exchange to direct neighbours. The proposed method relies on a linked cell algorithm, which makes it compatible with existing implementations in particle codes and does not modify the underlying algorithm for calculating the forces between particles. The method has been implemented into the molecular dynamics community code IMD and performance has been measured for various molecular dynamics simulations of systems representing realistic problems from materials science. It is found that the method proves to balance the work between processors in simulations with strongly inhomogeneous and dynamically changing particle distributions, which results in a significant increase of the efficiency of the parallel code compared both to unbalanced simulations and conventional load-balancing strategies.
An adaptive three-dimensional RHT-splines formulation in linear elasto-statics and elasto-dynamics
NASA Astrophysics Data System (ADS)
Nguyen-Thanh, N.; Muthu, J.; Zhuang, X.; Rabczuk, T.
2014-02-01
An adaptive three-dimensional isogeometric formulation based on rational splines over hierarchical T-meshes (RHT-splines) for problems in elasto-statics and elasto-dynamics is presented. RHT-splines avoid some short-comings of NURBS-based formulations; in particular they allow for adaptive h-refinement with ease. In order to drive the adaptive refinement, we present a recovery-based error estimator for RHT-splines. The method is applied to several problems in elasto-statics and elasto-dynamics including three-dimensional modeling of thin structures. The results are compared to analytical solutions and results of NURBS based isogeometric formulations.
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.
Free energy landscapes of short peptide chains using adaptively biased molecular dynamics
NASA Astrophysics Data System (ADS)
Karpusenka, Vadzim; Babin, Volodymyr; Roland, Christopher; Sagui, Celeste
2009-03-01
We present the results of a computational study of the free energy landscapes of short polypeptide chains, as a function of several reaction coordinates meant to distinguish between several known types of helices. The free energy landscapes were calculated using the recently developed adaptively biased molecular dynamics method followed up with equilibrium ``umbrella correction'' runs. Specific polypeptides investigated include small chains of pure and mixed alanine, glutamate, leucine, lysine and methionine (all amino acids with strong helix-forming propensities), as well as glycine, proline(having a low helix forming propensities), tyrosine, serine and arginine. Our results are consistent with the existing experimental and other theoretical evidence.
Ali, Hussnain; Hazrati, Oldooz; Tobey, Emily A.; Hansen, John H. L
2014-01-01
The aim of this study is to investigate the effect of Adaptive Dynamic Range Optimization (ADRO) on speech identification for cochlear implant (CI) users in adverse listening conditions. In this study, anechoic quiet, noisy, reverberant, noisy reverberant, and reverberant noisy conditions are evaluated. Two scenarios are considered when modeling the combined effects of reverberation and noise: (a) noise is added to the reverberant speech, and (b) noisy speech is reverberated. CI users were tested in different listening environments using IEEE sentences presented at 65 dB sound pressure level. No significant effect of ADRO processing on speech intelligibility was observed. PMID:25190428
Ali, Hussnain; Hazrati, Oldooz; Tobey, Emily A; Hansen, John H L
2014-09-01
The aim of this study is to investigate the effect of Adaptive Dynamic Range Optimization (ADRO) on speech identification for cochlear implant (CI) users in adverse listening conditions. In this study, anechoic quiet, noisy, reverberant, noisy reverberant, and reverberant noisy conditions are evaluated. Two scenarios are considered when modeling the combined effects of reverberation and noise: (a) noise is added to the reverberant speech, and (b) noisy speech is reverberated. CI users were tested in different listening environments using IEEE sentences presented at 65 dB sound pressure level. No significant effect of ADRO processing on speech intelligibility was observed. PMID:25190428
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.
ERIC Educational Resources Information Center
Hopson, Laura M.; Holleran Steiker, Lori K.
2010-01-01
Although there is a strong evidence base for effective substance abuse prevention programs for youths, there is a need to facilitate the implementation and evaluation of these programs in real-world settings. This study evaluates the effectiveness of adapted versions of an evidence-based prevention program, keepin' it REAL (kiR), with alternative…
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.
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).
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.
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.
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
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.
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
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
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
Dynamics of the adaptive natural gradient descent method for soft committee machines
NASA Astrophysics Data System (ADS)
Inoue, Masato; Park, Hyeyoung; Okada, Masato
2004-05-01
Adaptive natural gradient descent (ANGD) method realizes natural gradient descent (NGD) without needing to know the input distribution of learning data and reduces the calculation cost from a cubic order to a square order. However, no performance analysis of ANGD has been done. We have developed a statistical-mechanical theory of the simplified version of ANGD dynamics for soft committee machines in on-line learning; this method provides deterministic learning dynamics expressed through a few order parameters, even though ANGD intrinsically holds a large approximated Fisher information matrix. Numerical results obtained using this theory were consistent with those of a simulation, with respect not only to the learning curve but also to the learning failure. Utilizing this method, we numerically evaluated ANGD efficiency and found that ANGD generally performs as well as NGD. We also revealed the key condition affecting the learning plateau in ANGD.
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.
PSO-based multiobjective optimization with dynamic population size and adaptive local archives.
Leong, Wen-Fung; Yen, Gary G
2008-10-01
Recently, various multiobjective particle swarm optimization (MOPSO) algorithms have been developed to efficiently and effectively solve multiobjective optimization problems. However, the existing MOPSO designs generally adopt a notion to "estimate" a fixed population size sufficiently to explore the search space without incurring excessive computational complexity. To address the issue, this paper proposes the integration of a dynamic population strategy within the multiple-swarm MOPSO. The proposed algorithm is named dynamic population multiple-swarm MOPSO. An additional feature, adaptive local archives, is designed to improve the diversity within each swarm. Performance metrics and benchmark test functions are used to examine the performance of the proposed algorithm compared with that of five selected MOPSOs and two selected multiobjective evolutionary algorithms. In addition, the computational cost of the proposed algorithm is quantified and compared with that of the selected MOPSOs. The proposed algorithm shows competitive results with improved diversity and convergence and demands less computational cost. PMID:18784011
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
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.
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.
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.
Adaptation to shape switching by component selection in a constitutional dynamic system.
Ulrich, Sébastien; Lehn, Jean-Marie
2009-04-22
Molecules having different accessible shape states, which can be addressed in an effector-controlled manner, may be termed morphological switches. A dynamic covalent system can undergo adaptation to each state of a two-state morphological switch by generation of an optimal constitution through component selection. We have studied such a component selection in the dynamic covalent constituents generated by metal cation-induced shape switching of a core component between two states of W and U shape, characterized by both different geometries and different coordination features. The system performs shape-dependent self-sorting of metal ions and components. The origin of the selectivity was investigated through competition experiments, in solution and by analysis of solid state structures, which reveal the role of the molecular shape in the formation of a particular self-assembled architecture. The coordination features of each state as well as phase change also play an important role, in addition to the shape plasticity, in steering the covalent dynamic system toward the formation of a given entity by the selection of the most appropriate components. Different examples are described which show that the morphological switching of one component of a given self-assembled entity can lead to the exchange of the complementary one, which is no longer the best partner, for a new partner, able to form a more stable new assembly. Thus, the constitutional evolution of these dynamic systems is steered by the shape of a given state via both its geometry and its coordination features toward metal ions, leading to incorporation/decorporation of the most appropriate components. The controlled interconversion of the shape states of the morphological switches, induced by addition/removal of metal ions, results in a constitutional adaptation behavior through inversion of the selection preferences. PMID:19206535
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…
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
NASA Technical Reports Server (NTRS)
Nguyen, Nhan
2013-01-01
This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.
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.
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
Liu, Zongcheng; Dong, Xinmin; Xue, Jianping; Li, Hongbo; Chen, Yong
2016-09-01
This brief addresses the adaptive control problem for a class of pure-feedback systems with nonaffine functions possibly being nondifferentiable. Without using the mean value theorem, the difficulty of the control design for pure-feedback systems is overcome by modeling the nonaffine functions appropriately. With the help of neural network approximators, an adaptive neural controller is developed by combining the dynamic surface control (DSC) and minimal learning parameter (MLP) techniques. The key features of our approach are that, first, the restrictive assumptions on the partial derivative of nonaffine functions are removed, second, the DSC technique is used to avoid "the explosion of complexity" in the backstepping design, and the number of adaptive parameters is reduced significantly using the MLP technique, third, smooth robust compensators are employed to circumvent the influences of approximation errors and disturbances. Furthermore, it is proved that all the signals in the closed-loop system are semiglobal uniformly ultimately bounded. Finally, the simulation results are provided to demonstrate the effectiveness of the designed method. PMID:26277010
NASA Astrophysics Data System (ADS)
Lenski, Richard E.; Travisano, Michael
1994-07-01
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.
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.
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
Moulin, Jean-Paul
2006-03-01
Living systems are capable to have appropriate responses to unpredictable environment. This kind of self-organization seems to operate as a self-programming machine, i.e. an organization able to modify itself. Until now the models of self-organization of living beings proposed are functions solutions of differential systems or transition functions of automata. These functions are fixed and these models are therefore unable to modify their organization. On the other hand, computer science propose a lot of models having the properties of adaptive systems of living beings, but all these models depend on the comparison between a goal and the results and ingenious choices of parameters by programmers, whereas there are no programmer's intention nor choice in the living systems. From two best known examples of adaptive systems of living beings, nervous system and immune system that have in common that the external signals modify the rewriting of their organization and therefore work as self-organizing machines, we devised machines with a finite set of inputs, based upon a recurrence, are able to rewrite their organization (Self-programming machines or m(sp)) whenever external conditions vary and have striking properties of adaptation. M(sp) have similar properties whatever the operation defining the recurrence maybe. These results bring us to make the following statement: adaptive properties of living systems can be explained by their ability to rewrite their organization whenever external conditions vary under the only assumption that the rewriting mechanism be a deterministic constant recurrence in a finite state set. PMID:16545754
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.
An algorithm for the solution of dynamic linear programs
NASA Technical Reports Server (NTRS)
Psiaki, Mark L.
1989-01-01
The algorithm's objective is to efficiently solve Dynamic Linear Programs (DLP) by taking advantage of their special staircase structure. This algorithm constitutes a stepping stone to an improved algorithm for solving Dynamic Quadratic Programs, which, in turn, would make the nonlinear programming method of Successive Quadratic Programs more practical for solving trajectory optimization problems. The ultimate goal is to being trajectory optimization solution speeds into the realm of real-time control. The algorithm exploits the staircase nature of the large constraint matrix of the equality-constrained DLPs encountered when solving inequality-constrained DLPs by an active set approach. A numerically-stable, staircase QL factorization of the staircase constraint matrix is carried out starting from its last rows and columns. The resulting recursion is like the time-varying Riccati equation from multi-stage LQR theory. The resulting factorization increases the efficiency of all of the typical LP solution operations over that of a dense matrix LP code. At the same time numerical stability is ensured. The algorithm also takes advantage of dynamic programming ideas about the cost-to-go by relaxing active pseudo constraints in a backwards sweeping process. This further decreases the cost per update of the LP rank-1 updating procedure, although it may result in more changes of the active set that if pseudo constraints were relaxed in a non-stagewise fashion. The usual stability of closed-loop Linear/Quadratic optimally-controlled systems, if it carries over to strictly linear cost functions, implies that the saving due to reduced factor update effort may outweigh the cost of an increased number of updates. An aerospace example is presented in which a ground-to-ground rocket's distance is maximized. This example demonstrates the applicability of this class of algorithms to aerospace guidance. It also sheds light on the efficacy of the proposed pseudo constraint relaxation
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
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.
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
Brunel, L; Brun, A; Snabre, P; Cipelletti, L
2007-11-12
We describe an extension of multi-speckle diffusing wave spectroscopy adapted to follow the non-stationary microscopic dynamics in drying films and coatings in a very reactive way and with a high dynamic range. We call this technique "Adaptive Speckle Imaging Interferometry". We introduce an efficient tool, the inter-image distance, to evaluate the speckle dynamics, and the concept of "speckle rate" (SR, in Hz) to quantify this dynamics. The adaptive algorithm plots a simple kinetics, the time evolution of the SR, providing a non-invasive characterization of drying phenomena. A new commercial instrument, called HORUS(R), based on ASII and specialized in the analysis of film formation and drying processes is presented. PMID:19550809
NASA Astrophysics Data System (ADS)
Asif, Muhammad; Junaid Khan, Muhammad; Cai, Ning
2014-05-01
In this paper, novel adaptive sliding mode dynamic controller with integrator in the loop is proposed for nonholonomic wheeled mobile robot (WMR). The modified kinematics controller is used to generate kinematics velocities of WMR which are subsequently used as the input to adaptive dynamic controller. Actuator dynamics are also derived to generate actuator voltage of WMR through torque and velocity vectors. Stability of both kinematics and dynamic controller is presented using Lyapunov stability analysis. The proposed scheme is verified and validated using computer simulations for tracking the desired trajectory of WMR. The performance of proposed scheme is compared with standard backstepping kinematics controller and classical sliding mode control. In addition, the performance is further compared with standard backstepping kinematics controller with adaptive sliding mode controller without integrator. It is shown that the proposed scheme exhibits zero steady state error, fast error convergence and robustness in the presence of continuous disturbances and uncertainties.
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. PMID:25069127
Khezri, Mahdi; Firoozabadi, Mohammad; Sharafat, Ahmad Reza
2015-11-01
In this study, we proposed a new adaptive method for fusing multiple emotional modalities to improve the performance of the emotion recognition system. Three-channel forehead biosignals along with peripheral physiological measurements (blood volume pressure, skin conductance, and interbeat intervals) were utilized as emotional modalities. Six basic emotions, i.e., anger, sadness, fear, disgust, happiness, and surprise were elicited by displaying preselected video clips for each of the 25 participants in the experiment; the physiological signals were collected simultaneously. In our multimodal emotion recognition system, recorded signals with the formation of several classification units identified the emotions independently. Then the results were fused using the adaptive weighted linear model to produce the final result. Each classification unit is assigned a weight that is determined dynamically by considering the performance of the units during the testing phase and the training phase results. This dynamic weighting scheme enables the emotion recognition system to adapt itself to each new user. The results showed that the suggested method outperformed conventional fusion of the features and classification units using the majority voting method. In addition, a considerable improvement, compared to the systems that used the static weighting schemes for fusing classification units, was also shown. Using support vector machine (SVM) and k-nearest neighbors (KNN) classifiers, the overall classification accuracies of 84.7% and 80% were obtained in identifying the emotions, respectively. In addition, applying the forehead or physiological signals in the proposed scheme indicates that designing a reliable emotion recognition system is feasible without the need for additional emotional modalities. PMID:26253158
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.
Kersting, Anna R.; Bornberg-Bauer, Erich; Moore, Andrew D.; Grath, Sonja
2012-01-01
Plant genomes are generally very large, mostly paleopolyploid, and have numerous gene duplicates and complex genomic features such as repeats and transposable elements. Many of these features have been hypothesized to enable plants, which cannot easily escape environmental challenges, to rapidly adapt. Another mechanism, which has recently been well described as a major facilitator of rapid adaptation in bacteria, animals, and fungi but not yet for plants, is modular rearrangement of protein-coding genes. Due to the high precision of profile-based methods, rearrangements can be well captured at the protein level by characterizing the emergence, loss, and rearrangements of protein domains, their structural, functional, and evolutionary building blocks. Here, we study the dynamics of domain rearrangements and explore their adaptive benefit in 27 plant and 3 algal genomes. We use a phylogenomic approach by which we can explain the formation of 88% of all arrangements by single-step events, such as fusion, fission, and terminal loss of domains. We find many domains are lost along every lineage, but at least 500 domains are novel, that is, they are unique to green plants and emerged more or less recently. These novel domains duplicate and rearrange more readily within their genomes than ancient domains and are overproportionally involved in stress response and developmental innovations. Novel domains more often affect regulatory proteins and show a higher degree of structural disorder than ancient domains. Whereas a relatively large and well-conserved core set of single-domain proteins exists, long multi-domain arrangements tend to be species-specific. We find that duplicated genes are more often involved in rearrangements. Although fission events typically impact metabolic proteins, fusion events often create new signaling proteins essential for environmental sensing. Taken together, the high volatility of single domains and complex arrangements in plant genomes
Kersting, Anna R; Bornberg-Bauer, Erich; Moore, Andrew D; Grath, Sonja
2012-01-01
Plant genomes are generally very large, mostly paleopolyploid, and have numerous gene duplicates and complex genomic features such as repeats and transposable elements. Many of these features have been hypothesized to enable plants, which cannot easily escape environmental challenges, to rapidly adapt. Another mechanism, which has recently been well described as a major facilitator of rapid adaptation in bacteria, animals, and fungi but not yet for plants, is modular rearrangement of protein-coding genes. Due to the high precision of profile-based methods, rearrangements can be well captured at the protein level by characterizing the emergence, loss, and rearrangements of protein domains, their structural, functional, and evolutionary building blocks. Here, we study the dynamics of domain rearrangements and explore their adaptive benefit in 27 plant and 3 algal genomes. We use a phylogenomic approach by which we can explain the formation of 88% of all arrangements by single-step events, such as fusion, fission, and terminal loss of domains. We find many domains are lost along every lineage, but at least 500 domains are novel, that is, they are unique to green plants and emerged more or less recently. These novel domains duplicate and rearrange more readily within their genomes than ancient domains and are overproportionally involved in stress response and developmental innovations. Novel domains more often affect regulatory proteins and show a higher degree of structural disorder than ancient domains. Whereas a relatively large and well-conserved core set of single-domain proteins exists, long multi-domain arrangements tend to be species-specific. We find that duplicated genes are more often involved in rearrangements. Although fission events typically impact metabolic proteins, fusion events often create new signaling proteins essential for environmental sensing. Taken together, the high volatility of single domains and complex arrangements in plant genomes
NASA Astrophysics Data System (ADS)
Herfort, L.; Seaton, C. M.; Wilkin, M.; Baptista, A. M.; Roman, B.; Preston, C. M.; Scholin, C. A.; Melançon, C.; Simon, H. M.
2013-12-01
An autonomous microbial sampling device was integrated with a long-term (endurance) environmental sensor system to investigate variation in microbial composition and activities related to complex estuarine dynamics. This integration was a part of ongoing efforts in the Center for Coastal Margin Observation and Prediction (CMOP) to study estuarine carbon and nitrogen cycling using an observation and prediction system (SATURN, http://www.stccmop.org/saturn) as foundational infrastructure. The two endurance stations fitted with physical and biogeochemical sensors that were used in this study are located in the SATURN observation network. The microbial sampler is the Environmental Sample Processor (ESP), a commercially available electromechanical/fluidic system designed for automated collection, preservation and in situ analyses of marine water samples. The primary goal of the integration was to demonstrate that the ESP, developed for sampling of pelagic oceanic environments, could be successfully deployed for autonomous sample acquisition in the highly dynamic and turbid Columbia River estuary. The ability of the ESP to collect material at both pre-determined times and automatically in response to local conditions was tested. Pre-designated samples were acquired at specific times to capture variability in the tidal cycle. Autonomous, adaptive sampling was triggered when conditions associated with specific water masses were detected in real-time by the SATURN station's sensors and then communicated to the ESP via the station computer to initiate sample collection. Triggering criteria were based on our understanding of estuary dynamics, as provided by the analysis of extensive archives of high-resolution, long-term SATURN observations and simulations. In this manner, we used the ESP to selectively sample various microbial consortia in the estuary to facilitate the study of ephemeral microbial-driven processes. For example, during the summer of 2013 the adaptive sampling
2015-05-01
This final rule amends Department of Veterans Affairs (VA) regulations to establish a new program to provide grants to eligible entities to provide adaptive sports activities to disabled veterans and disabled members of the Armed Forces. This rulemaking is necessary to implement a change in the law that authorizes VA to make grants to entities other than the United States Olympic Committee for adaptive sports programs. It establishes procedures for evaluating grant applications under this grant program, and otherwise administering the grant program. This rule implements section 5 of the VA Expiring Authorities Extension Act of 2013. PMID:25985479
2014-07-01
This interim final rule amends Department of Veterans Affairs (VA) regulations to establish a new program to provide grants to eligible entities to provide adaptive sports activities to disabled veterans and disabled members of the Armed Forces. This rulemaking is necessary to implement a change in the law that authorizes VA to make grants to entities other than the United States Olympic Committee for adaptive sports programs. It establishes procedures for evaluating grant applications under this grant program, and otherwise administering the grant program. This rule implements section 5 of the VA Expiring Authorities Extension Act of 2013. PMID:25016618
Brown, M.A.; White, D.L.
1992-12-01
This study continues the series of evaluations of the Bonneville Power Administration's long-term Residential Weatherization Program (RWP) by examining the energy saved by its 1988 and 1989 participants. The sample of participants for this study was drawn from 10 utilities covering the region's three climate zones. Six of these utilities were included in the 1988 RWP evaluation, and eight of them were included in the 1989 RWP evaluation. This study analyzes data on 356 participating households in 1988, 433 participants in 1989, and a comparison group of 1170 nonparticipants in 1988 and 1466 in 1989. Previous evaluations of Bonneville's earlier weatherization programs provide an historic context for analyzing program dynamics.
Implementing efficient dynamic formal verification methods for MPI programs.
Vakkalanka, S.; DeLisi, M.; Gopalakrishnan, G.; Kirby, R. M.; Thakur, R.; Gropp, W.; Mathematics and Computer Science; Univ. of Utah; Univ. of Illinois
2008-01-01
We examine the problem of formally verifying MPI programs for safety properties through an efficient dynamic (runtime) method in which the processes of a given MPI program are executed under the control of an interleaving scheduler. To ensure full coverage for given input test data, the algorithm must take into consideration MPI's out-of-order completion semantics. The algorithm must also ensure that nondeterministic constructs (e.g., MPI wildcard receive matches) are executed in all possible ways. Our new algorithm rewrites wildcard receives to specific receives, one for each sender that can potentially match with the receive. It then recursively explores each case of the specific receives. The list of potential senders matching a receive is determined through a runtime algorithm that exploits MPI's operation ordering semantics. Our verification tool ISP that incorporates this algorithm efficiently verifies several programs and finds bugs missed by existing informal verification tools.
The Glen Canyon Dam adaptive management program: progress and immediate challenges
Hamill, John F.; Melis, Theodore S.
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
Calculation of the exchange ratio for the Adaptive Maneuvering Logic program
NASA Technical Reports Server (NTRS)
Neuman, F.; Erzberger, H.
1985-01-01
Improvements were made to the Adaptive Maneuvering Logic (AML) computer program, a computer-generated, air-to-air combat opponent. The primary improvement was incorporating a measure of performance, the exchange ratio, defined as the statistical measure of number of enemy kills divided by number of friendly losses. This measure was used to test a new modification of the AML's combat tactics. When the new version of the AML competed against the old version, the new version won with an exchange ratio of 1.4.
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
Escoffery, Cam; Wilkerson, Corinthia; Bell, Rashida; Flowers, Lisa
2014-01-01
Background From 1999 through 2009, African American women in the United States had the second highest incidence rates of cervical cancer and were more likely to die from cervical cancer than women of other races. Con Amor Aprendemos (CAA) is an intervention created to educate the Latino community to reduce their risk for cervical cancer and diseases related to human papilloma virus (HPV). CAA was adapted to With Love We Learn (WLWL) to prevent cervical cancer and HPV in African American communities. Community Context Health ministries of 2 churches in the Atlanta area partnered with the Spirit Foundation Inc to adapt CAA to WLWL by tailoring the curriculum to the African American faith-based community. Methods The National Cancer Institute’s Research to Reality (R2R) mentorship program pair collaborated with program staff on an adaptation summary form, a tool to document and assist with adapting the program curriculum with fidelity. Trainers, faith leaders, and participants adapted the program in 4 phases: 1) review of the CAA curriculum, 2) a focus group discussion to determine changes for the WLWL curriculum, 3) train-the-trainer sessions on program delivery, and 4) a pilot intervention and follow-up focus group to evaluate the new curriculum. Outcomes The CAA/WLWL curriculum was adapted and piloted in a faith-based setting. Adaptations to the CAA program included pictures, games, statistics on cervical cancer, dialogues, and delivery of curriculum. Interpretation Community engagement in the adaptation of WLWL through various methods was critical to tailoring an evidence-based program to a new population and setting. PMID:24762531
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
Molecular views of damaged DNA: Adaptation of the Program DUPLEX to parallel architectures
Hingerty, B.E.; Crawford, O.H.; Broyde, S.; Wagner, R.A.
1994-09-01
The nucleic acids molecular mechanics program DUPLEX has been designed with useful features for surveying the potential energy surface of polynucleotides, especially ones that are modified by polycyclic aromatic carcinogens. The program features helpful strategies for addressing the multiple minimum problem: (1) the reduced variable domain of torsion angle space; (2) search strategies that emphasize large scale searches for smaller subunits, followed by building to larger units by a variety of strategies; (3) the use of penalty functions to aid the minimizer in locating selected structural types in first stage minimizations; penalty functions are released in terminal minimizations to yield final unrestrained minimum energy conformations. Predictive capability is illustrated by DNA modified by activated benzo[a]pyrenes. The first stage of adaptation to parallel computers is described.
Clute, Rose
2015-01-01
A successful worksite diabetes prevention program, SugarWatch,was adapted for a seriously mentally ill patient population in a partial hospitalization program in Hawai‘i. A feasibility study was implemented using an intervention with 3 components:SugarWatch curriculum, structured physical activity,and Create a Plate lunch. Twenty participants completed the three month intervention. Only systolic blood pressure showed statistically significant improvement. However, trends in improvement were also seen with diastolic blood pressure and total cholesterol. Despite minimal improvement in physiological measures, the project changed practice in the setting to align with the 2004 American Diabetes Association and American Psychiatric Association Guidelines for the prevention of metabolic syndrome and better management of patients taking second generation antipsychotic medications. PMID:25821649
Zintzsch, I; Seidel, H; Lantzsch, C; Lantzsch, M
1979-01-01
The dynamic response of the adaptive closed-loop control system hypothalamus-anterior pituitary-adrenal cortex after application of short-time disturb pulses were examined experimentally in the pig. Blood sampling was performed biologically non-reactive by chronically implanted vascular catheters in the upper vena cava. A circadian biphase periodical dynamics characterizes the distrubance response of the adaptive control system, respectively, its direct and indirect parameters. After distrubance variables induced initial excess the plasma corticosteriods undershoot the basic level over a long period. Conversely, the dynamics of the eosinophils is determined through an initial eosinopenic phase and a subsequent typical overshoot. Periodical dynamic is absent in the steady state. The controller of the adaptive system does not show any spontaneous activity in the steady state without stress. The absence of an endogenic periodicity of the dependent parameters likewise gives evidence of an active oscillator. On the other hand, the controlling unit of the adaptive system constitutes a control response of circadian periodicty after activation by disturbance variables in pulse shape. The high damping of the control system terminates the transient state within 24 hours, and the corticosteriods and the eosinophils reach the steady state level. This control quality of the adaptive control system gains a high importance in the origination of the spontaneous circadian periodicity by corticosteriods and eosinophils and for the biological compensation of exogenous distrubance variables. PMID:233184
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. PMID:22106143
Cultural adaptation of the Focus on Kids program for college students in China.
Li, Xiaoming; Stanton, Bonita; Wang, Bo; Mao, Rong; Zhang, Hongshia; Qu, Minfeng; Sun, Zhifeng; Wang, Jing
2008-02-01
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 HIV risk reduction curriculum or a control group. Data were collected at baseline and 6 months postintervention. Outcome measures included HIV-related knowledge and perceptions, intention of risk behaviors, and self-reported risk behaviors. The participation in the intervention was significantly associated with increased HIV-related knowledge (including knowledge of condom use) and protective perceptions (e.g., self-efficacy), and associated with decreased intention of engaging in sexual intercourse in the next 6 months. There was no intervention effect on sexual behaviors because of the relatively low rates of sexual activities. The results suggest that a social cognitive theory based HIV risk reduction program for young adults can be effective in changing HIV-related perceptions and intentions in China. PMID:18312063
NASA Astrophysics Data System (ADS)
Xu, Yinyin; Tong, Shaocheng; Li, Yongming
2015-09-01
This paper discusses the adaptive fuzzy decentralised fault-tolerant control (FTC) problem for a class of nonlinear large-scale systems in strict-feedback form. The systems under study contain the unknown nonlinearities, unmodelled dynamics, actuator faults and without the direct measurements of state variables. With the help of fuzzy logic systems identifying the unknown functions and a fuzzy adaptive observer is designed to estimate the unmeasured states. By using the backstepping design technique and the dynamic surface control approach and combining with the changing supply function technique, a fuzzy adaptive FTC scheme is developed. The main features of the proposed control approach are that it can guarantee the closed-loop system to be input-to-state practically stable, and also has the robustness to the unmodelled dynamics. Moreover, it can overcome the so-called problem of 'explosion of complexity' existing in the previous literature. Finally, simulation studies are provided to illustrate the effectiveness of the proposed approach.
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
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)
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
Heuristic reusable dynamic programming: efficient updates of local sequence alignment.
Hong, Changjin; Tewfik, Ahmed H
2009-01-01
Recomputation of the previously evaluated similarity results between biological sequences becomes inevitable when researchers realize errors in their sequenced data or when the researchers have to compare nearly similar sequences, e.g., in a family of proteins. We present an efficient scheme for updating local sequence alignments with an affine gap model. In principle, using the previous matching result between two amino acid sequences, we perform a forward-backward alignment to generate heuristic searching bands which are bounded by a set of suboptimal paths. Given a correctly updated sequence, we initially predict a new score of the alignment path for each contour to select the best candidates among them. Then, we run the Smith-Waterman algorithm in this confined space. Furthermore, our heuristic alignment for an updated sequence shows that it can be further accelerated by using reusable dynamic programming (rDP), our prior work. In this study, we successfully validate "relative node tolerance bound" (RNTB) in the pruned searching space. Furthermore, we improve the computational performance by quantifying the successful RNTB tolerance probability and switch to rDP on perturbation-resilient columns only. In our searching space derived by a threshold value of 90 percent of the optimal alignment score, we find that 98.3 percent of contours contain correctly updated paths. We also find that our method consumes only 25.36 percent of the runtime cost of sparse dynamic programming (sDP) method, and to only 2.55 percent of that of a normal dynamic programming with the Smith-Waterman algorithm. PMID:19875856
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
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
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
NASA Technical Reports Server (NTRS)
Oakley, David R.; Knight, Norman F., Jr.
1994-01-01
A parallel adaptive dynamic relaxation (ADR) algorithm has been developed for nonlinear structural analysis. This algorithm has minimal memory requirements, is easily parallelizable and scalable to many processors, and is generally very reliable and efficient for highly nonlinear problems. Performance evaluations on single-processor computers have shown that the ADR algorithm is reliable and highly vectorizable, and that it is competitive with direct solution methods for the highly nonlinear problems considered. The present algorithm is implemented on the 512-processor Intel Touchstone DELTA system at Caltech, and it is designed to minimize the extent and frequency of interprocessor communication. The algorithm has been used to solve for the nonlinear static response of two and three dimensional hyperelastic systems involving contact. Impressive relative speedups have been achieved and demonstrate the high scalability of the ADR algorithm. For the class of problems addressed, the ADR algorithm represents a very promising approach for parallel-vector processing.
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.
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.
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.
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.
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. PMID:19051924
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.
An 'optimal' spawning algorithm for adaptive basis set expansion in nonadiabatic dynamics
Yang, Sandy; Coe, Joshua D.; Kaduk, Benjamin; Martinez, Todd J.
2009-04-07
The full multiple spawning (FMS) method has been developed to simulate quantum dynamics in the multistate electronic problem. In FMS, the nuclear wave function is represented in a basis of coupled, frozen Gaussians, and a 'spawning' procedure prescribes a means of adaptively increasing the size of this basis in order to capture population transfer between electronic states. Herein we detail a new algorithm for specifying the initial conditions of newly spawned basis functions that minimizes the number of spawned basis functions needed for convergence. 'Optimally' spawned basis functions are placed to maximize the coupling between parent and child trajectories at the point of spawning. The method is tested with a two-state, one-mode avoided crossing model and a two-state, two-mode conical intersection model.
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
Willis, Mike
2004-01-01
Many universities now deliver courses and programs in overseas markets such as China. Often these programs are delivered by foreign academics who teach in these overseas locations. This style and format of educational delivery raises the issue of the degree to which subject material and teaching styles need to be adapted to meet the needs of…
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…
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.
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.
Dynamic Programming and Graph Algorithms in Computer Vision*
Felzenszwalb, Pedro F.; Zabih, Ramin
2013-01-01
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 non-trivial guarantees concerning solution quality. In this paper we briefly 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. PMID:20660950
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.
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.
Dynamic Large-Scale Chromosomal Rearrangements Fuel Rapid Adaptation in Yeast Populations
Chang, Shang-Lin; Lai, Huei-Yi; Tung, Shu-Yun; Leu, Jun-Yi
2013-01-01
Large-scale genome rearrangements have been observed in cells adapting to various selective conditions during laboratory evolution experiments. However, it remains unclear whether these types of mutations can be stably maintained in populations and how they impact the evolutionary trajectories. Here we show that chromosomal rearrangements contribute to extremely high copper tolerance in a set of natural yeast strains isolated from Evolution Canyon (EC), Israel. The chromosomal rearrangements in EC strains result in segmental duplications in chromosomes 7 and 8, which increase the copy number of genes involved in copper regulation, including the crucial transcriptional activator CUP2 and the metallothionein CUP1. The copy number of CUP2 is correlated with the level of copper tolerance, indicating that increasing dosages of a single transcriptional activator by chromosomal rearrangements has a profound effect on a regulatory pathway. By gene expression analysis and functional assays, we identified three previously unknown downstream targets of CUP2: PHO84, SCM4, and CIN2, all of which contributed to copper tolerance in EC strains. Finally, we conducted an evolution experiment to examine how cells maintained these changes in a fluctuating environment. Interestingly, the rearranged chromosomes were reverted back to the wild-type configuration at a high frequency and the recovered chromosome became fixed in less selective conditions. Our results suggest that transposon-mediated chromosomal rearrangements can be highly dynamic and can serve as a reversible mechanism during early stages of adaptive evolution. PMID:23358723
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
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
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
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
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
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 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. PMID:26444205
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.
Gutowski, William J.; Prusa, Joseph M.; Smolarkiewicz, Piotr K.
2012-05-08
This project had goals of advancing the performance capabilities of the numerical general circulation model EULAG and using it to produce a fully operational atmospheric global climate model (AGCM) that can employ either static or dynamic grid stretching for targeted phenomena. The resulting AGCM combined EULAG's advanced dynamics core with the "physics" of the NCAR Community Atmospheric Model (CAM). Effort discussed below shows how we improved model performance and tested both EULAG and the coupled CAM-EULAG in several ways to demonstrate the grid stretching and ability to simulate very well a wide range of scales, that is, multi-scale capability. We leveraged our effort through interaction with an international EULAG community that has collectively developed new features and applications of EULAG, which we exploited for our own work summarized here. Overall, the work contributed to over 40 peer-reviewed publications and over 70 conference/workshop/seminar presentations, many of them invited. 3a. EULAG Advances EULAG is a non-hydrostatic, parallel computational model for all-scale geophysical flows. EULAG's name derives from its two computational options: EULerian (flux form) or semi-LAGrangian (advective form). The model combines nonoscillatory forward-in-time (NFT) numerical algorithms with a robust elliptic Krylov solver. A signature feature of EULAG is that it is formulated in generalized time-dependent curvilinear coordinates. In particular, this enables grid adaptivity. In total, these features give EULAG novel advantages over many existing dynamical cores. For EULAG itself, numerical advances included refining boundary conditions and filters for optimizing model performance in polar regions. We also added flexibility to the model's underlying formulation, allowing it to work with the pseudo-compressible equation set of Durran in addition to EULAG's standard anelastic formulation. Work in collaboration with others also extended the demonstrated range of
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
Scherer, Klaus R; Ellgring, Heiner
2007-02-01
The different assumptions made by discrete and componential emotion theories about the nature of the facial expression of emotion and the underlying mechanisms are reviewed. Explicit and implicit predictions are derived from each model. It is argued that experimental expression-production paradigms rather than recognition studies are required to critically test these differential predictions. Data from a large-scale actor portrayal study are reported to demonstrate the utility of this approach. The frequencies with which 12 professional actors use major facial muscle actions individually and in combination to express 14 major emotions show little evidence for emotion-specific prototypical affect programs. Rather, the results encourage empirical investigation of componential emotion model predictions of dynamic configurations of appraisal-driven adaptive facial actions. PMID:17352568
Stadler, A M; Garvey, C J; Bocahut, A; Sacquin-Mora, S; Digel, I; Schneider, G J; Natali, F; Artmann, G M; Zaccai, G
2012-11-01
Thermodynamic stability, configurational motions and internal forces of haemoglobin (Hb) of three endotherms (platypus, Ornithorhynchus anatinus; domestic chicken, Gallus gallus domesticus and human, Homo sapiens) and an ectotherm (salt water crocodile, Crocodylus porosus) were investigated using circular dichroism, incoherent elastic neutron scattering and coarse-grained Brownian dynamics simulations. The experimental results from Hb solutions revealed a direct correlation between protein resilience, melting temperature and average body temperature of the different species on the 0.1 ns time scale. Molecular forces appeared to be adapted to permit conformational fluctuations with a root mean square displacement close to 1.2 Å at the corresponding average body temperature of the endotherms. Strong forces within crocodile Hb maintain the amplitudes of motion within a narrow limit over the entire temperature range in which the animal lives. In fully hydrated powder samples of human and chicken, Hb mean square displacements and effective force constants on the 1 ns time scale showed no differences over the whole temperature range from 10 to 300 K, in contrast to the solution case. A complementary result of the study, therefore, is that one hydration layer is not sufficient to activate all conformational fluctuations of Hb in the pico- to nanosecond time scale which might be relevant for biological function. Coarse-grained Brownian dynamics simulations permitted to explore residue-specific effects. They indicated that temperature sensing of human and chicken Hb occurs mainly at residues lining internal cavities in the β-subunits. PMID:22696485
Highly Dynamic and Adaptive Traffic Congestion Avoidance in Real-Time Inspired by Honey Bee Behavior
NASA Astrophysics Data System (ADS)
Wedde, Horst F.; Lehnhoff, Sebastian; van Bonn, Bernhard; Bay, Z.; Becker, S.; Böttcher, S.; Brunner, C.; Büscher, A.; Fürst, T.; Lazarescu, A. M.; Rotaru, E.; Senge, S.; Steinbach, B.; Yilmaz, F.; Zimmermann, T.
Traffic congestions have become a major problem in metropolitan areas world-wide, within and between cities, to an extent where they make driving and transportation times largely unpredictable. Due to the highly dynamic character of congestion building and dissolving this phenomenon appears even to resist a formal treatment. Static approaches, and even more their global management, have proven counterproductive in practice. Given the latest progress in VANET technology and the remarkable commercially driven efforts like in the European C2C consortium, or the VSC Project in the US, allow meanwhile to tackle various aspects of traffic regulation through VANET communication. In this paper we introduce a novel, completely decentralized multi-agent routing algorithm (termed BeeJamA) which we have derived from the foraging behavior of honey bees. It is highly dynamic, adaptive, robust, and scalable, and it allows for both avoiding congestions, and minimizing traveling times to individual destinations. Vehicle guidance is provided well ahead of every intersection, depending on the individual speeds. Thus strict deadlines are imposed on, and respected by, the BeeJamA algorithm. We report on extensive simulation experiments which show the superior performance of BeeJamA over conventional approaches.
Spontaneous Neuronal Network Dynamics Reveal Circuit’s Functional Adaptations for Behavior
Romano, Sebastián A.; Pietri, Thomas; Pérez-Schuster, Verónica; Jouary, Adrien; Haudrechy, Mathieu; Sumbre, Germán
2015-01-01
Summary Spontaneous neuronal activity is spatiotemporally structured, influencing brain computations. Nevertheless, the neuronal interactions underlying these spontaneous activity patterns, and their biological relevance, remain elusive. Here, we addressed these questions using two-photon calcium imaging of intact zebrafish larvae to monitor the neuron-to-neuron spontaneous activity fine structure in the tectum, a region involved in visual spatial detection. Spontaneous activity was organized in topographically compact assemblies, grouping functionally similar neurons rather than merely neighboring ones, reflecting the tectal retinotopic map despite being independent of retinal drive. Assemblies represent all-or-none-like sub-networks shaped by competitive dynamics, mechanisms advantageous for visual detection in noisy natural environments. Notably, assemblies were tuned to the same angular sizes and spatial positions as prey-detection performance in behavioral assays, and their spontaneous activation predicted directional tail movements. Therefore, structured spontaneous activity represents “preferred” network states, tuned to behaviorally relevant features, emerging from the circuit’s intrinsic non-linear dynamics, adapted for its functional role. PMID:25704948
Fogarty, Aoife C. Potestio, Raffaello Kremer, Kurt
2015-05-21
A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydration shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations.