Adaptive Dynamic Programming for Control Algorithms and Stability
Zhang, Huaguang; Luo, Yanhong; Wang, Ding
2013-01-01
There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...
Adaptive dynamic programming with applications in optimal control
Liu, Derong; Wang, Ding; Yang, Xiong; Li, Hongliang
2017-01-01
This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP app...
Hamiltonian-Driven Adaptive Dynamic Programming for Continuous Nonlinear Dynamical Systems.
Yang, Yongliang; Wunsch, Donald; Yin, Yixin
2017-08-01
This paper presents a Hamiltonian-driven framework of adaptive dynamic programming (ADP) for continuous time nonlinear systems, which consists of evaluation of an admissible control, comparison between two different admissible policies with respect to the corresponding the performance function, and the performance improvement of an admissible control. It is showed that the Hamiltonian can serve as the temporal difference for continuous-time systems. In the Hamiltonian-driven ADP, the critic network is trained to output the value gradient. Then, the inner product between the critic and the system dynamics produces the value derivative. Under some conditions, the minimization of the Hamiltonian functional is equivalent to the value function approximation. An iterative algorithm starting from an arbitrary admissible control is presented for the optimal control approximation with its convergence proof. The implementation is accomplished by a neural network approximation. Two simulation studies demonstrate the effectiveness of Hamiltonian-driven ADP.
Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo
2017-07-01
This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.
Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors.
Zhu, Dongchen; Li, Jiamao; Wang, Xianshun; Peng, Jingquan; Shi, Wenjun; Zhang, Xiaolin
2018-04-03
Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison.
Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.
Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L
2017-10-01
The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.
Directory of Open Access Journals (Sweden)
Zhi-Jun Fu
2017-01-01
Full Text Available In view of the performance requirements (e.g., ride comfort, road holding, and suspension space limitation for vehicle suspension systems, this paper proposes an adaptive optimal control method for quarter-car active suspension system by using the approximate dynamic programming approach (ADP. Online optimal control law is obtained by using a single adaptive critic NN to approximate the solution of the Hamilton-Jacobi-Bellman (HJB equation. Stability of the closed-loop system is proved by Lyapunov theory. Compared with the classic linear quadratic regulator (LQR approach, the proposed ADP-based adaptive optimal control method demonstrates improved performance in the presence of parametric uncertainties (e.g., sprung mass and unknown road displacement. Numerical simulation results of a sedan suspension system are presented to verify the effectiveness of the proposed control strategy.
Lewis, F L; Vamvoudakis, Kyriakos G
2011-02-01
Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured input/output data from the system. Linear dynamical systems with deterministic behavior are considered herein, which are systems of great interest in the control system community. In control system theory, these types of methods are referred to as output feedback (OPFB). The stochastic equivalent of the systems dealt with in this paper is a class of partially observable Markov decision processes. We develop both policy iteration and value iteration algorithms that converge to an optimal controller that requires only OPFB. It is shown that, similar to Q -learning, the new methods have the important advantage that knowledge of the system dynamics is not needed for the implementation of these learning algorithms or for the OPFB control. Only the order of the system, as well as an upper bound on its "observability index," must be known. The learned OPFB controller is in the form of a polynomial autoregressive moving-average controller that has equivalent performance with the optimal state variable feedback gain.
Air-Breathing Hypersonic Vehicle Tracking Control Based on Adaptive Dynamic Programming.
Mu, Chaoxu; Ni, Zhen; Sun, Changyin; He, Haibo
2017-03-01
In this paper, we propose a data-driven supplementary control approach with adaptive learning capability for air-breathing hypersonic vehicle tracking control based on action-dependent heuristic dynamic programming (ADHDP). The control action is generated by the combination of sliding mode control (SMC) and the ADHDP controller to track the desired velocity and the desired altitude. In particular, the ADHDP controller observes the differences between the actual velocity/altitude and the desired velocity/altitude, and then provides a supplementary control action accordingly. The ADHDP controller does not rely on the accurate mathematical model function and is data driven. Meanwhile, it is capable to adjust its parameters online over time under various working conditions, which is very suitable for hypersonic vehicle system with parameter uncertainties and disturbances. We verify the adaptive supplementary control approach versus the traditional SMC in the cruising flight, and provide three simulation studies to illustrate the improved performance with the proposed approach.
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.
Exploring adaptive program behavior
DEFF Research Database (Denmark)
Bonnichsen, Lars Frydendal; Probst, Christian W.
Modern computer systems are increasingly complex, with ever changing bottlenecks. This makes it difficult to ensure consistent performance when porting software, or even running it. Adaptivity, ie, switching between program variations, and dynamic recompilation have been suggested as solutions....... Both solutions come at a cost; adaptivity issues a runtime overhead and requires more design effort, while dynamic recompilation takes time to perform. In this project, we plan to investigate the possibilities, limitations, and benefits of these techniques. This abstract covers our thoughts on how...
Wei, Qinglai; Liu, Derong; Lin, Qiao
In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.
Zhu, Yuanheng; Zhao, Dongbin; Li, Xiangjun
2017-03-01
H ∞ control is a powerful method to solve the disturbance attenuation problems that occur in some control systems. The design of such controllers relies on solving the zero-sum game (ZSG). But in practical applications, the exact dynamics is mostly unknown. Identification of dynamics also produces errors that are detrimental to the control performance. To overcome this problem, an iterative adaptive dynamic programming algorithm is proposed in this paper to solve the continuous-time, unknown nonlinear ZSG with only online data. A model-free approach to the Hamilton-Jacobi-Isaacs equation is developed based on the policy iteration method. Control and disturbance policies and value are approximated by neural networks (NNs) under the critic-actor-disturber structure. The NN weights are solved by the least-squares method. According to the theoretical analysis, our algorithm is equivalent to a Gauss-Newton method solving an optimization problem, and it converges uniformly to the optimal solution. The online data can also be used repeatedly, which is highly efficient. Simulation results demonstrate its feasibility to solve the unknown nonlinear ZSG. When compared with other algorithms, it saves a significant amount of online measurement time.
Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems.
Wei, Qinglai; Liu, Derong; Lin, Hanquan
2016-03-01
In this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear systems. The present value iteration ADP algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. A novel convergence analysis is developed to guarantee that the iterative value function converges to the optimal performance index function. Initialized by different initial functions, it is proven that the iterative value function will be monotonically nonincreasing, monotonically nondecreasing, or nonmonotonic and will converge to the optimum. In this paper, for the first time, the admissibility properties of the iterative control laws are developed for value iteration algorithms. It is emphasized that new termination criteria are established to guarantee the effectiveness of the iterative control laws. Neural networks are used to approximate the iterative value function and compute the iterative control law, respectively, for facilitating the implementation of the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the present method.
Adaptive Dynamic Programming for Discrete-Time Zero-Sum Games.
Wei, Qinglai; Liu, Derong; Lin, Qiao; Song, Ruizhuo
2018-04-01
In this paper, a novel adaptive dynamic programming (ADP) algorithm, called "iterative zero-sum ADP algorithm," is developed to solve infinite-horizon discrete-time two-player zero-sum games of nonlinear systems. The present iterative zero-sum ADP algorithm permits arbitrary positive semidefinite functions to initialize the upper and lower iterations. A novel convergence analysis is developed to guarantee the upper and lower iterative value functions to converge to the upper and lower optimums, respectively. When the saddle-point equilibrium exists, it is emphasized that both the upper and lower iterative value functions are proved to converge to the optimal solution of the zero-sum game, where the existence criteria of the saddle-point equilibrium are not required. If the saddle-point equilibrium does not exist, the upper and lower optimal performance index functions are obtained, respectively, where the upper and lower performance index functions are proved to be not equivalent. Finally, simulation results and comparisons are shown to illustrate the performance of the present method.
Dynamical adaptation in photoreceptors.
Directory of Open Access Journals (Sweden)
Damon A Clark
Full Text Available Adaptation is at the heart of sensation and nowhere is it more salient than in early visual processing. Light adaptation in photoreceptors is doubly dynamical: it depends upon the temporal structure of the input and it affects the temporal structure of the response. We introduce a non-linear dynamical adaptation model of photoreceptors. It is simple enough that it can be solved exactly and simulated with ease; analytical and numerical approaches combined provide both intuition on the behavior of dynamical adaptation and quantitative results to be compared with data. Yet the model is rich enough to capture intricate phenomenology. First, we show that it reproduces the known phenomenology of light response and short-term adaptation. Second, we present new recordings and demonstrate that the model reproduces cone response with great precision. Third, we derive a number of predictions on the response of photoreceptors to sophisticated stimuli such as periodic inputs, various forms of flickering inputs, and natural inputs. In particular, we demonstrate that photoreceptors undergo rapid adaptation of response gain and time scale, over ∼ 300[Formula: see text] ms-i. e., over the time scale of the response itself-and we confirm this prediction with data. For natural inputs, this fast adaptation can modulate the response gain more than tenfold and is hence physiologically relevant.
“Push” dynamics in policy experimentation: Downscaling climate change adaptation programs in Canada
Directory of Open Access Journals (Sweden)
Adam Wellstead
2016-12-01
Full Text Available Policy experiments have often been touted as valuable mechanisms for ensuring sustainability transitions and climate change adaptation. However problems exist both in the definition of ‘experiments’, and in their design and realization. While valuable, most experiments examined in the literature to date have been small-scale micro-level deployments or evaluations of policy tools in which the most problematic element revolves around their “scaling-up” or diffusion. The literature on the subject has generally neglected the problems and issues related to another class of experiments in which macro or meso-level initiatives are ‘scaled-down’ to the micro-level. This paper examines a recent effort of this kind in Canada involving the creation of Regional Adaptation Collaboratives (RACs across the country whose main purpose is to push national level initiatives down to the regions and localities. As the discussion shows, this top-down process has its own dynamics distinct from those involved in ‘scaling up’ and should be examined as a separate category of policy experiments in its own right.
Robust Adaptive Dynamic Programming of Two-Player Zero-Sum Games for Continuous-Time Linear Systems.
Fu, Yue; Fu, Jun; Chai, Tianyou
2015-12-01
In this brief, an online robust adaptive dynamic programming algorithm is proposed for two-player zero-sum games of continuous-time unknown linear systems with matched uncertainties, which are functions of system outputs and states of a completely unknown exosystem. The online algorithm is developed using the policy iteration (PI) scheme with only one iteration loop. A new analytical method is proposed for convergence proof of the PI scheme. The sufficient conditions are given to guarantee globally asymptotic stability and suboptimal property of the closed-loop system. Simulation studies are conducted to illustrate the effectiveness of the proposed method.
Chun, Tae Yoon; Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho
2018-06-01
In this paper, we propose two multirate generalised policy iteration (GPI) algorithms applied to discrete-time linear quadratic regulation problems. The proposed algorithms are extensions of the existing GPI algorithm that consists of the approximate policy evaluation and policy improvement steps. The two proposed schemes, named heuristic dynamic programming (HDP) and dual HDP (DHP), based on multirate GPI, use multi-step estimation (M-step Bellman equation) at the approximate policy evaluation step for estimating the value function and its gradient called costate, respectively. Then, we show that these two methods with the same update horizon can be considered equivalent in the iteration domain. Furthermore, monotonically increasing and decreasing convergences, so called value iteration (VI)-mode and policy iteration (PI)-mode convergences, are proved to hold for the proposed multirate GPIs. Further, general convergence properties in terms of eigenvalues are also studied. The data-driven online implementation methods for the proposed HDP and DHP are demonstrated and finally, we present the results of numerical simulations performed to verify the effectiveness of the proposed methods.
Brodin, Anders; Nilsson, Jan-Åke; Nord, Andreas
2017-09-01
Several species of small birds are resident in boreal forests where environmental temperatures can be -20 to -30 °C, or even lower, in winter. As winter days are short, and food is scarce, winter survival is a challenge for small endothermic animals. A bird of this size will have to gain almost 10% of its lean body mass in fat every day to sustain overnight metabolism. Birds such as parids (titmice and chickadees) can use facultative hypothermia, a process in which body temperature is actively down-regulated to a specific level, to reduce heat loss and thus save energy. During cold winter nights, these birds may decrease body temperature from the normal from 42 ° down to 35 °C, or even lower in some species. However, birds are unable to move in this deep hypothermic state, making it a risky strategy if predators are around. Why, then, do small northern birds enter a potentially dangerous physiological state for a relatively small reduction in energy expenditure? We used stochastic dynamic programming to investigate this. Our model suggests that the use of nocturnal hypothermia at night is paramount in these biomes, as it would increase winter survival for a small northern bird by 58% over a winter of 100 days. Our model also explains the phenomenon known as winter fattening, and its relationship to thermoregulation, in northern birds.
Zhang, Huaguang; Jiang, He; Luo, Chaomin; Xiao, Geyang
2017-10-01
In this paper, we investigate the nonzero-sum games for a class of discrete-time (DT) nonlinear systems by using a novel policy iteration (PI) adaptive dynamic programming (ADP) method. The main idea of our proposed PI scheme is to utilize the iterative ADP algorithm to obtain the iterative control policies, which not only ensure the system to achieve stability but also minimize the performance index function for each player. This paper integrates game theory, optimal control theory, and reinforcement learning technique to formulate and handle the DT nonzero-sum games for multiplayer. First, we design three actor-critic algorithms, an offline one and two online ones, for the PI scheme. Subsequently, neural networks are employed to implement these algorithms and the corresponding stability analysis is also provided via the Lyapunov theory. Finally, a numerical simulation example is presented to demonstrate the effectiveness of our proposed approach.
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.
Sun, Jingliang; Liu, Chunsheng
2018-01-01
In this paper, the problem of intercepting a manoeuvring target within a fixed final time is posed in a non-linear constrained zero-sum differential game framework. The Nash equilibrium solution is found by solving the finite-horizon constrained differential game problem via adaptive dynamic programming technique. Besides, a suitable non-quadratic functional is utilised to encode the control constraints into a differential game problem. The single critic network with constant weights and time-varying activation functions is constructed to approximate the solution of associated time-varying Hamilton-Jacobi-Isaacs equation online. To properly satisfy the terminal constraint, an additional error term is incorporated in a novel weight-updating law such that the terminal constraint error is also minimised over time. By utilising Lyapunov's direct method, the closed-loop differential game system and the estimation weight error of the critic network are proved to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is demonstrated by using a simple non-linear system and a non-linear missile-target interception system, assuming first-order dynamics for the interceptor and target.
Adaptive learning and complex dynamics
International Nuclear Information System (INIS)
Gomes, Orlando
2009-01-01
In this paper, we explore the dynamic properties of a group of simple deterministic difference equation systems in which the conventional perfect foresight assumption gives place to a mechanism of adaptive learning. These systems have a common feature: under perfect foresight (or rational expectations) they all possess a unique fixed point steady state. This long-term outcome is obtained also under learning if the quality underlying the learning process is high. Otherwise, when the degree of inefficiency of the learning process is relatively strong, nonlinear dynamics (periodic and a-periodic cycles) arise. The specific properties of each one of the proposed systems is explored both in terms of local and global dynamics. One macroeconomic model is used to illustrate how the formation of expectations through learning may eventually lead to awkward long-term outcomes.
Introduction to dynamic programming
Cooper, Leon; Rodin, E Y
1981-01-01
Introduction to Dynamic Programming provides information pertinent to the fundamental aspects of dynamic programming. This book considers problems that can be quantitatively formulated and deals with mathematical models of situations or phenomena that exists in the real world.Organized into 10 chapters, this book begins with an overview of the fundamental components of any mathematical optimization model. This text then presents the details of the application of dynamic programming to variational problems. Other chapters consider the application of dynamic programming to inventory theory, Mark
Adapting Activity and Participation (The ADAPT intervention program)
DEFF Research Database (Denmark)
von Bülow, Cecilie
Præsentation af et ergoterapeutisk gruppebaseret program, ADAPT programmet. ADAPT programmet er designet på baggrund af evidens samt understøttet af ergoterapeutiske teorier og modeller......Præsentation af et ergoterapeutisk gruppebaseret program, ADAPT programmet. ADAPT programmet er designet på baggrund af evidens samt understøttet af ergoterapeutiske teorier og modeller...
Adaptive, dynamic, and resilient systems
Suri, Niranjan
2015-01-01
As the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of networked computers rely on. It introduces the key issues, describes their interrelationships, and presents new research in support of these areas.The book presents the insights of a different group of international experts in each chapter. Reporting on r
Dual Dynamic Programming - DDP
International Nuclear Information System (INIS)
Velasquez Bermudez, Jesus M
1998-01-01
Objections are presented to the mathematical formulation of the denominated Dual Dynamic programming-PDD that is the theoretical base of several computational model available for the optimal formulation of interconnected hydrothermal systems
Luy, N. T.
2018-04-01
The design of distributed cooperative H∞ optimal controllers for multi-agent systems is a major challenge when the agents' models are uncertain multi-input and multi-output nonlinear systems in strict-feedback form in the presence of external disturbances. In this paper, first, the distributed cooperative H∞ optimal tracking problem is transformed into controlling the cooperative tracking error dynamics in affine form. Second, control schemes and online algorithms are proposed via adaptive dynamic programming (ADP) and the theory of zero-sum differential graphical games. The schemes use only one neural network (NN) for each agent instead of three from ADP to reduce computational complexity as well as avoid choosing initial NN weights for stabilising controllers. It is shown that despite not using knowledge of cooperative internal dynamics, the proposed algorithms not only approximate values to Nash equilibrium but also guarantee all signals, such as the NN weight approximation errors and the cooperative tracking errors in the closed-loop system, to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is shown by simulation results of an application to wheeled mobile multi-robot systems.
Bender, Christian; Gärtner, Christian; Schweizer, Nikolaus
2017-01-01
We present a novel method for deriving tight Monte Carlo confidence intervals for solutions of stochastic dynamic programming equations. Taking some approximate solution to the equation as an input, we construct pathwise recursions with a known bias. Suitably coupling the recursions for lower and
Dynamic adaption of vascular morphology
DEFF Research Database (Denmark)
Okkels, Fridolin; Jacobsen, Jens Christian Brings
2012-01-01
The structure of vascular networks adapts continuously to meet changes in demand of the surrounding tissue. Most of the known vascular adaptation mechanisms are based on local reactions to local stimuli such as pressure and flow, which in turn reflects influence from the surrounding tissue. Here ...
Robust adaptive synchronization of general dynamical networks ...
Indian Academy of Sciences (India)
Robust adaptive synchronization; dynamical network; multiple delays; multiple uncertainties. ... Networks such as neural networks, communication transmission networks, social rela- tionship networks etc. ..... a very good effect. Pramana – J.
Dynamic optimization and adaptive controller design
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.
Adaptive numerical modeling of dynamic crack propagation
International Nuclear Information System (INIS)
Adouani, H.; Tie, B.; Berdin, C.; Aubry, D.
2006-01-01
We propose an adaptive numerical strategy that aims at developing reliable and efficient numerical tools to model dynamic crack propagation and crack arrest. We use the cohesive zone theory as behavior of interface-type elements to model crack. Since the crack path is generally unknown beforehand, adaptive meshing is proposed to model the dynamic crack propagation. The dynamic study requires the development of specific solvers for time integration. As both geometry and finite element mesh of the studied structure evolve in time during transient analysis, the stability behavior of dynamic solver becomes a major concern. For this purpose, we use the space-time discontinuous Galerkin finite element method, well-known to provide a natural framework to manage meshes that evolve in time. As an important result, we prove that the space-time discontinuous Galerkin solver is unconditionally stable, when the dynamic crack propagation is modeled by the cohesive zone theory, which is highly non-linear. (authors)
Dynamical Adaptation in Terrorist Cells/Networks
DEFF Research Database (Denmark)
Hussain, Dil Muhammad Akbar; Ahmed, Zaki
2010-01-01
Typical terrorist cells/networks have dynamical structure as they evolve or adapt to changes which may occur due to capturing or killing of a member of the cell/network. Analytical measures in graph theory like degree centrality, betweenness and closeness centralities are very common and have long...
Adaptation dynamics of the quasispecies model
Indian Academy of Sciences (India)
We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly ...
Complex and adaptive dynamical systems a primer
Gros, Claudius
2007-01-01
We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...
Complex and Adaptive Dynamical Systems A Primer
Gros, Claudius
2011-01-01
We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...
Adaptive Integration of Nonsmooth Dynamical Systems
2017-10-11
2017 W911NF-12-R-0012-03: Adaptive Integration of Nonsmooth Dynamical Systems The views, opinions and/or findings contained in this report are those of...Integration of Nonsmooth Dynamical Systems Report Term: 0-Other Email: drum@gwu.edu Distribution Statement: 1-Approved for public release; distribution is...classdrake_1_1systems_1_1_integrator_base.html ; 3) a solver for dynamical systems with arbitrary unilateral and bilateral constraints (the key component of the time stepping systems )- see
Dynamic Information Encoding With Dynamic Synapses in Neural Adaptation
Li, Luozheng; Mi, Yuanyuan; Zhang, Wenhao; Wang, Da-Hui; Wu, Si
2018-01-01
Adaptation refers to the general phenomenon that the neural system dynamically adjusts its response property according to the statistics of external inputs. In response to an invariant stimulation, neuronal firing rates first increase dramatically and then decrease gradually to a low level close to the background activity. This prompts a question: during the adaptation, how does the neural system encode the repeated stimulation with attenuated firing rates? It has been suggested that the neural system may employ a dynamical encoding strategy during the adaptation, the information of stimulus is mainly encoded by the strong independent spiking of neurons at the early stage of the adaptation; while the weak but synchronized activity of neurons encodes the stimulus information at the later stage of the adaptation. The previous study demonstrated that short-term facilitation (STF) of electrical synapses, which increases the synchronization between neurons, can provide a mechanism to realize dynamical encoding. In the present study, we further explore whether short-term plasticity (STP) of chemical synapses, an interaction form more common than electrical synapse in the cortex, can support dynamical encoding. We build a large-size network with chemical synapses between neurons. Notably, facilitation of chemical synapses only enhances pair-wise correlations between neurons mildly, but its effect on increasing synchronization of the network can be significant, and hence it can serve as a mechanism to convey the stimulus information. To read-out the stimulus information, we consider that a downstream neuron receives balanced excitatory and inhibitory inputs from the network, so that the downstream neuron only responds to synchronized firings of the network. Therefore, the response of the downstream neuron indicates the presence of the repeated stimulation. Overall, our study demonstrates that STP of chemical synapse can serve as a mechanism to realize dynamical neural
Stochastic integer programming by dynamic programming
Lageweg, B.J.; Lenstra, J.K.; Rinnooy Kan, A.H.G.; Stougie, L.; Ermoliev, Yu.; Wets, R.J.B.
1988-01-01
Stochastic integer programming is a suitable tool for modeling hierarchical decision situations with combinatorial features. In continuation of our work on the design and analysis of heuristics for such problems, we now try to find optimal solutions. Dynamic programming techniques can be used to
Adaptive resummation of Markovian quantum dynamics
International Nuclear Information System (INIS)
Lucas, Felix
2014-01-01
In this thesis we derive a highly convergent, nonperturbative expansion of Markovian open quantum dynamics. It is based on a splitting of the incoherent dynamics into periods of continuous evolution and abrupt jumps and attains its favorable convergence properties from an adaptive resummation of this so-called jump expansion. By means of the long-standing problems of spatial particle detection and Landau-Zener tunneling in the presence of dephasing, we show that this adaptive resummation technique facilitates new highly accurate analytic approximations of Markovian open systems. The open Landau-Zener model leads us to propose an efficient and robust incoherent control technique for the isomerization reaction of the visual pigment protein rhodopsin. Besides leading to approximate analytic descriptions of Markovian open quantum dynamics, the adaptive resummation of the jump expansion implies an efficient numerical simulation method. We spell out the corresponding numerical algorithm by means of Monte Carlo integration of the relevant terms in the jump expansion and demonstrate it in a set of paradigmatic open quantum systems.
Adaptive-network models of collective dynamics
Zschaler, G.
2012-09-01
Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge
Towards Trustworthy Adaptive Case Management with Dynamic Condition Response Graphs
DEFF Research Database (Denmark)
Mukkamala, Raghava Rao; Hildebrandt, Thomas; Slaats, Tijs
2013-01-01
We describe how the declarative Dynamic Condition Response (DCR) Graphs process model can be used for trustworthy adaptive case management by leveraging the flexible execution, dynamic composition and adaptation supported by DCR Graphs. The dynamically composed and adapted graphs are verified for...
Automated adaptive inference of phenomenological dynamical models
Daniels, Bryan
Understanding the dynamics of biochemical systems can seem impossibly complicated at the microscopic level: detailed properties of every molecular species, including those that have not yet been discovered, could be important for producing macroscopic behavior. The profusion of data in this area has raised the hope that microscopic dynamics might be recovered in an automated search over possible models, yet the combinatorial growth of this space has limited these techniques to systems that contain only a few interacting species. We take a different approach inspired by coarse-grained, phenomenological models in physics. Akin to a Taylor series producing Hooke's Law, forgoing microscopic accuracy allows us to constrain the search over dynamical models to a single dimension. This makes it feasible to infer dynamics with very limited data, including cases in which important dynamical variables are unobserved. We name our method Sir Isaac after its ability to infer the dynamical structure of the law of gravitation given simulated planetary motion data. Applying the method to output from a microscopically complicated but macroscopically simple biological signaling model, it is able to adapt the level of detail to the amount of available data. Finally, using nematode behavioral time series data, the method discovers an effective switch between behavioral attractors after the application of a painful stimulus.
Introduction to stochastic dynamic programming
Ross, Sheldon M; Lukacs, E
1983-01-01
Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist-providing counterexamples where appropriate-and the
Dynamic Programming Foundations and Principles
Sniedovich, Moshe
2010-01-01
Focusing on the modeling and solution of deterministic multistage decision problems, this book looks at dynamic programming as a problem-solving optimization method. With over 400 useful references, this edition discusses the dynamic programming analysis of a problem, illustrates the rationale behind this analysis, and clarifies the theoretical grounds that justify the rationale. It also explains the meaning and role of the concept of state in dynamic programming, examines the purpose and function of the principle of optimality, and outlines solution strategies for problems defiant of conventi
Dynamic programming models and applications
Denardo, Eric V
2003-01-01
Introduction to sequential decision processes covers use of dynamic programming in studying models of resource allocation, methods for approximating solutions of control problems in continuous time, production control, more. 1982 edition.
The TMT Adaptive Optics Program
Ellerbroek, Brent
2011-09-01
We provide an overview of the Thirty Meter Telescope (TMT) AO program, with an emphasis upon the progress made since the first AO4ELT conference held in 2009. The first light facility AO system for TMT is the Narrow Field Infra-Red AO System (NFIRAOS), which will provide diffraction-limited performance in the J, H, and K bands over 18-30 arc sec diameter fields with 50% sky coverage at the galactic pole. This is accomplished with order 60x60 wavefront sensing and correction, two deformable mirrors conjugate to ranges of 0 and 11.2 km, 6 sodium laser guide stars in an asterism with a diameter of 70 arc sec, and three low order (tip/tilt or tip/tilt focus), infra-red natural guide star (NGS) wavefront sensors deployable within a 2 arc minute diameter patrol field. The first light LGS asterism is generated by the Laser Guide Star Facility (LGSF), which initially incorporates 6 20-25W class laser systems mounted to the telescope elevation journal, a mirror-based beam transfer optics system, and a 0.4m diameter laser launch telescope located behind the TMT secondary mirror. Future plans for additional AO capabilities include a mid infra-red AO (MIRAO) system to support science instruments in the 4-20 micron range, a ground-layer AO (GLAO) system for wide-field spectroscopy, a multi-object AO (MOAO) system for multi-object integral field unit spectroscopy, and extreme AO (ExAO) for high contrast imaging. Significant progress has been made in developing the first-light AO architecture since 2009. This includes the adoption of a new NFIRAOS opto-mechanical design consisting of two off-axis parabola (OAP) relays in series, which eliminates field distortion and also significantly simplifies the designs of the LGS wavefront sensors, optical source simulators, and turbulence generator subsystem. The design of the LGSF has also been interated, and has been simplfied by the relocation of the (smaller, gravity invarient) laser systems to the telescope elevation journal
Adaptation and inertia in dynamic environments
DEFF Research Database (Denmark)
Stieglitz, Nils; Knudsen, Thorbjørn; Becker, Markus C.
2016-01-01
responses to these dimensions. Our results show how frequent directional changes undermine the value of exploration and decisively shift performance advantages to inert organizations that restrict exploration. In contrast, increased environmental variance rewards exploration. Our results also show that......Research summary: We address conflicting claims and mixed empirical findings about adaptation as a response to increased environmental dynamism. We disentangle distinct dimensions of environmental dynamism—the direction, magnitude, and frequency of change—and identify how selection shapes adaptive...... business environments characterized by persistent trends and by large, infrequently occurring structural shocks reward strategic pursuit of temporary advantage. Thus, exploration and strategic flexibility are preferred strategies. In contrast, the challenge in frequently changing environments with fleeting...
Adaptive Dynamic Process Scheduling on Distributed Memory Parallel Computers
Directory of Open Access Journals (Sweden)
Wei Shu
1994-01-01
Full Text Available One of the challenges in programming distributed memory parallel machines is deciding how to allocate work to processors. This problem is particularly important for computations with unpredictable dynamic behaviors or irregular structures. We present a scheme for dynamic scheduling of medium-grained processes that is useful in this context. The adaptive contracting within neighborhood (ACWN is a dynamic, distributed, load-dependent, and scalable scheme. It deals with dynamic and unpredictable creation of processes and adapts to different systems. The scheme is described and contrasted with two other schemes that have been proposed in this context, namely the randomized allocation and the gradient model. The performance of the three schemes on an Intel iPSC/2 hypercube is presented and analyzed. The experimental results show that even though the ACWN algorithm incurs somewhat larger overhead than the randomized allocation, it achieves better performance in most cases due to its adaptiveness. Its feature of quickly spreading the work helps it outperform the gradient model in performance and scalability.
Adaptive typography for dynamic mapping environments
Bardon, Didier
1991-08-01
When typography moves across a map, it passes over areas of different colors, densities, and textures. In such a dynamic environment, the aspect of typography must be constantly adapted to provide disernibility for every new background. Adaptive typography undergoes two adaptive operations: background control and contrast control. The background control prevents the features of the map (edges, lines, abrupt changes of densities) from destroying the integrity of the letterform. This is achieved by smoothing the features of the map in the area where a text label is displayed. The modified area is limited to the space covered by the characters of the label. Dispositions are taken to insure that the smoothing operation does not introduce any new visual noise. The contrast control assures that there are sufficient lightness differences between the typography and its ever-changing background. For every new situation, background color and foreground color are compared and the foreground color lightness is adjusted according to a chosen contrast value. Criteria and methods of choosing the appropriate contrast value are presented as well as the experiments that led to them.
1978-10-01
8 Track Bushing Research, . . . . . . . . . . . * . . . 8 Advanced frack Concept Development ..... . . . . . 9 TECHNICAL DISCUSSION...machine design effort was conducted. The design which was developed has separate servocontrolled hydraulic actuators to apply radial...back bending-but, in the order and magnitude of the way the torsional stress is incurred in service. This suggests a programable, hydraulically actuated
Modulation of neuronal dynamic range using two different adaptation mechanisms
Directory of Open Access Journals (Sweden)
Lei Wang
2017-01-01
Full Text Available The capability of neurons to discriminate between intensity of external stimulus is measured by its dynamic range. A larger dynamic range indicates a greater probability of neuronal survival. In this study, the potential roles of adaptation mechanisms (ion currents in modulating neuronal dynamic range were numerically investigated. Based on the adaptive exponential integrate-and-fire model, which includes two different adaptation mechanisms, i.e. subthreshold and suprathreshold (spike-triggered adaptation, our results reveal that the two adaptation mechanisms exhibit rather different roles in regulating neuronal dynamic range. Specifically, subthreshold adaptation acts as a negative factor that observably decreases the neuronal dynamic range, while suprathreshold adaptation has little influence on the neuronal dynamic range. Moreover, when stochastic noise was introduced into the adaptation mechanisms, the dynamic range was apparently enhanced, regardless of what state the neuron was in, e.g. adaptive or non-adaptive. Our model results suggested that the neuronal dynamic range can be differentially modulated by different adaptation mechanisms. Additionally, noise was a non-ignorable factor, which could effectively modulate the neuronal dynamic range.
Secure Dynamic Program Repartitioning
DEFF Research Database (Denmark)
Hansen, Rene Rydhoff; Probst, Christian
2005-01-01
Secure program partitioning has been introduced as a language-based technique to allow the distribution of data and computation across mutualy untrusted hosts, while at the same time guaranteeing the protection of confidential data. Programs that have been annotated with security types......, but the partitioning compiler becomes a part of the network and can recompile applications, thus alowing hosts to enter or leave the framework. We contend that this setting is superior to static partitioning, since it allows redistribution of data and computations. This is especialy beneficial if the new host alows...... data and computations to better fulfil the trust requirements of the users. Erasure Policies ensure that the original host of the redistributed data or computation does not store the data any longer....
Opinion dynamics on an adaptive random network
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.
Complex and adaptive dynamical systems a primer
Gros, Claudius
2015-01-01
This primer offers readers an introduction to the central concepts that form our modern understanding of complex and emergent behavior, together with detailed coverage of accompanying mathematical methods. All calculations are presented step by step and are easy to follow. This new fourth edition has been fully reorganized and includes new chapters, figures and exercises. The core aspects of modern complex system sciences are presented in the first chapters, covering network theory, dynamical systems, bifurcation and catastrophe theory, chaos and adaptive processes, together with the principle of self-organization in reaction-diffusion systems and social animals. Modern information theoretical principles are treated in further chapters, together with the concept of self-organized criticality, gene regulation networks, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase transitions and the cognitive system approach to the brain. Technical course prerequisites are the standard ...
Complex and adaptive dynamical systems a primer
Gros, Claudius
2013-01-01
Complex system theory is rapidly developing and gaining importance, providing tools and concepts central to our modern understanding of emergent phenomena. This primer offers an introduction to this area together with detailed coverage of the mathematics involved. All calculations are presented step by step and are straightforward to follow. This new third edition comes with new material, figures and exercises. Network theory, dynamical systems and information theory, the core of modern complex system sciences, are developed in the first three chapters, covering basic concepts and phenomena like small-world networks, bifurcation theory and information entropy. Further chapters use a modular approach to address the most important concepts in complex system sciences, with the emergence and self-organization playing a central role. Prominent examples are self-organized criticality in adaptive systems, life at the edge of chaos, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase...
Constitutional dynamic chemistry: bridge from supramolecular chemistry to adaptive chemistry.
Lehn, Jean-Marie
2012-01-01
Supramolecular chemistry aims at implementing highly complex chemical systems from molecular components held together by non-covalent intermolecular forces and effecting molecular recognition, catalysis and transport processes. A further step consists in the investigation of chemical systems undergoing self-organization, i.e. systems capable of spontaneously generating well-defined functional supramolecular architectures by self-assembly from their components, thus behaving as programmed chemical systems. Supramolecular chemistry is intrinsically a dynamic chemistry in view of the lability of the interactions connecting the molecular components of a supramolecular entity and the resulting ability of supramolecular species to exchange their constituents. The same holds for molecular chemistry when the molecular entity contains covalent bonds that may form and break reversibility, so as to allow a continuous change in constitution by reorganization and exchange of building blocks. These features define a Constitutional Dynamic Chemistry (CDC) on both the molecular and supramolecular levels.CDC introduces a paradigm shift with respect to constitutionally static chemistry. The latter relies on design for the generation of a target entity, whereas CDC takes advantage of dynamic diversity to allow variation and selection. The implementation of selection in chemistry introduces a fundamental change in outlook. Whereas self-organization by design strives to achieve full control over the output molecular or supramolecular entity by explicit programming, self-organization with selection operates on dynamic constitutional diversity in response to either internal or external factors to achieve adaptation.The merging of the features: -information and programmability, -dynamics and reversibility, -constitution and structural diversity, points to the emergence of adaptive and evolutive chemistry, towards a chemistry of complex matter.
Improvements to the adaptive maneuvering logic program
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.
Adaptive dynamics of extortion and compliance.
Directory of Open Access Journals (Sweden)
Christian Hilbe
Full Text Available Direct reciprocity is a mechanism for the evolution of cooperation. For the iterated prisoner's dilemma, a new class of strategies has recently been described, the so-called zero-determinant strategies. Using such a strategy, a player can unilaterally enforce a linear relationship between his own payoff and the co-player's payoff. In particular the player may act in such a way that it becomes optimal for the co-player to cooperate unconditionally. In this way, a player can manipulate and extort his co-player, thereby ensuring that the own payoff never falls below the co-player's payoff. However, using a compliant strategy instead, a player can also ensure that his own payoff never exceeds the co-player's payoff. Here, we use adaptive dynamics to study when evolution leads to extortion and when it leads to compliance. We find a remarkable cyclic dynamics: in sufficiently large populations, extortioners play a transient role, helping the population to move from selfish strategies to compliance. Compliant strategies, however, can be subverted by altruists, which in turn give rise to selfish strategies. Whether cooperative strategies are favored in the long run critically depends on the size of the population; we show that cooperation is most abundant in large populations, in which case average payoffs approach the social optimum. Our results are not restricted to the case of the prisoners dilemma, but can be extended to other social dilemmas, such as the snowdrift game. Iterated social dilemmas in large populations do not lead to the evolution of strategies that aim to dominate their co-player. Instead, generosity succeeds.
Adaptive pseudolinear compensators of dynamic characteristics of automatic control systems
Skorospeshkin, M. V.; Sukhodoev, M. S.; Timoshenko, E. A.; Lenskiy, F. V.
2016-04-01
Adaptive pseudolinear gain and phase compensators of dynamic characteristics of automatic control systems are suggested. The automatic control system performance with adaptive compensators has been explored. The efficiency of pseudolinear adaptive compensators in the automatic control systems with time-varying parameters has been demonstrated.
Time course of dynamic range adaptation in the auditory nerve
Wang, Grace I.; Dean, Isabel; Delgutte, Bertrand
2012-01-01
Auditory adaptation to sound-level statistics occurs as early as in the auditory nerve (AN), the first stage of neural auditory processing. In addition to firing rate adaptation characterized by a rate decrement dependent on previous spike activity, AN fibers show dynamic range adaptation, which is characterized by a shift of the rate-level function or dynamic range toward the most frequently occurring levels in a dynamic stimulus, thereby improving the precision of coding of the most common sound levels (Wen B, Wang GI, Dean I, Delgutte B. J Neurosci 29: 13797–13808, 2009). We investigated the time course of dynamic range adaptation by recording from AN fibers with a stimulus in which the sound levels periodically switch from one nonuniform level distribution to another (Dean I, Robinson BL, Harper NS, McAlpine D. J Neurosci 28: 6430–6438, 2008). Dynamic range adaptation occurred rapidly, but its exact time course was difficult to determine directly from the data because of the concomitant firing rate adaptation. To characterize the time course of dynamic range adaptation without the confound of firing rate adaptation, we developed a phenomenological “dual adaptation” model that accounts for both forms of AN adaptation. When fitted to the data, the model predicts that dynamic range adaptation occurs as rapidly as firing rate adaptation, over 100–400 ms, and the time constants of the two forms of adaptation are correlated. These findings suggest that adaptive processing in the auditory periphery in response to changes in mean sound level occurs rapidly enough to have significant impact on the coding of natural sounds. PMID:22457465
The Hitchhiker’s Guide to Adaptive Dynamics
Directory of Open Access Journals (Sweden)
Jacob Johansson
2013-06-01
Full Text Available Adaptive dynamics is a mathematical framework for studying evolution. It extends evolutionary game theory to account for more realistic ecological dynamics and it can incorporate both frequency- and density-dependent selection. This is a practical guide to adaptive dynamics that aims to illustrate how the methodology can be applied to the study of specific systems. The theory is presented in detail for a single, monomorphic, asexually reproducing population. We explain the necessary terminology to understand the basic arguments in models based on adaptive dynamics, including invasion fitness, the selection gradient, pairwise invasibility plots (PIP, evolutionarily singular strategies, and the canonical equation. The presentation is supported with a worked-out example of evolution of arrival times in migratory birds. We show how the adaptive dynamics methodology can be extended to study evolution in polymorphic populations using trait evolution plots (TEPs. We give an overview of literature that generalises adaptive dynamics techniques to other scenarios, such as sexual, diploid populations, and spatially-structured populations. We conclude by discussing how adaptive dynamics relates to evolutionary game theory and how adaptive-dynamics techniques can be used in speciation research.
Robust adaptive synchronization of general dynamical networks ...
Indian Academy of Sciences (India)
Home; Journals; Pramana – Journal of Physics; Volume 86; Issue 6. Robust ... A robust adaptive synchronization scheme for these general complex networks with multiple delays and uncertainties is established and raised by employing the robust adaptive control principle and the Lyapunov stability theory. We choose ...
Recruitment dynamics in adaptive social networks
International Nuclear Information System (INIS)
Shkarayev, Maxim S; Shaw, Leah B; Schwartz, Ira B
2013-01-01
We model recruitment in adaptive social networks in the presence of birth and death processes. Recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. Only a susceptible subset of nodes can be recruited. The recruiting individuals may adapt their connections in order to improve recruitment capabilities, thus changing the network structure adaptively. We derive a mean-field theory to predict the dependence of the growth threshold of the recruiting class on the adaptation parameter. Furthermore, we investigate the effect of adaptation on the recruitment level, as well as on network topology. The theoretical predictions are compared with direct simulations of the full system. We identify two parameter regimes with qualitatively different bifurcation diagrams depending on whether nodes become susceptible frequently (multiple times in their lifetime) or rarely (much less than once per lifetime). (paper)
Recruitment dynamics in adaptive social networks
Shkarayev, Maxim S.; Schwartz, Ira B.; Shaw, Leah B.
2013-06-01
We model recruitment in adaptive social networks in the presence of birth and death processes. Recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. Only a susceptible subset of nodes can be recruited. The recruiting individuals may adapt their connections in order to improve recruitment capabilities, thus changing the network structure adaptively. We derive a mean-field theory to predict the dependence of the growth threshold of the recruiting class on the adaptation parameter. Furthermore, we investigate the effect of adaptation on the recruitment level, as well as on network topology. The theoretical predictions are compared with direct simulations of the full system. We identify two parameter regimes with qualitatively different bifurcation diagrams depending on whether nodes become susceptible frequently (multiple times in their lifetime) or rarely (much less than once per lifetime).
Neural network based adaptive control for nonlinear dynamic regimes
Shin, Yoonghyun
Adaptive control designs using neural networks (NNs) based on dynamic inversion are investigated for aerospace vehicles which are operated at highly nonlinear dynamic regimes. NNs play a key role as the principal element of adaptation to approximately cancel the effect of inversion error, which subsequently improves robustness to parametric uncertainty and unmodeled dynamics in nonlinear regimes. An adaptive control scheme previously named 'composite model reference adaptive control' is further developed so that it can be applied to multi-input multi-output output feedback dynamic inversion. It can have adaptive elements in both the dynamic compensator (linear controller) part and/or in the conventional adaptive controller part, also utilizing state estimation information for NN adaptation. This methodology has more flexibility and thus hopefully greater potential than conventional adaptive designs for adaptive flight control in highly nonlinear flight regimes. The stability of the control system is proved through Lyapunov theorems, and validated with simulations. The control designs in this thesis also include the use of 'pseudo-control hedging' techniques which are introduced to prevent the NNs from attempting to adapt to various actuation nonlinearities such as actuator position and rate saturations. Control allocation is introduced for the case of redundant control effectors including thrust vectoring nozzles. A thorough comparison study of conventional and NN-based adaptive designs for a system under a limit cycle, wing-rock, is included in this research, and the NN-based adaptive control designs demonstrate their performances for two highly maneuverable aerial vehicles, NASA F-15 ACTIVE and FQM-117B unmanned aerial vehicle (UAV), operated under various nonlinearities and uncertainties.
Fluid dynamics computer programs for NERVA turbopump
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.
On Organizational Adaptation via Dynamic Process Selection
National Research Council Canada - National Science Library
Handley, Holly A; Levis, Alexander H
2000-01-01
.... An executable organizational model composed of individual models of a five stage interacting decision maker is used to evaluate the effectiveness of the different adaptation strategies on organizational performance...
DyNAvectors: dynamic constitutional vectors for adaptive DNA transfection.
Clima, Lilia; Peptanariu, Dragos; Pinteala, Mariana; Salic, Adrian; Barboiu, Mihail
2015-12-25
Dynamic constitutional frameworks, based on squalene, PEG and PEI components, reversibly connected to core centers, allow the efficient identification of adaptive vectors for good DNA transfection efficiency and are well tolerated by mammalian cells.
Global network reorganization during dynamic adaptations of Bacillus subtilis metabolism
DEFF Research Database (Denmark)
Buescher, Joerg Martin; Liebermeister, Wolfram; Jules, Matthieu
2012-01-01
Adaptation of cells to environmental changes requires dynamic interactions between metabolic and regulatory networks, but studies typically address only one or a few layers of regulation. For nutritional shifts between two preferred carbon sources of Bacillus subtilis, we combined statistical...
Chemotactic response and adaptation dynamics in Escherichia coli.
Directory of Open Access Journals (Sweden)
Diana Clausznitzer
2010-05-01
Full Text Available Adaptation of the chemotaxis sensory pathway of the bacterium Escherichia coli is integral for detecting chemicals over a wide range of background concentrations, ultimately allowing cells to swim towards sources of attractant and away from repellents. Its biochemical mechanism based on methylation and demethylation of chemoreceptors has long been known. Despite the importance of adaptation for cell memory and behavior, the dynamics of adaptation are difficult to reconcile with current models of precise adaptation. Here, we follow time courses of signaling in response to concentration step changes of attractant using in vivo fluorescence resonance energy transfer measurements. Specifically, we use a condensed representation of adaptation time courses for efficient evaluation of different adaptation models. To quantitatively explain the data, we finally develop a dynamic model for signaling and adaptation based on the attractant flow in the experiment, signaling by cooperative receptor complexes, and multiple layers of feedback regulation for adaptation. We experimentally confirm the predicted effects of changing the enzyme-expression level and bypassing the negative feedback for demethylation. Our data analysis suggests significant imprecision in adaptation for large additions. Furthermore, our model predicts highly regulated, ultrafast adaptation in response to removal of attractant, which may be useful for fast reorientation of the cell and noise reduction in adaptation.
Complexity and network dynamics in physiological adaptation: An integrated view
Baffy, Gyorgy; Loscalzo, Joseph
2014-01-01
Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of t...
Dynamic Adaptation in Child-Adult Language Interaction
van Dijk, Marijn; van Geert, Paul; Korecky-Kröll, Katharina; Maillochon, Isabelle; Laaha, Sabine; Dressler, Wolfgang U.; Bassano, Dominique
2013-01-01
When speaking to young children, adults adapt their language to that of the child. In this article, we suggest that this child-directed speech (CDS) is the result of a transactional process of dynamic adaptation between the child and the adult. The study compares developmental trajectories of three children to those of the CDS of their caregivers.…
Probabilistic dual heuristic programming-based adaptive critic
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.
Adaptive game AI with dynamic scripting
Spronck, P.; Ponsen, M.J.V.; Sprinkhuizen-Kuyper, I.G.; Postma, E.O.
2006-01-01
Online learning in commercial computer games allows computer-controlled opponents to adapt to the way the game is being played. As such it provides a mechanism to deal with weaknesses in the game AI, and to respond to changes in human player tactics.We argue that online learning of game AI should
Exploring dynamics of embedded ADC through adapted digital input stimuli
Sheng, Xiaoqin; Kerkhoff, Hans G.; Zjajo, A.; Gronthoud, G.
2008-01-01
This paper reports an evaluation of adapted digital signals as a test stimulus to test dynamic parameters of analog-to-digital converters (ADC). In the first instance, the simplest digital waveform, a pulse signal, is taken as the test stimulus. The dynamics of the device under test while applying
Adaptive game AI with dynamic scripting
Spronck, P.; Ponsen, M.J.V.; Sprinkhuizen-Kuyper, I.G.; Postma, E.O.
2006-01-01
Online learning in commercial computer games allows computer-controlled opponents to adapt to the way the game is being played. As such it provides a mechanism to deal with weaknesses in the game AI, and to respond to changes in human player tactics.We argue that online learning of game AI should meet four computational and four functional requirements. The computational requirements are speed, effectiveness, robustness and ef- ficiency. The functional requirements are clarity, variety, consi...
Analog forecasting with dynamics-adapted kernels
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.
Strategic Defense Initiative Organization adaptive structures program overview
Obal, Michael; Sater, Janet M.
In the currently envisioned architecture none of the Strategic Defense System (SDS) elements to be deployed will receive scheduled maintenance. Assessments of performance capability due to changes caused by the uncertain effects of environments will be difficult, at best. In addition, the system will have limited ability to adjust in order to maintain its required performance levels. The Materials and Structures Office of the Strategic Defense Initiative Organization (SDIO) has begun to address solutions to these potential difficulties via an adaptive structures technology program that combines health and environment monitoring with static and dynamic structural control. Conceivable system benefits include improved target tracking and hit-to-kill performance, on-orbit system health monitoring and reporting, and threat attack warning and assessment.
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. Published by Elsevier Inc.
Adaptive Strategies for Dynamic Pricing Agents
S. Ramezani (Sara); P.A.N. Bosman (Peter); J.A. La Poutré (Han)
2011-01-01
htmlabstractDynamic Pricing (DyP) is a form of Revenue Management in which the price of a (usually) perishable good is changed over time to increase revenue. It is an effective method that has become even more relevant and useful with the emergence of Internet firms and the possibility of readily
Adaptation Planning for the National Estuary Program
This document is a resource for coastal communities to start planning to adapt to climate change. It describes elements, such as vulnerability assessments and stakeholder outreach, and provides examples as well as suggestions for additional resources.
Programs for Intercultural Adaptation: Practical Training Course
Kleen, Sue
1970-01-01
Briefly described is an extension workshop conducted in the United States to help home economists from other countries adapt and translate nutritional principles to their respective cultural circumstances. Included is a description of the workshop's curriculum objectives and content. (SB)
Brain-wide neuronal dynamics during motor adaptation in zebrafish.
Ahrens, Misha B; Li, Jennifer M; Orger, Michael B; Robson, Drew N; Schier, Alexander F; Engert, Florian; Portugues, Ruben
2012-05-09
A fundamental question in neuroscience is how entire neural circuits generate behaviour and adapt it to changes in sensory feedback. Here we use two-photon calcium imaging to record the activity of large populations of neurons at the cellular level, throughout the brain of larval zebrafish expressing a genetically encoded calcium sensor, while the paralysed animals interact fictively with a virtual environment and rapidly adapt their motor output to changes in visual feedback. We decompose the network dynamics involved in adaptive locomotion into four types of neuronal response properties, and provide anatomical maps of the corresponding sites. A subset of these signals occurred during behavioural adjustments and are candidates for the functional elements that drive motor learning. Lesions to the inferior olive indicate a specific functional role for olivocerebellar circuitry in adaptive locomotion. This study enables the analysis of brain-wide dynamics at single-cell resolution during behaviour.
On Sustaining Dynamic Adaptation of Context-Aware Services
Directory of Open Access Journals (Sweden)
Boudjemaa Boudaa
2015-03-01
Full Text Available The modern human is getting more and more mobile having access to online services by using mobile cutting-edge computational devices. In the last decade, the field of context-aware services had led to emerge several works. However, most of the proposed approaches have not provided clear adaptation strategies in case of unforeseen contexts. Dealing with this last at runtime is also another crucial need that has been ignored in their proposals. This paper aims to propose a generic dynamic adaptation process as a phase in a model-driven development life-cycle for context-aware services using the MAPE-K control loop to meet the runtime adaptation. This process is validated by implementing an illustrative application on FraSCAti platform. The main benefit of the proposed process is to sustain the self-reconfiguration of such services at model and code levels by enabling successive dynamic adaptations depending on the changing context.
Neutrophil programming dynamics and its disease relevance.
Ran, Taojing; Geng, Shuo; Li, Liwu
2017-11-01
Neutrophils are traditionally considered as first responders to infection and provide antimicrobial host defense. However, recent advances indicate that neutrophils are also critically involved in the modulation of host immune environments by dynamically adopting distinct functional states. Functionally diverse neutrophil subsets are increasingly recognized as critical components mediating host pathophysiology. Despite its emerging significance, molecular mechanisms as well as functional relevance of dynamically programmed neutrophils remain to be better defined. The increasing complexity of neutrophil functions may require integrative studies that address programming dynamics of neutrophils and their pathophysiological relevance. This review aims to provide an update on the emerging topics of neutrophil programming dynamics as well as their functional relevance in diseases.
Adaptive dynamic capacity borrowing in road-covering mobile networks
Ule, A.; Boucherie, Richardus J.; Li, W.; Pan, Y.
2006-01-01
This paper introduces adaptive dynamic capacity borrowing strategies for wireless networks covering a road. In a F/TDMA-based model, road traffic prediction models are used to characterise the movement of hot spots, such as traffic jams, and subsequently to predict the teletraffic load offered to
Dynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture
Energy Technology Data Exchange (ETDEWEB)
Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT)
2015-01-01
Dynamic Adaptive Neural Network Array (DANNA) is a neuromorphic hardware implementation. It differs from most other neuromorphic projects in that it allows for programmability of structure, and it is trained or designed using evolutionary optimization. This paper describes the DANNA structure, how DANNA is trained using evolutionary optimization, and an application of DANNA to a very simple classification task.
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.
Yuan, Ruoxi; Geng, Shuo; Li, Liwu
2016-01-01
In adaptation to rising stimulant strength, innate monocytes can be dynamically programed to preferentially express either pro- or anti-inflammatory mediators. Such dynamic innate adaptation or programing may bear profound relevance in host health and disease. However, molecular mechanisms that govern innate adaptation to varying strength of stimulants are not well understood. Using lipopolysaccharide (LPS), the model stimulant of toll-like-receptor 4 (TLR4), we reported that the expressions of pro-inflammatory mediators are preferentially sustained in monocytes adapted by lower doses of LPS, and suppressed/tolerized in monocytes adapted by higher doses of LPS. Mechanistically, monocytes adapted by super-low dose LPS exhibited higher levels of transcription factor, interferon regulatory factor 5 (IRF5), and reduced levels of transcriptional modulator B lymphocyte-induced maturation protein-1 (Blimp-1). Intriguingly, the inflammatory monocyte adaptation by super-low dose LPS is dependent upon TRAM/TRIF but not MyD88. Similar to LPS, we also observed biphasic inflammatory adaptation and tolerance in monocytes challenged with varying dosages of TLR7 agonist. In sharp contrast, rising doses of TLR3 agonist preferentially caused inflammatory adaptation without inducing tolerance. At the molecular level, the differential regulation of IRF5 and Blimp-1 coincides with unique monocyte adaptation dynamics by TLR4/7 and TLR3 agonists. Our study provides novel clue toward the understanding of monocyte adaptation and memory toward distinct TLR ligands.
Directory of Open Access Journals (Sweden)
Ruoxi Yuan
2016-11-01
Full Text Available In adaptation to rising stimulant strength, innate monocytes can be dynamically programmed to preferentially express either pro- or anti-inflammatory mediators. Such dynamic innate adaptation or programming may bear profound relevance in host health and disease. However, molecular mechanisms that govern innate adaptation to varying strength of stimulants are not well understood. Using lipopolysaccharide (LPS, the model stimulant of Toll-Like-Receptor 4 (TLR4, we reported that the expressions of pro-inflammatory mediators are preferentially sustained in monocytes adapted by lower doses of LPS, and suppressed/tolerized in monocytes adapted by higher doses of LPS. Mechanistically, monocytes adapted by super-low dose LPS exhibited higher levels of transcription factor IRF5 and reduced levels of transcriptional modulator BLIMP-1. Intriguingly, the inflammatory monocyte adaptation by super-low dose LPS is dependent upon TRAM/TRIF but not MyD88. Similar to LPS, we also observed biphasic inflammatory adaptation and tolerance in monocytes challenged with varying dosages of TLR7 agonist. In sharp contrast, rising doses of TLR3 agonist preferentially caused inflammatory adaptation without inducing tolerance. At the molecular level, the differential regulation of IRF5 and Blimp-1 coincides with unique monocyte adaptation dynamics by TLR4/7 and TLR3 agonists. Our study provides novel clue toward the understanding of monocyte adaptation and memory toward distinct TLR ligands.
Adapting Dynamic Mathematical Models to a Pilot Anaerobic Digestion Reactor
Directory of Open Access Journals (Sweden)
F. Haugen, R. Bakke, and B. Lie
2013-04-01
Full Text Available A dynamic model has been adapted to a pilot anaerobic reactor fed diarymanure. Both steady-state data from online sensors and laboratory analysis anddynamic operational data from online sensors are used in the model adaptation.The model is based on material balances, and comprises four state variables,namely biodegradable volatile solids, volatile fatty acids, acid generatingmicrobes (acidogens, and methane generating microbes (methanogens. The modelcan predict the methane gas flow produced in the reactor. The model may beused for optimal reactor design and operation, state-estimation and control.Also, a dynamic model for the reactor temperature based on energy balance ofthe liquid in the reactor is adapted. This model may be used for optimizationand control when energy and economy are taken into account.
Optimization of Algorithms Using Extensions of Dynamic Programming
AbouEisha, Hassan M.
2017-04-09
We study and answer questions related to the complexity of various important problems such as: multi-frontal solvers of hp-adaptive finite element method, sorting and majority. We advocate the use of dynamic programming as a viable tool to study optimal algorithms for these problems. The main approach used to attack these problems is modeling classes of algorithms that may solve this problem using a discrete model of computation then defining cost functions on this discrete structure that reflect different complexity measures of the represented algorithms. As a last step, dynamic programming algorithms are designed and used to optimize those models (algorithms) and to obtain exact results on the complexity of the studied problems. The first part of the thesis presents a novel model of computation (element partition tree) that represents a class of algorithms for multi-frontal solvers along with cost functions reflecting various complexity measures such as: time and space. It then introduces dynamic programming algorithms for multi-stage and bi-criteria optimization of element partition trees. In addition, it presents results based on optimal element partition trees for famous benchmark meshes such as: meshes with point and edge singularities. New improved heuristics for those benchmark meshes were ob- tained based on insights of the optimal results found by our algorithms. The second part of the thesis starts by introducing a general problem where different problems can be reduced to and show how to use a decision table to model such problem. We describe how decision trees and decision tests for this table correspond to adaptive and non-adaptive algorithms for the original problem. We present exact bounds on the average time complexity of adaptive algorithms for the eight elements sorting problem. Then bounds on adaptive and non-adaptive algorithms for a variant of the majority problem are introduced. Adaptive algorithms are modeled as decision trees whose depth
The role of conservation programs in drought risk adaptation
Steven Wallander; Marcel Aillery; Daniel Hellerstein; Michael Hand
2013-01-01
This report evaluates the extent to which farms facing higher levels of drought risk are more likely to participate in conservation programs, and fi nds a strong link between drought risk and program participation. Prior research has shown that climate-related risk exposure infl uences production decisions such as crop choice; our research shows that adaptation also...
Teaching Adaptability of Object-Oriented Programming Language Curriculum
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…
Rule of Thumb and Dynamic Programming
Lettau, M.; Uhlig, H.F.H.V.S.
1995-01-01
This paper studies the relationships between learning about rules of thumb (represented by classifier systems) and dynamic programming. Building on a result about Markovian stochastic approximation algorithms, we characterize all decision functions that can be asymptotically obtained through
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
2012-04-01
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.
Dynamic Programming: An Introduction by Example
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…
Testing Object-Oriented Programs using Dynamic Aspects and Non-Determinism
DEFF Research Database (Denmark)
Achenbach, Michael; Ostermann, Klaus
2010-01-01
decisions exposing private data. We present an approach that both improves the expressiveness of test cases using non-deterministic choice and reduces design modifications using dynamic aspect-oriented programming techniques. Non-deterministic choice facilitates local definitions of multiple executions...... without parameterization or generation of tests. It also eases modelling naturally non-deterministic program features like IO or multi-threading in integration tests. Dynamic AOP facilitates powerful design adaptations without exposing test features, keeping the scope of these adaptations local to each...... test. We also combine non-determinism and dynamic aspects in a new approach to testing multi-threaded programs using co-routines....
Guidelines for dynamic international programs
International Nuclear Information System (INIS)
Gold, M.A.
1993-01-01
Matters of global concern-deforestation, global warming, biodiversity loss, sustainable development, fuelwood crises, watershed destruction, and large-scale flooding-frequently involve forests and natural resources. In the future, university students will enter a global setting that more than ever depends on a strong knowledge of international issues. USA land-grant universities are attempting to prepare students for this challenge by improving their international programs including forestry. To improve university programs, several factors will need to be addressed and are discussed, with examples, in this article: commitment of the faculty; program specialization; geographic specialization; reward systems for international contributions; international collaboration; recycled dollars within the university; active teaching programs; research; extention and outreach; language training; international faculty; travel grants; twinning relationships with sister institutions; selective in pursuit of international development assistance; and study centers. 6 refs
Spontaneous formation of dynamical groups in an adaptive networked system
International Nuclear Information System (INIS)
Li Menghui; Guan Shuguang; Lai, C-H
2010-01-01
In this work, we investigate a model of an adaptive networked dynamical system, where the coupling strengths among phase oscillators coevolve with the phase states. It is shown that in this model the oscillators can spontaneously differentiate into two dynamical groups after a long time evolution. Within each group, the oscillators have similar phases, while oscillators in different groups have approximately opposite phases. The network gradually converts from the initial random structure with a uniform distribution of connection strengths into a modular structure that is characterized by strong intra-connections and weak inter-connections. Furthermore, the connection strengths follow a power-law distribution, which is a natural consequence of the coevolution of the network and the dynamics. Interestingly, it is found that if the inter-connections are weaker than a certain threshold, the two dynamical groups will almost decouple and evolve independently. These results are helpful in further understanding the empirical observations in many social and biological networks.
Selecting, adapting, and sustaining programs in health care systems
Directory of Open Access Journals (Sweden)
Zullig LL
2015-04-01
Full Text Available Leah L Zullig,1,2 Hayden B Bosworth1–4 1Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, NC, USA; 2Department of Medicine, Duke University Medical Center, Durham, NC, USA; 3School of Nursing, 4Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA Abstract: 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. Keywords: program sustainability, diffusion of innovation, information dissemination, health services research, intervention studies
Extracting neuronal functional network dynamics via adaptive Granger causality analysis.
Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash
2018-04-24
Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.
Evaluating Dynamic Analysis Techniques for Program Comprehension
Cornelissen, S.G.M.
2009-01-01
Program comprehension is an essential part of software development and software maintenance, as software must be sufficiently understood before it can be properly modified. One of the common approaches in getting to understand a program is the study of its execution, also known as dynamic analysis.
Market mood, adaptive beliefs and asset price dynamics
International Nuclear Information System (INIS)
Dieci, Roberto; Foroni, Ilaria; Gardini, Laura; He Xuezhong
2006-01-01
Empirical evidence has suggested that, facing different trading strategies and complicated decision, the proportions of agents relying on particular strategies may stay at constant level or vary over time. This paper presents a simple 'dynamic market fraction' model of two groups of traders, fundamentalists and trend followers, under a market maker scenario. Market mood and evolutionary adaption are characterized by fixed and adaptive switching fraction among two groups, respectively. Using local stability and bifurcation analysis, as well as numerical simulation, the role played by the key parameters in the market behaviour is examined. Particular attention is paid to the impact of the market fraction, determined by the fixed proportions of confident fundamentalists and trend followers, and by the proportion of adaptively rational agents, who adopt different strategies over time depending on realized profits
Hybrid Differential Dynamic Programming with Stochastic Search
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 programming for QFD in PES optimization
Energy Technology Data Exchange (ETDEWEB)
Sorrentino, R. [Mediterranean Univ. of Reggio Calabria, Reggio Calabria (Italy). Dept. of Computer Science and Electrical Technology
2008-07-01
Quality function deployment (QFD) is a method for linking the needs of the customer with design, development, engineering, manufacturing, and service functions. In the electric power industry, QFD is used to help designers concentrate on the most important technical attributes to develop better electrical services. Most optimization approaches used in QFD analysis have been based on integer or linear programming. These approaches perform well in certain circumstances, but there are problems that hinder their practical use. This paper proposed an approach to optimize Power and Energy Systems (PES). A dynamic programming approach was used along with an extended House of Quality to gather information. Dynamic programming was used to allocate the limited resources to the technical attributes. The approach integrated dynamic programming into the electrical service design process. The dynamic programming approach did not require the full relationship curve between technical attributes and customer satisfaction, or the relationship between technical attributes and cost. It only used a group of discrete points containing information about customer satisfaction, technical attributes, and the cost to find the optimal product design. Therefore, it required less time and resources than other approaches. At the end of the optimization process, the value of each technical attribute, the related cost, and the overall customer satisfaction were obtained at the same time. It was concluded that compared with other optimization methods, the dynamic programming method requires less information and the optimal results are more relevant. 21 refs., 2 tabs., 2 figs.
Enhancing Functional Performance using Sensorimotor Adaptability Training Programs
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.
Adaptive sampling program support for expedited site characterization
International Nuclear Information System (INIS)
Johnson, R.
1993-01-01
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
Directory of Open Access Journals (Sweden)
Andrey Fyodorovich Shorikov
2013-06-01
Full Text Available This paper reviews a methodical approach to solve multi-step dynamic problem of optimal integrated adaptive management of a product portfolio structure of the enterprise. For the organization of optimal adaptive terminal control of the system the recurrent algorithm, which reduces an initial multistage problem to the realization of the final sequence of problems of optimal program terminal control is offered. In turn, the decision of each problem of optimal program terminal control is reduced to the realization of the final sequence only single-step operations in the form of the problems solving of linear and convex mathematical programming. Thus, the offered approach allows to develop management solutions at current information support, which consider feedback, and which create the optimal structure of an enterprise’s product lines, contributing to optimising of profits, as well as maintenance of the desired level of profit for a long period of time
Dynamic analysis program for frame structure
International Nuclear Information System (INIS)
Ando, Kozo; Chiba, Toshio
1975-01-01
A general purpose computer program named ISTRAN/FD (Isub(HI) STRucture ANalysis/Frame structure, Dynamic analysis) has been developed for dynamic analysis of three-dimensional frame structures. This program has functions of free vibration analysis, seismic response analysis, graphic display by plotter and CRT, etc. This paper introduces ISTRAN/FD; examples of its application are shown with various problems : idealization of the cantilever, dynamic analysis of the main tower of the suspension bridge, three-dimensional vibration in the plate girder bridge, seismic response in the boiler steel structure, and dynamic properties of the underground LNG tank. In this last example, solid elements, in addition to beam elements, are especially used for the analysis. (auth.)
Generalization in adaptation to stable and unstable dynamics.
Directory of Open Access Journals (Sweden)
Abdelhamid Kadiallah
Full Text Available Humans skillfully manipulate objects and tools despite the inherent instability. In order to succeed at these tasks, the sensorimotor control system must build an internal representation of both the force and mechanical impedance. As it is not practical to either learn or store motor commands for every possible future action, the sensorimotor control system generalizes a control strategy for a range of movements based on learning performed over a set of movements. Here, we introduce a computational model for this learning and generalization, which specifies how to learn feedforward muscle activity in a function of the state space. Specifically, by incorporating co-activation as a function of error into the feedback command, we are able to derive an algorithm from a gradient descent minimization of motion error and effort, subject to maintaining a stability margin. This algorithm can be used to learn to coordinate any of a variety of motor primitives such as force fields, muscle synergies, physical models or artificial neural networks. This model for human learning and generalization is able to adapt to both stable and unstable dynamics, and provides a controller for generating efficient adaptive motor behavior in robots. Simulation results exhibit predictions consistent with all experiments on learning of novel dynamics requiring adaptation of force and impedance, and enable us to re-examine some of the previous interpretations of experiments on generalization.
Planar multibody dynamics formulation, programming and applications
Nikravesh, Parviz E
2007-01-01
Introduction Multibody Mechanical Systems Types of Analyses Methods of Formulation Computer Programming Application Examples Unit System Remarks Preliminaries Reference Axes Scalars and Vectors Matrices Vector, Array, and Matrix Differentiation Equations and Expressions Remarks Problems Fundamentals of Kinematics A Particle Kinematics of a Rigid Body Definitions Remarks Problems Fundamentals of Dynamics Newton's Laws of Motion Dynamics of a Body Force Elements Applied Forces Reaction Force Remarks Problems Point-Coordinates: Kinematics Multipoint
A Multi-Pathfinder for Developing Adaptive Robust Policies in System Dynamics
Hamarat, C.; Pruyt, E.; Loonen, E.T.
2013-01-01
Adaptivity is essential for dynamically complex and uncertain systems. Adaptive policymaking is an approach to design policies that can be adapted over time to how the future unfolds. It is crucial for adaptive policymaking to specify under what conditions and how to adapt the policy. The
Configuring Airspace Sectors with Approximate Dynamic Programming
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.
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.
Use of dynamic grid adaption in the ASWR-method
International Nuclear Information System (INIS)
Graf, U.; Romstedt, P.; Werner, W.
1985-01-01
A dynamic grid adaption method has been developed for use with the ASWR-method. The method automatically adapts the number and position of the spatial meshpoints as the solution of hyperbolic or parabolic vector partial differential equations progresses in time. The mesh selection algorithm is based on the minimization of the L 2 -norm of the spatial discretization error. The method permits accurate calculation of the evolution of inhomogenities like wave fronts, shock layers and other sharp transitions, while generally using a coarse computational grid. The number of required mesh points is significantly reduced, relative to a fixed Eulerian grid. Since the mesh selection algorithm is computationally inexpensive, a corresponding reduction of computing time results
Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks
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.
Adaptive learning by extremal dynamics and negative feedback
International Nuclear Information System (INIS)
Bak, Per; Chialvo, Dante R.
2001-01-01
We describe a mechanism for biological learning and adaptation based on two simple principles: (i) Neuronal activity propagates only through the network's strongest synaptic connections (extremal dynamics), and (ii) the strengths of active synapses are reduced if mistakes are made, otherwise no changes occur (negative feedback). The balancing of those two tendencies typically shapes a synaptic landscape with configurations which are barely stable, and therefore highly flexible. This allows for swift adaptation to new situations. Recollection of past successes is achieved by punishing synapses which have once participated in activity associated with successful outputs much less than neurons that have never been successful. Despite its simplicity, the model can readily learn to solve complicated nonlinear tasks, even in the presence of noise. In particular, the learning time for the benchmark parity problem scales algebraically with the problem size N, with an exponent k∼1.4
Elucidating Microbial Adaptation Dynamics via Autonomous Exposure and Sampling
Grace, Joseph M.; Verseux, Cyprien; Gentry, Diana; Moffet, Amy; Thayabaran, Ramanen; Wong, Nathan; Rothschild, Lynn
2013-01-01
The adaptation of micro-organisms to their environments is a complex process of interaction between the pressures of the environment and of competition. Reducing this multifactorial process to environmental exposure in the laboratory is a common tool for elucidating individual mechanisms of evolution, such as mutation rates. Although such studies inform fundamental questions about the way adaptation and even speciation occur, they are often limited by labor-intensive manual techniques. Current methods for controlled study of microbial adaptation limit the length of time, the depth of collected data, and the breadth of applied environmental conditions. Small idiosyncrasies in manual techniques can have large effects on outcomes; for example, there are significant variations in induced radiation resistances following similar repeated exposure protocols. We describe here a project under development to allow rapid cycling of multiple types of microbial environmental exposure. The system allows continuous autonomous monitoring and data collection of both single species and sampled communities, independently and concurrently providing multiple types of controlled environmental pressure (temperature, radiation, chemical presence or absence, and so on) to a microbial community in dynamic response to the ecosystem's current status. When combined with DNA sequencing and extraction, such a controlled environment can cast light on microbial functional development, population dynamics, inter- and intra-species competition, and microbe-environment interaction. The project's goal is to allow rapid, repeatable iteration of studies of both natural and artificial microbial adaptation. As an example, the same system can be used both to increase the pH of a wet soil aliquot over time while periodically sampling it for genetic activity analysis, or to repeatedly expose a culture of bacteria to the presence of a toxic metal, automatically adjusting the level of toxicity based on the
Dynamic and adaptive data-management in ATLAS
Lassnig, M; Branco, M; Molfetas, A
2010-01-01
Distributed data-management on the grid is subject to huge uncertainties yet static policies govern its usage. Due to the unpredictability of user behaviour, the high-latency and the heterogeneous nature of the environment, distributed data-management on the grid is challenging. In this paper we present the first steps towards a future dynamic data-management system that adapts to the changing conditions and environment. Such a system would eliminate the number of manual interventions and remove unnecessary software layers, thereby providing a higher quality of service to the collaboration.
Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems
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 synchronization between two different order and topology dynamical systems
International Nuclear Information System (INIS)
Bowong, S.; Moukam Kakmeni, F.M.; Yamapi, R.
2006-07-01
This contribution studies adaptive synchronization between two dynamical systems of different order whose topological structure is also different. By order we mean the number of first order differential equations. The problem is closely related to the synchronization of strictly different systems. The master system is given by a sixth order equation with chaotic behavior whereas the slave system is a fourth-order nonautonomous with rational nonlinear terms. Based on the Lyapunov stability theory, sufficient conditions for the synchronization have been analyzed theoretically and numerically. (author)
Hydrodynamics in adaptive resolution particle simulations: Multiparticle collision dynamics
Energy Technology Data Exchange (ETDEWEB)
Alekseeva, Uliana, E-mail: Alekseeva@itc.rwth-aachen.de [Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation (IAS), Forschungszentrum Jülich, D-52425 Jülich (Germany); German Research School for Simulation Sciences (GRS), Forschungszentrum Jülich, D-52425 Jülich (Germany); Winkler, Roland G., E-mail: r.winkler@fz-juelich.de [Theoretical Soft Matter and Biophysics, Institute for Advanced Simulation (IAS), Forschungszentrum Jülich, D-52425 Jülich (Germany); Sutmann, Godehard, E-mail: g.sutmann@fz-juelich.de [Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation (IAS), Forschungszentrum Jülich, D-52425 Jülich (Germany); ICAMS, Ruhr-University Bochum, D-44801 Bochum (Germany)
2016-06-01
A new adaptive resolution technique for particle-based multi-level simulations of fluids is presented. In the approach, the representation of fluid and solvent particles is changed on the fly between an atomistic and a coarse-grained description. The present approach is based on a hybrid coupling of the multiparticle collision dynamics (MPC) method and molecular dynamics (MD), thereby coupling stochastic and deterministic particle-based methods. Hydrodynamics is examined by calculating velocity and current correlation functions for various mixed and coupled systems. We demonstrate that hydrodynamic properties of the mixed fluid are conserved by a suitable coupling of the two particle methods, and that the simulation results agree well with theoretical expectations.
Dynamics of epidemic diseases on a growing adaptive network.
Demirel, Güven; Barter, Edmund; Gross, Thilo
2017-02-10
The study of epidemics on static networks has revealed important effects on disease prevalence of network topological features such as the variance of the degree distribution, i.e. the distribution of the number of neighbors of nodes, and the maximum degree. Here, we analyze an adaptive network where the degree distribution is not independent of epidemics but is shaped through disease-induced dynamics and mortality in a complex interplay. We study the dynamics of a network that grows according to a preferential attachment rule, while nodes are simultaneously removed from the network due to disease-induced mortality. We investigate the prevalence of the disease using individual-based simulations and a heterogeneous node approximation. Our results suggest that in this system in the thermodynamic limit no epidemic thresholds exist, while the interplay between network growth and epidemic spreading leads to exponential networks for any finite rate of infectiousness when the disease persists.
The Dynamic Geometrisation of Computer Programming
Sinclair, Nathalie; Patterson, Margaret
2018-01-01
The goal of this paper is to explore dynamic geometry environments (DGE) as a type of computer programming language. Using projects created by secondary students in one particular DGE, we analyse the extent to which the various aspects of computational thinking--including both ways of doing things and particular concepts--were evident in their…
A Dynamic Programming Approach to Constrained Portfolios
DEFF Research Database (Denmark)
Kraft, Holger; Steffensen, Mogens
2013-01-01
This paper studies constrained portfolio problems that may involve constraints on the probability or the expected size of a shortfall of wealth or consumption. Our first contribution is that we solve the problems by dynamic programming, which is in contrast to the existing literature that applies...
Quantum optical device accelerating dynamic programming
Grigoriev, D.; Kazakov, A.; Vakulenko, S.
2005-01-01
In this paper we discuss analogue computers based on quantum optical systems accelerating dynamic programming for some computational problems. These computers, at least in principle, can be realized by actually existing devices. We estimate an acceleration in resolving of some NP-hard problems that can be obtained in such a way versus deterministic computers
Microsoft Dynamics NAV 7 programming cookbook
Raul, Rakesh
2013-01-01
Written in the style of a cookbook. Microsoft Dynamics NAV 7 Programming Cookbook is full of recipes to help you get the job done.If you are a junior / entry-level NAV developer then the first half of the book is designed primarily for you. You may or may not have any experience programming. It focuses on the basics of NAV programming.If you are a mid-level NAV developer, you will find these chapters explain how to think outside of the NAV box when building solutions. There are also recipes that senior developers will find useful.
Efficient dynamic optimization of logic programs
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.
When do mixotrophs specialize? Adaptive dynamics theory applied to a dynamic energy budget model.
Troost, T.A.; Kooi, B.W.; Kooijman, S.A.L.M.
2005-01-01
In evolutionary history, several events have occurred at which mixotrophs specialized into pure autotrophs and heterotrophs. We studied the conditions under which such events take place, using the Dynamic Energy Budget (DEB) theory for physiological rules of the organisms' metabolism and Adaptive
Stochastic control theory dynamic programming principle
Nisio, Makiko
2015-01-01
This book offers a systematic introduction to the optimal stochastic control theory via the dynamic programming principle, which is a powerful tool to analyze control problems. First we consider completely observable control problems with finite horizons. Using a time discretization we construct a nonlinear semigroup related to the dynamic programming principle (DPP), whose generator provides the Hamilton–Jacobi–Bellman (HJB) equation, and we characterize the value function via the nonlinear semigroup, besides the viscosity solution theory. When we control not only the dynamics of a system but also the terminal time of its evolution, control-stopping problems arise. This problem is treated in the same frameworks, via the nonlinear semigroup. Its results are applicable to the American option price problem. Zero-sum two-player time-homogeneous stochastic differential games and viscosity solutions of the Isaacs equations arising from such games are studied via a nonlinear semigroup related to DPP (the min-ma...
Selective host molecules obtained by dynamic adaptive chemistry.
Matache, Mihaela; Bogdan, Elena; Hădade, Niculina D
2014-02-17
Up till 20 years ago, in order to endow molecules with function there were two mainstream lines of thought. One was to rationally design the positioning of chemical functionalities within candidate molecules, followed by an iterative synthesis-optimization process. The second was the use of a "brutal force" approach of combinatorial chemistry coupled with advanced screening for function. Although both methods provided important results, "rational design" often resulted in time-consuming efforts of modeling and synthesis only to find that the candidate molecule was not performing the designed job. "Combinatorial chemistry" suffered from a fundamental limitation related to the focusing of the libraries employed, often using lead compounds that limit its scope. Dynamic constitutional chemistry has developed as a combination of the two approaches above. Through the rational use of reversible chemical bonds together with a large plethora of precursor libraries, one is now able to build functional structures, ranging from quite simple molecules up to large polymeric structures. Thus, by introduction of the dynamic component within the molecular recognition processes, a new perspective of deciphering the world of the molecular events has aroused together with a new field of chemistry. Since its birth dynamic constitutional chemistry has continuously gained attention, in particular due to its ability to easily create from scratch outstanding molecular structures as well as the addition of adaptive features. The fundamental concepts defining the dynamic constitutional chemistry have been continuously extended to currently place it at the intersection between the supramolecular chemistry and newly defined adaptive chemistry, a pivotal feature towards evolutive chemistry. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A program for dynamic noise investigations of reactor systems
International Nuclear Information System (INIS)
Antonov, N.A.; Yaneva, N.B.
1980-01-01
A stochastic process analysis in nuclear reactors is used for the state diagnosis and dynamic characteristic investigation of the reactor system. A program DENSITY adapted and tested on an IBM 360 ES type computer is developed. The program is adjusted for fast processing of long series exploiting a relatively small memory. The testing procedure is discussed and the method of the periodic sequences corresponding to characteristic reactivity perturbations of the reactor systems is considered. The program is written for calculating the auto-power spectral density and the cross-power spectral density, as well as the coherence function of stationary statistical time series using the advantages of the fast Fourier transformation. In particular, it is shown that the multi-frequency binary sequences are very useful with respect to the signal-to-noise ratio and the frequency distribution in view of the frequency reactor test
A dynamical system that describes vein graft adaptation and failure.
Garbey, Marc; Berceli, Scott A
2013-11-07
Adaptation of vein bypass grafts to the mechanical stresses imposed by the arterial circulation is thought to be the primary determinant for lesion development, yet an understanding of how the various forces dictate local wall remodeling is lacking. We develop a dynamical system that summarizes the complex interplay between the mechanical environment and cell/matrix kinetics, ultimately dictating changes in the vein graft architecture. Based on a systematic mapping of the parameter space, three general remodeling response patterns are observed: (1) shear stabilized intimal thickening, (2) tension induced wall thinning and lumen expansion, and (3) tension stabilized wall thickening. Notable is our observation that the integration of multiple feedback mechanisms leads to a variety of non-linear responses that would be unanticipated by an analysis of each system component independently. This dynamic analysis supports the clinical observation that the majority of vein grafts proceed along an adaptive trajectory, where grafts dilate and mildly thicken in response to the increased tension and shear, but a small portion of the grafts demonstrate a maladaptive phenotype, where progressive inward remodeling and accentuated wall thickening lead to graft failure. © 2013 The Authors. Published by Elsevier Ltd. All rights reserved.
Adaptive sampling strategies with high-throughput molecular dynamics
Clementi, Cecilia
Despite recent significant hardware and software developments, the complete thermodynamic and kinetic characterization of large macromolecular complexes by molecular simulations still presents significant challenges. The high dimensionality of these systems and the complexity of the associated potential energy surfaces (creating multiple metastable regions connected by high free energy barriers) does not usually allow to adequately sample the relevant regions of their configurational space by means of a single, long Molecular Dynamics (MD) trajectory. Several different approaches have been proposed to tackle this sampling problem. We focus on the development of ensemble simulation strategies, where data from a large number of weakly coupled simulations are integrated to explore the configurational landscape of a complex system more efficiently. Ensemble methods are of increasing interest as the hardware roadmap is now mostly based on increasing core counts, rather than clock speeds. The main challenge in the development of an ensemble approach for efficient sampling is in the design of strategies to adaptively distribute the trajectories over the relevant regions of the systems' configurational space, without using any a priori information on the system global properties. We will discuss the definition of smart adaptive sampling approaches that can redirect computational resources towards unexplored yet relevant regions. Our approaches are based on new developments in dimensionality reduction for high dimensional dynamical systems, and optimal redistribution of resources. NSF CHE-1152344, NSF CHE-1265929, Welch Foundation C-1570.
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. Copyright © 2010 Elsevier B.V. All rights reserved.
Flatness-based adaptive fuzzy control of chaotic finance dynamics
Rigatos, G.; Siano, P.; Loia, V.; Tommasetti, A.; Troisi, O.
2017-11-01
A flatness-based adaptive fuzzy control is applied to the problem of stabilization of the dynamics of a chaotic finance system, describing interaction between the interest rate, the investment demand and the price exponent. By proving that the system is differentially flat and by applying differential flatness diffeomorphisms, its transformation to the linear canonical (Brunovsky) is performed. For the latter description of the system, the design of a stabilizing state feedback controller becomes possible. A first problem in the design of such a controller is that the dynamic model of the finance system is unknown and thus it has to be identified with the use neurofuzzy approximators. The estimated dynamics provided by the approximators is used in the computation of the control input, thus establishing an indirect adaptive control scheme. The learning rate of the approximators is chosen from the requirement the system's Lyapunov function to have always a negative first-order derivative. Another problem that has to be dealt with is that the control loop is implemented only with the use of output feedback. To estimate the non-measurable state vector elements of the finance system, a state observer is implemented in the control loop. The computation of the feedback control signal requires the solution of two algebraic Riccati equations at each iteration of the control algorithm. Lyapunov stability analysis demonstrates first that an H-infinity tracking performance criterion is satisfied. This signifies elevated robustness against modelling errors and external perturbations. Moreover, the global asymptotic stability is proven for the control loop.
Strategic tradeoffs in competitor dynamics on adaptive networks.
Hébert-Dufresne, Laurent; Allard, Antoine; Noël, Pierre-André; Young, Jean-Gabriel; Libby, Eric
2017-08-08
Recent empirical work highlights the heterogeneity of social competitions such as political campaigns: proponents of some ideologies seek debate and conversation, others create echo chambers. While symmetric and static network structure is typically used as a substrate to study such competitor dynamics, network structure can instead be interpreted as a signature of the competitor strategies, yielding competition dynamics on adaptive networks. Here we demonstrate that tradeoffs between aggressiveness and defensiveness (i.e., targeting adversaries vs. targeting like-minded individuals) creates paradoxical behaviour such as non-transitive dynamics. And while there is an optimal strategy in a two competitor system, three competitor systems have no such solution; the introduction of extreme strategies can easily affect the outcome of a competition, even if the extreme strategies have no chance of winning. Not only are these results reminiscent of classic paradoxical results from evolutionary game theory, but the structure of social networks created by our model can be mapped to particular forms of payoff matrices. Consequently, social structure can act as a measurable metric for social games which in turn allows us to provide a game theoretical perspective on online political debates.
Nonlinear attractor dynamics in the fundamental and extended prism adaptation paradigm
International Nuclear Information System (INIS)
Frank, T.D.; Blau, Julia J.C.; Turvey, M.T.
2009-01-01
Adaptation and re-adaptation processes are studied in terms of dynamic attractors that evolve and devolve. In doing so, a theoretical account is given for the fundamental observation that adaptation and re-adaptation processes do not exhibit one-trial learning. Moreover, the emergence of the latent aftereffect in the extended prism paradigm is addressed
Markdown Optimization via Approximate Dynamic Programming
Directory of Open Access Journals (Sweden)
Cos?gun
2013-02-01
Full Text Available We consider the markdown optimization problem faced by the leading apparel retail chain. Because of substitution among products the markdown policy of one product affects the sales of other products. Therefore, markdown policies for product groups having a significant crossprice elasticity among each other should be jointly determined. Since the state space of the problem is very huge, we use Approximate Dynamic Programming. Finally, we provide insights on the behavior of how each product price affects the markdown policy.
Joint Chance-Constrained Dynamic Programming
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.
Adaptive contact networks change effective disease infectiousness and dynamics.
Van Segbroeck, Sven; Santos, Francisco C; Pacheco, Jorge M
2010-08-19
Human societies are organized in complex webs that are constantly reshaped by a social dynamic which is influenced by the information individuals have about others. Similarly, epidemic spreading may be affected by local information that makes individuals aware of the health status of their social contacts, allowing them to avoid contact with those infected and to remain in touch with the healthy. Here we study disease dynamics in finite populations in which infection occurs along the links of a dynamical contact network whose reshaping may be biased based on each individual's health status. We adopt some of the most widely used epidemiological models, investigating the impact of the reshaping of the contact network on the disease dynamics. We derive analytical results in the limit where network reshaping occurs much faster than disease spreading and demonstrate numerically that this limit extends to a much wider range of time scales than one might anticipate. Specifically, we show that from a population-level description, disease propagation in a quickly adapting network can be formulated equivalently as disease spreading on a well-mixed population but with a rescaled infectiousness. We find that for all models studied here--SI, SIS and SIR--the effective infectiousness of a disease depends on the population size, the number of infected in the population, and the capacity of healthy individuals to sever contacts with the infected. Importantly, we indicate how the use of available information hinders disease progression, either by reducing the average time required to eradicate a disease (in case recovery is possible), or by increasing the average time needed for a disease to spread to the entire population (in case recovery or immunity is impossible).
Adaptive Dynamic Surface Control for Generator Excitation Control System
Directory of Open Access Journals (Sweden)
Zhang Xiu-yu
2014-01-01
Full Text Available For the generator excitation control system which is equipped with static var compensator (SVC and unknown parameters, a novel adaptive dynamic surface control scheme is proposed based on neural network and tracking error transformed function with the following features: (1 the transformation of the excitation generator model to the linear systems is omitted; (2 the prespecified performance of the tracking error can be guaranteed by combining with the tracking error transformed function; (3 the computational burden is greatly reduced by estimating the norm of the weighted vector of neural network instead of the weighted vector itself; therefore, it is more suitable for the real time control; and (4 the explosion of complicity problem inherent in the backstepping control can be eliminated. It is proved that the new scheme can make the system semiglobally uniformly ultimately bounded. Simulation results show the effectiveness of this control scheme.
Adaptation and learning: characteristic time scales of performance dynamics.
Newell, Karl M; Mayer-Kress, Gottfried; Hong, S Lee; Liu, Yeou-Teh
2009-12-01
A multiple time scales landscape model is presented that reveals structures of performance dynamics that were not resolved in the traditional power law analysis of motor learning. It shows the co-existence of separate processes during and between practice sessions that evolve in two independent dimensions characterized by time scales that differ by about an order of magnitude. Performance along the slow persistent dimension of learning improves often as much and sometimes more during rest (memory consolidation and/or insight generation processes) than during a practice session itself. In contrast, the process characterized by the fast, transient dimension of adaptation reverses direction between practice sessions, thereby significantly degrading performance at the beginning of the next practice session (warm-up decrement). The theoretical model fits qualitatively and quantitatively the data from Snoddy's [Snoddy, G. S. (1926). Learning and stability. Journal of Applied Psychology, 10, 1-36] classic learning study of mirror tracing and other averaged and individual data sets, and provides a new account of the processes of change in adaptation and learning. 2009 Elsevier B.V. All rights reserved.
Dynamic changes in brain activity during prism adaptation.
Luauté, Jacques; Schwartz, Sophie; Rossetti, Yves; Spiridon, Mona; Rode, Gilles; Boisson, Dominique; Vuilleumier, Patrik
2009-01-07
Prism adaptation does not only induce short-term sensorimotor plasticity, but also longer-term reorganization in the neural representation of space. We used event-related fMRI to study dynamic changes in brain activity during both early and prolonged exposure to visual prisms. Participants performed a pointing task before, during, and after prism exposure. Measures of trial-by-trial pointing errors and corrections allowed parametric analyses of brain activity as a function of performance. We show that during the earliest phase of prism exposure, anterior intraparietal sulcus was primarily implicated in error detection, whereas parieto-occipital sulcus was implicated in error correction. Cerebellum activity showed progressive increases during prism exposure, in accordance with a key role for spatial realignment. This time course further suggests that the cerebellum might promote neural changes in superior temporal cortex, which was selectively activated during the later phase of prism exposure and could mediate the effects of prism adaptation on cognitive spatial representations.
PAQ: Persistent Adaptive Query Middleware for Dynamic Environments
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.
Sandia Dynamic Materials Program Strategic Plan.
Energy Technology Data Exchange (ETDEWEB)
Flicker, Dawn Gustine [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Benage, John F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Desjarlais, Michael P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Knudson, Marcus D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Leifeste, Gordon T. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lemke, Raymond W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mattsson, Thomas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wise, Jack L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-05-01
Materials in nuclear and conventional weapons can reach multi-megabar pressures and 1000s of degree temperatures on timescales ranging from microseconds to nanoseconds. Understanding the response of complex materials under these conditions is important for designing and assessing changes to nuclear weapons. In the next few decades, a major concern will be evaluating the behavior of aging materials and remanufactured components. The science to enable the program to underwrite decisions quickly and confidently on use, remanufacturing, and replacement of these materials will be critical to NNSA’s new Stockpile Responsiveness Program. Material response is also important for assessing the risks posed by adversaries or proliferants. Dynamic materials research, which refers to the use of high-speed experiments to produce extreme conditions in matter, is an important part of NNSA’s Stockpile Stewardship Program.
Dynamic programming algorithms for biological sequence comparison.
Pearson, W R; Miller, W
1992-01-01
Efficient dynamic programming algorithms are available for a broad class of protein and DNA sequence comparison problems. These algorithms require computer time proportional to the product of the lengths of the two sequences being compared [O(N2)] but require memory space proportional only to the sum of these lengths [O(N)]. Although the requirement for O(N2) time limits use of the algorithms to the largest computers when searching protein and DNA sequence databases, many other applications of these algorithms, such as calculation of distances for evolutionary trees and comparison of a new sequence to a library of sequence profiles, are well within the capabilities of desktop computers. In particular, the results of library searches with rapid searching programs, such as FASTA or BLAST, should be confirmed by performing a rigorous optimal alignment. Whereas rapid methods do not overlook significant sequence similarities, FASTA limits the number of gaps that can be inserted into an alignment, so that a rigorous alignment may extend the alignment substantially in some cases. BLAST does not allow gaps in the local regions that it reports; a calculation that allows gaps is very likely to extend the alignment substantially. Although a Monte Carlo evaluation of the statistical significance of a similarity score with a rigorous algorithm is much slower than the heuristic approach used by the RDF2 program, the dynamic programming approach should take less than 1 hr on a 386-based PC or desktop Unix workstation. For descriptive purposes, we have limited our discussion to methods for calculating similarity scores and distances that use gap penalties of the form g = rk. Nevertheless, programs for the more general case (g = q+rk) are readily available. Versions of these programs that run either on Unix workstations, IBM-PC class computers, or the Macintosh can be obtained from either of the authors.
Cluster Optimization and Parallelization of Simulations with Dynamically Adaptive Grids
Schreiber, Martin; Weinzierl, Tobias; Bungartz, Hans-Joachim
2013-01-01
The present paper studies solvers for partial differential equations that work on dynamically adaptive grids stemming from spacetrees. Due to the underlying tree formalism, such grids efficiently can be decomposed into connected grid regions (clusters) on-the-fly. A graph on those clusters classified according to their grid invariancy, workload, multi-core affinity, and further meta data represents the inter-cluster communication. While stationary clusters already can be handled more efficiently than their dynamic counterparts, we propose to treat them as atomic grid entities and introduce a skip mechanism that allows the grid traversal to omit those regions completely. The communication graph ensures that the cluster data nevertheless are kept consistent, and several shared memory parallelization strategies are feasible. A hyperbolic benchmark that has to remesh selected mesh regions iteratively to preserve conforming tessellations acts as benchmark for the present work. We discuss runtime improvements resulting from the skip mechanism and the implications on shared memory performance and load balancing. © 2013 Springer-Verlag.
Loss Aversion, Adaptive Beliefs, and Asset Pricing Dynamics
Directory of Open Access Journals (Sweden)
Kamal Samy Selim
2015-01-01
Full Text Available We study asset pricing dynamics in artificial financial markets model. The financial market is populated with agents following two heterogeneous trading beliefs, the technical and the fundamental prediction rules. Agents switch between trading rules with respect to their past performance. The agents are loss averse over asset price fluctuations. Loss aversion behaviour depends on the past performance of the trading strategies in terms of an evolutionary fitness measure. We propose a novel application of the prospect theory to agent-based modelling, and by simulation, the effect of evolutionary fitness measure on adaptive belief system is investigated. For comparison, we study pricing dynamics of a financial market populated with chartists perceive losses and gains symmetrically. One of our contributions is validating the agent-based models using real financial data of the Egyptian Stock Exchange. We find that our framework can explain important stylized facts in financial time series, such as random walk price behaviour, bubbles and crashes, fat-tailed return distributions, power-law tails in the distribution of returns, excess volatility, volatility clustering, the absence of autocorrelation in raw returns, and the power-law autocorrelations in absolute returns. In addition to this, we find that loss aversion improves market quality and market stability.
Adaptation of an asthma management program to a small clinic.
Kwong, Kenny Yat-Choi; Redjal, Nasser; Scott, Lyne; Li, Marilyn; Thobani, Salima; Yang, Brian
2017-07-01
Asthma management programs, such as the Breathmobile program, have been extremely effective in reducing asthma morbidity and increasing disease control; however, their high start-up costs may preclude their implementation in smaller health systems. In this study, we extended validated asthma disease management principles from the Breathmobile program to a smaller clinic system utilizing existing resources and compared clinical outcomes. Cox-regression analyses were conducted to determine the cumulative probability that a new patient entering the program would achieve improved clinical control of asthma with each subsequent visit to the program. A weekly asthma disease management clinic was initiated in an existing multi-specialty pediatric clinic in collaboration with the Breathmobile program. Existing nursing staff was utilized in conjunction with an asthma specialist provider. Patients were referred from a regional healthcare maintenance organization and patients were evaluated and treated every 2 months. Reduction in emergency department (ED) visits and hospitalizations, and improvements in asthma control were assessed at the end of 1 year. A total of 116 patients were enrolled over a period of 1 year. Mean patient age was 6.4 years at the time of their first visit. Patient ethnicity was self-described predominantly as Hispanic or African American. Initial asthma severity for most patients, classified in accordance with national guidelines, was "moderate persistent." After 1 year of enrollment, there was a 69% and 92% reduction in ED/urgent care visits and hospitalizations, respectively, compared with the year before enrollment. Up to 70% of patients achieved asthma control by the third visit. Thirty-six different patients were seen during 1 year for a total of $15,938.70 in contracted reimbursements. A large-scale successful asthma management program can be adapted to a stationary clinic system and achieve comparable results.
Adaptive control of dynamic balance in human gait on a split-belt treadmill.
Buurke, Tom J W; Lamoth, Claudine J C; Vervoort, Danique; van der Woude, Lucas H V; den Otter, Rob
2018-05-17
Human bipedal gait is inherently unstable and staying upright requires adaptive control of dynamic balance. Little is known about adaptive control of dynamic balance in reaction to long-term, continuous perturbations. We examined how dynamic balance control adapts to a continuous perturbation in gait, by letting people walk faster with one leg than the other on a treadmill with two belts (i.e. split-belt walking). In addition, we assessed whether changes in mediolateral dynamic balance control coincide with changes in energy use during split-belt adaptation. In nine minutes of split-belt gait, mediolateral margins of stability and mediolateral foot roll-off changed during adaptation to the imposed gait asymmetry, especially on the fast side, and returned to baseline during washout. Interestingly, no changes in mediolateral foot placement (i.e. step width) were found during split-belt adaptation. Furthermore, the initial margin of stability and subsequent mediolateral foot roll-off were strongly coupled to maintain mediolateral dynamic balance throughout the gait cycle. Consistent with previous results net metabolic power was reduced during split-belt adaptation, but changes in mediolateral dynamic balance control were not correlated with the reduction of net metabolic power during split-belt adaptation. Overall, this study has shown that a complementary mechanism of relative foot positioning and mediolateral foot roll-off adapts to continuously imposed gait asymmetry to maintain dynamic balance in human bipedal gait. © 2018. Published by The Company of Biologists Ltd.
Directory of Open Access Journals (Sweden)
Guillermo J. Martínez Pastur
2007-09-01
Full Text Available Social demands related to native forest ecosystems are based on an efficient management, with a balance between conservation and timber production. This paper describes the industry adaptation to a biodiversity program with an alternative regeneration method. The proposed method leaves 30% of the timber-quality forest as aggregated retention and 15 m² ha-1 basal area as dispersed retention. While many costs increased considerably, the incomes also may increase by applying new management strategies and technology innovation. A monitoring program was established in the harvested stands to evaluate the ecological functionality of the applied regeneration system (forest structure, climate change, regeneration dynamics, habitat quality and abiotic cycles. The implementation of an innovated technology and monitoring program in the forest and industry determined a balance between economic values and biodiversity conservation.
The Import-Substitution Adaptation of Power Engineering Programs
Directory of Open Access Journals (Sweden)
Aleksandr N. Kuzminov
2017-03-01
Full Text Available The realization problem of the import substitution policy in the context of existing programs for the individual branches development is considered in the paper on the example of power engineering. There is a contradiction to the objective of programs reflected in the process of alignment, which consists in stabilizing on the one hand and on the development of innovative on the other hand. In addition, the analysis of the implementation of power engineering of the Russian Federation for 2010-2020 and up to 2030 revealed significant shortcomings and deficiencies that reinforce the negative trends of this pairing. Classification of problems and purpose allowed choosing the most significant conceptual directions, methodologically based on the ideas of self-organization and balance, which can get instrumentality software by adapting programs for the development of power engineering in the system of the European model of Industry 4.0. As a fundamental position addresses the need for such a project, which would ensure the greatest impact with limited resources, including public funding, which lags far behind foreign. It is proposed to transform the efforts to implement the existing strategies of industry development in view of the policy of import substitution based on the implementation of the program of production of a balanced range of innovative products and providing replacement of imported equipment and the formation of the technological basis for the development of the industry
Automated Flight Routing Using Stochastic Dynamic Programming
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
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.
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.
A mathematical programming approach for sequential clustering of dynamic networks
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.
Approximate Dynamic Programming in Tracking Control of a Robotic Manipulator
Directory of Open Access Journals (Sweden)
Marcin Szuster
2016-02-01
Full Text Available This article focuses on the implementation of an approximate dynamic programming algorithm in the discrete tracking control system of the three-degrees of freedom Scorbot-ER 4pc robotic manipulator. The controlled system is included in an articulated robots group which uses rotary joints to access their work space. The main part of the control system is a dual heuristic dynamic programming algorithm that consists of two structures designed in the form of neural networks: an actor and a critic. The actor generates the suboptimal control law while the critic approximates the difference of the value function from Bellman's equation with respect to the state. The residual elements of the control system are the PD controller, the supervisory term and an additional control signal. The structure of the supervisory term derives from the stability analysis performed using the Lyapunov stability theorem. The control system works online, the neural networks' weights-adaptation procedure is performed in every iteration step, and the neural networks' preliminary learning process is not required. The performance of the control system was verified by a series of computer simulations and experiments performed using the Scorbot-ER 4pc robotic manipulator.
Energy Technology Data Exchange (ETDEWEB)
Halfmann, C.; Holzmann, H.; Isermann, R. [Technische Univ. Darmstadt (Germany). Inst. fuer Automatisierungstechnik; Hamann, C.D.; Simm, N. [Opel (A.) AG, Ruesselsheim (Germany). Gruppe Chassis und Fahrerassistenzsysteme
1999-12-01
The application of modern simulation tools offering additional support during the vehicle development process is accepted to a large extent by most car manufacturers. Just like new model-based control strategies, these simulation investigations require very accurate - and thus very complex - models of vehicle dynamics, which can be processed in real time. As an example of such a vehicle model, this article describes a real-time vehicle simulation model which was developed at the Institute of Automatic Control at Darmstadt University of Technology, in co-operation with the ITDC of the Adam OPEL AG. By applying modern adaptation techniques, this vehicle model is able to calculate onboard the important variables describing the actual driving state even if the environmental conditions change. (orig.) [German] Der Einsatz von Simulationswerkzeugen zur Unterstuetzung der Fahrzeugentwicklung hat sich bei den meisten Automobilherstellern weitgehend durchgesetzt. Ebenso wie neuartige modellbasierte Regelstrategien verlangen diese Simulationsuntersuchungen nach immer exakteren - und damit komplexeren - fahrdynamischen Modellen, die in Echtzeit ausgewertet werden. Als Beispiel fuer ein solches Gesamtfahrzeugmodell beschreibt dieser Beitrag ein echtzeitfaehiges Modell fuer die Bewegung des Fahrzeugs um alle drei Hauptachsen, das am Institut fuer Automatisierungstechnik der TU Darmstadt in Kooperation mit dem Internationalen Technischen Entwicklungszentrum (ITEZ) der Adam Opel AG entwickelt wurde. Es ist durch den Einsatz von Adaptionsmethoden in der Lage, wichtige fahrdynamische Zustandsgroessen im Fahrzeug auch unter veraenderlichen Umgebungsbedingungen zu ermitteln. (orig.)
Quinoa - Adaptive Computational Fluid Dynamics, 0.2
Energy Technology Data Exchange (ETDEWEB)
2017-09-22
Quinoa is a set of computational tools that enables research and numerical analysis in fluid dynamics. At this time it remains a test-bed to experiment with various algorithms using fully asynchronous runtime systems. Currently, Quinoa consists of the following tools: (1) Walker, a numerical integrator for systems of stochastic differential equations in time. It is a mathematical tool to analyze and design the behavior of stochastic differential equations. It allows the estimation of arbitrary coupled statistics and probability density functions and is currently used for the design of statistical moment approximations for multiple mixing materials in variable-density turbulence. (2) Inciter, an overdecomposition-aware finite element field solver for partial differential equations using 3D unstructured grids. Inciter is used to research asynchronous mesh-based algorithms and to experiment with coupling asynchronous to bulk-synchronous parallel code. Two planned new features of Inciter, compared to the previous release (LA-CC-16-015), to be implemented in 2017, are (a) a simple Navier-Stokes solver for ideal single-material compressible gases, and (b) solution-adaptive mesh refinement (AMR), which enables dynamically concentrating compute resources to regions with interesting physics. Using the NS-AMR problem we plan to explore how to scale such high-load-imbalance simulations, representative of large production multiphysics codes, to very large problems on very large computers using an asynchronous runtime system. (3) RNGTest, a test harness to subject random number generators to stringent statistical tests enabling quantitative ranking with respect to their quality and computational cost. (4) UnitTest, a unit test harness, running hundreds of tests per second, capable of testing serial, synchronous, and asynchronous functions. (5) MeshConv, a mesh file converter that can be used to convert 3D tetrahedron meshes from and to either of the following formats: Gmsh
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.
An Adaptive Learning Based Network Selection Approach for 5G Dynamic Environments
Directory of Open Access Journals (Sweden)
Xiaohong Li
2018-03-01
Full Text Available Networks will continue to become increasingly heterogeneous as we move toward 5G. Meanwhile, the intelligent programming of the core network makes the available radio resource be more changeable rather than static. In such a dynamic and heterogeneous network environment, how to help terminal users select optimal networks to access is challenging. Prior implementations of network selection are usually applicable for the environment with static radio resources, while they cannot handle the unpredictable dynamics in 5G network environments. To this end, this paper considers both the fluctuation of radio resources and the variation of user demand. We model the access network selection scenario as a multiagent coordination problem, in which a bunch of rationally terminal users compete to maximize their benefits with incomplete information about the environment (no prior knowledge of network resource and other users’ choices. Then, an adaptive learning based strategy is proposed, which enables users to adaptively adjust their selections in response to the gradually or abruptly changing environment. The system is experimentally shown to converge to Nash equilibrium, which also turns out to be both Pareto optimal and socially optimal. Extensive simulation results show that our approach achieves significantly better performance compared with two learning and non-learning based approaches in terms of load balancing, user payoff and the overall bandwidth utilization efficiency. In addition, the system has a good robustness performance under the condition with non-compliant terminal users.
Implementing a Dynamic Street-Children's Program: Successes and ...
African Journals Online (AJOL)
dynamic street children's program in Mzuzu Malawi – using a developmental ... dynamics of parentchild, parent-parent and child-parent-environment; life-events; ... of child and adolescent development, and how they can influence the child's ...
Gao, Zilin; Wang, Yinhe; Zhang, Lili
2018-02-01
In the existing research results of the complex dynamical networks controlled, the controllers are mainly used to guarantee the synchronization or stabilization of the nodes’ state, and the terms coupled with connection relationships may affect the behaviors of nodes, this obviously ignores the dynamic common behavior of the connection relationships between the nodes. In fact, from the point of view of large-scale system, a complex dynamical network can be regarded to be composed of two time-varying dynamic subsystems, which can be called the nodes subsystem and the connection relationships subsystem, respectively. Similar to the synchronization or stabilization of the nodes subsystem, some characteristic phenomena can be also emerged in the connection relationships subsystem. For example, the structural balance in the social networks and the synaptic facilitation in the biological neural networks. This paper focuses on the structural balance in dynamic complex networks. Generally speaking, the state of the connection relationships subsystem is difficult to be measured accurately in practical applications, and thus it is not easy to implant the controller directly into the connection relationships subsystem. It is noted that the nodes subsystem and the relationships subsystem are mutually coupled, which implies that the state of the connection relationships subsystem can be affected by the controllable state of nodes subsystem. Inspired by this observation, by using the structural balance theory of triad, the controller with the parameter adaptive law is proposed for the nodes subsystem in this paper, which may ensure the connection relationship matrix to approximate a given structural balance matrix in the sense of the uniformly ultimately bounded (UUB). That is, the structural balance may be obtained by employing the controlling state of the nodes subsystem. Finally, the simulations are used to show the validity of the method in this paper.
Students' Adaptation in the Social and Cultural Dynamics
Sadyrin, Vladimir Vitalievich; Potapova, Marina Vladimirovna; Gnatyshina, Elena Alexandrovna; Uvarina, Nataliya Viktorovna; Danilova, Viktoriya Valerievna
2016-01-01
Modern scientific literature views issues on adaptation based on various aspects: biological, medical, pedagogical, sociological, cybernetic, interdisciplinary, etc. The given article is devoted to the analysis of the problem of adaptation as social and psychological phenomenon including peculiarities of its functioning in the conditions of social…
Body surface adaptations to boundary-layer dynamics
Videler, J.J.
1995-01-01
Evolutionary processes have adapted nektonic animals to interact efficiently with the water that surrounds them. Not all these adaptations serve the same purpose. This paper concentrates on reduction of drag due to friction in the boundary layer close to the body surface. Mucus, compliant skins,
Adaptation strategies of airline travel agencies to the dynamics of ...
African Journals Online (AJOL)
The role of airline travel agencies in a changing operational environment depends on their ability to adapt and survive in the airline travel industry. This paper examines the adaptation strategies airline travel agencies adopt to remain in business. Data for this paper was obtained through multi-stage sampling system that ...
Convergence of Sample Path Optimal Policies for Stochastic Dynamic Programming
National Research Council Canada - National Science Library
Fu, Michael C; Jin, Xing
2005-01-01
.... These results have practical implications for Monte Carlo simulation-based solution approaches to stochastic dynamic programming problems where it is impractical to extract the explicit transition...
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
Directory of Open Access Journals (Sweden)
James N Ingram
2011-09-01
Full Text Available Motor learning has been extensively studied using dynamic (force-field perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar
Tao, Ye; Xu, Lijia; Zhang, Zhen; Chen, Runfeng; Li, Huanhuan; Xu, Hui; Zheng, Chao; Huang, Wei
2016-08-03
Current static-state explorations of organic semiconductors for optimal material properties and device performance are hindered by limited insights into the dynamically changed molecular states and charge transport and energy transfer processes upon device operation. Here, we propose a simple yet successful strategy, resonance variation-based dynamic adaptation (RVDA), to realize optimized self-adaptive properties in donor-resonance-acceptor molecules by engineering the resonance variation for dynamic tuning of organic semiconductors. Organic light-emitting diodes hosted by these RVDA materials exhibit remarkably high performance, with external quantum efficiencies up to 21.7% and favorable device stability. Our approach, which supports simultaneous realization of dynamically adapted and selectively enhanced properties via resonance engineering, illustrates a feasible design map for the preparation of smart organic semiconductors capable of dynamic structure and property modulations, promoting the studies of organic electronics from static to dynamic.
Ready or Not: Microbial Adaptive Responses in Dynamic Symbiosis Environments.
Cao, Mengyi; Goodrich-Blair, Heidi
2017-08-01
In mutually beneficial and pathogenic symbiotic associations, microbes must adapt to the host environment for optimal fitness. Both within an individual host and during transmission between hosts, microbes are exposed to temporal and spatial variation in environmental conditions. The phenomenon of phenotypic variation, in which different subpopulations of cells express distinctive and potentially adaptive characteristics, can contribute to microbial adaptation to a lifestyle that includes rapidly changing environments. The environments experienced by a symbiotic microbe during its life history can be erratic or predictable, and each can impact the evolution of adaptive responses. In particular, the predictability of a rhythmic or cyclical series of environments may promote the evolution of signal transduction cascades that allow preadaptive responses to environments that are likely to be encountered in the future, a phenomenon known as adaptive prediction. In this review, we summarize environmental variations known to occur in some well-studied models of symbiosis and how these may contribute to the evolution of microbial population heterogeneity and anticipatory behavior. We provide details about the symbiosis between Xenorhabdus bacteria and Steinernema nematodes as a model to investigate the concept of environmental adaptation and adaptive prediction in a microbial symbiosis. Copyright © 2017 American Society for Microbiology.
Spatial cluster detection using dynamic programming
Directory of Open Access Journals (Sweden)
Sverchkov Yuriy
2012-03-01
Full Text Available Abstract Background The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. Methods We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. Results When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. Conclusions We conclude that the dynamic
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,…
Directory of Open Access Journals (Sweden)
Pusztai Beáta
2015-08-01
Full Text Available With respect to adaptation studies, contemporary Japanese popular culture signifies a unique case, as different types of media (be those textual, auditive, visual or audio-visual are tightly intertwined through the “recycling” of successful characters and stories. As a result, a neatly woven net of intermedial adaptations has been formed - the core of this complex system being the manga-anime-live-action film “adaptational triangle.” On the one hand, the paper addresses the interplay of the various factors by which the very existence of this network is made possible, such as the distinctive cultural attitude to “originality,” the structure of the comics, animation and film industries, and finally, the role of fictitious genealogies of both traditional and contemporary media in the negotiation of national identity. On the other hand, the essay also considers some of the most significant thematic, narrative, and stylistic effects this close interconnectedness has on the individual medium. Special attention is being paid to the nascent trend of merging the adaptive medium with that of the original story (viewing adaptation as integration, apparent in contemporary manga-based live- action comedies, as the extreme case of intermedial adaptation. That is, when the aim of the adaptational process is no longer the transposition of the story but the adaptation (i.e. the incorporation of the medium itself- elevating certain medium-specific devices into transmedial phenomena.
The Dynamics of Learning and the Emergence of Distributed Adaption
National Research Council Canada - National Science Library
Crutchfield, James P
2006-01-01
.... The second goal was to adapt this single-agent learning theory and associated learning algorithms to the distributed setting in which a population of autonomous agents communicate to achieve a desired group task...
Energy Technology Data Exchange (ETDEWEB)
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.
Greciano, Miguel Cristian
2016-01-01
This work focuses on the combination of two key concepts: Dynamic Difficulty Adjustment/Adaptation (video games adapting their difficulty according to the in-game performance of players, making themselves easier if the player performs poorly or more difficult if the player performs well) and Collaborative Multiplayer Games (video games where two or more human players work together to achieve a common goal). It considers and analyzes the challenges, potential and possibilities of Dynamic Diffi...
Dynamic adaptation of tendon and muscle connective tissue to mechanical loading
DEFF Research Database (Denmark)
Mackey, Abigail; Heinemeier, Katja Maria; Koskinen, Satu Osmi Anneli
2008-01-01
The connective tissue of tendon and skeletal muscle is a crucial structure for force transmission. A dynamic adaptive capacity of these tissues in healthy individuals is evident from reports of altered gene expression and protein levels of the fibrillar and network-forming collagens, when subjected...... in this article provide strong evidence for the highly adaptable nature of connective tissue in muscle and tendon....
International Nuclear Information System (INIS)
Han Liangxiu
2009-01-01
Grid computing aims to enable 'resource sharing and coordinated problem solving in dynamic, multi-institutional virtual organizations (VOs)'. However, due to the nature of heterogeneous and dynamic resources, dynamic failures in the distributed grid environment usually occur more than in traditional computation platforms, which cause failed VO formations. In this paper, we develop a novel self-adaptive mechanism to dynamic failures during VO formations. Such a self-adaptive scheme allows an individual and member of VOs to automatically find other available or replaceable one once a failure happens and therefore makes systems automatically recover from dynamic failures. We define dynamic failure situations of a system by using two standard indicators: mean time between failures (MTBF) and mean time to recover (MTTR). We model both MTBF and MTTR as Poisson distributions. We investigate and analyze the efficiency of the proposed self-adaptation mechanism to dynamic failures by comparing the success probability of VO formations before and after adopting it in three different cases: (1) different failure situations; (2) different organizational structures and scales; (3) different task complexities. The experimental results show that the proposed scheme can automatically adapt to dynamic failures and effectively improve the dynamic VO formation performance in the event of node failures, which provide a valuable addition to the field.
An Agent Model Integrating an Adaptive Model for Environmental Dynamics
Treur, J.; Umair, M.
2011-01-01
The environments in which agents are used often may be described by dynamical models, e.g., in the form of a set of differential equations. In this paper, an agent model is proposed that can perform model-based reasoning about the environment, based on a numerical (dynamical system) model of the
Techniques for grid manipulation and adaptation. [computational fluid dynamics
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.
Adaptive Competency Acquisition: Why LPN-to-ADN Career Mobility Education Programs Work.
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…
A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy
Directory of Open Access Journals (Sweden)
Ge Jianjun
2017-12-01
Full Text Available Nowadays, the battlefield environment has become much more complex and variable. This paper presents a quantitative method and lower bound for the amount of target information acquired from multiple radar observations to adaptively and dynamically organize the detection of battlefield resources based on the principle of information entropy. Furthermore, for minimizing the given information entropy’s lower bound for target measurement at every moment, a method to dynamically and adaptively select radars with a high amount of information for target tracking is proposed. The simulation results indicate that the proposed method has higher tracking accuracy than that of tracking without adaptive radar selection based on entropy.
Top-k Based Adaptive Enumeration in Constraint Programming
Directory of Open Access Journals (Sweden)
Ricardo Soto
2015-01-01
order for variables and values is employed along the search. In this paper, we present a new and more lightweight approach for performing adaptive enumeration. We incorporate a powerful classification technique named Top-k in order to adaptively select strategies along the resolution. We report results on a set of well-known benchmarks where the proposed approach noticeably competes with classical and modern adaptive enumeration methods for constraint satisfaction.
Advanced Dynamically Adaptive Algorithms for Stochastic Simulations on Extreme Scales
Energy Technology Data Exchange (ETDEWEB)
Xiu, Dongbin [Univ. of Utah, Salt Lake City, UT (United States)
2017-03-03
The focus of the project is the development of mathematical methods and high-performance computational tools for stochastic simulations, with a particular emphasis on computations on extreme scales. The core of the project revolves around the design of highly efficient and scalable numerical algorithms that can adaptively and accurately, in high dimensional spaces, resolve stochastic problems with limited smoothness, even containing discontinuities.
An extension of the classification of evolutionary singular strategies in Adaptive Dynamics
Boldin, Barbara; Diekmann, Odo
2014-01-01
The existing classification of evolutionarily singular strategies in Adaptive Dynamics (Geritz et al. in Evol Ecol 12:35–57, 1998; Metz et al. in Stochastic and spatial structures of dynamical systems, pp 183–231, 1996) assumes an invasion exponent that is differentiable twice as a function of both
Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin
2014-03-01
In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Adaptive control of an exoskeleton robot with uncertainties on kinematics and dynamics.
Brahmi, Brahim; Saad, Maarouf; Ochoa-Luna, Cristobal; Rahman, Mohammad H
2017-07-01
In this paper, we propose a new adaptive control technique based on nonlinear sliding mode control (JSTDE) taking into account kinematics and dynamics uncertainties. This approach is applied to an exoskeleton robot with uncertain kinematics and dynamics. The adaptation design is based on Time Delay Estimation (TDE). The proposed strategy does not necessitate the well-defined dynamic and kinematic models of the system robot. The updated laws are designed using Lyapunov-function to solve the adaptation problem systematically, proving the close loop stability and ensuring the convergence asymptotically of the outputs tracking errors. Experiments results show the effectiveness and feasibility of JSTDE technique to deal with the variation of the unknown nonlinear dynamics and kinematics of the exoskeleton model.
Quantitative adaptation analytics for assessing dynamic systems of systems: LDRD Final Report
Energy Technology Data Exchange (ETDEWEB)
Gauthier, John H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). System Readiness & Sustainment Technologies (6133, M/S 1188); Miner, Nadine E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Military & Energy Systems Analysis (6114, M/S 1188); Wilson, Michael L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Resilience and Regulatory Effects (6921, M/S 1138); Le, Hai D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). System Readiness & Sustainment Technologies (6133, M/S 1188); Kao, Gio K. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Networked System Survivability & Assurance (5629, M/S 0671); Melander, Darryl J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Software Systems R& D (9525, M/S 1188); Longsine, Dennis Earl [Sandia National Laboratories, Unknown, Unknown; Vander Meer, Jr., Robert C. [SAIC, Inc., Albuquerque, NM (United States)
2015-01-01
Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combining the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.
Strategies in edge plasma simulation using adaptive dynamic nodalization techniques
International Nuclear Information System (INIS)
Kainz, A.; Weimann, G.; Kamelander, G.
2003-01-01
A wide span of steady-state and transient edge plasma processes simulation problems require accurate discretization techniques and can then be treated with Finite Element (FE) and Finite Volume (FV) methods. The software used here to meet these meshing requirements is a 2D finite element grid generator. It allows to produce adaptive unstructured grids taking into consideration the flux surface characteristics. To comply with the common mesh handling features of FE/FV packages, some options have been added to the basic generation tool. These enhancements include quadrilateral meshes without non-regular transition elements obtained by substituting them by transition constructions consisting of regular quadrilateral elements. Furthermore triangular grids can be created with one edge parallel to the magnetic field and modified by the basic adaptation/realignment techniques. Enhanced code operation properties and processing capabilities are expected. (author)
Dynamics of Individual and Collective Agricultural Adaptation to Water Scarcity
Burchfield, E. K.; Gilligan, J. M.
2016-12-01
Drought and water scarcity are challenging agricultural systems around the world. We draw on extensive field-work conducted with paddy farmers in rural Sri Lanka to study adaptations to water scarcity, including switching to less water-intensive crops, farming collectively on shared land, and turning to groundwater by digging wells. We explore how variability in climate affects agricultural decision-making at the community and individual levels using three decision-making heuristics, each characterized by an objective function: risk-averse expected utility, regret-adjusted expected utility, and prospect theory loss-aversion. We also assess how the introduction of individualized access to irrigation water with wells affects long-standing community-based drought mitigation practices. Results suggest that the growth of well-irrigation may produce sudden disruptions to community-based adaptations, but that this depends on the mental models farmers use to think about risk and make decisions under uncertainty.
Zealotry effects on opinion dynamics in the adaptive voter model
Klamser, Pascal P.; Wiedermann, Marc; Donges, Jonathan F.; Donner, Reik V.
2017-11-01
The adaptive voter model has been widely studied as a conceptual model for opinion formation processes on time-evolving social networks. Past studies on the effect of zealots, i.e., nodes aiming to spread their fixed opinion throughout the system, only considered the voter model on a static network. Here we extend the study of zealotry to the case of an adaptive network topology co-evolving with the state of the nodes and investigate opinion spreading induced by zealots depending on their initial density and connectedness. Numerical simulations reveal that below the fragmentation threshold a low density of zealots is sufficient to spread their opinion to the whole network. Beyond the transition point, zealots must exhibit an increased degree as compared to ordinary nodes for an efficient spreading of their opinion. We verify the numerical findings using a mean-field approximation of the model yielding a low-dimensional set of coupled ordinary differential equations. Our results imply that the spreading of the zealots' opinion in the adaptive voter model is strongly dependent on the link rewiring probability and the average degree of normal nodes in comparison with that of the zealots. In order to avoid a complete dominance of the zealots' opinion, there are two possible strategies for the remaining nodes: adjusting the probability of rewiring and/or the number of connections with other nodes, respectively.
Dynamic Nature of Noncoding RNA Regulation of Adaptive Immune Response
Directory of Open Access Journals (Sweden)
Franca Citarella
2013-08-01
Full Text Available Immune response plays a fundamental role in protecting the organism from infections; however, dysregulation often occurs and can be detrimental for the organism, leading to a variety of immune-mediated diseases. Recently our understanding of the molecular and cellular networks regulating the immune response, and, in particular, adaptive immunity, has improved dramatically. For many years, much of the focus has been on the study of protein regulators; nevertheless, recent evidence points to a fundamental role for specific classes of noncoding RNAs (ncRNAs in regulating development, activation and homeostasis of the immune system. Although microRNAs (miRNAs are the most comprehensive and well-studied, a number of reports suggest the exciting possibility that long ncRNAs (lncRNAs could mediate host response and immune function. Finally, evidence is also accumulating that suggests a role for miRNAs and other small ncRNAs in autocrine, paracrine and exocrine signaling events, thus highlighting an elaborate network of regulatory interactions mediated by different classes of ncRNAs during immune response. This review will explore the multifaceted roles of ncRNAs in the adaptive immune response. In particular, we will focus on the well-established role of miRNAs and on the emerging role of lncRNAs and circulating ncRNAs, which all make indispensable contributions to the understanding of the multilayered modulation of the adaptive immune response.
Approximate Dynamic Programming Solving the Curses of Dimensionality
Powell, Warren B
2011-01-01
Praise for the First Edition "Finally, a book devoted to dynamic programming and written using the language of operations research (OR)! This beautiful book fills a gap in the libraries of OR specialists and practitioners."-Computing Reviews This new edition showcases a focus on modeling and computation for complex classes of approximate dynamic programming problems Understanding approximate dynamic programming (ADP) is vital in order to develop practical and high-quality solutions to complex industrial problems, particularly when those problems involve making decisions in the presence of unce
Granular contact dynamics using mathematical programming methods
DEFF Research Database (Denmark)
Krabbenhoft, K.; Lyamin, A. V.; Huang, J.
2012-01-01
granular contact dynamics formulation uses an implicit time discretization, thus allowing for large time steps. Moreover, in the limit of an infinite time step, the general dynamic formulation reduces to a static formulation that is useful in simulating common quasi-static problems such as triaxial tests...... is developed and it is concluded that the associated sliding rule, in the context of granular contact dynamics, may be viewed as an artifact of the time discretization and that the use of an associated flow rule at the particle scale level generally is physically acceptable. (C) 2012 Elsevier Ltd. All rights...
Adaptive spectrum decision framework for heterogeneous dynamic spectrum access networks
CSIR Research Space (South Africa)
Masonta, M
2015-09-01
Full Text Available Spectrum decision is the ability of a cognitive radio (CR) system to select the best available spectrum band to satisfy dynamic spectrum access network (DSAN) users¿ quality of service (QoS) requirements without causing harmful interference...
Privacy context model for dynamic privacy adaptation in ubiquitous computing
Schaub, Florian; Koenings, Bastian; Dietzel, Stefan; Weber, M.; Kargl, Frank
Ubiquitous computing is characterized by the merger of physical and virtual worlds as physical artifacts gain digital sensing, processing, and communication capabilities. Maintaining an appropriate level of privacy in the face of such complex and often highly dynamic systems is challenging. We argue
Vehicle-to-infrastructure program cooperative adaptive cruise control.
2015-03-01
This report documents the work completed by the Crash Avoidance Metrics Partners LLC (CAMP) Vehicle to Infrastructure (V2I) Consortium during the project titled Cooperative Adaptive Cruise Control (CACC). Participating companies in the V2I Cons...
Stochastic dynamic programming model for optimal resource ...
Indian Academy of Sciences (India)
M Bhuvaneswari
2018-04-11
Apr 11, 2018 ... handover in VANET; because of high dynamics in net- work topology, collaboration ... containers, doctors, nurses, cash and stocks. Similarly, ... GTBA does not take the resource types and availability into consideration.
A parameter-adaptive dynamic programming approach for inferring cophylogenies
DEFF Research Database (Denmark)
Merkle, Daniel; Middendorf, Martin; Wieseke, Nicolas
2010-01-01
Background: Coevolutionary systems like hosts and their parasites are commonly used model systems for evolutionary studies. Inferring the coevolutionary history based on given phylogenies of both groups is often done by employing a set of possible types of events that happened during coevolution....
Dynamic Programming Algorithms in Speech Recognition
Directory of Open Access Journals (Sweden)
Titus Felix FURTUNA
2008-01-01
Full Text Available In a system of speech recognition containing words, the recognition requires the comparison between the entry signal of the word and the various words of the dictionary. The problem can be solved efficiently by a dynamic comparison algorithm whose goal is to put in optimal correspondence the temporal scales of the two words. An algorithm of this type is Dynamic Time Warping. This paper presents two alternatives for implementation of the algorithm designed for recognition of the isolated words.
What to change and what to keep? Values and dynamics of adaptation to climate change
Directory of Open Access Journals (Sweden)
Sebastian Wessels
2015-04-01
Full Text Available This paper uses a complex systems theory framework to clarify what adaptation to climate change means in practice, which is to make targeted changes to a society's functioning in order to avoid changes happening to that which is of value to the members of that society. It is shown that the question what is to be changed and what to be preserved is not prescribed by the facts of climate change and technology, but a contingent one to be made by society. Discussing four important domains of adaptation and the respective narratives found in academia and politics, it is investigated how these decisions are formed, giving special consideration to the case of Germany. This leads to the finding that the generally defensive framings that characterizes common notions of adaptation reinforce predominant cultural paradigms and social dynamics that arguably have contributed considerably to the need for adaptation to climate change in the first place and will most likely create further need for adaptation in the future. A paradoxical tendency to accelerate predominant social dynamics in attempts to keep current states of affairs unchanged is identified. It is concluded that the concept of adaptation is a regression behind the concept of sustainability which can easily accommodate adaptation needs but avoids the identified pitfalls of adaptation by its future orientation and oft-criticized openness.
International Nuclear Information System (INIS)
Hunter, J.A.
1984-01-01
Equipment qualification research is being conducted to investigate acceptable criteria, requirements, and methodologies for the dynamic (including seismic) and environmental qualification of mechanical equipment and for the dynamic (including seismic) qualification of electrical equipment. The program is organized into three elements: (1) General Research, (2) Environmental Research, and (3) Dynamic Research. This paper presents the highlights of the results to date in these three elements of the program
Dynamically adaptive data-driven simulation of extreme hydrological flows
Kumar Jain, Pushkar; Mandli, Kyle; Hoteit, Ibrahim; Knio, Omar; Dawson, Clint
2018-02-01
Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.
Dynamically adaptive data-driven simulation of extreme hydrological flows
Kumar Jain, Pushkar
2017-12-27
Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.
Dynamic programming approach to optimization of approximate decision rules
Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata
2013-01-01
This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number
Dynamic Programming Approach for Exact Decision Rule Optimization
Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata
2013-01-01
This chapter is devoted to the study of an extension of dynamic programming approach that allows sequential optimization of exact decision rules relative to the length and coverage. It contains also results of experiments with decision tables from
Evolutionary programming for goal-driven dynamic planning
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
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. PsycINFO Database Record (c) 2013 APA, all rights reserved
Dynamic Modelling and Adaptive Traction Control for Mobile Robots
Directory of Open Access Journals (Sweden)
A. Albagul
2004-09-01
Full Text Available Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used kinematic models to develop motion control strategy for mobile robots. Their argument and assumption that these models are valid if the robot has low speed, low acceleration and light load. However, dynamic modelling of mobile robots is very important as they are designed to travel at higher speed and perform heavy duty work. This paper presents and discusses a new approach to develop a dynamic model and control strategy for wheeled mobile robot which I modelled as a rigid body that roles on two wheels and a castor. The motion control strategy consists of two levels. The first level is dealing with the dynamic of the system and denoted as ‘Low’ level controller. The second level is developed to take care of path planning and trajectory generation.
Novel Fuzzy-Modeling-Based Adaptive Synchronization of Nonlinear Dynamic Systems
Directory of Open Access Journals (Sweden)
Shih-Yu Li
2017-01-01
Full Text Available In this paper, a novel fuzzy-model-based adaptive synchronization scheme and its fuzzy update laws of parameters are proposed to address the adaptive synchronization problem. The proposed fuzzy controller does not share the same premise of fuzzy system, and the numbers of fuzzy controllers is reduced effectively through the novel modeling strategy. In addition, based on the adaptive synchronization scheme, the error dynamic system can be guaranteed to be asymptotically stable and the true values of unknown parameters can be obtained. Two identical complicated dynamic systems, Mathieu-Van der pol system (M-V system with uncertainties, are illustrated for numerical simulation example to show the effectiveness and feasibility of the proposed novel adaptive control strategy.
Adaptive and dynamic meshing methods for numerical simulations
Acikgoz, Nazmiye
For the numerical simulation of many problems of engineering interest, it is desirable to have an automated mesh adaption tool capable of producing high quality meshes with an affordably low number of mesh points. This is important especially for problems, which are characterized by anisotropic features of the solution and require mesh clustering in the direction of high gradients. Another significant issue in meshing emerges in the area of unsteady simulations with moving boundaries or interfaces, where the motion of the boundary has to be accommodated by deforming the computational grid. Similarly, there exist problems where current mesh needs to be adapted to get more accurate solutions because either the high gradient regions are initially predicted inaccurately or they change location throughout the simulation. To solve these problems, we propose three novel procedures. For this purpose, in the first part of this work, we present an optimization procedure for three-dimensional anisotropic tetrahedral grids based on metric-driven h-adaptation. The desired anisotropy in the grid is dictated by a metric that defines the size, shape, and orientation of the grid elements throughout the computational domain. Through the use of topological and geometrical operators, the mesh is iteratively adapted until the final mesh minimizes a given objective function. In this work, the objective function measures the distance between the metric of each simplex and a target metric, which can be either user-defined (a-priori) or the result of a-posteriori error analysis. During the adaptation process, one tries to decrease the metric-based objective function until the final mesh is compliant with the target within a given tolerance. However, in regions such as corners and complex face intersections, the compliance condition was found to be very difficult or sometimes impossible to satisfy. In order to address this issue, we propose an optimization process based on an ad
An Improved Dynamic Programming Decomposition Approach for Network Revenue Management
Dan Zhang
2011-01-01
We consider a nonlinear nonseparable functional approximation to the value function of a dynamic programming formulation for the network revenue management (RM) problem with customer choice. We propose a simultaneous dynamic programming approach to solve the resulting problem, which is a nonlinear optimization problem with nonlinear constraints. We show that our approximation leads to a tighter upper bound on optimal expected revenue than some known bounds in the literature. Our approach can ...
Dynamic Programming Approaches for the Traveling Salesman Problem with Drone
Bouman, Paul; Agatz, Niels; Schmidt, Marie
2017-01-01
markdownabstractA promising new delivery model involves the use of a delivery truck that collaborates with a drone to make deliveries. Effectively combining a drone and a truck gives rise to a new planning problem that is known as the Traveling Salesman Problem with Drone (TSP-D). This paper presents an exact solution approach for the TSP-D based on dynamic programming and present experimental results of different dynamic programming based heuristics. Our numerical experiments show that our a...
Adapting proofs-as-programs the Curry-Howard protocol
Poernomo, Iman Hafiz; Crossley, John Newsome
2007-01-01
Details developments in the direction of a practical proofs-as-programs paradigm, which constitutes a set of approaches to developing programs from proofs in constructive logic with applications to industrial-scale, complex software engineering problems.
The Use of Format Adaptation in Danish Public Service Programming
DEFF Research Database (Denmark)
Jensen, Pia Majbritt
2013-01-01
The article investigates Danish public service broadcasters’ use of format adaptations over a 12-year period in order to examine claims that formats constitute a potential threat to public service broadcasting and the national Danish television industry and culture. The article’s findings, howeve...... service orientation. Instead the article argues, following German sociologist Ulrich Beck, that format adaptation can represent a form of ‘banal transnationalism’, pointing to the fact that the world is no longer exclusively defined by national boundaries.......The article investigates Danish public service broadcasters’ use of format adaptations over a 12-year period in order to examine claims that formats constitute a potential threat to public service broadcasting and the national Danish television industry and culture. The article’s findings, however......, bear little evidence to support these claims. The practice of format adaptation constitutes a comparatively small proportion of the overall production of Danish public service content, and, more importantly, most of the formats adapted by the public broadcasters have a comparatively solid public...
Roman, Paul M.
1980-01-01
Strategies for initiating employee alcoholism and assistance programs in higher education institutions are considered. Barriers to faculty utilization of such programs include visibility of work performance and nature of supervision. Modes for adapting existing program designs to higher education are suggested. (Author/JMF)
Dynamic Performance Tuning Supported by Program Specification
Directory of Open Access Journals (Sweden)
Eduardo César
2002-01-01
Full Text Available Performance analysis and tuning of parallel/distributed applications are very difficult tasks for non-expert programmers. It is necessary to provide tools that automatically carry out these tasks. These can be static tools that carry out the analysis on a post-mortem phase or can tune the application on the fly. Both kind of tools have their target applications. Static automatic analysis tools are suitable for stable application while dynamic tuning tools are more appropriate to applications with dynamic behaviour. In this paper, we describe KappaPi as an example of a static automatic performance analysis tool, and also a general environment based on parallel patterns for developing and dynamically tuning parallel/distributed applications.
Cortical microcircuit dynamics mediating Binocular Rivalry: The role of adaptation in inhibition
Directory of Open Access Journals (Sweden)
Panagiota eTheodoni
2011-11-01
Full Text Available Perceptual bistability arises when two conflicting interpretations of an ambiguous stimulus or images in binocular rivalry (BR compete for perceptual dominance. From a computational point of view competition models based on cross-inhibition and adaptation have shown that noise is a crucial force for rivalry and operates in balance with adaptation in order to explain the observed alternations in perception. In particular, noise-driven transitions and adaptation-driven oscillations define two dynamical regimes and the system operates near its boundary. In order to gain insights into the microcircuit dynamics mediating spontaneous perceptual alternations we used a reduced recurrent attractor-based biophysically realistic spiking network well known for working memory, attention and decision-making, where a spike-frequency adaptation mechanism is implemented to account for perceptual bistability. We, thus, derived a consistently reduced four-variable population rate model using mean-field techniques and tested it on BR data collected from human subjects. Our model accounts for experimental data parameters such as time dominance, coefficient of variation and gamma distribution. In addition, we show that our model also operates on the boundary between noise and adaptation and agrees with Levelt’s second revised and fourth propositions. These results show for the first time that a consistent reduction of a biophysically realistic spiking network of integrate and fire neurons with spike frequency adaptation could account for BR. Moreover, we demonstrate that BR can be explained only through the dynamics of the competing neuronal pools, without taking into account the adaptation of inhibitory interneurons..However, adaptation of interneurons affects the optimal parametric space of the system, by decreasing the overall adaptation necessary for the bifurcation to occur.
Adaptive Process Management in Highly Dynamic and Pervasive Scenarios
Directory of Open Access Journals (Sweden)
Massimiliano de Leoni
2009-06-01
Full Text Available Process Management Systems (PMSs are currently more and more used as a supporting tool for cooperative processes in pervasive and highly dynamic situations, such as emergency situations, pervasive healthcare or domotics/home automation. But in all such situations, designed processes can be easily invalidated since the execution environment may change continuously due to frequent unforeseeable events. This paper aims at illustrating the theoretical framework and the concrete implementation of SmartPM, a PMS that features a set of sound and complete techniques to automatically cope with unplanned exceptions. PMS SmartPM is based on a general framework which adopts the Situation Calculus and Indigolog.
INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization
Energy Technology Data Exchange (ETDEWEB)
Groer, Christopher S [ORNL; Sullivan, Blair D [ORNL; Weerapurage, Dinesh P [ORNL
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.
Nanostructural self-organization and dynamic adaptation of metal-polymer tribosystems
Mashkov, Yu. K.
2017-02-01
The results of investigating the effect of nanosize modifiers of a polymer matrix on the nanostructural self-organization of polymer composites and dynamic adaptation of metal-polymer tribosystems, which considerably affect the wear resistance of polymer composite materials, have been analyzed. It has been shown that the physicochemical nanostructural self-organization processes are developed in metal-polymer tribosystems with the formation of thermotropic liquid-crystal structures of the polymer matrix, followed by the transition of the system to the stationary state with a negative feedback that ensures dynamic adaptation of the tribosystem to given operating conditions.
Dynamic Surface Adaptive Robust Control of Unmanned Marine Vehicles with Disturbance Observer
Directory of Open Access Journals (Sweden)
Pengchao Zhang
2018-01-01
Full Text Available This paper presents a dynamic surface adaptive robust control method with disturbance observer for unmanned marine vehicles (UMV. It uses adaptive law to estimate and compensate the disturbance observer error. Dynamic surface is introduced to solve the “differential explosion” caused by the virtual control derivation in traditional backstepping method. The final controlled system is proved to be globally uniformly bounded based on Lyapunov stability theory. Simulation results illustrate the effectiveness of the proposed controller, which can realize the three-dimensional trajectory tracking for UMV with the systematic uncertainty and time-varying disturbances.
Energy Technology Data Exchange (ETDEWEB)
Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teachers' College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Sun Wen [School of Mathematics and Information, Yangtze University, Hubei Jingzhou 434023 (China)
2010-04-05
This Letter investigates the synchronization of a general complex dynamical network with non-derivative and derivative coupling. Based on LaSalle's invariance principle, adaptive synchronization criteria are obtained. Analytical result shows that under the designed adaptive controllers, a general complex dynamical network with non-derivative and derivative coupling can asymptotically synchronize to a given trajectory, and several useful criteria for synchronization are given. What is more, the coupling matrix is not assumed to be symmetric or irreducible. Finally, simulations results show the method is effective.
Intelligent control of non-linear dynamical system based on the adaptive neurocontroller
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.
Dynamic and adaptive policy models for coalition operations
Verma, Dinesh; Calo, Seraphin; Chakraborty, Supriyo; Bertino, Elisa; Williams, Chris; Tucker, Jeremy; Rivera, Brian; de Mel, Geeth R.
2017-05-01
It is envisioned that the success of future military operations depends on the better integration, organizationally and operationally, among allies, coalition members, inter-agency partners, and so forth. However, this leads to a challenging and complex environment where the heterogeneity and dynamism in the operating environment intertwines with the evolving situational factors that affect the decision-making life cycle of the war fighter. Therefore, the users in such environments need secure, accessible, and resilient information infrastructures where policy-based mechanisms adopt the behaviours of the systems to meet end user goals. By specifying and enforcing a policy based model and framework for operations and security which accommodates heterogeneous coalitions, high levels of agility can be enabled to allow rapid assembly and restructuring of system and information resources. However, current prevalent policy models (e.g., rule based event-condition-action model and its variants) are not sufficient to deal with the highly dynamic and plausibly non-deterministic nature of these environments. Therefore, to address the above challenges, in this paper, we present a new approach for policies which enables managed systems to take more autonomic decisions regarding their operations.
Directory of Open Access Journals (Sweden)
Joshua Rodewald
2016-10-01
Full Text Available Supply networks existing today in many industries can behave as complex adaptive systems making them more difficult to analyze and assess. Being able to fully understand both the complex static and dynamic structures of a complex adaptive supply network (CASN are key to being able to make more informed management decisions and prioritize resources and production throughout the network. Previous efforts to model and analyze CASN have been impeded by the complex, dynamic nature of the systems. However, drawing from other complex adaptive systems sciences, information theory provides a model-free methodology removing many of those barriers, especially concerning complex network structure and dynamics. With minimal information about the network nodes, transfer entropy can be used to reverse engineer the network structure while local transfer entropy can be used to analyze the network structure’s dynamics. Both simulated and real-world networks were analyzed using this methodology. Applying the methodology to CASNs allows the practitioner to capitalize on observations from the highly multidisciplinary field of information theory which provides insights into CASN’s self-organization, emergence, stability/instability, and distributed computation. This not only provides managers with a more thorough understanding of a system’s structure and dynamics for management purposes, but also opens up research opportunities into eventual strategies to monitor and manage emergence and adaption within the environment.
A Theory of Secondary Teachers' Adaptations When Implementing a Reading Intervention Program
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…
Design of device driver program for PCI data acquisition adapters based on WDM of windows 2000
International Nuclear Information System (INIS)
Yuan Weihua; Qiao Weimin; Jing Lan; Zhu Haijun
2003-01-01
The paper describes the design of device driver program for PCI data acquisition adapters based on WDM of Windows 2000. Give an actual example of PCI6208. Now, several data acquisition adapters based in this method are using in national big science engineer HIRFL-CSR. (authors)
Dynamic Learning Objects to Teach Java Programming Language
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…
Proving deadlock freedom of logic programs with dynamic scheduling
E. Marchiori; F. Teusink (Frank)
1996-01-01
textabstractIn increasingly many logic programming systems, the Prolog left to right selection rule has been replaced with dynamic selection rules, that select an atom of a query among those satisfying suitable conditions. These conditions describe the form of the arguments of every program
Dynamic game balancing implementation using adaptive algorithm in mobile-based Safari Indonesia game
Yuniarti, Anny; Nata Wardanie, Novita; Kuswardayan, Imam
2018-03-01
In developing a game there is one method that should be applied to maintain the interest of players, namely dynamic game balancing. Dynamic game balancing is a process to match a player’s playing style with the behaviour, attributes, and game environment. This study applies dynamic game balancing using adaptive algorithm in scrolling shooter game type called Safari Indonesia which developed using Unity. The game of this type is portrayed by a fighter aircraft character trying to defend itself from insistent enemy attacks. This classic game is chosen to implement adaptive algorithms because it has quite complex attributes to be developed using dynamic game balancing. Tests conducted by distributing questionnaires to a number of players indicate that this method managed to reduce frustration and increase the pleasure factor in playing.
Dynamic adaptation of myocardial proteome during heart failure development
Poesch, Axel; Dörr, Marcus; Völker, Uwe; Grube, Karina; Hammer, Elke; Felix, Stephan B.
2017-01-01
Heart failure (HF) development is characterized by huge structural changes that are crucial for disease progression. Analysis of time dependent global proteomic adaptations during HF progression offers the potential to gain deeper insights in the disease development and identify new biomarker candidates. Therefore, hearts of TAC (transverse aortic constriction) and sham mice were examined by cardiac MRI on either day 4, 14, 21, 28, 42, and 56 after surgery (n = 6 per group/time point). At each time point, proteomes of the left (LV) and right ventricles (RV) of TAC and sham mice were analyzed by mass spectrometry (MS). In TAC mice, systolic LV heart function worsened from day 4 to day 14, remained on a stable level from day 14 to day 42, and showed a further pronounced decline at day 56. MS analysis identified in the LV 330 and in RV 246 proteins with altered abundance over time (TAC vs. sham, fc≥±2). Functional categorization of proteins disclosed the time-dependent alteration of different pathways. Heat shock protein beta-7 (HSPB7) displayed differences in abundance in tissue and serum at an early stage of HF. This study not only provides an overview of the time dependent molecular alterations during transition to HF, but also identified HSPB7 as a novel blood biomarker candidate for the onset of cardiac remodeling. PMID:28973020
Workload Model Based Dynamic Adaptation of Social Internet of Vehicles
Directory of Open Access Journals (Sweden)
Kazi Masudul Alam
2015-09-01
Full Text Available Social Internet of Things (SIoT has gained much interest among different research groups in recent times. As a key member of a smart city, the vehicular domain of SIoT (SIoV is also undergoing steep development. In the SIoV, vehicles work as sensor-hub to capture surrounding information using the in-vehicle and Smartphone sensors and later publish them for the consumers. A cloud centric cyber-physical system better describes the SIoV model where physical sensing-actuation process affects the cloud based service sharing or computation in a feedback loop or vice versa. The cyber based social relationship abstraction enables distributed, easily navigable and scalable peer-to-peer communication among the SIoV subsystems. These cyber-physical interactions involve a huge amount of data and it is difficult to form a real instance of the system to test the feasibility of SIoV applications. In this paper, we propose an analytical model to measure the workloads of various subsystems involved in the SIoV process. We present the basic model which is further extended to incorporate complex scenarios. We provide extensive simulation results for different parameter settings of the SIoV system. The findings of the analyses are further used to design example adaptation strategies for the SIoV subsystems which would foster deployment of intelligent transport systems.
Workload Model Based Dynamic Adaptation of Social Internet of Vehicles
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
Voter dynamics on an adaptive network with finite average connectivity
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.
Nonlinear beam dynamics experimental program at SPEAR
International Nuclear Information System (INIS)
Tran, P.; Pellegrini, C.; Cornacchia, M.; Lee, M.; Corbett, W.
1995-01-01
Since nonlinear effects can impose strict performance limitations on modern colliders and storage rings, future performance improvements depend on further understanding of nonlinear beam dynamics. Experimental studies of nonlinear beam motion in three-dimensional space have begun in SPEAR using turn-by-turn transverse and longitudinal phase-space monitors. This paper presents preliminary results from an on-going experiment in SPEAR
AbouEisha, Hassan M.
2017-07-13
We consider a class of two-and three-dimensional h-refined meshes generated by an adaptive finite element method. We introduce an element partition tree, which controls the execution of the multi-frontal solver algorithm over these refined grids. We propose and study algorithms with polynomial computational cost for the optimization of these element partition trees. The trees provide an ordering for the elimination of unknowns. The algorithms automatically optimize the element partition trees using extensions of dynamic programming. The construction of the trees by the dynamic programming approach is expensive. These generated trees cannot be used in practice, but rather utilized as a learning tool to propose fast heuristic algorithms. In this first part of our paper we focus on the dynamic programming approach, and draw a sketch of the heuristic algorithm. The second part will be devoted to a more detailed analysis of the heuristic algorithm extended for the case of hp-adaptive
AbouEisha, Hassan M.; Calo, Victor Manuel; Jopek, Konrad; Moshkov, Mikhail; Paszyńka, Anna; Paszyński, Maciej; Skotniczny, Marcin
2017-01-01
We consider a class of two-and three-dimensional h-refined meshes generated by an adaptive finite element method. We introduce an element partition tree, which controls the execution of the multi-frontal solver algorithm over these refined grids. We propose and study algorithms with polynomial computational cost for the optimization of these element partition trees. The trees provide an ordering for the elimination of unknowns. The algorithms automatically optimize the element partition trees using extensions of dynamic programming. The construction of the trees by the dynamic programming approach is expensive. These generated trees cannot be used in practice, but rather utilized as a learning tool to propose fast heuristic algorithms. In this first part of our paper we focus on the dynamic programming approach, and draw a sketch of the heuristic algorithm. The second part will be devoted to a more detailed analysis of the heuristic algorithm extended for the case of hp-adaptive
Modelling of windmill induction generators in dynamic simulation programs
DEFF Research Database (Denmark)
Akhmatov, Vladislav; Knudsen, Hans
1999-01-01
with and without a model of the mechanical shaft. The reason for the discrepancies are explained, and it is shown that the phenomenon is due partly to the presence of DC offset currents in the induction machine stator, and partly to the mechanical shaft system of the wind turbine and the generator rotor......For AC networks with large amounts of induction generators-in case of e.g. windmills-the paper demonstrates a significant discrepancy in the simulated voltage recovery after faults in weak networks, when comparing result obtained with dynamic stability programs and transient programs, respectively....... It is shown that it is possible to include a transient model in dynamic stability programs and thus obtain correct results also in dynamic stability programs. A mechanical model of the shaft system has also been included in the generator model...
A Rural Special Education Teacher Training Program: Successful Adaptations.
Prater, Greg; And Others
The Rural Special Education Program (RSEP), a partnership between Northern Arizona University (NAU) and Kayenta Unified School District (KUSD), provides training for preservice special education teachers to work with Native American students and their families. To date, the program has provided training for 63 preservice special education…
A Sawmill Manager Adapts To Change With Linear Programming
George F. Dutrow; James E. Granskog
1973-01-01
Linear programming provides guidelines for increasing sawmill capacity and flexibility and for determining stumpagepurchasing strategy. The operator of a medium-sized sawmill implemented improvements suggested by linear programming analysis; results indicate a 45 percent increase in revenue and a 36 percent hike in volume processed.
Modeling for deformable mirrors and the adaptive optics optimization program
International Nuclear Information System (INIS)
Henesian, M.A.; Haney, S.W.; Trenholme, J.B.; Thomas, M.
1997-01-01
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
Park, Sang Cheol; Leader, Joseph Ken; Tan, Jun; Lee, Guee Sang; Kim, Soo Hyung; Na, In Seop; Zheng, Bin
2011-01-01
Objective this article presents a new computerized scheme that aims to accurately and robustly separate left and right lungs on CT examinations. Methods we developed and tested a method to separate the left and right lungs using sequential CT information and a guided dynamic programming algorithm using adaptively and automatically selected start point and end point with especially severe and multiple connections. Results the scheme successfully identified and separated all 827 connections on the total 4034 CT images in an independent testing dataset of CT examinations. The proposed scheme separated multiple connections regardless of their locations, and the guided dynamic programming algorithm reduced the computation time to approximately 4.6% in comparison with the traditional dynamic programming and avoided the permeation of the separation boundary into normal lung tissue. Conclusions The proposed method is able to robustly and accurately disconnect all connections between left and right lungs and the guided dynamic programming algorithm is able to remove redundant processing. PMID:21412104
Program packages for dynamics systems analysis and design
International Nuclear Information System (INIS)
Athani, V.V.
1976-01-01
The development of computer program packages for dynamic system analysis and design are reported. The purpose of developing these program packages is to take the burden of writing computer programs off the mind of the system engineer and to enable him to concentrate on his main system analysis and design work. Towards this end, four standard computer program packages have been prepared : (1) TFANA - starting from system transfer function this program computes transient response, frequency response, root locus and stability by Routh Hurwitz criterion, (2) TFSYN - classical synthesis using algebraic method of Shipley, (3) MODANA - starting from state equations of the system this program computes solution of state equations, controllability, observability and stability, (4) OPTCON - This program obtains solutions of (i) linear regulator problem, (ii) servomechanism problems and (iii) problem of pole placement. The paper describes these program packages with the help of flowcharts and illustrates their use with the help of examples. (author)
Normalized value coding explains dynamic adaptation in the human valuation process.
Khaw, Mel W; Glimcher, Paul W; Louie, Kenway
2017-11-28
The notion of subjective value is central to choice theories in ecology, economics, and psychology, serving as an integrated decision variable by which options are compared. Subjective value is often assumed to be an absolute quantity, determined in a static manner by the properties of an individual option. Recent neurobiological studies, however, have shown that neural value coding dynamically adapts to the statistics of the recent reward environment, introducing an intrinsic temporal context dependence into the neural representation of value. Whether valuation exhibits this kind of dynamic adaptation at the behavioral level is unknown. Here, we show that the valuation process in human subjects adapts to the history of previous values, with current valuations varying inversely with the average value of recently observed items. The dynamics of this adaptive valuation are captured by divisive normalization, linking these temporal context effects to spatial context effects in decision making as well as spatial and temporal context effects in perception. These findings suggest that adaptation is a universal feature of neural information processing and offer a unifying explanation for contextual phenomena in fields ranging from visual psychophysics to economic choice.
Adaptation Decision Support: An Application of System Dynamics Modeling in Coastal Communities
Institute of Scientific and Technical Information of China (English)
Daniel Lane; Shima Beigzadeh; Richard Moll
2017-01-01
This research develops and applies a system dynamics (SD) model for the strategic evaluation of environmental adaptation options for coastal communities.The article defines and estimates asset-based measures for community vulnerability,resilience,and adaptive capacity with respect to the environmental,economic,social,and cultural pillars of the coastal community under threat.The SD model simulates the annual multidimensional dynamic impacts of severe coastal storms and storm surges on the community pillars under alternative adaptation strategies.The calculation of the quantitative measures provides valuable information for decision makers for evaluating the alternative strategies.The adaptation strategies are designed model results illustrated for the specific context of the coastal community of Charlottetown,Prince Edward Island,Canada.The dynamic trend of the measures and model sensitivity analyses for Charlottetown-facing increased frequency of severe storms,storm surges,and sea-level rise-provide impetus for enhanced community strategic planning for the changing coastal environment.This research is presented as part of the International Community-University Research Alliance C-Change project "Managing Adaptation to Environmental Change in Coastal Communities:Canada and the Caribbean" sponsored by the Social Science and Humanities Research Council of Canada and the International Development Resource Centre.
Improve Problem Solving Skills through Adapting Programming Tools
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.
A double-loop adaptive sampling approach for sensitivity-free dynamic reliability analysis
International Nuclear Information System (INIS)
Wang, Zequn; Wang, Pingfeng
2015-01-01
Dynamic reliability measures reliability of an engineered system considering time-variant operation condition and component deterioration. Due to high computational costs, conducting dynamic reliability analysis at an early system design stage remains challenging. This paper presents a confidence-based meta-modeling approach, referred to as double-loop adaptive sampling (DLAS), for efficient sensitivity-free dynamic reliability analysis. The DLAS builds a Gaussian process (GP) model sequentially to approximate extreme system responses over time, so that Monte Carlo simulation (MCS) can be employed directly to estimate dynamic reliability. A generic confidence measure is developed to evaluate the accuracy of dynamic reliability estimation while using the MCS approach based on developed GP models. A double-loop adaptive sampling scheme is developed to efficiently update the GP model in a sequential manner, by considering system input variables and time concurrently in two sampling loops. The model updating process using the developed sampling scheme can be terminated once the user defined confidence target is satisfied. The developed DLAS approach eliminates computationally expensive sensitivity analysis process, thus substantially improves the efficiency of dynamic reliability analysis. Three case studies are used to demonstrate the efficacy of DLAS for dynamic reliability analysis. - Highlights: • Developed a novel adaptive sampling approach for dynamic reliability analysis. • POD Developed a new metric to quantify the accuracy of dynamic reliability estimation. • Developed a new sequential sampling scheme to efficiently update surrogate models. • Three case studies were used to demonstrate the efficacy of the new approach. • Case study results showed substantially enhanced efficiency with high accuracy
Method and system for training dynamic nonlinear adaptive filters which have embedded memory
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.
DEFF Research Database (Denmark)
Hundebøll, Martin; Pedersen, Morten Videbæk; Roetter, Daniel Enrique Lucani
2014-01-01
This work studies the potential and impact of the FRANC network coding protocol for delivering high quality Dynamic Adaptive Streaming over HTTP (DASH) in wireless networks. Although DASH aims to tailor the video quality rate based on the available throughput to the destination, it relies...
Adaptive dynamics on an environmental gradient that changes over a geological time-scale.
Fortelius, Mikael; Geritz, Stefan; Gyllenberg, Mats; Toivonen, Jaakko
2015-07-07
The standard adaptive dynamics framework assumes two timescales, i.e. fast population dynamics and slow evolutionary dynamics. We further assume a third timescale, which is even slower than the evolutionary timescale. We call this the geological timescale and we assume that slow climatic change occurs within this timescale. We study the evolution of our model population over this very slow geological timescale with bifurcation plots of the standard adaptive dynamics framework. The bifurcation parameter being varied describes the abiotic environment that changes over the geological timescale. We construct evolutionary trees over the geological timescale and observe both gradual phenotypic evolution and punctuated branching events. We concur with the established notion that branching of a monomorphic population on an environmental gradient only happens when the gradient is not too shallow and not too steep. However, we show that evolution within the habitat can produce polymorphic populations that inhabit steep gradients. What is necessary is that the environmental gradient at some point in time is such that the initial branching of the monomorphic population can occur. We also find that phenotypes adapted to environments in the middle of the existing environmental range are more likely to branch than phenotypes adapted to extreme environments. Copyright © 2015 Elsevier Ltd. All rights reserved.
A Self-adaptive Scope Allocation Scheme for Labeling Dynamic XML Documents
Shen, Y.; Feng, L.; Shen, T.; Wang, B.
This paper proposes a self-adaptive scope allocation scheme for labeling dynamic XML documents. It is general, light-weight and can be built upon existing data retrieval mechanisms. Bayesian inference is used to compute the actual scope allocated for labeling a certain node based on both the prior
High Dynamic Range adaptive ΔΣ-based Focal Plane Array architecture
Yao, Shun; Kavusi, Sam; Salama, Khaled N.
2012-01-01
In this paper, an Adaptive Delta-Sigma based architecture for High Dynamic Range (HDR) Focal Plane Arrays is presented. The noise shaping effect of the Delta-Sigma modulation in the low end, and the distortion noise induced in the high end of Photo
A feasibility study of dynamic adaptive radiotherapy for nonsmall cell lung cancer
Energy Technology Data Exchange (ETDEWEB)
Kim, Minsun, E-mail: mk688@uw.edu [Department of Radiation Oncology, University of Washington, Seattle, Washington 98195-6043 (United States); Phillips, Mark H. [Departments of Radiation Oncology and Neurological Surgery, University of Washington, Seattle, Washington 98195-6043 (United States)
2016-05-15
Purpose: The final state of the tumor at the end of a radiotherapy course is dependent on the doses given in each fraction during the treatment course. This study investigates the feasibility of using dynamic adaptive radiotherapy (DART) in treating lung cancers assuming CBCT is available to observe midtreatment tumor states. DART adapts treatment plans using a dynamic programming technique to consider the expected changes of the tumor in the optimization process. Methods: DART is constructed using a stochastic control formalism framework. It minimizes the total expected number of tumor cells at the end of a treatment course, which is equivalent to maximizing tumor control probability, subject to the uncertainty inherent in the tumor response. This formulation allows for nonstationary dose distributions as well as nonstationary fractional doses as needed to achieve a series of optimal plans that are conformal to the tumor over time, i.e., spatiotemporally optimal plans. Sixteen phantom cases with various sizes and locations of tumors and organs-at-risk (OAR) were generated using in-house software. Each case was planned with DART and conventional IMRT prescribing 60 Gy in 30 fractions. The observations of the change in the tumor volume over a treatment course were simulated using a two-level cell population model. Monte Carlo simulations of the treatment course for each case were run to account for uncertainty in the tumor response. The same OAR dose constraints were applied for both methods. The frequency of replanning was varied between 1, 2, 5 (weekly), and 29 times (daily). The final average tumor dose and OAR doses have been compared to quantify the potential dosimetric benefits of DART. Results: The average tumor max, min, mean, and D95 doses using DART relative to these using conventional IMRT were 124.0%–125.2%, 102.1%–114.7%, 113.7%–123.4%, and 102.0%–115.9% (range dependent on the frequency of replanning). The average relative maximum doses for the
Taheri, Mehdi; Sheikholeslam, Farid; Najafi, Majddedin; Zekri, Maryam
2017-07-01
In this paper, consensus problem is considered for second order multi-agent systems with unknown nonlinear dynamics under undirected graphs. A novel distributed control strategy is suggested for leaderless systems based on adaptive fuzzy wavelet networks. Adaptive fuzzy wavelet networks are employed to compensate for the effect of unknown nonlinear dynamics. Moreover, the proposed method is developed for leader following systems and leader following systems with state time delays. Lyapunov functions are applied to prove uniformly ultimately bounded stability of closed loop systems and to obtain adaptive laws. Three simulation examples are presented to illustrate the effectiveness of the proposed control algorithms. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
HOLD MODE BASED DYNAMIC PRIORITY LOAD ADAPTIVE INTERPICONET SCHEDULING FOR BLUETOOTH SCATTERNETS
Directory of Open Access Journals (Sweden)
G.S. Mahalakshmi
2011-09-01
Full Text Available Scheduling in piconets has emerged as a challenging research area. Interpiconet scheduling focuses on when a bridge is switched among various piconets and how a bridge node communicates with the masters in different piconets. This paper proposes an interpiconet scheduling algorithm named, hold mode based dynamic traffic priority load adaptive scheduling. The bridges are adaptively switched between the piconets according to various traffic loads. The main goal is to maximize the utilization of the bridge by reducing the bridge switch wastes, utilize intelligent decision making algorithm, resolve conflict between the masters, and allow negotiation for bridge utilization in HDPLIS using bridge failure-bridge repair procedure . The Hold mode - dynamic traffic - priority based - load adaptive scheduling reduces the number of bridge switch wastes and hence increases the efficiency of the bridge which results in increased performance of the system.
Macroscopic reality and the dynamical reduction program
International Nuclear Information System (INIS)
Ghirardi, G.C.
1995-10-01
With reference to recently proposed theoretical models accounting for reduction in terms of a unified dynamics governing all physical processes, we analyze the problem of working out a worldview accommodating our knowledge about natural phenomena. We stress the relevant conceptual differences between the considered models and standard quantum mechanics. In spite of the fact that both theories describe individual physical systems within a genuine Hilbert space framework, the nice features of spontaneous reduction theories drastically limit the class of states which are dynamically stable. This allows one to work out a description of the world in terms of a mass density function in ordinary configuration space. A topology based on this function and differing radically from the one characterizing the Hilbert space is introduced and in terms of it the idea of similarity of macroscopic situations is made precise. Finally it is shown how the formalism and the proposed interpretation yield a natural criterion for establishing the psychophysical parallelism. The conclusion is that, within the considered theoretical models and at the nonrelativistic level, one can satisfy all sensible requirements for a consistent, unified, and objective description of reality at the macroscopic level. (author). 16 refs
Macroscopic reality and the dynamical reduction program
Energy Technology Data Exchange (ETDEWEB)
Ghirardi, G C
1995-10-01
With reference to recently proposed theoretical models accounting for reduction in terms of a unified dynamics governing all physical processes, we analyze the problem of working out a worldview accommodating our knowledge about natural phenomena. We stress the relevant conceptual differences between the considered models and standard quantum mechanics. In spite of the fact that both theories describe individual physical systems within a genuine Hilbert space framework, the nice features of spontaneous reduction theories drastically limit the class of states which are dynamically stable. This allows one to work out a description of the world in terms of a mass density function in ordinary configuration space. A topology based on this function and differing radically from the one characterizing the Hilbert space is introduced and in terms of it the idea of similarity of macroscopic situations is made precise. Finally it is shown how the formalism and the proposed interpretation yield a natural criterion for establishing the psychophysical parallelism. The conclusion is that, within the considered theoretical models and at the nonrelativistic level, one can satisfy all sensible requirements for a consistent, unified, and objective description of reality at the macroscopic level. (author). 16 refs.
The application of dynamic programming in production planning
Wu, Run
2017-05-01
Nowadays, with the popularity of the computers, various industries and fields are widely applying computer information technology, which brings about huge demand for a variety of application software. In order to develop software meeting various needs with most economical cost and best quality, programmers must design efficient algorithms. A superior algorithm can not only soul up one thing, but also maximize the benefits and generate the smallest overhead. As one of the common algorithms, dynamic programming algorithms are used to solving problems with some sort of optimal properties. When solving problems with a large amount of sub-problems that needs repetitive calculations, the ordinary sub-recursive method requires to consume exponential time, and dynamic programming algorithm can reduce the time complexity of the algorithm to the polynomial level, according to which we can conclude that dynamic programming algorithm is a very efficient compared to other algorithms reducing the computational complexity and enriching the computational results. In this paper, we expound the concept, basic elements, properties, core, solving steps and difficulties of the dynamic programming algorithm besides, establish the dynamic programming model of the production planning problem.
Wavelet and adaptive methods for time dependent problems and applications in aerosol dynamics
Guo, Qiang
Time dependent partial differential equations (PDEs) are widely used as mathematical models of environmental problems. Aerosols are now clearly identified as an important factor in many environmental aspects of climate and radiative forcing processes, as well as in the health effects of air quality. The mathematical models for the aerosol dynamics with respect to size distribution are nonlinear partial differential and integral equations, which describe processes of condensation, coagulation and deposition. Simulating the general aerosol dynamic equations on time, particle size and space exhibits serious difficulties because the size dimension ranges from a few nanometer to several micrometer while the spatial dimension is usually described with kilometers. Therefore, it is an important and challenging task to develop efficient techniques for solving time dependent dynamic equations. In this thesis, we develop and analyze efficient wavelet and adaptive methods for the time dependent dynamic equations on particle size and further apply them to the spatial aerosol dynamic systems. Wavelet Galerkin method is proposed to solve the aerosol dynamic equations on time and particle size due to the fact that aerosol distribution changes strongly along size direction and the wavelet technique can solve it very efficiently. Daubechies' wavelets are considered in the study due to the fact that they possess useful properties like orthogonality, compact support, exact representation of polynomials to a certain degree. Another problem encountered in the solution of the aerosol dynamic equations results from the hyperbolic form due to the condensation growth term. We propose a new characteristic-based fully adaptive multiresolution numerical scheme for solving the aerosol dynamic equation, which combines the attractive advantages of adaptive multiresolution technique and the characteristics method. On the aspect of theoretical analysis, the global existence and uniqueness of
Understanding barriers to implementation of an adaptive land management program
Jacobson, S.K.; Morris, J.K.; Sanders, J.S.; Wiley, E.N.; Brooks, M.; Bennetts, R.E.; Percival, H.F.; Marynowski, S.
2006-01-01
The Florida Fish and Wildlife Conservation Commission manages over 650,000 ha, including 26 wildlife management and environmental areas. To improve management, they developed an objective-based vegetation management (OBVM) process that focuses on desired conditions of plant communities through an adaptive management framework. Our goals were to understand potential barriers to implementing OBVM and to recommend strategies to overcome barriers. A literature review identified 47 potential barriers in six categories to implementation of adaptive and ecosystem management: logistical, communication, attitudinal, institutional, conceptual, and educational. We explored these barriers through a bureau-wide survey of 90 staff involved in OBVM and personal interviews with area managers, scientists, and administrators. The survey incorporated an organizational culture assessment instrument to gauge how institutional factors might influence OBVM implementation. The survey response rate was 69%. Logistics and communications were the greatest barriers to implementing OBVM. Respondents perceived that the agency had inadequate resources for implementing OBVM and provided inadequate information. About one-third of the respondents believed OBVM would decrease their job flexibility and perceived greater institutional barriers to the approach. The 43% of respondents who believed they would have more responsibility under OBVM also had greater attitudinal barriers. A similar percentage of respondents reported OBVM would not give enough priority to wildlife. Staff believed that current agency culture was hierarchical but preferred a culture that would provide more flexibility for adaptive management and would foster learning from land management activities. In light of the barriers to OBVM, we recommend the following: (1) mitigation of logistical barriers by addressing real and perceived constraints of staff, funds, and other resources in a participatory manner; (2) mitigation of
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
Fei, Juntao; Lu, Cheng
2018-04-01
In this paper, an adaptive sliding mode control system using a double loop recurrent neural network (DLRNN) structure is proposed for a class of nonlinear dynamic systems. A new three-layer RNN is proposed to approximate unknown dynamics with two different kinds of feedback loops where the firing weights and output signal calculated in the last step are stored and used as the feedback signals in each feedback loop. Since the new structure has combined the advantages of internal feedback NN and external feedback NN, it can acquire the internal state information while the output signal is also captured, thus the new designed DLRNN can achieve better approximation performance compared with the regular NNs without feedback loops or the regular RNNs with a single feedback loop. The new proposed DLRNN structure is employed in an equivalent controller to approximate the unknown nonlinear system dynamics, and the parameters of the DLRNN are updated online by adaptive laws to get favorable approximation performance. To investigate the effectiveness of the proposed controller, the designed adaptive sliding mode controller with the DLRNN is applied to a -axis microelectromechanical system gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed methodology can achieve good tracking property, and the comparisons of the approximation performance between radial basis function NN, RNN, and DLRNN show that the DLRNN can accurately estimate the unknown dynamics with a fast speed while the internal states of DLRNN are more stable.
Adaptive Control Based Harvesting Strategy for a Predator-Prey Dynamical System.
Sen, Moitri; Simha, Ashutosh; Raha, Soumyendu
2018-04-23
This paper deals with designing a harvesting control strategy for a predator-prey dynamical system, with parametric uncertainties and exogenous disturbances. A feedback control law for the harvesting rate of the predator is formulated such that the population dynamics is asymptotically stabilized at a positive operating point, while maintaining a positive, steady state harvesting rate. The hierarchical block strict feedback structure of the dynamics is exploited in designing a backstepping control law, based on Lyapunov theory. In order to account for unknown parameters, an adaptive control strategy has been proposed in which the control law depends on an adaptive variable which tracks the unknown parameter. Further, a switching component has been incorporated to robustify the control performance against bounded disturbances. Proofs have been provided to show that the proposed adaptive control strategy ensures asymptotic stability of the dynamics at a desired operating point, as well as exact parameter learning in the disturbance-free case and learning with bounded error in the disturbance prone case. The dynamics, with uncertainty in the death rate of the predator, subjected to a bounded disturbance has been simulated with the proposed control strategy.
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.
Efficient Dynamic Adaptation Strategies for Object Tracking Tree in Wireless Sensor Network
Directory of Open Access Journals (Sweden)
CHEN, M.
2012-12-01
Full Text Available Most object tracking trees are established using the predefined mobility profile. However, when the real object's movement behaviors and query rates are different from the predefined mobility profile and query rates, the update cost and query cost of object tracking tree may increase. To upgrade the object tracking tree, the sink needs to send very large messages to collect the real movement information from the network, introducing a very large message overhead, which is referred to as adaptation cost. The Sub Root Message-Tree Adaptive procedure was proposed to dynamically collect the real movement information under the sub-tree and reconstruct the sub-tree to provide good performance based on the collected information. The simulation results indicates that the Sub Root Message-Tree Adaptive procedure is sufficient to achieve good total cost and lower adaptation cost.
Parallel adaptation of a vectorised quantumchemical program system
International Nuclear Information System (INIS)
Van Corler, L.C.H.; Van Lenthe, J.H.
1987-01-01
Supercomputers, like the CRAY 1 or the Cyber 205, have had, and still have, a marked influence on Quantum Chemistry. Vectorization has led to a considerable increase in the performance of Quantum Chemistry programs. However, clockcycle times more than a factor 10 smaller than those of the present supercomputers are not to be expected. Therefore future supercomputers will have to depend on parallel structures. Recently, the first examples of such supercomputers have been installed. To be prepared for this new generation of (parallel) supercomputers one should consider the concepts one wants to use and the kind of problems one will encounter during implementation of existing vectorized programs on those parallel systems. The authors implemented four important parts of a large quantumchemical program system (ATMOL), i.e. integrals, SCF, 4-index and Direct-CI in the parallel environment at ECSEC (Rome, Italy). This system offers simulated parallellism on the host computer (IBM 4381) and real parallellism on at most 10 attached processors (FPS-164). Quantumchemical programs usually handle large amounts of data and very large, often sparse matrices. The transfer of that many data can cause problems concerning communication and overhead, in view of which shared memory and shared disks must be considered. The strategy and the tools that were used to parallellise the programs are shown. Also, some examples are presented to illustrate effectiveness and performance of the system in Rome for these type of calculations
Approximate dynamic programming solving the curses of dimensionality
Powell, Warren B
2007-01-01
Warren B. Powell, PhD, is Professor of Operations Research and Financial Engineering at Princeton University, where he is founder and Director of CASTLE Laboratory, a research unit that works with industrial partners to test new ideas found in operations research. The recipient of the 2004 INFORMS Fellow Award, Dr. Powell has authored over 100 refereed publications on stochastic optimization, approximate dynamic programming, and dynamic resource management.
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 electricity pricing—Which programs do consumers prefer?
International Nuclear Information System (INIS)
Dütschke, Elisabeth; Paetz, Alexandra-Gwyn
2013-01-01
Dynamic pricing is being discussed as one method of demand side management (DSM) which could be crucial for integrating more renewable energy sources into the electricity system. At the same time, there have been very few analyses of consumer preferences in this regard: Which type of pricing program are consumers most likely to choose and why? This paper sheds some light on these issues based on two empirical studies from Germany: (1) A questionnaire study including a conjoint analysis-design and (2) A field experiment with test-residents of a smart home laboratory. The results show that consumers are open to dynamic pricing, but prefer simple programs to complex and highly dynamic ones; smart home technologies including demand automation are seen as a prerequisite for DSM. The study provides some indications that consumers might be more willing to accept more dynamic pricing programs if they have the chance to experience in practice how these can be managed in everyday life. At the same time, the individual and societal advantages of such programs are not obvious to consumers. For this reason, any market roll-out will need to be accompanied by convincing communication and information campaigns to ensure that these advantages are perceived. - Highlights: • Little is known about consumer preferences on dynamic pricing. • Two studies are conducted to analyze this topic. • A survey shows that consumers without experience prefer conventional programs. • Test residents of a smart home were more open to dynamic pricing. • They also prefer well-structured programs
Step by step parallel programming method for molecular dynamics code
International Nuclear Information System (INIS)
Orii, Shigeo; Ohta, Toshio
1996-07-01
Parallel programming for a numerical simulation program of molecular dynamics is carried out with a step-by-step programming technique using the two phase method. As a result, within the range of a certain computing parameters, it is found to obtain parallel performance by using the level of parallel programming which decomposes the calculation according to indices of do-loops into each processor on the vector parallel computer VPP500 and the scalar parallel computer Paragon. It is also found that VPP500 shows parallel performance in wider range computing parameters. The reason is that the time cost of the program parts, which can not be reduced by the do-loop level of the parallel programming, can be reduced to the negligible level by the vectorization. After that, the time consuming parts of the program are concentrated on less parts that can be accelerated by the do-loop level of the parallel programming. This report shows the step-by-step parallel programming method and the parallel performance of the molecular dynamics code on VPP500 and Paragon. (author)
Adapting the Behavior Education Program for Preschool Settings
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…
Fast and Cache-Oblivious Dynamic Programming with Local Dependencies
DEFF Research Database (Denmark)
Bille, Philip; Stöckel, Morten
2012-01-01
are widely used in bioinformatics to compare DNA and protein sequences. These problems can all be solved using essentially the same dynamic programming scheme over a two-dimensional matrix, where each entry depends locally on at most 3 neighboring entries. We present a simple, fast, and cache......-oblivious algorithm for this type of local dynamic programming suitable for comparing large-scale strings. Our algorithm outperforms the previous state-of-the-art solutions. Surprisingly, our new simple algorithm is competitive with a complicated, optimized, and tuned implementation of the best cache-aware algorithm...
A Stereo Dual-Channel Dynamic Programming Algorithm for UAV Image Stitching.
Li, Ming; Chen, Ruizhi; Zhang, Weilong; Li, Deren; Liao, Xuan; Wang, Lei; Pan, Yuanjin; Zhang, Peng
2017-09-08
Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new algorithm for seamlessly stitching UAV images based on a dynamic programming approach. Our solution consists of two steps: Firstly, an image matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is developed based on the concept of a stereo dual-channel energy accumulation. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching, especially for the cases in dense urban areas. Our solution is also direction-independent, which has better adaptability and robustness for stitching images.
Gr-GDHP: A New Architecture for Globalized Dual Heuristic Dynamic Programming.
Zhong, Xiangnan; Ni, Zhen; He, Haibo
2017-10-01
Goal representation globalized dual heuristic dynamic programming (Gr-GDHP) method is proposed in this paper. A goal neural network is integrated into the traditional GDHP method providing an internal reinforcement signal and its derivatives to help the control and learning process. From the proposed architecture, it is shown that the obtained internal reinforcement signal and its derivatives can be able to adjust themselves online over time rather than a fixed or predefined function in literature. Furthermore, the obtained derivatives can directly contribute to the objective function of the critic network, whose learning process is thus simplified. Numerical simulation studies are applied to show the performance of the proposed Gr-GDHP method and compare the results with other existing adaptive dynamic programming designs. We also investigate this method on a ball-and-beam balancing system. The statistical simulation results are presented for both the Gr-GDHP and the GDHP methods to demonstrate the improved learning and controlling performance.
Programming adaptive control to evolve increased metabolite production.
Chou, Howard H; Keasling, Jay D
2013-01-01
The complexity inherent in biological systems challenges efforts to rationally engineer novel phenotypes, especially those not amenable to high-throughput screens and selections. In nature, increased mutation rates generate diversity in a population that can lead to the evolution of new phenotypes. Here we construct an adaptive control system that increases the mutation rate in order to generate diversity in the population, and decreases the mutation rate as the concentration of a target metabolite increases. This system is called feedback-regulated evolution of phenotype (FREP), and is implemented with a sensor to gauge the concentration of a metabolite and an actuator to alter the mutation rate. To evolve certain novel traits that have no known natural sensors, we develop a framework to assemble synthetic transcription factors using metabolic enzymes and construct four different sensors that recognize isopentenyl diphosphate in bacteria and yeast. We verify FREP by evolving increased tyrosine and isoprenoid production.
A short note on dynamic programming in a band.
Gibrat, Jean-François
2018-06-15
Third generation sequencing technologies generate long reads that exhibit high error rates, in particular for insertions and deletions which are usually the most difficult errors to cope with. The only exact algorithm capable of aligning sequences with insertions and deletions is a dynamic programming algorithm. In this note, for the sake of efficiency, we consider dynamic programming in a band. We show how to choose the band width in function of the long reads' error rates, thus obtaining an [Formula: see text] algorithm in space and time. We also propose a procedure to decide whether this algorithm, when applied to semi-global alignments, provides the optimal score. We suggest that dynamic programming in a band is well suited to the problem of aligning long reads between themselves and can be used as a core component of methods for obtaining a consensus sequence from the long reads alone. The function implementing the dynamic programming algorithm in a band is available, as a standalone program, at: https://forgemia.inra.fr/jean-francois.gibrat/BAND_DYN_PROG.git.
Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making
Kwakkel, Jan; Haasnoot, Marjolijn
2017-04-01
Dealing with climate risks in water management requires confronting a wide variety of deeply uncertain factors, while navigating a many dimensional space of trade-offs amongst objectives. There is an emerging body of literature on supporting this type of decision problem, under the label of decision making under deep uncertainty. Two approaches within this literature are Many-Objective Robust Decision Making, and Dynamic Adaptive Policy Pathways. In recent work, these approaches have been compared. One of the main conclusions of this comparison was that they are highly complementary. Many-Objective Robust Decision Making is a model based decision support approach, while Dynamic Adaptive Policy Pathways is primarily a conceptual framework for the design of flexible strategies that can be adapted over time in response to how the future is actually unfolding. In this research we explore this complementarity in more detail. Specifically, we demonstrate how Many-Objective Robust Decision Making can be used to design adaptation pathways. We demonstrate this combined approach using a water management problem, in the Netherlands. The water level of Lake IJselmeer, the main fresh water resource of the Netherlands, is currently managed through discharge by gravity. Due to climate change, this won't be possible in the future, unless water levels are changed. Changing the water level has undesirable flood risk and spatial planning consequences. The challenge is to find promising adaptation pathways that balance objectives related to fresh water supply, flood risk, and spatial issues, while accounting for uncertain climatic and land use change. We conclude that the combination of Many-Objective Robust Decision Making and Dynamic Adaptive Policy Pathways is particularly suited for dealing with deeply uncertain climate risks.
Dynamic balance during walking adaptability tasks in individuals post-stroke.
Vistamehr, Arian; Balasubramanian, Chitralakshmi K; Clark, David J; Neptune, Richard R; Fox, Emily J
2018-04-24
Maintaining dynamic balance during community ambulation is a major challenge post-stroke. Community ambulation requires performance of steady-state level walking as well as tasks that require walking adaptability. Prior studies on balance control post-stroke have mainly focused on steady-state walking, but walking adaptability tasks have received little attention. The purpose of this study was to quantify and compare dynamic balance requirements during common walking adaptability tasks post-stroke and in healthy adults and identify differences in underlying mechanisms used for maintaining dynamic balance. Kinematic data were collected from fifteen individuals with post-stroke hemiparesis during steady-state forward and backward walking, obstacle negotiation, and step-up tasks. In addition, data from ten healthy adults provided the basis for comparison. Dynamic balance was quantified using the peak-to-peak range of whole-body angular-momentum in each anatomical plane during the paretic, nonparetic and healthy control single-leg-stance phase of the gait cycle. To understand differences in some of the key underlying mechanisms for maintaining dynamic balance, foot placement and plantarflexor muscle activation were examined. Individuals post-stroke had significant dynamic balance deficits in the frontal plane across most tasks, particularly during the paretic single-leg-stance. Frontal plane balance deficits were associated with wider paretic foot placement, elevated body center-of-mass, and lower soleus activity. Further, the obstacle negotiation task imposed a higher balance requirement, particularly during the trailing leg single-stance. Thus, improving paretic foot placement and ankle plantarflexor activity, particularly during obstacle negotiation, may be important rehabilitation targets to enhance dynamic balance during post-stroke community ambulation. Copyright © 2018. Published by Elsevier Ltd.
International Development Research Centre (IDRC) Digital Library (Canada)
building skills, knowledge or networks on adaptation, ... the African partners leading the AfricaAdapt network, together with the UK-based Institute of Development Studies; and ... UNCCD Secretariat, Regional Coordination Unit for Africa, Tunis, Tunisia .... 26 Rural–urban Cooperation on Water Management in the Context of.
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
A Dynamic Programming Algorithm for the k-Haplotyping Problem
Institute of Scientific and Technical Information of China (English)
Zhen-ping Li; Ling-yun Wu; Yu-ying Zhao; Xiang-sun Zhang
2006-01-01
The Minimum Fragments Removal (MFR) problem is one of the haplotyping problems: given a set of fragments, remove the minimum number of fragments so that the resulting fragments can be partitioned into k classes of non-conflicting subsets. In this paper, we formulate the k-MFR problem as an integer linear programming problem, and develop a dynamic programming approach to solve the k-MFR problem for both the gapless and gap cases.
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.
Adaptive Synchronization of Fractional Order Complex-Variable Dynamical Networks via Pinning Control
Ding, Da-Wei; Yan, Jie; Wang, Nian; Liang, Dong
2017-09-01
In this paper, the synchronization of fractional order complex-variable dynamical networks is studied using an adaptive pinning control strategy based on close center degree. Some effective criteria for global synchronization of fractional order complex-variable dynamical networks are derived based on the Lyapunov stability theory. From the theoretical analysis, one concludes that under appropriate conditions, the complex-variable dynamical networks can realize the global synchronization by using the proper adaptive pinning control method. Meanwhile, we succeed in solving the problem about how much coupling strength should be applied to ensure the synchronization of the fractional order complex networks. Therefore, compared with the existing results, the synchronization method in this paper is more general and convenient. This result extends the synchronization condition of the real-variable dynamical networks to the complex-valued field, which makes our research more practical. Finally, two simulation examples show that the derived theoretical results are valid and the proposed adaptive pinning method is effective. Supported by National Natural Science Foundation of China under Grant No. 61201227, National Natural Science Foundation of China Guangdong Joint Fund under Grant No. U1201255, the Natural Science Foundation of Anhui Province under Grant No. 1208085MF93, 211 Innovation Team of Anhui University under Grant Nos. KJTD007A and KJTD001B, and also supported by Chinese Scholarship Council
Effect of the CTL proliferation program on virus dynamics
DEFF Research Database (Denmark)
Wodarz, Dominik; Thomsen, Allan Randrup
2005-01-01
Experiments have established that CTLs do not require continuous antigenic stimulation for expansion. Instead, responses develop by a process of programmed proliferation which involves approximately 7-10 antigen-independent cell divisions, the generation of effector cells and the differentiation...... virus loads and thus acute symptoms. The reason is that the programmed divisions are independent from antigenic stimulation, and an increase in virus load does not speed up the rate of CTL expansion. We hypothesize that the 7-10 programmed divisions observed in vivo represent an optimal solution...... into memory cells. The effect of this program on the infection dynamics and the advantages gained by the program have, however, not been explored yet. We investigate this with mathematical models. We find that more programmed divisions can make virus clearance more efficient because CTL division continues...
McKenna, Erin; Bray, Laurence C Jayet; Zhou, Weiwei; Joiner, Wilsaan M
2017-10-01
Delays in transmitting and processing sensory information require correctly associating delayed feedback to issued motor commands for accurate error compensation. The flexibility of this alignment between motor signals and feedback has been demonstrated for movement recalibration to visual manipulations, but the alignment dependence for adapting movement dynamics is largely unknown. Here we examined the effect of visual feedback manipulations on force-field adaptation. Three subject groups used a manipulandum while experiencing a lag in the corresponding cursor motion (0, 75, or 150 ms). When the offset was applied at the start of the session (continuous condition), adaptation was not significantly different between groups. However, these similarities may be due to acclimation to the offset before motor adaptation. We tested additional subjects who experienced the same delays concurrent with the introduction of the perturbation (abrupt condition). In this case adaptation was statistically indistinguishable from the continuous condition, indicating that acclimation to feedback delay was not a factor. In addition, end-point errors were not significantly different across the delay or onset conditions, but end-point correction (e.g., deceleration duration) was influenced by the temporal offset. As an additional control, we tested a group of subjects who performed without visual feedback and found comparable movement adaptation results. These results suggest that visual feedback manipulation (absence or temporal misalignment) does not affect adaptation to novel dynamics, independent of both acclimation and perceptual awareness. These findings could have implications for modeling how the motor system adjusts to errors despite concurrent delays in sensory feedback information. NEW & NOTEWORTHY A temporal offset between movement and distorted visual feedback (e.g., visuomotor rotation) influences the subsequent motor recalibration, but the effects of this offset for
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).
Directory of Open Access Journals (Sweden)
Zhaoxia Peng
2014-01-01
Full Text Available This paper investigates the distributed consensus-based robust adaptive formation control for nonholonomic mobile robots with partially known dynamics. Firstly, multirobot formation control problem has been converted into a state consensus problem. Secondly, the practical control strategies, which incorporate the distributed kinematic controllers and the robust adaptive torque controllers, are designed for solving the formation control problem. Thirdly, the specified reference trajectory for the geometric centroid of the formation is assumed as the trajectory of a virtual leader, whose information is available to only a subset of the followers. Finally, numerical results are provided to illustrate the effectiveness of the proposed control approaches.
A mobile communication device adapted to provide a dynamic display arrangement
DEFF Research Database (Denmark)
2011-01-01
The invention relates to a mobile communication device comprising a light projector adapted to project a multi-coloured image onto a surface; a hinged mirror comprising a first mirror part adapted to be tilted around the hinge into the light path of the light projector; wherein the first mirror...... part comprises means for correcting a skew angle in the multi-coloured image projected onto a surface. Thereby is achieved that the mobile communication device is able to provide RGB full colour dynamic image projection which is preferred over monochromatic laser projection because it is a speckle free...... and eye-friendly projection....
An Adaptable Neuromorphic Model of Orientation Selectivity Based On Floating Gate Dynamics
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Priti eGupta
2014-04-01
Full Text Available The biggest challenge that the neuromorphic community faces today is to build systems that can be considered truly cognitive. Adaptation and self-organization are the two basic principles that underlie any cognitive function that the brain performs. If we can replicate this behavior in hardware, we move a step closer to our goal of having cognitive neuromorphic systems. Adaptive feature selectivity is a mechanism by which nature optimizes resources so as to have greater acuity for more abundant features. Developing neuromorphic feature maps can help design generic machines that can emulate this adaptive behavior. Most neuromorphic models that have attempted to build self-organizing systems, follow the approach of modeling abstract theoretical frameworks in hardware. While this is good from a modeling and analysis perspective, it may not lead to the most efficient hardware. On the other hand, exploiting hardware dynamics to build adaptive systems rather than forcing the hardware to behave like mathematical equations, seems to be a more robust methodology when it comes to developing actual hardware for real world applications. In this paper we use a novel time-staggered Winner Take All circuit, that exploits the adaptation dynamics of floating gate transistors, to model an adaptive cortical cell that demonstrates Orientation Selectivity, a well-known biological phenomenon observed in the visual cortex. The cell performs competitive learning, refining its weights in response to input patterns resembling different oriented bars, becoming selective to a particular oriented pattern. Different analysis performed on the cell such as orientation tuning, application of abnormal inputs, response to spatial frequency and periodic patterns reveal close similarity between our cell and its biological counterpart. Embedded in a RC grid, these cells interact diffusively exhibiting cluster formation, making way for adaptively building orientation selective maps
Jansen-Osmann, Petra; Richter, Stefanie; Konczak, Jürgen; Kalveram, Karl-Theodor
2002-03-01
When humans perform goal-directed arm movements under the influence of an external damping force, they learn to adapt to these external dynamics. After removal of the external force field, they reveal kinematic aftereffects that are indicative of a neural controller that still compensates the no longer existing force. Such behavior suggests that the adult human nervous system uses a neural representation of inverse arm dynamics to control upper-extremity motion. Central to the notion of an inverse dynamic model (IDM) is that learning generalizes. Consequently, aftereffects should be observable even in untrained workspace regions. Adults have shown such behavior, but the ontogenetic development of this process remains unclear. This study examines the adaptive behavior of children and investigates whether learning a force field in one hemifield of the right arm workspace has an effect on force adaptation in the other hemifield. Thirty children (aged 6-10 years) and ten adults performed 30 degrees elbow flexion movements under two conditions of external damping (negative and null). We found that learning to compensate an external damping force transferred to the opposite hemifield, which indicates that a model of the limb dynamics rather than an association of visited space and experienced force was acquired. Aftereffects were more pronounced in the younger children and readaptation to a null-force condition was prolonged. This finding is consistent with the view that IDMs in children are imprecise neural representations of the actual arm dynamics. It indicates that the acquisition of IDMs is a developmental achievement and that the human motor system is inherently flexible enough to adapt to any novel force within the limits of the organism's biomechanics.
A Program to Prepare Graduate Students for Careers in Climate Adaptation Science
Huntly, N.; Belmont, P.; Flint, C.; Gordillo, L.; Howe, P. D.; Lutz, J. A.; Null, S. E.; Reed, S.; Rosenberg, D. E.; Wang, S. Y.
2017-12-01
We describe our experiences creating a graduate program that addresses the need for a next generation of scientists who can produce, communicate, and help implement actionable science. The Climate Adaptation Science (CAS) graduate program, funded by the National Science Foundation Research Traineeship (NRT) program, prepares graduate students for careers at the interfaces of science with policy and management in the field of climate adaptation, which is a major 21st-century challenge for science and society. The program is interdisciplinary, with students and faculty from natural, social, and physical sciences, engineering, and mathematics, and is based around interdisciplinary team research in collaboration with partners from outside of academia who have climate adaptation science needs. The program embeds students in a cycle of creating and implementing actionable science through a two-part internship, with partners from government, non-governmental organizations, and industry, that brackets and informs a year of interdisciplinary team research. The program is communication-rich, with events that foster information exchange and understanding across disciplines and workplaces. We describe the CAS program, our experiences in developing it, the research and internship experiences of students in the program, and initial metrics and feedback on the effectiveness of the program.
Schwing, Alan Michael
For computational fluid dynamics, the governing equations are solved on a discretized domain of nodes, faces, and cells. The quality of the grid or mesh can be a driving source for error in the results. While refinement studies can help guide the creation of a mesh, grid quality is largely determined by user expertise and understanding of the flow physics. Adaptive mesh refinement is a technique for enriching the mesh during a simulation based on metrics for error, impact on important parameters, or location of important flow features. This can offload from the user some of the difficult and ambiguous decisions necessary when discretizing the domain. This work explores the implementation of adaptive mesh refinement in an implicit, unstructured, finite-volume solver. Consideration is made for applying modern computational techniques in the presence of hanging nodes and refined cells. The approach is developed to be independent of the flow solver in order to provide a path for augmenting existing codes. It is designed to be applicable for unsteady simulations and refinement and coarsening of the grid does not impact the conservatism of the underlying numerics. The effect on high-order numerical fluxes of fourth- and sixth-order are explored. Provided the criteria for refinement is appropriately selected, solutions obtained using adapted meshes have no additional error when compared to results obtained on traditional, unadapted meshes. In order to leverage large-scale computational resources common today, the methods are parallelized using MPI. Parallel performance is considered for several test problems in order to assess scalability of both adapted and unadapted grids. Dynamic repartitioning of the mesh during refinement is crucial for load balancing an evolving grid. Development of the methods outlined here depend on a dual-memory approach that is described in detail. Validation of the solver developed here against a number of motivating problems shows favorable
Adaptations to the coping power program's structure, delivery settings, and clinician training.
Lochman, John E; Powell, Nicole; Boxmeyer, Caroline; Andrade, Brendan; Stromeyer, Sara L; Jimenez-Camargo, Luis Alberto
2012-06-01
This article describes the conceptual framework for the Coping Power program that has focused on proximal risk factors that can actively alter preadolescent children's aggressive behavior. The results of initial controlled efficacy trials are summarized. However, consistent with the theme of this special section, some clinicians and workshop participants have indicated barriers to the implementation of the Coping Power program in their service settings. In response to these types of concerns, three key areas of programmatic adaptation of the program that serve to address these concerns are then described in the article. First, existing and in-process studies of variations in how the program can be delivered are presented. Existing findings indicate how the child component fares when delivered by itself without the parent component, how simple monthly boosters affect intervention effects, and whether the program can be reduced by a third of its length and still be effective. Research planned or in progress on program variations examines whether group versus individual delivery of the program affects outcomes, whether the program can be adapted for early adolescents, whether the program can be delivered in an adaptive manner with the use of the Family Check Up, and whether a brief, efficient version of the program in conjunction with Internet programming can be developed and be effective. Second, the program has been and is being developed for use in different settings, other than the school-based delivery in the efficacy trials. Research has examined its use with aggressive deaf youth in a residential setting, with Oppositional Defiant Disorder and Conduct Disorder children in outpatient clinics, and in after-school programs. Third, the article reports how variations in training clinicians affect their ability to effectively use the program. PsycINFO Database Record (c) 2012 APA, all rights reserved.
Directory of Open Access Journals (Sweden)
Yao Yao
Full Text Available One of the important challenges in the field of evolutionary robotics is the development of systems that can adapt to a changing environment. However, the ability to adapt to unknown and fluctuating environments is not straightforward. Here, we explore the adaptive potential of simulated swarm robots that contain a genomic encoding of a bio-inspired gene regulatory network (GRN. An artificial genome is combined with a flexible agent-based system, representing the activated part of the regulatory network that transduces environmental cues into phenotypic behaviour. Using an artificial life simulation framework that mimics a dynamically changing environment, we show that separating the static from the conditionally active part of the network contributes to a better adaptive behaviour. Furthermore, in contrast with most hitherto developed ANN-based systems that need to re-optimize their complete controller network from scratch each time they are subjected to novel conditions, our system uses its genome to store GRNs whose performance was optimized under a particular environmental condition for a sufficiently long time. When subjected to a new environment, the previous condition-specific GRN might become inactivated, but remains present. This ability to store 'good behaviour' and to disconnect it from the novel rewiring that is essential under a new condition allows faster re-adaptation if any of the previously observed environmental conditions is reencountered. As we show here, applying these evolutionary-based principles leads to accelerated and improved adaptive evolution in a non-stable environment.
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
Weather and Climate Manipulation as an Optimal Control for Adaptive Dynamical Systems
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Sergei A. Soldatenko
2017-01-01
Full Text Available The weather and climate manipulation is examined as an optimal control problem for the earth climate system, which is considered as a complex adaptive dynamical system. Weather and climate manipulations are actually amorphous operations. Since their objectives are usually formulated vaguely, the expected results are fairly unpredictable and uncertain. However, weather and climate modification is a purposeful process and, therefore, we can formulate operations to manipulate weather and climate as the optimization problem within the framework of the optimal control theory. The complexity of the earth’s climate system is discussed and illustrated using the simplified low-order coupled chaotic dynamical system. The necessary conditions of optimality are derived for the large-scale atmospheric dynamics. This confirms that even a relatively simplified control problem for the atmospheric dynamics requires significant efforts to obtain the solution.
Martinez, N.
2016-09-06
Water and protein dynamics on a nanometer scale were measured by quasi-elastic neutron scattering in the piezophile archaeon Thermococcus barophilus and the closely related pressure-sensitive Thermococcus kodakarensis, at 0.1 and 40 MPa. We show that cells of the pressure sensitive organism exhibit higher intrinsic stability. Both the hydration water dynamics and the fast protein and lipid dynamics are reduced under pressure. In contrast, the proteome of T. barophilus is more pressure sensitive than that of T. kodakarensis. The diffusion coefficient of hydration water is reduced, while the fast protein and lipid dynamics are slightly enhanced with increasing pressure. These findings show that the coupling between hydration water and cellular constituents might not be simply a master-slave relationship. We propose that the high flexibility of the T. barophilus proteome associated with reduced hydration water may be the keys to the molecular adaptation of the cells to high hydrostatic pressure.
Martinez, N.; Michoud, Gregoire; Cario, A.; Ollivier, J.; Franzetti, B.; Jebbar, M.; Oger, P.; Peters, J.
2016-01-01
Water and protein dynamics on a nanometer scale were measured by quasi-elastic neutron scattering in the piezophile archaeon Thermococcus barophilus and the closely related pressure-sensitive Thermococcus kodakarensis, at 0.1 and 40 MPa. We show that cells of the pressure sensitive organism exhibit higher intrinsic stability. Both the hydration water dynamics and the fast protein and lipid dynamics are reduced under pressure. In contrast, the proteome of T. barophilus is more pressure sensitive than that of T. kodakarensis. The diffusion coefficient of hydration water is reduced, while the fast protein and lipid dynamics are slightly enhanced with increasing pressure. These findings show that the coupling between hydration water and cellular constituents might not be simply a master-slave relationship. We propose that the high flexibility of the T. barophilus proteome associated with reduced hydration water may be the keys to the molecular adaptation of the cells to high hydrostatic pressure.
A note on dynamic programming in accounts receivable management
Dirickx, Y.M.I.; Kistner, K.-P.
1982-01-01
The paper considers a dynamic programming formulation of the accounts receivable problem for single outstanding amounts. An optimal collection policy can be computed efficiently by invoking a “planning horizon” result that determines a time period beyond which the decision process cannot extend. The
PACE: A dynamic programming algorithm for hardware/software partitioning
DEFF Research Database (Denmark)
Knudsen, Peter Voigt; Madsen, Jan
1996-01-01
This paper presents the PACE partitioning algorithm which is used in the LYCOS co-synthesis system for partitioning control/dataflow graphs into hardware and software parts. The algorithm is a dynamic programming algorithm which solves both the problem of minimizing system execution time...
Dynamic Programming Approach for Exact Decision Rule Optimization
Amin, Talha
2013-01-01
This chapter is devoted to the study of an extension of dynamic programming approach that allows sequential optimization of exact decision rules relative to the length and coverage. It contains also results of experiments with decision tables from UCI Machine Learning Repository. © Springer-Verlag Berlin Heidelberg 2013.
Dynamic Frames Based Verification Method for Concurrent Java Programs
Mostowski, Wojciech
2016-01-01
In this paper we discuss a verification method for concurrent Java programs based on the concept of dynamic frames. We build on our earlier work that proposes a new, symbolic permission system for concurrent reasoning and we provide the following new contributions. First, we describe our approach
Optimum workforce-size model using dynamic programming approach
African Journals Online (AJOL)
This paper presents an optimum workforce-size model which determines the minimum number of excess workers (overstaffing) as well as the minimum total recruitment cost during a specified planning horizon. The model is an extension of other existing dynamic programming models for manpower planning in the sense ...
The Functional Programming Language R and the Paradigm of Dynamic Scientific Programming
Trancón y Widemann, B.; Bolz, C.F.; Grelck, C.; Loidl, H.-W.; Peña, R.
2013-01-01
R is an environment and functional programming language for statistical data analysis and visualization. Largely unknown to the functional programming community, it is popular and influential in many empirical sciences. Due to its integrated combination of dynamic and reflective scripting on one
Coxon, Kristy; Keay, Lisa
2015-12-09
Safe-transport is important to well-being in later life but balancing safety and independence for older drivers can be challenging. While self-regulation is a promising tool to promote road safety, more research is required to optimise programs. Qualitative research was used to inform the choice and adaptation of a safe-transport education program for older drivers. Three focus groups were conducted with older drivers living in northwest Sydney to explore four key areas related to driving in later life including aged-based licensing, stopping or limiting driving, barriers to driving cessation and alternative modes of transportation. Data were analysed using content analysis. Four categories emerged from the data; bad press for older drivers, COMPETENCE not age, call for fairness in licensing regulations, and hanging up the keys: It's complicated! Two key issues being (1) older drivers wanted to drive for as long as possible but (2) were not prepared for driving cessation; guided the choice and adaption of the Knowledge Enhances Your Safety (KEYS) program. This program was adapted for the Australian context and focus group findings raised the need for practical solutions, including transport alternatives, to be added. Targeted messages were developed from the data using the Precaution Adoption Process Model (PAPM), allowing the education to be tailored to the individual's stage of behaviour change. Adapting our program based on insights gained from community consultation should ensure the program is sensitive to the needs, skills and preferences of older drivers.
Largenet2: an object-oriented programming library for simulating large adaptive networks.
Zschaler, Gerd; Gross, Thilo
2013-01-15
The largenet2 C++ library provides an infrastructure for the simulation of large dynamic and adaptive networks with discrete node and link states. The library is released as free software. It is available at http://biond.github.com/largenet2. Largenet2 is licensed under the Creative Commons Attribution-NonCommercial 3.0 Unported License. gerd@biond.org
Intensive Research Program on Advances in Nonsmooth Dynamics 2016
Jeffrey, Mike; Lázaro, J; Olm, Josep
2017-01-01
This volume contains extended abstracts outlining selected talks and other selected presentations given by participants throughout the "Intensive Research Program on Advances in Nonsmooth Dynamics 2016", held at the Centre de Recerca Matemàtica (CRM) in Barcelona from February 1st to April 29th, 2016. They include brief research articles reporting new results, descriptions of preliminary work or open problems, and outlines of prominent discussion sessions. The articles are all the result of direct collaborations initiated during the research program. The topic is the theory and applications of Nonsmooth Dynamics. This includes systems involving elements of: impacting, switching, on/off control, hybrid discrete-continuous dynamics, jumps in physical properties, and many others. Applications include: electronics, climate modeling, life sciences, mechanics, ecology, and more. Numerous new results are reported concerning the dimensionality and robustness of nonsmooth models, shadowing variables, numbers of limit...
Hybrid Semantics of Stochastic Programs with Dynamic Reconfiguration
Directory of Open Access Journals (Sweden)
Alberto Policriti
2009-10-01
Full Text Available We begin by reviewing a technique to approximate the dynamics of stochastic programs --written in a stochastic process algebra-- by a hybrid system, suitable to capture a mixed discrete/continuous evolution. In a nutshell, the discrete dynamics is kept stochastic while the continuous evolution is given in terms of ODEs, and the overall technique, therefore, naturally associates a Piecewise Deterministic Markov Process with a stochastic program. The speciﬁc contribution in this work consists in an increase of the ﬂexibility of the translation scheme, obtained by allowing a dynamic reconﬁguration of the degree of discreteness/continuity of the semantics. We also discuss the relationships of this approach with other hybrid simulation strategies for biochemical systems.
Truong, Hoai-An; Taylor, Catherine R; DiPietro, Natalie A
2012-02-10
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. 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. 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. 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.
Directory of Open Access Journals (Sweden)
Richard C. Cervantes
2012-12-01
Full Text Available Behavioral health is defined as the absence of mental illness or substance use problems and the presence of positive emotional well being. Although many U.S. Hispanic youth are at increased risk for substance abuse, suicidality, teen pregnancy, unsafe sexual practices and HIV, there exists a lack of available evidence-based practices for Hispanic youth which promotes behavioral health and HIV prevention. The objective of the current research was to adapt and revise the Familia Adelante (FA Program, a behavioral health, drug intervention and prevention program to incorporate an HIV prevention component. Through qualitative community based participatory methods, including an expert panel and members of the target population, the curriculum was redesigned to integrate effective HIV risk reduction strategies. The process of adapting the intervention is described in this paper, as well as recommendations for future research in program adaptation.
Energy Technology Data Exchange (ETDEWEB)
Courteau, R.; Bose, T. K. [Universite du Quebec a Trois-Rivieres, Hydrogen Research Institute, Trois-Rivieres, PQ (Canada)
2004-07-01
An algorithm for self-adaptive tuning of an internal combustion engine is proposed, based on a Kalman filter operating on a few selected metrics of the dynamic pressure curve. Piezoelectric transducers are devices to monitor dynamic cylinder pressure; spark plugs with embedded piezo elements are now available to provide diagnostic engine functions. Such transducers are also capable of providing signals to the engine controller to perform auto tuning, a function that is considered very useful particularly in vehicles using alternative fuels whose characteristics frequently show variations between fill-ups. 2 refs., 2 figs.
Chaos Synchronization Using Adaptive Dynamic Neural Network Controller with Variable Learning Rates
Directory of Open Access Journals (Sweden)
Chih-Hong Kao
2011-01-01
Full Text Available This paper addresses the synchronization of chaotic gyros with unknown parameters and external disturbance via an adaptive dynamic neural network control (ADNNC system. The proposed ADNNC system is composed of a neural controller and a smooth compensator. The neural controller uses a dynamic RBF (DRBF network to online approximate an ideal controller. The DRBF network can create new hidden neurons online if the input data falls outside the hidden layer and prune the insignificant hidden neurons online if the hidden neuron is inappropriate. The smooth compensator is designed to compensate for the approximation error between the neural controller and the ideal controller. Moreover, the variable learning rates of the parameter adaptation laws are derived based on a discrete-type Lyapunov function to speed up the convergence rate of the tracking error. Finally, the simulation results which verified the chaotic behavior of two nonlinear identical chaotic gyros can be synchronized using the proposed ADNNC scheme.
Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network
International Nuclear Information System (INIS)
Mai, Huanhuan; Liao, Xiaofeng; Song, Gangbing
2013-01-01
Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller. (paper)
Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network
Mai, Huanhuan; Song, Gangbing; Liao, Xiaofeng
2013-01-01
Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller.
Behavioral and neural Darwinism: selectionist function and mechanism in adaptive behavior dynamics.
McDowell, J J
2010-05-01
An evolutionary theory of behavior dynamics and a theory of neuronal group selection share a common selectionist framework. The theory of behavior dynamics instantiates abstractly the idea that behavior is selected by its consequences. It implements Darwinian principles of selection, reproduction, and mutation to generate adaptive behavior in virtual organisms. The behavior generated by the theory has been shown to be quantitatively indistinguishable from that of live organisms. The theory of neuronal group selection suggests a mechanism whereby the abstract principles of the evolutionary theory may be implemented in the nervous systems of biological organisms. According to this theory, groups of neurons subserving behavior may be selected by synaptic modifications that occur when the consequences of behavior activate value systems in the brain. Together, these theories constitute a framework for a comprehensive account of adaptive behavior that extends from brain function to the behavior of whole organisms in quantitative detail. Copyright (c) 2009 Elsevier B.V. All rights reserved.
Understanding role of genome dynamics in host adaptation of gut commensal, L. reuteri
Directory of Open Access Journals (Sweden)
Shikha Sharma
2017-10-01
Full Text Available Lactobacillus reuteri is a gram-positive gut commensal and exhibits noteworthy adaptation to its vertebrate hosts. Host adaptation is often driven by inter-strain genome dynamics like expansion of insertion sequences that lead to acquisition and loss of gene(s and creation of large dynamic regions. In this regard we carried in-house genome sequencing of large number of L. reuteri strains origination from human, chicken, pig and rodents. We further next generation sequence data in understanding invasion and expansion of an IS element in shaping genome of strains belonging to human associated lineage. Finally, we share our experience in high-throughput genomic library preparation and generating high quality sequence data of a very low GC bacterium like L. reuteri.
Directory of Open Access Journals (Sweden)
Zhihua Zhang
2016-01-01
Full Text Available Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO. Rechenberg’s 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter.
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.
Quantum Information Biology: From Theory of Open Quantum Systems to Adaptive Dynamics
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.
Energy Technology Data Exchange (ETDEWEB)
Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teacher' s College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Lu Hongqian [Shandong Institute of Light Industry, Shandong Jinan 250353 (China)
2009-12-28
This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.
Calculation Method for Equilibrium Points in Dynamical Systems Based on Adaptive Sinchronization
Directory of Open Access Journals (Sweden)
Manuel Prian Rodríguez
2017-12-01
Full Text Available In this work, a control system is proposed as an equivalent numerical procedure whose aim is to obtain the natural equilibrium points of a dynamical system. These equilibrium points may be employed later as setpoint signal for different control techniques. The proposed procedure is based on the adaptive synchronization between an oscillator and a reference model driven by the oscillator state variables. A stability analysis is carried out and a simplified algorithm is proposed. Finally, satisfactory simulation results are shown.
International Nuclear Information System (INIS)
Xu Yuhua; Zhou Wuneng; Fang Jian'an; Lu Hongqian
2009-01-01
This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.
Dynamically adaptive Lattice Boltzmann simulation of shallow water flows with the Peano framework
Neumann, Philipp
2015-09-01
© 2014 Elsevier Inc. All rights reserved. We present a dynamically adaptive Lattice Boltzmann (LB) implementation for solving the shallow water equations (SWEs). Our implementation extends an existing LB component of the Peano framework. We revise the modular design with respect to the incorporation of new simulation aspects and LB models. The basic SWE-LB implementation is validated in different breaking dam scenarios. We further provide a numerical study on stability of the MRT collision operator used in our simulations.
An Adaptive Genetic Algorithm with Dynamic Population Size for Optimizing Join Queries
Vellev, Stoyan
2008-01-01
The problem of finding the optimal join ordering executing a query to a relational database management system is a combinatorial optimization problem, which makes deterministic exhaustive solution search unacceptable for queries with a great number of joined relations. In this work an adaptive genetic algorithm with dynamic population size is proposed for optimizing large join queries. The performance of the algorithm is compared with that of several classical non-determinis...
Payen, Celia; Di Rienzi, Sara C; Ong, Giang T; Pogachar, Jamie L; Sanchez, Joseph C; Sunshine, Anna B; Raghuraman, M K; Brewer, Bonita J; Dunham, Maitreya J
2014-03-20
Population adaptation to strong selection can occur through the sequential or parallel accumulation of competing beneficial mutations. The dynamics, diversity, and rate of fixation of beneficial mutations within and between populations are still poorly understood. To study how the mutational landscape varies across populations during adaptation, we performed experimental evolution on seven parallel populations of Saccharomyces cerevisiae continuously cultured in limiting sulfate medium. By combining quantitative polymerase chain reaction, array comparative genomic hybridization, restriction digestion and contour-clamped homogeneous electric field gel electrophoresis, and whole-genome sequencing, we followed the trajectory of evolution to determine the identity and fate of beneficial mutations. During a period of 200 generations, the yeast populations displayed parallel evolutionary dynamics that were driven by the coexistence of independent beneficial mutations. Selective amplifications rapidly evolved under this selection pressure, in particular common inverted amplifications containing the sulfate transporter gene SUL1. Compared with single clones, detailed analysis of the populations uncovers a greater complexity whereby multiple subpopulations arise and compete despite a strong selection. The most common evolutionary adaptation to strong selection in these populations grown in sulfate limitation is determined by clonal interference, with adaptive variants both persisting and replacing one another.
Dynamic adjustments of cognitive control: oscillatory correlates of the conflict adaptation effect.
Pastötter, Bernhard; Dreisbach, Gesine; Bäuml, Karl-Heinz T
2013-12-01
It is a prominent idea that cognitive control mediates conflict adaptation, in that response conflict in a previous trial triggers control adjustments that reduce conflict in a current trial. In the present EEG study, we investigated the dynamics of cognitive control in a response-priming task by examining the effects of previous trial conflict on intertrial and current trial oscillatory brain activities, both on the electrode and the source level. Behavioral results showed conflict adaptation effects for RTs and response accuracy. Physiological results showed sustained intertrial effects in left parietal theta power, originating in the left inferior parietal cortex, and midcentral beta power, originating in the left and right (pre)motor cortex. Moreover, physiological analysis revealed a current trial conflict adaptation effect in midfrontal theta power, originating in the ACC. Correlational analyses showed that intertrial effects predicted conflict-induced midfrontal theta power in currently incongruent trials. In addition, conflict adaptation effects in midfrontal theta power and RTs were positively related. Together, these findings point to a dynamic cognitive control system that, as a function of previous trial type, up- and down-regulates attention and preparatory motor activities in anticipation of the next trial.
Directory of Open Access Journals (Sweden)
Li Zhao
2016-01-01
Full Text Available An improved smooth adaptive internal model control based on U model control method is presented to simplify modeling structure and parameter identification for a class of uncertain dynamic systems with unknown model parameters and bounded external disturbances. Differing from traditional adaptive methods, the proposed controller can simplify the identification of time-varying parameters in presence of bounded external disturbances. Combining the small gain theorem and the virtual equivalent system theory, learning rate of smooth adaptive internal model controller has been analyzed and the closed-loop virtual equivalent system based on discrete U model has been constructed as well. The convergence of this virtual equivalent system is proved, which further shows the convergence of the complex closed-loop discrete U model system. Finally, simulation and experimental results on a typical nonlinear dynamic system verified the feasibility of the proposed algorithm. The proposed method is shown to have lighter identification burden and higher control accuracy than the traditional adaptive controller.
Block Fusion on Dynamically Adaptive Spacetree Grids for Shallow Water Waves
Weinzierl, Tobias
2014-09-01
© 2014 World Scientific Publishing Company. Spacetrees are a popular formalism to describe dynamically adaptive Cartesian grids. Even though they directly yield a mesh, it is often computationally reasonable to embed regular Cartesian blocks into their leaves. This promotes stencils working on homogeneous data chunks. The choice of a proper block size is sensitive. While large block sizes foster loop parallelism and vectorisation, they restrict the adaptivity\\'s granularity and hence increase the memory footprint and lower the numerical accuracy per byte. In the present paper, we therefore use a multiscale spacetree-block coupling admitting blocks on all spacetree nodes. We propose to find sets of blocks on the finest scale throughout the simulation and to replace them by fused big blocks. Such a replacement strategy can pick up hardware characteristics, i.e. which block size yields the highest throughput, while the dynamic adaptivity of the fine grid mesh is not constrained - applications can work with fine granular blocks. We study the fusion with a state-of-the-art shallow water solver at hands of an Intel Sandy Bridge and a Xeon Phi processor where we anticipate their reaction to selected block optimisation and vectorisation.
Evolution dynamics of a model for gene duplication under adaptive conflict
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.
Patient-adapted reconstruction and acquisition dynamic imaging method (PARADIGM) for MRI
International Nuclear Information System (INIS)
Aggarwal, Nitin; Bresler, Yoram
2008-01-01
Dynamic magnetic resonance imaging (MRI) is a challenging problem because the MR data acquisition is often not fast enough to meet the combined spatial and temporal Nyquist sampling rate requirements. Current approaches to this problem include hardware-based acceleration of the acquisition, and model-based image reconstruction techniques. In this paper we propose an alternative approach, called PARADIGM, which adapts both the acquisition and reconstruction to the spatio-temporal characteristics of the imaged object. The approach is based on time-sequential sampling theory, addressing the problem of acquiring a spatio-temporal signal under the constraint that only a limited amount of data can be acquired at a time instant. PARADIGM identifies a model class for the particular imaged object using a scout MR scan or auxiliary data. This object-adapted model is then used to optimize MR data acquisition, such that the imaging constraints are met, acquisition speed requirements are minimized, essentially perfect reconstruction of any object in the model class is guaranteed, and the inverse problem of reconstructing the dynamic object has a condition number of one. We describe spatio-temporal object models for various dynamic imaging applications including cardiac imaging. We present the theory underlying PARADIGM and analyze its performance theoretically and numerically. We also propose a practical MR imaging scheme for 2D dynamic cardiac imaging based on the theory. For this application, PARADIGM is predicted to provide a 10–25 × acceleration compared to the optimal non-adaptive scheme. Finally we present generalized optimality criteria and extend the scheme to dynamic imaging with three spatial dimensions
Directory of Open Access Journals (Sweden)
R.M. Wise
2016-01-01
Full Text Available Achieving climate compatible development (CCD is a necessity in developing countries, but there are few examples of requisite planning processes, or manifestations of CCD. This paper presents a multi-stakeholder, participatory planning process designed to screen and prioritise rural livelihood adaptation strategies against nine CCD criteria. The process also integrated three principles of adaptation pathways: interventions should be (1 ‘no regrets’ and maintain reversibility to avoid mal-adaptation; (2 address both proximate and underlying systemic drivers of community vulnerability; and (3 linked across spatial scales and jurisdictional levels to promote coordination. Using examples of two rural sub-districts in Indonesia, we demonstrate the process and resulting CCD strategies. Priority strategies varied between the sub-districts but all reflected standard development interventions: water management, intensification or diversification of agriculture and aquaculture, education, health, food security and skills-building for communities. Strategies delivered co-benefits for human development and ecosystem services and hence adaptive capacity, but greenhouse mitigation co-benefits were less significant. Actions to deliver the strategies’ objectives were screened for reversibility, and a minority were potentially mal-adaptive (i.e. path dependent, disproportionately burdening the most vulnerable, reducing incentives to adapt, or increasing greenhouse gas emissions yet highly feasible. These related to infrastructure, which paradoxically is necessary to deliver ‘soft’ adaptation benefits (i.e. road access to health services. Only a small minority of transformative strategies addressed the systemic (i.e. institutional and political drivers of vulnerability. Strategies were well-matched by development programs, suggesting that current interventions mirror CCD. However, development programs tackled fewer systemic drivers, were poorly
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
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.
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.
Spike-threshold adaptation predicted by membrane potential dynamics in vivo.
Directory of Open Access Journals (Sweden)
Bertrand Fontaine
2014-04-01
Full Text Available Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo.
Use of a complete starter feed in grain adaptation programs for feedlot cattle.
Schneider, C J; Nuttelman, B L; Shreck, A L; Burken, D B; Griffin, W A; Gramkow, J L; Stock, R A; Klopfenstein, T J; Erickson, G E
2017-08-01
Four experiments evaluated the use of a complete starter feed (RAMP; Cargill Corn Milling, Blair, NE) for grain adaptation. In Exp. 1, 229 yearling steers (397 ± 28.4 kg BW) were used to compare a traditional adaptation program (CON) with adapting cattle with RAMP in either a 1- (RAMP-1RS) or 2- (RAMP-2RS) ration system. From d 23 to slaughter, cattle were fed a common finishing diet. In Exp. 2, 390 yearling steers (341 ± 14 kg BW) were used to compare accelerated grain adaptation programs with RAMP with 2 control treatments where RAMP was blended with a finishing diet containing either 25 (CON25) or 47.5% (CON47) Sweet Bran (Cargill Corn Milling) in 4 steps fed over 24 d to adapt cattle. Rapid adaptation treatments involved feeding RAMP for 10 d followed by a blend of RAMP and a 47% Sweet Bran finishing diet to transition cattle with 3 blends fed for 1 d each (3-1d), 2 blends fed for 2 d each (2-2d), or 1 blend fed for 4 d (1-4d). From d 29 to slaughter, all cattle were fed a common finishing diet. In Exp. 3, 300 steer calves (292 ± 21 kg BW) were used to compare the CON47 and 1-4d adaptation programs with directly transitioning cattle from RAMP, which involved feeding RAMP for 10 d and then switching directly to F1 on d 11 (1-STEP). From d 29 until slaughter, F2 was fed to all cattle. In Exp. 4, 7 ruminally fistulated steers (482 ± 49 kg BW) were used in a 35-d trial to compare the CON47 and 1-STEP adaptation programs. Ruminal pH and intake data from the first 6 d of F1and first 6 d of F2 were used to compare adaptation systems. Adaptation with RAMP-1RS and RAMP-2RS increased ( cattle adapted using CON in Exp. 1. Feeding RAMP-1RS increased ADG ( = 0.03) compared with CON. Intakes were similar ( = 0.39) among treatments. Daily gain, DMI, G:F, and carcass traits were similar ( > 0.11) among treatments in Exp. 2. Daily gain, DMI, and G:F were not different ( > 0.20) among treatments on d 39 or over the entire feeding period in Exp. 3. When F1 or F2 was being fed
Optimal Operation of Radial Distribution Systems Using Extended Dynamic Programming
DEFF Research Database (Denmark)
Lopez, Juan Camilo; Vergara, Pedro P.; Lyra, Christiano
2018-01-01
An extended dynamic programming (EDP) approach is developed to optimize the ac steady-state operation of radial electrical distribution systems (EDS). Based on the optimality principle of the recursive Hamilton-Jacobi-Bellman equations, the proposed EDP approach determines the optimal operation o...... approach is illustrated using real-scale systems and comparisons with commercial programming solvers. Finally, generalizations to consider other EDS operation problems are also discussed.......An extended dynamic programming (EDP) approach is developed to optimize the ac steady-state operation of radial electrical distribution systems (EDS). Based on the optimality principle of the recursive Hamilton-Jacobi-Bellman equations, the proposed EDP approach determines the optimal operation...... of the EDS by setting the values of the controllable variables at each time period. A suitable definition for the stages of the problem makes it possible to represent the optimal ac power flow of radial EDS as a dynamic programming problem, wherein the 'curse of dimensionality' is a minor concern, since...
Perceptions of Preservice Teachers about Adaptive Learning Programs in K-8 Mathematics Education
Smith, Kevin
2018-01-01
Adaptivelearning programs are frequently used in the K-8 mathematics classroom. Theseprograms provide instruction to students at the appropriate level of difficultyby presenting content, providing feedback, and allowing students to masterskills before progressing. The purpose of the study was to seek to interprethow preservice teachers’ experiences influence their perceptions and plans tointegrate adaptive learning programs in their future K-8 mathematics classroom.This was a qualitative stud...
Möbus, Claus; Schröder, Olaf
1993-01-01
The topic of our project has been to empirically investigate and to model processes of the acquisition, utilization, and optimization of knowledge while working with the ABSYNT Problem Solving Monitor (PSM ). The ABSYNT PSM is designed to support the acquisition of basic functional programming concepts by supplying learners with individualized, adaptive online help and proposals. ABSYNT ("Abstract Syntax Trees") is a functional visual programming language developed in the project. The ABSYNT ...
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. © The Author(s) 2014.
International Nuclear Information System (INIS)
Courteau, R.; Bose, T.K.
2004-01-01
Piezoelectric transducers offer an effective, non-intrusive way to monitor dynamic cylinder pressure in internal combustion engines. Devices dedicated to this purpose are appearing on the market, often in the form of spark plugs with embedded piezo elements. Dynamic cylinder pressure is typically used to provide diagnostic functions, or to help map an engine after it is designed. With the advent of powerful signal processor chips, it is now possible to embed enough computing power in the engine controller to perform auto tuning based on the signals provided by such transducers. Such functionality is very useful if the fuel characteristics vary between fill ups, as is often the case with alternative fuels. We propose here an algorithm for self-adaptive tuning based on a Kalman filter operating on a few selected metrics of the dynamic pressure curve. (author)
Directory of Open Access Journals (Sweden)
Fritzie Arce
2010-01-01
Full Text Available Motor control and adaptation are multi-determinate processes with complex interactions. This is reflected for example in the ambiguous nature of interactions during sequential adaptation of reaching under kinematics and dynamics perturbations. It has been suggested that perturbations based on the same kinematic parameter interfere. Others posited that opposing motor adjustments underlie interference. Here, we examined the influence of discordances in task and in motor adjustments on sequential adaptations to visuomotor rotation and viscous force field perturbations. These two factors – perturbation direction and task discordance – have been examined separately by previous studies, thus the inherent difficulty to identify the roots of interference. Forty-eight human subjects adapted sequentially to one or two types of perturbations, of matched or conflicting directions. We found a gradient of interaction effects based on perturbation direction and task discordance. Perturbations of matched directions showed facilitation while perturbations of opposite directions, which required opposing motor adjustments, interfered with each other. Further, interaction effects increased with greater task discordance. We also found that force field and visuomotor rotation had mutual anterograde and retrograde effects. However, we found independence between anterograde and retrograde interferences between similar tasks. The results suggest that the newly acquired internal models of kinematic and dynamic perturbations are not independent but they share common neuronal resources and interact between them. Such overlap does not necessarily imply competition of resources. Rather, our results point to an additional principle of sensorimotor adaptation allowing the system to tap or harness common features across diverse sensory inputs and task contexts whenever available.
Chiang, Austin W T; Liu, Wei-Chung; Charusanti, Pep; Hwang, Ming-Jing
2014-01-15
A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system's dynamics. We demonstrate our methodology on a prototype biological system of perfect adaptation dynamics, namely the chemotaxis model for Escherichia coli. Our results agreed well with those derived from experimental data and theoretical studies in the literature. Using this model system, we showed that there are motifs in kinetic parameters and that these motifs are governed by constraints of the specified system dynamics. A systematic approach based on enrichment statistical tests has been developed to elucidate the relationships between model parameters and the roles they play in affecting system dynamics of a prototype biological network. The proposed approach is generally applicable and therefore can find wide use in systems biology modeling research.
Discrete Globalised Dual Heuristic Dynamic Programming in Control of the Two-Wheeled Mobile Robot
Directory of Open Access Journals (Sweden)
Marcin Szuster
2014-01-01
Full Text Available Network-based control systems have been emerging technologies in the control of nonlinear systems over the past few years. This paper focuses on the implementation of the approximate dynamic programming algorithm in the network-based tracking control system of the two-wheeled mobile robot, Pioneer 2-DX. The proposed discrete tracking control system consists of the globalised dual heuristic dynamic programming algorithm, the PD controller, the supervisory term, and an additional control signal. The structure of the supervisory term derives from the stability analysis realised using the Lyapunov stability theorem. The globalised dual heuristic dynamic programming algorithm consists of two structures: the actor and the critic, realised in a form of neural networks. The actor generates the suboptimal control law, while the critic evaluates the realised control strategy by approximation of value function from the Bellman’s equation. The presented discrete tracking control system works online, the neural networks’ weights adaptation process is realised in every iteration step, and the neural networks preliminary learning procedure is not required. The performance of the proposed control system was verified by a series of computer simulations and experiments realised using the wheeled mobile robot Pioneer 2-DX.
The climate adaptation programs and activities of the Yellowstone to Yukon Conservation Initiative
Wendy L. Francis
2011-01-01
The Yellowstone to Yukon Conservation Initiative (Y2Y) is an innovative transboundary effort to protect biodiversity and facilitate climate adaptation by linking large protected core areas through compatible land uses on matrix lands. The Y2Y organization acts as the keeper of the Y2Y vision and implements two interconnected programs - Science and Action, and Vision...
Program of Adaptation Assistance in Foster Families and Particular Features of Its Implementation
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…
Effectiveness of Structured Teacher Adaptations to an Evidence-Based Summer Literacy Program
Kim, James S.; Burkhauser, Mary A.; Quinn, David M.; Guryan, Jonathan; Kingston, Helen Chen; Aleman, Kirsten
2017-01-01
The authors conducted a cluster-randomized trial to examine the effectiveness of structured teacher adaptations to the implementation of an evidence-based summer literacy program that provided students with (a) books matched to their reading level and interests and (b) teacher scaffolding for summer reading in the form of end-of-year comprehension…
Climate Change Adaptation in Africa Program : 2009-10 in brief
International Development Research Centre (IDRC) Digital Library (Canada)
CCAA
adaptation efforts should be grounded in scientific knowledge, and integrated into policy and development ... methodology and designing strategies to inform policies has ensured that policymakers were engaged ... in 2006, the CCAA research and capacity building program works on the premise that Africans themselves ...
Synthesizing Dynamic Programming Algorithms from Linear Temporal Logic Formulae
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.
Directory of Open Access Journals (Sweden)
S. Alonso-Quesada
2010-01-01
Full Text Available This paper presents a strategy for designing a robust discrete-time adaptive controller for stabilizing linear time-invariant (LTI continuous-time dynamic systems. Such systems may be unstable and noninversely stable in the worst case. A reduced-order model is considered to design the adaptive controller. The control design is based on the discretization of the system with the use of a multirate sampling device with fast-sampled control signal. A suitable on-line adaptation of the multirate gains guarantees the stability of the inverse of the discretized estimated model, which is used to parameterize the adaptive controller. A dead zone is included in the parameters estimation algorithm for robustness purposes under the presence of unmodeled dynamics in the controlled dynamic system. The adaptive controller guarantees the boundedness of the system measured signal for all time. Some examples illustrate the efficacy of this control strategy.
GLOBEC (Global Ocean Ecosystems Dynamics: Northwest Atlantic program
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.
Dynamic Post-Earthquake Image Segmentation with an Adaptive Spectral-Spatial Descriptor
Directory of Open Access Journals (Sweden)
Genyun Sun
2017-08-01
Full Text Available The region merging algorithm is a widely used segmentation technique for very high resolution (VHR remote sensing images. However, the segmentation of post-earthquake VHR images is more difficult due to the complexity of these images, especially high intra-class and low inter-class variability among damage objects. Herein two key issues must be resolved: the first is to find an appropriate descriptor to measure the similarity of two adjacent regions since they exhibit high complexity among the diverse damage objects, such as landslides, debris flow, and collapsed buildings. The other is how to solve over-segmentation and under-segmentation problems, which are commonly encountered with conventional merging strategies due to their strong dependence on local information. To tackle these two issues, an adaptive dynamic region merging approach (ADRM is introduced, which combines an adaptive spectral-spatial descriptor and a dynamic merging strategy to adapt to the changes of merging regions for successfully detecting objects scattered globally in a post-earthquake image. In the new descriptor, the spectral similarity and spatial similarity of any two adjacent regions are automatically combined to measure their similarity. Accordingly, the new descriptor offers adaptive semantic descriptions for geo-objects and thus is capable of characterizing different damage objects. Besides, in the dynamic region merging strategy, the adaptive spectral-spatial descriptor is embedded in the defined testing order and combined with graph models to construct a dynamic merging strategy. The new strategy can find the global optimal merging order and ensures that the most similar regions are merged at first. With combination of the two strategies, ADRM can identify spatially scattered objects and alleviates the phenomenon of over-segmentation and under-segmentation. The performance of ADRM has been evaluated by comparing with four state-of-the-art segmentation methods
Optimization of a pump-pipe system by dynamic programming
DEFF Research Database (Denmark)
Vidal, Rene Victor Valqui; Ferreira, Jose S.
1984-01-01
In this paper the problem of minimizing the total cost of a pump-pipe system in series is considered. The route of the pipeline and the number of pumping stations are known. The optimization will then consist in determining the control variables, diameter and thickness of the pipe and the size of...... of the pumps. A general mathematical model is formulated and Dynamic Programming is used to find an optimal solution....
Systems and methods for interpolation-based dynamic programming
Rockwood, Alyn
2013-01-03
Embodiments of systems and methods for interpolation-based dynamic programming. In one embodiment, the method includes receiving an object function and a set of constraints associated with the objective function. The method may also include identifying a solution on the objective function corresponding to intersections of the constraints. Additionally, the method may include generating an interpolated surface that is in constant contact with the solution. The method may also include generating a vector field in response to the interpolated surface.
Dynamic Programming Approach for Construction of Association Rule Systems
Alsolami, Fawaz
2016-11-18
In the paper, an application of dynamic programming approach for optimization of association rules from the point of view of knowledge representation is considered. The association rule set is optimized in two stages, first for minimum cardinality and then for minimum length of rules. Experimental results present cardinality of the set of association rules constructed for information system and lower bound on minimum possible cardinality of rule set based on the information obtained during algorithm work as well as obtained results for length.
Systems and methods for interpolation-based dynamic programming
Rockwood, Alyn
2013-01-01
Embodiments of systems and methods for interpolation-based dynamic programming. In one embodiment, the method includes receiving an object function and a set of constraints associated with the objective function. The method may also include identifying a solution on the objective function corresponding to intersections of the constraints. Additionally, the method may include generating an interpolated surface that is in constant contact with the solution. The method may also include generating a vector field in response to the interpolated surface.
DYNAMIC PROGRAMMING – EFFICIENT TOOL FOR POWER SYSTEM EXPANSION PLANNING
Directory of Open Access Journals (Sweden)
SIMO A.
2015-03-01
Full Text Available The paper isfocusing on dynamic programming use for power system expansion planning (EP – transmission network (TNEP and distribution network (DNEP. The EP problem has been approached from the retrospective and prospective point of view. To achieve this goal, the authors are developing two software-tools in Matlab environment. Two techniques have been tackled: particle swarm optimization (PSO and genetic algorithms (GA. The case study refers to Test 25 buses test power system developed within the Power Systems Department.
Dynamic Programming Approach for Construction of Association Rule Systems
Alsolami, Fawaz; Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata
2016-01-01
In the paper, an application of dynamic programming approach for optimization of association rules from the point of view of knowledge representation is considered. The association rule set is optimized in two stages, first for minimum cardinality and then for minimum length of rules. Experimental results present cardinality of the set of association rules constructed for information system and lower bound on minimum possible cardinality of rule set based on the information obtained during algorithm work as well as obtained results for length.
SEWER NETWORK DISCHARGE OPTIMIZATION USING THE DYNAMIC PROGRAMMING
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Viorel MINZU
2015-12-01
Full Text Available It is necessary to adopt an optimal control that allows an efficient usage of the existing sewer networks, in order to avoid the building of new retention facilities. The main objective of the control action is to minimize the overflow volume of a sewer network. This paper proposes a method to apply a solution obtained by discrete dynamic programming through a realistic closed loop system.
An Approximate Dynamic Programming Mode for Optimal MEDEVAC Dispatching
2015-03-26
over the myopic policy. This indicates the ADP policy is efficiently managing resources by 28 not immediately sending the nearest available MEDEVAC...DISPATCHING THESIS Presented to the Faculty Department of Operational Sciences Graduate School of Engineering and Management Air Force Institute of Technology...medical evacuation (MEDEVAC) dispatch policies. To solve the MDP, we apply an ap- proximate dynamic programming (ADP) technique. The problem of deciding
Approximate Dynamic Programming Based on High Dimensional Model Representation
Czech Academy of Sciences Publication Activity Database
Pištěk, Miroslav
2013-01-01
Roč. 49, č. 5 (2013), s. 720-737 ISSN 0023-5954 R&D Projects: GA ČR(CZ) GAP102/11/0437 Institutional support: RVO:67985556 Keywords : approximate dynamic programming * Bellman equation * approximate HDMR minimization * trust region problem Subject RIV: BC - Control Systems Theory Impact factor: 0.563, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/pistek-0399560.pdf
Adaptive control of dynamical synchronization on evolving networks with noise disturbances
Yuan, Wu-Jie; Zhou, Jian-Fang; Sendiña-Nadal, Irene; Boccaletti, Stefano; Wang, Zhen
2018-02-01
In real-world networked systems, the underlying structure is often affected by external and internal unforeseen factors, making its evolution typically inaccessible. An adaptive strategy was introduced for maintaining synchronization on unpredictably evolving networks [Sorrentino and Ott, Phys. Rev. Lett. 100, 114101 (2008), 10.1103/PhysRevLett.100.114101], which yet does not consider the noise disturbances widely existing in networks' environments. We provide here strategies to control dynamical synchronization on slowly and unpredictably evolving networks subjected to noise disturbances which are observed at the node and at the communication channel level. With our strategy, the nodes' coupling strength is adaptively adjusted with the aim of controlling synchronization, and according only to their received signal and noise disturbances. We first provide a theoretical analysis of the control scheme by introducing an error potential function to seek for the minimization of the synchronization error. Then, we show numerical experiments which verify our theoretical results. In particular, it is found that our adaptive strategy is effective even for the case in which the dynamics of the uncontrolled network would be explosive (i.e., the states of all the nodes would diverge to infinity).
Directory of Open Access Journals (Sweden)
Shihai Zhang
2018-06-01
Full Text Available Unbalance vibration is one of the main vibration forms of a high speed machine tool spindle. The overlarge unbalance vibration will have some adverse effects on the working life of the spindle system and the surface quality of the work-piece. In order to reduce the unbalance of a high speed spindle system, a pneumatic online dynamic balance device and its control system are presented in the paper. To improve the balance accuracy and adaptation of the balance system, the gain parameter adaption and scheduling control method are proposed first, and then the different balance effects of the influence coefficient method and the gain scheduling control method are compared through many dynamic balance experiments of the high speed spindle. The experimental results indicate that the gain parameters can be changed timely according to the transformation of the speed and kinetic parameters of the spindle system. The balance accuracy can be improved for a high speed spindle with time-varying characteristics, based on the adaptive gain scheduling control method.
International Nuclear Information System (INIS)
Zhao, Zhanqi; Möller, Knut; Guttmann, Josef
2012-01-01
The objective of this paper is to introduce and evaluate the adaptive SLICE method (ASM) for continuous determination of intratidal nonlinear dynamic compliance and resistance. The tidal volume is subdivided into a series of volume intervals called slices. For each slice, one compliance and one resistance are calculated by applying a least-squares-fit method. The volume window (width) covered by each slice is determined based on the confidence interval of the parameter estimation. The method was compared to the original SLICE method and evaluated using simulation and animal data. The ASM was also challenged with separate analysis of dynamic compliance during inspiration. If the signal-to-noise ratio (SNR) in the respiratory data decreased from +∞ to 10 dB, the relative errors of compliance increased from 0.1% to 22% for the ASM and from 0.2% to 227% for the SLICE method. Fewer differences were found in resistance. When the SNR was larger than 40 dB, the ASM delivered over 40 parameter estimates (42.2 ± 1.3). When analyzing the compliance during inspiration separately, the estimates calculated with the ASM were more stable. The adaptive determination of slice bounds results in consistent and reliable parameter values. Online analysis of nonlinear respiratory mechanics will profit from such an adaptive selection of interval size. (paper)
An algorithm for the solution of dynamic linear programs
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
Adapting high-level language programs for parallel processing using data flow
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
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.
Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set
Directory of Open Access Journals (Sweden)
Jinna Li
2012-01-01
Full Text Available A novel fault detection technique is proposed to explicitly account for the nonlinear, dynamic, and multimodal problems existed in the practical and complex dynamic processes. Just-in-time (JIT detection method and k-nearest neighbor (KNN rule-based statistical process control (SPC approach are integrated to construct a flexible and adaptive detection scheme for the control process with nonlinear, dynamic, and multimodal cases. Mahalanobis distance, representing the correlation among samples, is used to simplify and update the raw data set, which is the first merit in this paper. Based on it, the control limit is computed in terms of both KNN rule and SPC method, such that we can identify whether the current data is normal or not by online approach. Noted that the control limit obtained changes with updating database such that an adaptive fault detection technique that can effectively eliminate the impact of data drift and shift on the performance of detection process is obtained, which is the second merit in this paper. The efficiency of the developed method is demonstrated by the numerical examples and an industrial case.
Directory of Open Access Journals (Sweden)
Ali Tavasoli
2012-01-01
Full Text Available Nonlinear vehicle control allocation is achieved through distributing the task of vehicle control among individual tire forces, which are constrained to nonlinear saturation conditions. A high-level sliding mode control with adaptive upper bounds is considered to assess the body yaw moment and lateral force for the vehicle motion. The proposed controller only requires the online adaptation of control gains without acquiring the knowledge of upper bounds on system uncertainties. Static and dynamic control allocation approaches have been formulated to distribute high-level control objectives among the system inputs. For static control allocation, the interior-point method is applied to solve the formulated nonlinear optimization problem. Based on the dynamic control allocation method, a dynamic update law is derived to allocate vehicle control to tire forces. The allocated tire forces are fed into a low-level control module, where the applied torque and active steering angle at each wheel are determined through a slip-ratio controller and an inverse tire model. Computer simulations are used to prove the significant effects of the proposed control allocation methods on improving the stability and handling performance. The advantages and limitations of each method have been discussed, and conclusions have been derived.
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Philipp S Orekhov
2015-10-01
Full Text Available Motile bacteria and archaea respond to chemical and physical stimuli seeking optimal conditions for survival. To this end transmembrane chemo- and photoreceptors organized in large arrays initiate signaling cascades and ultimately regulate the rotation of flagellar motors. To unravel the molecular mechanism of signaling in an archaeal phototaxis complex we performed coarse-grained molecular dynamics simulations of a trimer of receptor/transducer dimers, namely NpSRII/NpHtrII from Natronomonas pharaonis. Signaling is regulated by a reversible methylation mechanism called adaptation, which also influences the level of basal receptor activation. Mimicking two extreme methylation states in our simulations we found conformational changes for the transmembrane region of NpSRII/NpHtrII which resemble experimentally observed light-induced changes. Further downstream in the cytoplasmic domain of the transducer the signal propagates via distinct changes in the dynamics of HAMP1, HAMP2, the adaptation domain and the binding region for the kinase CheA, where conformational rearrangements were found to be subtle. Overall these observations suggest a signaling mechanism based on dynamic allostery resembling models previously proposed for E. coli chemoreceptors, indicating similar properties of signal transduction for archaeal photoreceptors and bacterial chemoreceptors.
Dynamic Self-Adaptive Reliability Control for Electric-Hydraulic Systems
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Yi Wan
2015-02-01
Full Text Available The high-speed electric-hydraulic proportional control is a new development of the hydraulic control technique with high reliability, low cost, efficient energy, and easy maintenance; it is widely used in industrial manufacturing and production. However, there are still some unresolved challenges, the most notable being the requirements of high stability and real-time by the classical control algorithm due to its high nonlinear characteristics. We propose a dynamic self-adaptive mixed control method based on the least squares support vector machine (LSSVM and the genetic algorithm for high-speed electric-hydraulic proportional control systems in this paper; LSSVM is used to identify and adjust online a nonlinear electric-hydraulic proportional system, and the genetic algorithm is used to optimize the control law of the controlled system and dynamic self-adaptive internal model control and predictive control are implemented by using the mixed intelligent method. The internal model and the inverse control model are online adjusted together. At the same time, a time-dependent Hankel matrix is constructed based on sample data; thus finite dimensional solution can be optimized on finite dimensional space. The results of simulation experiments show that the dynamic characteristics are greatly improved by the mixed intelligent control strategy, and good tracking and high stability are met in condition of high frequency response.
Vasseur, David A; Fox, Jeremy W
2011-10-01
Consumers acquire essential nutrients by ingesting the tissues of resource species. When these tissues contain essential nutrients in a suboptimal ratio, consumers may benefit from ingesting a mixture of nutritionally complementary resource species. We investigate the joint ecological and evolutionary consequences of competition for complementary resources, using an adaptive dynamics model of two consumers and two resources that differ in their relative content of two essential nutrients. In the absence of competition, a nutritionally balanced diet rarely maximizes fitness because of the dynamic feedbacks between uptake rate and resource density, whereas in sympatry, nutritionally balanced diets maximize fitness because competing consumers with different nutritional requirements tend to equalize the relative abundances of the two resources. Adaptation from allopatric to sympatric fitness optima can generate character convergence, divergence, and parallel shifts, depending not on the degree of diet overlap but on the match between resource nutrient content and consumer nutrient requirements. Contrary to previous verbal arguments that suggest that character convergence leads to neutral stability, coadaptation of competing consumers always leads to stable coexistence. Furthermore, we show that incorporating costs of consuming or excreting excess nonlimiting nutrients selects for nutritionally balanced diets and so promotes character convergence. This article demonstrates that resource-use overlap has little bearing on coexistence when resources are nutritionally complementary, and it highlights the importance of using mathematical models to infer the stability of ecoevolutionary dynamics.
An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks.
Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Zhang, Xuekun
2015-12-03
Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT), Machine-to-Machine (M2M) communications, Vehicular-to-Vehicular (V2V) communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than 95 % of the theoretical optimal throughput and 0 . 97 of fairness index especially in dynamic and dense networks.
An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks
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Chunyang Lei
2015-12-01
Full Text Available Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT, Machine-to-Machine (M2M communications, Vehicular-to-Vehicular (V2V communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than 95 % of the theoretical optimal throughput and 0 . 97 of fairness index especially in dynamic and dense networks.
DEFF Research Database (Denmark)
Hu, Rui; Hu, Weihao; Li, Pengfei
2016-01-01
and relatively low cost. Thus, many countries are increasing the wind power penetration in their power system step by step, such as Denmark, Spain and Germany. The incremental wind power penetration brings a lot of new issues in operation and programming. The power system sometimes will operate close to its...... stable limits. Once the blackout happens, a well-designed restoration strategy is significant. This paper focuses on how to ameliorate the power system restoration procedures to adapt the high wind power penetration and how to take full advantages of the wind power plants during the restoration....... In this paper, the possibility to exploit the stochastic wind power during restoration was discussed, and a Dynamic Programming (DP) method was proposed to make wind power contribute in the restoration rationally as far as possible. In this paper, the method is tested and verified by a modified IEEE 30 Buses...
Universal dynamics of complex adaptive systems: Gauge theory of things alive
International Nuclear Information System (INIS)
Mack, G.
1994-04-01
A universal dynamics of objects and their relations - a kind of ''universal chemistry'' - is discussed which satisfies general principles of locality and relativity. Einsteins theory of gravitation and the gauge theory of elementary particles are prototypes, but complex adaptive systems - anything that is alive in the widest sense - fall under the same paradigma. Frustration and gauge symmetry arise naturally in this context. Besides a nondissipative deterministic dynamics, which is thought to operate at a fundamental levle, a Thermo-Dynamics in sense of Prigogine is introduced by adding a diffusion process. It introduces irreversibility and entropy production. It equilibrates the chaotic local model of the time development (only) and is designed to be undetectable under continued observation with given finite measuring accuracy. Compositeness and the development of structure can be described in this framework. The existence of a critical equilibrium state may be postulated which is invariant under the dynamics. But it is usually not reached in a finite time from a given starting configuration, because local dynamics suffers from critical slowing down, especially in the presence of frustration. (orig.)
Use of a dynamic grid adaptation in the asymmetric weighted residual method
International Nuclear Information System (INIS)
Graf, V.; Romstedt, P.; Werner, W.
1986-01-01
A dynamic grid adaptive method has been developed for use with the asymmetric weighted residual method. The method automatically adapts the number and position of the spatial mesh points as the solution of hyperbolic or parabolic vector partial differential equations progresses in time. The mesh selection algorithm is based on the minimization of the L 2 norm of the spatial discretization error. The method permits the accurate calculation of the evolution of inhomogeneities, like wave fronts, shock layers, and other sharp transitions, while generally using a coarse computational grid. The number of required mesh points is significantly reduced, relative to a fixed Eulerian grid. Since the mesh selection algorithm is computationally inexpensive, a corresponding reduction of computing time results
International Nuclear Information System (INIS)
Ma Huanfei; Lin Wei
2009-01-01
The existing adaptive synchronization technique based on the stability theory and invariance principle of dynamical systems, though theoretically proved to be valid for parameters identification in specific models, is always showing slow convergence rate and even failed in practice when the number of parameters becomes large. Here, for parameters update, a novel nonlinear adaptive rule is proposed to accelerate the rate. Its feasibility is validated by analytical arguments as well as by specific parameters identification in the Lotka-Volterra model with multiple species. Two adjustable factors in this rule influence the identification accuracy, which means that a proper choice of these factors leads to an optimal performance of this rule. In addition, a feasible method for avoiding the occurrence of the approximate linear dependence among terms with parameters on the synchronized manifold is also proposed.
A dynamic programming approach to missing data estimation using neural networks
CSIR Research Space (South Africa)
Nelwamondo, FV
2013-01-01
Full Text Available method where dynamic programming is not used. This paper also suggests a different way of formulating a missing data problem such that the dynamic programming is applicable to estimate the missing data....
Programming Unconventional Computers: Dynamics, Development, Self-Reference
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Susan Stepney
2012-10-01
Full Text Available Classical computing has well-established formalisms for specifying, refining, composing, proving, and otherwise reasoning about computations. These formalisms have matured over the past 70 years or so. Unconventional Computing includes the use of novel kinds of substrates–from black holes and quantum effects, through to chemicals, biomolecules, even slime moulds–to perform computations that do not conform to the classical model. Although many of these unconventional substrates can be coerced into performing classical computation, this is not how they “naturally” compute. Our ability to exploit unconventional computing is partly hampered by a lack of corresponding programming formalisms: we need models for building, composing, and reasoning about programs that execute in these substrates. What might, say, a slime mould programming language look like? Here I outline some of the issues and properties of these unconventional substrates that need to be addressed to find “natural” approaches to programming them. Important concepts include embodied real values, processes and dynamical systems, generative systems and their meta-dynamics, and embodied self-reference.
Aperiodic dynamics in a deterministic adaptive network model of attitude formation in social groups
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
An Experimental Trial of Adaptive Programming in Drug Court: Outcomes at 6, 12 and 18 Months.
Marlowe, Douglas B; Festinger, David S; Dugosh, Karen L; Benasutti, Kathleen M; Fox, Gloria; Harron, Ashley
2014-06-01
Test whether an adaptive program improves outcomes in drug court by adjusting the schedule of court hearings and clinical case-management sessions pursuant to a priori performance criteria. Consenting participants in a misdemeanor drug court were randomly assigned to the adaptive program (n = 62) or to a baseline-matching condition (n = 63) in which they attended court hearings based on the results of a criminal risk assessment. Outcome measures were re-arrest rates at 18 months post-entry to the drug court and urine drug test results and structured interview results at 6 and 12 months post-entry. Although previously published analyses revealed significantly fewer positive drug tests for participants in the adaptive condition during the first 18 weeks of drug court, current analyses indicate the effects converged during the ensuing year. Between-group differences in new arrest rates, urine drug test results and self-reported psychosocial problems were small and non-statistically significant at 6, 12 and 18 months post-entry. A non-significant trend (p = .10) suggests there may have been a small residual impact (Cramer's ν = .15) on new misdemeanor arrests after 18 months. Adaptive programming shows promise for enhancing short-term outcomes in drug courts; however, additional efforts are needed to extend the effects beyond the first 4 to 6 months of enrollment.
Adapted recreational and sports programs for children with disabilities: A decade of experience.
Moberg-Wolff, Elizabeth; Kiesling, Sarah
2008-01-01
To identify and describe community based adapted sports and recreational programs (SARPs) for children with physically disabilities, documenting program types, benefits, challenges, growth and/or decline, and lessons they have learned over a 10-year period. In 1996, a total of 277 children's hospitals and freestanding rehabilitation hospitals stating that they provided pediatric rehabilitation services were contacted and asked to provide information regarding adapted recreational and sports programs in their region. Seventy-nine SARPs were identified, contacted, and survyed about programming, benefits and challenges they faced. They were then re-surveyed in 2006 for comparison data. Ten years ago, the average SARP served 25 or fewer clients and was led by a therapeutic recreation specialist with assistance from volunteers. Most programs had been in place for 5 years or more, met weekly for 2-3 hours, and were recreational in orientation. Activities varied, with basketball, aquatics, horseback riding and snow skiing being most common. Fund-raisers and grants supported most programs, and securing funding was their greatest challenge. Participant benefits noted by programs included improved socialization, enhanced physical fitness, increased self esteem, improved therapeutic skills (ADL's, transfers, etc.), enhanced cognition, expanded client independence, improved community relations, and enhanced leisure skills. Ten years later, the majority of SARPs noted similar benefits, and reported an increase in number of participants despite continued challenges with funding and staffing. Leadership and mentorship by those with disabilities was still very low, but community awareness of the abilities of those with disabilities had increased. Adapted sports and recreation programs surveyed in 1996 and again in 2006, report overall that their health is good, and many have retained the same programming, financial support mechanisms, leadership and participant mix over the years
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.
2012-03-30
... DEPARTMENT OF TRANSPORTATION Dynamic Mobility Applications and Data Capture Management Programs... stakeholders an update on the Data Capture and Management (DCM) and Dynamic Mobility Applications (DMA... critical issues designed to garner stakeholder feedback. About the Dynamic Mobility Application and Data...
Directory of Open Access Journals (Sweden)
David Gresham
2008-12-01
Full Text Available The experimental evolution of laboratory populations of microbes provides an opportunity to observe the evolutionary dynamics of adaptation in real time. Until very recently, however, such studies have been limited by our inability to systematically find mutations in evolved organisms. We overcome this limitation by using a variety of DNA microarray-based techniques to characterize genetic changes -- including point mutations, structural changes, and insertion variation -- that resulted from the experimental adaptation of 24 haploid and diploid cultures of Saccharomyces cerevisiae to growth in either glucose, sulfate, or phosphate-limited chemostats for approximately 200 generations. We identified frequent genomic amplifications and rearrangements as well as novel retrotransposition events associated with adaptation. Global nucleotide variation detection in ten clonal isolates identified 32 point mutations. On the basis of mutation frequencies, we infer that these mutations and the subsequent dynamics of adaptation are determined by the batch phase of growth prior to initiation of the continuous phase in the chemostat. We relate these genotypic changes to phenotypic outcomes, namely global patterns of gene expression, and to increases in fitness by 5-50%. We found that the spectrum of available mutations in glucose- or phosphate-limited environments combined with the batch phase population dynamics early in our experiments allowed several distinct genotypic and phenotypic evolutionary pathways in response to these nutrient limitations. By contrast, sulfate-limited populations were much more constrained in both genotypic and phenotypic outcomes. Thus, the reproducibility of evolution varies with specific selective pressures, reflecting the constraints inherent in the system-level organization of metabolic processes in the cell. We were able to relate some of the observed adaptive mutations (e.g., transporter gene amplifications to known features
International Nuclear Information System (INIS)
Zajnullin, V.G.; Yushkova, E.A.
2008-01-01
In genetically non-uniform populations D. melanogaster in conditions of a chronic irradiation in a doze 10-11 about sGy/generation dynamics parameters of populations was investigated. It is established, that number of individuals in irradiated populations is lower, than in control. It is revealed, that viability of populations undergone to a chronic irradiation depends on their genotype. The gradual increase in fruitfulness, viability of individuals and decrease in a level of lethal mutations in a number of generations after of an irradiation in low doses is caused by adaptable opportunities of populations. (authors)
Kasatkin, D. V.; Yanchuk, S.; Schöll, E.; Nekorkin, V. I.
2017-12-01
We report the phenomenon of self-organized emergence of hierarchical multilayered structures and chimera states in dynamical networks with adaptive couplings. This process is characterized by a sequential formation of subnetworks (layers) of densely coupled elements, the size of which is ordered in a hierarchical way, and which are weakly coupled between each other. We show that the hierarchical structure causes the decoupling of the subnetworks. Each layer can exhibit either a two-cluster state, a periodic traveling wave, or an incoherent state, and these states can coexist on different scales of subnetwork sizes.
The neural dynamics of conflict adaptation within a look-to-do transition.
Directory of Open Access Journals (Sweden)
Dandan Tang
Full Text Available BACKGROUND: For optimal performance in conflict situations, conflict adaptation (conflict detection and adjustment is necessary. However, the neural dynamics of conflict adaptation is still unclear. METHODS: In the present study, behavioral and electroencephalography (EEG data were recorded from seventeen healthy participants during performance of a color-word Stroop task with a novel look-to-do transition. Within this transition, participants looked at the Stroop stimuli but no responses were required in the 'look' trials; or made manual responses to the Stroop stimuli in the 'do' trials. RESULTS: In the 'look' trials, the amplitude modulation of N450 occurred exclusively in the right-frontal region. Subsequently, the amplitude modulation of sustained potential (SP emerged in the posterior parietal and right-frontal regions. A significantly positive correlation between the modulation of reconfiguration in the 'look' trials and the behavioral conflict adaptation in the 'do' trials was observed. Specially, a stronger information flow from right-frontal region to posterior parietal region in the beta band was observed for incongruent condition than for congruent condition. In the 'do' trials, the conflict of 'look' trials enhanced the amplitude modulations of N450 in the right-frontal and posterior parietal regions, but decreased the amplitude modulations of SP in these regions. Uniquely, a stronger information flow from centro-parietal region to right-frontal region in the theta band was observed for iI condition than for cI condition. CONCLUSION: All these findings showed that top-down conflict adaptation is implemented by: (1 enhancing the sensitivity to conflict detection and the adaptation to conflict resolution; (2 modulating the effective connectivity between parietal region and right-frontal region.
Sandovici, Ionel; Hoelle, Katharina; Angiolini, Emily; Constância, Miguel
2012-07-01
The placenta is a transient organ found in eutherian mammals that evolved primarily to provide nutrients for the developing fetus. The placenta exchanges a wide array of nutrients, endocrine signals, cytokines and growth factors with the mother and the fetus, thereby regulating intrauterine development. Recent studies show that the placenta is not just a passive organ mediating maternal-fetal exchange. It can adapt its capacity to supply nutrients in response to intrinsic and extrinsic variations in the maternal-fetal environment. These dynamic adaptations are thought to occur to maximize fetal growth and viability at birth in the prevailing conditions in utero. However, some of these adaptations may also affect the development of individual fetal tissues, with patho-physiological consequences long after birth. Here, this review summarizes current knowledge on the causes, possible mechanisms and consequences of placental adaptive responses, with a focus on the regulation of transporter-mediated processes for nutrients. This review also highlights the emerging roles that imprinted genes and epigenetic mechanisms of gene regulation may play in placental adaptations to the maternal-fetal environment. Copyright © 2012 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.
Run-Time and Compiler Support for Programming in Adaptive Parallel Environments
Directory of Open Access Journals (Sweden)
Guy Edjlali
1997-01-01
Full Text Available For better utilization of computing resources, it is important to consider parallel programming environments in which the number of available processors varies at run-time. In this article, we discuss run-time support for data-parallel programming in such an adaptive environment. Executing programs in an adaptive environment requires redistributing data when the number of processors changes, and also requires determining new loop bounds and communication patterns for the new set of processors. We have developed a run-time library to provide this support. We discuss how the run-time library can be used by compilers of high-performance Fortran (HPF-like languages to generate code for an adaptive environment. We present performance results for a Navier-Stokes solver and a multigrid template run on a network of workstations and an IBM SP-2. Our experiments show that if the number of processors is not varied frequently, the cost of data redistribution is not significant compared to the time required for the actual computation. Overall, our work establishes the feasibility of compiling HPF for a network of nondedicated workstations, which are likely to be an important resource for parallel programming in the future.
Experimental evolution and the dynamics of adaptation and genome evolution in microbial populations.
Lenski, Richard E
2017-10-01
Evolution is an on-going process, and it can be studied experimentally in organisms with rapid generations. My team has maintained 12 populations of Escherichia coli in a simple laboratory environment for >25 years and 60 000 generations. We have quantified the dynamics of adaptation by natural selection, seen some of the populations diverge into stably coexisting ecotypes, described changes in the bacteria's mutation rate, observed the new ability to exploit a previously untapped carbon source, characterized the dynamics of genome evolution and used parallel evolution to identify the genetic targets of selection. I discuss what the future might hold for this particular experiment, briefly highlight some other microbial evolution experiments and suggest how the fields of experimental evolution and microbial ecology might intersect going forward.
A New Fuzzy Harmony Search Algorithm Using Fuzzy Logic for Dynamic Parameter Adaptation
Directory of Open Access Journals (Sweden)
Cinthia Peraza
2016-10-01
Full Text Available In this paper, a new fuzzy harmony search algorithm (FHS for solving optimization problems is presented. FHS is based on a recent method using fuzzy logic for dynamic adaptation of the harmony memory accepting (HMR and pitch adjustment (PArate parameters that improve the convergence rate of traditional harmony search algorithm (HS. The objective of the method is to dynamically adjust the parameters in the range from 0.7 to 1. The impact of using fixed parameters in the harmony search algorithm is discussed and a strategy for efficiently tuning these parameters using fuzzy logic is presented. The FHS algorithm was successfully applied to different benchmarking optimization problems. The results of simulation and comparison studies demonstrate the effectiveness and efficiency of the proposed approach.
Hajipour, Ahmad; Tavakoli, Hamidreza
2017-12-01
In this study, the dynamic behavior and chaos control of a chaotic fractional incommensurate-order financial system are investigated. Using well-known tools of nonlinear theory, i.e. Lyapunov exponents, phase diagrams and bifurcation diagrams, we observe some interesting phenomena, e.g. antimonotonicity, crisis phenomena and route to chaos through a period doubling sequence. Adopting largest Lyapunov exponent criteria, we find that the system yields chaos at the lowest order of 2.15. Next, in order to globally stabilize the chaotic fractional incommensurate order financial system with uncertain dynamics, an adaptive fractional sliding mode controller is designed. Numerical simulations are used to demonstrate the effectiveness of the proposed control method.
Peng, Zhouhua; Wang, Dan; Zhang, Hongwei; Sun, Gang
2014-08-01
This paper addresses the leader-follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive synchronization controllers are proposed based on the state information of neighboring agents. The control design is developed for both undirected and directed communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case where a neighborhood observer is proposed based on relative output information of neighboring agents. Then, distributed observer-based synchronization controllers are derived and a parameter-dependent Riccati inequality is employed to prove the stability. This design has a favorable decouple property between the observer and the controller designs for nonlinear multiagent systems. For both cases, the developed controllers guarantee that the state of each agent synchronizes to that of the leader with bounded residual errors. Two illustrative examples validate the efficacy of the proposed methods.
Adaptive Pulsed Laser Line Extraction for Terrain Reconstruction using a Dynamic Vision Sensor
Directory of Open Access Journals (Sweden)
Christian eBrandli
2014-01-01
Full Text Available Mobile robots need to know the terrain in which they are moving for path planning and obstacle avoidance. This paper proposes the combination of a bio-inspired, redundancy-suppressing dynamic vision sensor with a pulsed line laser to allow fast terrain reconstruction. A stable laser stripe extraction is achieved by exploiting the sensor’s ability to capture the temporal dynamics in a scene. An adaptive temporal filter for the sensor output allows a reliable reconstruction of 3D terrain surfaces. Laser stripe extractions up to pulsing frequencies of 500Hz were achieved using a line laser of 3mW at a distance of 45cm using an event-based algorithm that exploits the sparseness of the sensor output. As a proof of concept, unstructured rapid prototype terrain samples have been successfully reconstructed with an accuracy of 2mm.
Development and demonstration program for dynamic nuclear materials control
International Nuclear Information System (INIS)
Augustson, R.H.; Baron, N.; Ford, R.F.; Ford, W.; Hagen, J.; Li, T.K.; Marshall, R.S.; Reams, V.S.; Severe, W.R.; Shirk, D.G.
1978-01-01
A significant portion of the Los Alamos Scientific Laboratory Safeguards Program is directed toward the development and demonstration of dynamic nuclear materials control. The building chosen for the demonstration system is the new Plutonium Processing Facility in Los Alamos, which houses such operations as metal-to-oxide conversion, fuel pellet fabrication, and scrap recovery. A DYnamic MAterials Control (DYMAC) system is currently being installed in the facility as an integral part of the processing operation. DYMAC is structured around interlocking unit-process accounting areas. It relies heavily on nondestructive assay measurements made in the process line to draw dynamic material balances in near real time. In conjunction with the nondestructive assay instrumentation, process operators use interactive terminals to transmit additional accounting and process information to a dedicated computer. The computer verifies and organizes the incoming data, immediately updates the inventory records, monitors material in transit using elapsed time, and alerts the Nuclear Materials Officer in the event that material balances exceed the predetermined action limits. DYMAC is part of the United States safeguards system under control of the facility operator. Because of its advanced features, the system will present a new set of inspection conditions to the IAEA, whose response is the subject of a study being sponsored by the US-IAEA Technical Assistance Program. The central issue is how the IAEA can use the increased capabilities of such a system and still maintain independent verification
Directory of Open Access Journals (Sweden)
Min Wang
2017-01-01
Full Text Available A dynamic learning method is developed for an uncertain n-link robot with unknown system dynamics, achieving predefined performance attributes on the link angular position and velocity tracking errors. For a known nonsingular initial robotic condition, performance functions and unconstrained transformation errors are employed to prevent the violation of the full-state tracking error constraints. By combining two independent Lyapunov functions and radial basis function (RBF neural network (NN approximator, a novel and simple adaptive neural control scheme is proposed for the dynamics of the unconstrained transformation errors, which guarantees uniformly ultimate boundedness of all the signals in the closed-loop system. In the steady-state control process, RBF NNs are verified to satisfy the partial persistent excitation (PE condition. Subsequently, an appropriate state transformation is adopted to achieve the accurate convergence of neural weight estimates. The corresponding experienced knowledge on unknown robotic dynamics is stored in NNs with constant neural weight values. Using the stored knowledge, a static neural learning controller is developed to improve the full-state tracking performance. A comparative simulation study on a 2-link robot illustrates the effectiveness of the proposed scheme.
Musical structure analysis using similarity matrix and dynamic programming
Shiu, Yu; Jeong, Hong; Kuo, C.-C. Jay
2005-10-01
Automatic music segmentation and structure analysis from audio waveforms based on a three-level hierarchy is examined in this research, where the three-level hierarchy includes notes, measures and parts. The pitch class profile (PCP) feature is first extracted at the note level. Then, a similarity matrix is constructed at the measure level, where a dynamic time warping (DTW) technique is used to enhance the similarity computation by taking the temporal distortion of similar audio segments into account. By processing the similarity matrix, we can obtain a coarse-grain music segmentation result. Finally, dynamic programming is applied to the coarse-grain segments so that a song can be decomposed into several major parts such as intro, verse, chorus, bridge and outro. The performance of the proposed music structure analysis system is demonstrated for pop and rock music.
A Self-adaptive Dynamic Evaluation Model for Diabetes Mellitus, Based on Evolutionary Strategies
Directory of Open Access Journals (Sweden)
An-Jiang Lu
2016-03-01
Full Text Available In order to evaluate diabetes mellitus objectively and accurately, this paper builds a self-adaptive dynamic evaluation model for diabetes mellitus, based on evolutionary strategies. First of all, on the basis of a formalized description of the evolutionary process of diabetes syndromes, using a state transition function, it judges whether a disease is evolutionary, through an excitation parameter. It then, provides evidence for the rebuilding of the evaluation index system. After that, by abstracting and rebuilding the composition of evaluation indexes, it makes use of a heuristic algorithm to determine the composition of the evolved evaluation index set of diabetes mellitus, It then, calculates the weight of each index in the evolved evaluation index set of diabetes mellitus by building a dependency matrix and realizes the self-adaptive dynamic evaluation of diabetes mellitus under an evolutionary environment. Using this evaluation model, it is possible to, quantify all kinds of diagnoses and treatment experiences of diabetes and finally to adopt ideal diagnoses and treatment measures for different patients with diabetics.
Exploiting the Adaptation Dynamics to Predict the Distribution of Beneficial Fitness Effects.
Directory of Open Access Journals (Sweden)
Sona John
Full Text Available Adaptation of asexual populations is driven by beneficial mutations and therefore the dynamics of this process, besides other factors, depends on the distribution of beneficial fitness effects. It is known that on uncorrelated fitness landscapes, this distribution can only be of three types: truncated, exponential and power law. We performed extensive stochastic simulations to study the adaptation dynamics on rugged fitness landscapes, and identified two quantities that can be used to distinguish the underlying distribution of beneficial fitness effects. The first quantity studied here is the fitness difference between successive mutations that spread in the population, which is found to decrease in the case of truncated distributions, remains nearly a constant for exponentially decaying distributions and increases when the fitness distribution decays as a power law. The second quantity of interest, namely, the rate of change of fitness with time also shows quantitatively different behaviour for different beneficial fitness distributions. The patterns displayed by the two aforementioned quantities are found to hold good for both low and high mutation rates. We discuss how these patterns can be exploited to determine the distribution of beneficial fitness effects in microbial experiments.
Reactive power and voltage control strategy based on dynamic and adaptive segment for DG inverter
Zhai, Jianwei; Lin, Xiaoming; Zhang, Yongjun
2018-03-01
The inverter of distributed generation (DG) can support reactive power to help solve the problem of out-of-limit voltage in active distribution network (ADN). Therefore, a reactive voltage control strategy based on dynamic and adaptive segment for DG inverter is put forward to actively control voltage in this paper. The proposed strategy adjusts the segmented voltage threshold of Q(U) droop curve dynamically and adaptively according to the voltage of grid-connected point and the power direction of adjacent downstream line. And then the reactive power reference of DG inverter can be got through modified Q(U) control strategy. The reactive power of inverter is controlled to trace the reference value. The proposed control strategy can not only control the local voltage of grid-connected point but also help to maintain voltage within qualified range considering the terminal voltage of distribution feeder and the reactive support for adjacent downstream DG. The scheme using the proposed strategy is compared with the scheme without the reactive support of DG inverter and the scheme using the Q(U) control strategy with constant segmented voltage threshold. The simulation results suggest that the proposed method has a significant improvement on solving the problem of out-of-limit voltage, restraining voltage variation and improving voltage quality.
Dynamic modeling and adaptive vibration suppression of a high-speed macro-micro manipulator
Yang, Yi-ling; Wei, Yan-ding; Lou, Jun-qiang; Fu, Lei; Fang, Sheng; Chen, Te-huan
2018-05-01
This paper presents a dynamic modeling and microscopic vibration suppression for a flexible macro-micro manipulator dedicated to high-speed operation. The manipulator system mainly consists of a macro motion stage and a flexible micromanipulator bonded with one macro-fiber-composite actuator. Based on Hamilton's principle and the Bouc-Wen hysteresis equation, the nonlinear dynamic model is obtained. Then, a hybrid control scheme is proposed to simultaneously suppress the elastic vibration during and after the motor motion. In particular, the hybrid control strategy is composed of a trajectory planning approach and an adaptive variable structure control. Moreover, two optimization indices regarding the comprehensive torques and synthesized vibrations are designed, and the optimal trajectories are acquired using a genetic algorithm. Furthermore, a nonlinear fuzzy regulator is used to adjust the switching gain in the variable structure control. Thus, a fuzzy variable structure control with nonlinear adaptive control law is achieved. A series of experiments are performed to verify the effectiveness and feasibility of the established system model and hybrid control strategy. The excited vibration during the motor motion and the residual vibration after the motor motion are decreased. Meanwhile, the settling time is shortened. Both the manipulation stability and operation efficiency of the manipulator are improved by the proposed hybrid strategy.
Mata-Machuca, Juan L.; Aguilar-López, Ricardo
2018-01-01
This work deals with the adaptative synchronization of complex dynamical networks with fractional-order nodes and its application in secure communications employing chaotic parameter modulation. The complex network is composed of multiple fractional-order systems with mismatch parameters and the coupling functions are given to realize the network synchronization. We introduce a fractional algebraic synchronizability condition (FASC) and a fractional algebraic identifiability condition (FAIC) which are used to know if the synchronization and parameters estimation problems can be solved. To overcome these problems, an adaptative synchronization methodology is designed; the strategy consists in proposing multiple receiver systems which tend to follow asymptotically the uncertain transmitters systems. The coupling functions and parameters of the receiver systems are adjusted continually according to a convenient sigmoid-like adaptative controller (SLAC), until the measurable output errors converge to zero, hence, synchronization between transmitter and receivers is achieved and message signals are recovered. Indeed, the stability analysis of the synchronization error is based on the fractional Lyapunov direct method. Finally, numerical results corroborate the satisfactory performance of the proposed scheme by means of the synchronization of a complex network consisting of several fractional-order unified chaotic systems.
High Dynamic Range adaptive ΔΣ-based Focal Plane Array architecture
Yao, Shun
2012-10-16
In this paper, an Adaptive Delta-Sigma based architecture for High Dynamic Range (HDR) Focal Plane Arrays is presented. The noise shaping effect of the Delta-Sigma modulation in the low end, and the distortion noise induced in the high end of Photo-diode current were analyzed in detail. The proposed architecture can extend the DR for about 20N log2 dB at the high end of Photo-diode current with an N bit Up-Down counter. At the low end, it can compensate for the larger readout noise by employing Extended Counting. The Adaptive Delta-Sigma architecture employing a 4-bit Up-Down counter achieved about 160dB in the DR, with a Peak SNR (PSNR) of 80dB at the high end. Compared to the other HDR architectures, the Adaptive Delta-Sigma based architecture provides the widest DR with the best SNR performance in the extended range.
Lin, Hui; Gao, Jian; Mei, Qing; He, Yunbo; Liu, Junxiu; Wang, Xingjin
2016-04-04
It is a challenge for any optical method to measure objects with a large range of reflectivity variation across the surface. Image saturation results in incorrect intensities in captured fringe pattern images, leading to phase and measurement errors. This paper presents a new adaptive digital fringe projection technique which avoids image saturation and has a high signal to noise ratio (SNR) in the three-dimensional (3-D) shape measurement of objects that has a large range of reflectivity variation across the surface. Compared to previous high dynamic range 3-D scan methods using many exposures and fringe pattern projections, which consumes a lot of time, the proposed technique uses only two preliminary steps of fringe pattern projection and image capture to generate the adapted fringe patterns, by adaptively adjusting the pixel-wise intensity of the projected fringe patterns based on the saturated pixels in the captured images of the surface being measured. For the bright regions due to high surface reflectivity and high illumination by the ambient light and surfaces interreflections, the projected intensity is reduced just to be low enough to avoid image saturation. Simultaneously, the maximum intensity of 255 is used for those dark regions with low surface reflectivity to maintain high SNR. Our experiments demonstrate that the proposed technique can achieve higher 3-D measurement accuracy across a surface with a large range of reflectivity variation.
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.
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
Moving finite elements: A continuously adaptive method for computational fluid dynamics
International Nuclear Information System (INIS)
Glasser, A.H.; Miller, K.; Carlson, N.
1991-01-01
Moving Finite Elements (MFE), a recently developed method for computational fluid dynamics, promises major advances in the ability of computers to model the complex behavior of liquids, gases, and plasmas. Applications of computational fluid dynamics occur in a wide range of scientifically and technologically important fields. Examples include meteorology, oceanography, global climate modeling, magnetic and inertial fusion energy research, semiconductor fabrication, biophysics, automobile and aircraft design, industrial fluid processing, chemical engineering, and combustion research. The improvements made possible by the new method could thus have substantial economic impact. Moving Finite Elements is a moving node adaptive grid method which has a tendency to pack the grid finely in regions where it is most needed at each time and to leave it coarse elsewhere. It does so in a manner which is simple and automatic, and does not require a large amount of human ingenuity to apply it to each particular problem. At the same time, it often allows the time step to be large enough to advance a moving shock by many shock thicknesses in a single time step, moving the grid smoothly with the solution and minimizing the number of time steps required for the whole problem. For 2D problems (two spatial variables) the grid is composed of irregularly shaped and irregularly connected triangles which are very flexible in their ability to adapt to the evolving solution. While other adaptive grid methods have been developed which share some of these desirable properties, this is the only method which combines them all. In many cases, the method can save orders of magnitude of computing time, equivalent to several generations of advancing computer hardware
Developmental cascade effects of the New Beginnings Program on adolescent adaptation outcomes.
McClain, Darya Bonds; Wolchik, Sharlene A; Winslow, Emily; Tein, Jenn-Yun; Sandler, Irwin N; Millsap, Roger E
2010-11-01
Using data from a 6-year longitudinal follow-up sample of 240 youth who participated in a randomized experimental trial of a preventive intervention for divorced families with children ages 9-12, the current study tested alternative cascading pathways by which the intervention decreased symptoms of internalizing disorders, symptoms of externalizing disorders, substance use, and risky sexual behavior and increased self-esteem and academic performance in mid- to late adolescence (15-19 years old). It was hypothesized that the impact of the program on adolescent adaptation outcomes would be explained by progressive associations between program-induced changes in parenting and youth adaptation outcomes. The results supported a cascading model of program effects in which the program was related to increased mother-child relationship quality that was related to subsequent decreases in child internalizing problems, which then was related to subsequent increases in self-esteem and decreases in symptoms of internalizing disorders in adolescence. The results were also consistent with a model in which the program increased maternal effective discipline that was related to decreased child externalizing problems, which was related to subsequent decreases in symptoms of externalizing disorders, less substance use, and better academic performance in adolescence. There were no significant differences in the model based on level of baseline risk or adolescent gender. These results provide support for a cascading pathways model of child and adolescent development.
Obtainment of nuclear power plant dynamic parameters by adaptive mesh technique
International Nuclear Information System (INIS)
Carvalho Miranda, W. de.
1979-01-01
This thesis involves the problem in determination of the parameters of the Mathematical Model of a Nuclear Reactor, including non-linearity which is considered as a bi-linear system. Being a non-linear model, the determination of its parameters cannot be made with the classical techniques as in obtaining its experimental frequency response. In the present work, we examine the possibility of using a model with parameters that adapt according to a algorithm of Newton type minimization, showing that in the case of the single parameter determination, the method is successful. This work was done, using the CSMP (Continuous System Modelling Program) of IBM 1130 of IME. (author)
DEGAS: Dynamic Exascale Global Address Space Programming Environments
Energy Technology Data Exchange (ETDEWEB)
Demmel, James [Univ. of California, Berkeley, CA (United States)
2018-02-23
The Dynamic, Exascale Global Address Space programming environment (DEGAS) project will develop the next generation of programming models and runtime systems to meet the challenges of Exascale computing. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speed and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speed and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics.
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.
Flexible and adaptive water systems operations through more informed and dynamic decisions
Castelletti, A.; Giuliani, M.
2016-12-01
Timely adapting the operations of water systems to be resilient against rapid changes in both hydroclimatic and socioeconomic forcing is generally recommended as a part of planning and managing water resources under uncertain futures. A great opportunity to make the operations more flexible and adaptive is offered by the unprecedented amount of information that is becoming available to water system operators, providing a wide range of data at increasingly higher temporal and spatial resolution. Yet, many water systems are still operated using very simple information systems, typically based on basic statistical analysis and the operator's experience. In this work, we discuss the potential offered by incorporating improved information to enhance water systems operation and increase their ability of adapting to different external conditions and resolving potential conflicts across sectors. In particular, we focus on the use of different variables associated to different dynamics of the system (slow and fast) diversely impacting the operating objectives on the short-, medium- and long-term. The multi-purpose operations of the Hoa Binh reservoir in the Red River Basin (Vietnam) is used to demonstrate our approach. Numerical results show that our procedure is able to automatically select the most valuable information for improving the Hoa Binh operations and mitigating the conflict between short-term objectives, i.e. hydropower production and flood control. Moreover, we also successfully identify low-frequency climate information associated to El-Nino Southern Oscillation for improving the performance in terms of long-term objectives, i.e. water supply. Finally, we assess the value of better informing operational decisions for adapting the system operations to changing conditions by considering different climate change projections.
The puzzle of partial migration: Adaptive dynamics and evolutionary game theory perspectives.
De Leenheer, Patrick; Mohapatra, Anushaya; Ohms, Haley A; Lytle, David A; Cushing, J M
2017-01-07
We consider the phenomenon of partial migration which is exhibited by populations in which some individuals migrate between habitats during their lifetime, but others do not. First, using an adaptive dynamics approach, we show that partial migration can be explained on the basis of negative density dependence in the per capita fertilities alone, provided that this density dependence is attenuated for increasing abundances of the subtypes that make up the population. We present an exact formula for the optimal proportion of migrants which is expressed in terms of the vital rates of migrant and non-migrant subtypes only. We show that this allocation strategy is both an evolutionary stable strategy (ESS) as well as a convergence stable strategy (CSS). To establish the former, we generalize the classical notion of an ESS because it is based on invasion exponents obtained from linearization arguments, which fail to capture the stabilizing effects of the nonlinear density dependence. These results clarify precisely when the notion of a "weak ESS", as proposed in Lundberg (2013) for a related model, is a genuine ESS. Secondly, we use an evolutionary game theory approach, and confirm, once again, that partial migration can be attributed to negative density dependence alone. In this context, the result holds even when density dependence is not attenuated. In this case, the optimal allocation strategy towards migrants is the same as the ESS stemming from the analysis based on the adaptive dynamics. The key feature of the population models considered here is that they are monotone dynamical systems, which enables a rather comprehensive mathematical analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.
Development of nonlinear dynamic analysis program for nuclear piping systems
International Nuclear Information System (INIS)
Kamichika, Ryoichi; Izawa, Masahiro; Yamadera, Masao
1980-01-01
In the design for nuclear power piping, pipe-whip protection shall be considered in order to keep the function of safety related system even when postulated piping rupture occurs. This guideline was shown in U.S. Regulatory Guide 1.46 for the first time and has been applied in Japanese nuclear power plants. In order to analyze the dynamic behavior followed by pipe rupture, nonlinear analysis is required for the piping system including restraints which play the role of an energy absorber. REAPPS (Rupture Effective Analysis of Piping Systems) has been developed for this purpose. This program can be applied to general piping systems having branches etc. Pre- and post- processors are prepared in this program in order to easily input the data for the piping engineer and show the results optically by use of a graphic display respectively. The piping designer can easily solve many problems in his daily work by use of this program. This paper describes about the theoretical background and functions of this program and shows some examples. (author)
Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick
2018-01-01
When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. Copyright © 2017 The Authors. Cognitive Science published by Wiley
Evaluation of Electric Power Procurement Strategies by Stochastic Dynamic Programming
Saisho, Yuichi; Hayashi, Taketo; Fujii, Yasumasa; Yamaji, Kenji
In deregulated electricity markets, the role of a distribution company is to purchase electricity from the wholesale electricity market at randomly fluctuating prices and to provide it to its customers at a given fixed price. Therefore the company has to take risk stemming from the uncertainties of electricity prices and/or demand fluctuation instead of the customers. The way to avoid the risk is to make a bilateral contact with generating companies or install its own power generation facility. This entails the necessity to develop a certain method to make an optimal strategy for electric power procurement. In such a circumstance, this research has the purpose for proposing a mathematical method based on stochastic dynamic programming and additionally considering the characteristics of the start-up cost of electric power generation facility to evaluate strategies of combination of the bilateral contract and power auto-generation with its own facility for procuring electric power in deregulated electricity market. In the beginning we proposed two approaches to solve the stochastic dynamic programming, and they are a Monte Carlo simulation method and a finite difference method to derive the solution of a partial differential equation of the total procurement cost of electric power. Finally we discussed the influences of the price uncertainty on optimal strategies of power procurement.
International Nuclear Information System (INIS)
Wu, Xia; Wu, Genhua
2014-01-01
Highlights: • A high efficient method for optimization of atomic clusters is developed. • Its performance is studied by optimizing Lennard-Jones clusters and Ag clusters. • The method is proved to be quite efficient. • A new Ag 61 cluster with stacking-fault face-centered cubic motif is found. - Abstract: Geometrical optimization of atomic clusters is performed by a development of adaptive immune optimization algorithm (AIOA) with dynamic lattice searching (DLS) operation (AIOA-DLS method). By a cycle of construction and searching of the dynamic lattice (DL), DLS algorithm rapidly makes the clusters more regular and greatly reduces the potential energy. DLS can thus be used as an operation acting on the new individuals after mutation operation in AIOA to improve the performance of the AIOA. The AIOA-DLS method combines the merit of evolutionary algorithm and idea of dynamic lattice. The performance of the proposed method is investigated in the optimization of Lennard-Jones clusters within 250 atoms and silver clusters described by many-body Gupta potential within 150 atoms. Results reported in the literature are reproduced, and the motif of Ag 61 cluster is found to be stacking-fault face-centered cubic, whose energy is lower than that of previously obtained icosahedron
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Iyad Husni Alshami
2017-08-01
Full Text Available The Global Positioning System demonstrates the significance of Location Based Services but it cannot be used indoors due to the lack of line of sight between satellites and receivers. Indoor Positioning Systems are needed to provide indoor Location Based Services. Wireless LAN fingerprints are one of the best choices for Indoor Positioning Systems because of their low cost, and high accuracy, however they have many drawbacks: creating radio maps is time consuming, the radio maps will become outdated with any environmental change, different mobile devices read the received signal strength (RSS differently, and peoples’ presence in LOS between access points and mobile device affects the RSS. This research proposes a new Adaptive Indoor Positioning System model (called DIPS based on: a dynamic radio map generator, RSS certainty technique and peoples’ presence effect integration for dynamic and multi-floor environments. Dynamic in our context refers to the effects of people and device heterogeneity. DIPS can achieve 98% and 92% positioning accuracy for floor and room positioning, and it achieves 1.2 m for point positioning error. RSS certainty enhanced the positioning accuracy for floor and room for different mobile devices by 11% and 9%. Then by considering the peoples’ presence effect, the error is reduced by 0.2 m. In comparison with other works, DIPS achieves better positioning without extra devices.
Patriarca, M.; Kuronen, A.; Robles, M.; Kaski, K.
2007-01-01
The study of crystal defects and the complex processes underlying their formation and time evolution has motivated the development of the program ALINE for interactive molecular dynamics experiments. This program couples a molecular dynamics code to a Graphical User Interface and runs on a UNIX-X11 Window System platform with the MOTIF library, which is contained in many standard Linux releases. ALINE is written in C, thus giving the user the possibility to modify the source code, and, at the same time, provides an effective and user-friendly framework for numerical experiments, in which the main parameters can be interactively varied and the system visualized in various ways. We illustrate the main features of the program through some examples of detection and dynamical tracking of point-defects, linear defects, and planar defects, such as stacking faults in lattice-mismatched heterostructures. Program summaryTitle of program:ALINE Catalogue identifier:ADYJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYJ_v1_0 Program obtainable from: CPC Program Library, Queen University of Belfast, N. Ireland Computer for which the program is designed and others on which it has been tested: Computers:DEC ALPHA 300, Intel i386 compatible computers, G4 Apple Computers Installations:Laboratory of Computational Engineering, Helsinki University of Technology, Helsinki, Finland Operating systems under which the program has been tested:True64 UNIX, Linux-i386, Mac OS X 10.3 and 10.4 Programming language used:Standard C and MOTIF libraries Memory required to execute with typical data:6 Mbytes but may be larger depending on the system size No. of lines in distributed program, including test data, etc.:16 901 No. of bytes in distributed program, including test data, etc.:449 559 Distribution format:tar.gz Nature of physical problem:Some phenomena involving defects take place inside three-dimensional crystals at times which can be hardly predicted. For this reason they are
Masia, Lorenzo; Frascarelli, Flaminia; Morasso, Pietro; Di Rosa, Giuseppe; Petrarca, Maurizio; Castelli, Enrico; Cappa, Paolo
2011-05-21
It is known that healthy adults can quickly adapt to a novel dynamic environment, generated by a robotic manipulandum as a structured disturbing force field. We suggest that it may be of clinical interest to evaluate to which extent this kind of motor learning capability is impaired in children affected by cerebal palsy. We adapted the protocol already used with adults, which employs a velocity dependant viscous field, and compared the performance of a group of subjects affected by Cerebral Palsy (CP group, 7 subjects) with a Control group of unimpaired age-matched children. The protocol included a familiarization phase (FA), during which no force was applied, a force field adaptation phase (CF), and a wash-out phase (WO) in which the field was removed. During the CF phase the field was shut down in a number of randomly selected "catch" trials, which were used in order to evaluate the "learning index" for each single subject and the two groups. Lateral deviation, speed and acceleration peaks and average speed were evaluated for each trajectory; a directional analysis was performed in order to inspect the role of the limb's inertial anisotropy in the different experimental phases. During the FA phase the movements of the CP subjects were more curved, displaying greater and variable directional error; over the course of the CF phase both groups showed a decreasing trend in the lateral error and an after-effect at the beginning of the wash-out, but the CP group had a non significant adaptation rate and a lower learning index, suggesting that CP subjects have reduced ability to learn to compensate external force. Moreover, a directional analysis of trajectories confirms that the control group is able to better predict the force field by tuning the kinematic features of the movements along different directions in order to account for the inertial anisotropy of arm. Spatial abnormalities in children affected by cerebral palsy may be related not only to disturbance in
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Di Rosa Giuseppe
2011-05-01
Full Text Available Abstract Background It is known that healthy adults can quickly adapt to a novel dynamic environment, generated by a robotic manipulandum as a structured disturbing force field. We suggest that it may be of clinical interest to evaluate to which extent this kind of motor learning capability is impaired in children affected by cerebal palsy. Methods We adapted the protocol already used with adults, which employs a velocity dependant viscous field, and compared the performance of a group of subjects affected by Cerebral Palsy (CP group, 7 subjects with a Control group of unimpaired age-matched children. The protocol included a familiarization phase (FA, during which no force was applied, a force field adaptation phase (CF, and a wash-out phase (WO in which the field was removed. During the CF phase the field was shut down in a number of randomly selected "catch" trials, which were used in order to evaluate the "learning index" for each single subject and the two groups. Lateral deviation, speed and acceleration peaks and average speed were evaluated for each trajectory; a directional analysis was performed in order to inspect the role of the limb's inertial anisotropy in the different experimental phases. Results During the FA phase the movements of the CP subjects were more curved, displaying greater and variable directional error; over the course of the CF phase both groups showed a decreasing trend in the lateral error and an after-effect at the beginning of the wash-out, but the CP group had a non significant adaptation rate and a lower learning index, suggesting that CP subjects have reduced ability to learn to compensate external force. Moreover, a directional analysis of trajectories confirms that the control group is able to better predict the force field by tuning the kinematic features of the movements along different directions in order to account for the inertial anisotropy of arm. Conclusions Spatial abnormalities in children affected
Adapting Animal-Assisted Therapy Trials to Prison-Based Animal Programs.
Allison, Molly; Ramaswamy, Megha
2016-09-01
Prison-based animal programs have shown promise when it comes to increased sociability, responsibility, and levels of patience for inmates who participate in these programs. Yet there remains a dearth of scientific research that demonstrates the impact of prison-based animal programs on inmates' physical and mental health. Trials of animal-assisted therapy interventions, a form of human-animal interaction therapy most often used with populations affected by depression/anxiety, mental illness, and trauma, may provide models of how prison-based animal program research can have widespread implementation in jail and prison settings, whose populations have high rates of mental health problems. This paper reviews the components of prison-based animal programs most commonly practiced in prisons today, presents five animal-assisted therapy case studies, evaluates them based on their adaptability to prison-based animal programs, and discusses the institutional constraints that act as barriers for rigorous prison-based animal program research implementation. This paper can serve to inform the development of a research approach to animal-assisted therapy that nurses and other public health researchers can use in working with correctional populations. © 2016 Wiley Periodicals, Inc.
Shen, Lin; Yang, Weitao
2018-03-13
Direct molecular dynamics (MD) simulation with ab initio quantum mechanical and molecular mechanical (QM/MM) methods is very powerful for studying the mechanism of chemical reactions in a complex environment but also very time-consuming. The computational cost of QM/MM calculations during MD simulations can be reduced significantly using semiempirical QM/MM methods with lower accuracy. To achieve higher accuracy at the ab initio QM/MM level, a correction on the existing semiempirical QM/MM model is an attractive idea. Recently, we reported a neural network (NN) method as QM/MM-NN to predict the potential energy difference between semiempirical and ab initio QM/MM approaches. The high-level results can be obtained using neural network based on semiempirical QM/MM MD simulations, but the lack of direct MD samplings at the ab initio QM/MM level is still a deficiency that limits the applications of QM/MM-NN. In the present paper, we developed a dynamic scheme of QM/MM-NN for direct MD simulations on the NN-predicted potential energy surface to approximate ab initio QM/MM MD. Since some configurations excluded from the database for NN training were encountered during simulations, which may cause some difficulties on MD samplings, an adaptive procedure inspired by the selection scheme reported by Behler [ Behler Int. J. Quantum Chem. 2015 , 115 , 1032 ; Behler Angew. Chem., Int. Ed. 2017 , 56 , 12828 ] was employed with some adaptions to update NN and carry out MD iteratively. We further applied the adaptive QM/MM-NN MD method to the free energy calculation and transition path optimization on chemical reactions in water. The results at the ab initio QM/MM level can be well reproduced using this method after 2-4 iteration cycles. The saving in computational cost is about 2 orders of magnitude. It demonstrates that the QM/MM-NN with direct MD simulations has great potentials not only for the calculation of thermodynamic properties but also for the characterization of
Takiyama, Ken
2017-12-01
How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.
Fast and intuitive programming of adaptive laser cutting of lace enabled by machine vision
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.
An adaptive staircase procedure for the E-Prime programming environment.
Hairston, W David; Maldjian, Joseph A
2009-01-01
Many studies need to determine a subject's threshold for a given task. This can be achieved efficiently using an adaptive staircase procedure. While the logic and algorithms for staircases have been well established, the few pre-programmed routines currently available to researchers require at least moderate programming experience to integrate into new paradigms and experimental settings. Here, we describe a freely distributed routine developed for the E-Prime programming environment that can be easily integrated into any experimental protocol with only a basic understanding of E-Prime. An example experiment (visual temporal-order-judgment task) where subjects report the order of occurrence of two circles illustrates the behavior and consistency of the routine.
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. (c) 2007 APA, all rights reserved.
Dynamic electricity pricing for electric vehicles using stochastic programming
International Nuclear Information System (INIS)
Soares, João; Ghazvini, Mohammad Ali Fotouhi; Borges, Nuno; Vale, Zita
2017-01-01
Electric Vehicles (EVs) are an important source of uncertainty, due to their variable demand, departure time and location. In smart grids, the electricity demand can be controlled via Demand Response (DR) programs. Smart charging and vehicle-to-grid seem highly promising methods for EVs control. However, high capital costs remain a barrier to implementation. Meanwhile, incentive and price-based schemes that do not require high level of control can be implemented to influence the EVs' demand. Having effective tools to deal with the increasing level of uncertainty is increasingly important for players, such as energy aggregators. This paper formulates a stochastic model for day-ahead energy resource scheduling, integrated with the dynamic electricity pricing for EVs, to address the challenges brought by the demand and renewable sources uncertainty. The two-stage stochastic programming approach is used to obtain the optimal electricity pricing for EVs. A realistic case study projected for 2030 is presented based on Zaragoza network. The results demonstrate that it is more effective than the deterministic model and that the optimal pricing is preferable. This study indicates that adequate DR schemes like the proposed one are promising to increase the customers' satisfaction in addition to improve the profitability of the energy aggregation business. - Highlights: • A stochastic model for energy scheduling tackling several uncertainty sources. • A two-stage stochastic programming is used to tackle the developed model. • Optimal EV electricity pricing seems to improve the profits. • The propose results suggest to increase the customers' satisfaction.
Energy Technology Data Exchange (ETDEWEB)
Luo, Shaohua [School of Automation, Chongqing University, Chongqing 400044, China and College of Mechanical Engineering, Hunan University of Arts and Science, Hunan 415000 (China)
2014-09-01
This paper is concerned with the problem of adaptive fuzzy dynamic surface control (DSC) for the permanent magnet synchronous motor (PMSM) system with chaotic behavior, disturbance and unknown control gain and parameters. Nussbaum gain is adopted to cope with the situation that the control gain is unknown. And the unknown items can be estimated by fuzzy logic system. The proposed controller guarantees that all the signals in the closed-loop system are bounded and the system output eventually converges to a small neighborhood of the desired reference signal. Finally, the numerical simulations indicate that the proposed scheme can suppress the chaos of PMSM and show the effectiveness and robustness of the proposed method.
Adaptive polarization image fusion based on regional energy dynamic weighted average
Institute of Scientific and Technical Information of China (English)
ZHAO Yong-qiang; PAN Quan; ZHANG Hong-cai
2005-01-01
According to the principle of polarization imaging and the relation between Stokes parameters and the degree of linear polarization, there are much redundant and complementary information in polarized images. Since man-made objects and natural objects can be easily distinguished in images of degree of linear polarization and images of Stokes parameters contain rich detailed information of the scene, the clutters in the images can be removed efficiently while the detailed information can be maintained by combining these images. An algorithm of adaptive polarization image fusion based on regional energy dynamic weighted average is proposed in this paper to combine these images. Through an experiment and simulations,most clutters are removed by this algorithm. The fusion method is used for different light conditions in simulation, and the influence of lighting conditions on the fusion results is analyzed.
A self-adapting herding model: The agent judge-abilities influence the dynamic behaviors
Dong, Linrong
2008-10-01
We propose a self-adapting herding model, in which the financial markets consist of agent clusters with different sizes and market desires. The ratio of successful exchange and merger depends on the volatility of the market and the market desires of the agent clusters. The desires are assigned in term of the wealth of the agent clusters when they merge. After an exchange, the beneficial cluster’s desire keeps on the same, the losing one’s desire is altered which is correlative with the agent judge-ability. A parameter R is given to all agents to denote the judge-ability. The numerical calculation shows that the dynamic behaviors of the market are influenced distinctly by R, which includes the exponential magnitudes of the probability distribution of sizes of the agent clusters and the volatility autocorrelation of the returns, the intensity and frequency of the volatility.
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David Fouchet
Full Text Available BACKGROUND: Regulatory T cells are central actors in the maintenance of tolerance of self-antigens or allergens and in the regulation of the intensity of the immune response during infections by pathogens. An understanding of the network of the interaction between regulatory T cells, antigen presenting cells and effector T cells is starting to emerge. Dynamical systems analysis can help to understand the dynamical properties of an interaction network and can shed light on the different tasks that can be accomplished by a network. METHODOLOGY AND PRINCIPAL FINDINGS: We used a mathematical model to describe a interaction network of adaptive regulatory T cells, in which mature precursor T cells may differentiate into either adaptive regulatory T cells or effector T cells, depending on the activation state of the cell by which the antigen was presented. Using an equilibrium analysis of the mathematical model we show that, for some parameters, the network has two stable equilibrium states: one in which effector T cells are strongly regulated by regulatory T cells and another in which effector T cells are not regulated because the regulatory T cell population is vanishingly small. We then simulate different types of perturbations, such as the introduction of an antigen into a virgin system, and look at the state into which the system falls. We find that whether or not the interaction network switches from the regulated (tolerant state to the unregulated state depends on the strength of the antigenic stimulus and the state from which the network has been perturbed. CONCLUSION/SIGNIFICANCE: Our findings suggest that the interaction network studied in this paper plays an essential part in generating and maintaining tolerance against allergens and self-antigens.
Quantum Dynamics with Short-Time Trajectories and Minimal Adaptive Basis Sets.
Saller, Maximilian A C; Habershon, Scott
2017-07-11
Methods for solving the time-dependent Schrödinger equation via basis set expansion of the wave function can generally be categorized as having either static (time-independent) or dynamic (time-dependent) basis functions. We have recently introduced an alternative simulation approach which represents a middle road between these two extremes, employing dynamic (classical-like) trajectories to create a static basis set of Gaussian wavepackets in regions of phase-space relevant to future propagation of the wave function [J. Chem. Theory Comput., 11, 8 (2015)]. Here, we propose and test a modification of our methodology which aims to reduce the size of basis sets generated in our original scheme. In particular, we employ short-time classical trajectories to continuously generate new basis functions for short-time quantum propagation of the wave function; to avoid the continued growth of the basis set describing the time-dependent wave function, we employ Matching Pursuit to periodically minimize the number of basis functions required to accurately describe the wave function. Overall, this approach generates a basis set which is adapted to evolution of the wave function while also being as small as possible. In applications to challenging benchmark problems, namely a 4-dimensional model of photoexcited pyrazine and three different double-well tunnelling problems, we find that our new scheme enables accurate wave function propagation with basis sets which are around an order-of-magnitude smaller than our original trajectory-guided basis set methodology, highlighting the benefits of adaptive strategies for wave function propagation.
Dynamics of the exponential integrate-and-fire model with slow currents and adaptation.
Barranca, Victor J; Johnson, Daniel C; Moyher, Jennifer L; Sauppe, Joshua P; Shkarayev, Maxim S; Kovačič, Gregor; Cai, David
2014-08-01
In order to properly capture spike-frequency adaptation with a simplified point-neuron model, we study approximations of Hodgkin-Huxley (HH) models including slow currents by exponential integrate-and-fire (EIF) models that incorporate the same types of currents. We optimize the parameters of the EIF models under the external drive consisting of AMPA-type conductance pulses using the current-voltage curves and the van Rossum metric to best capture the subthreshold membrane potential, firing rate, and jump size of the slow current at the neuron's spike times. Our numerical simulations demonstrate that, in addition to these quantities, the approximate EIF-type models faithfully reproduce bifurcation properties of the HH neurons with slow currents, which include spike-frequency adaptation, phase-response curves, critical exponents at the transition between a finite and infinite number of spikes with increasing constant external drive, and bifurcation diagrams of interspike intervals in time-periodically forced models. Dynamics of networks of HH neurons with slow currents can also be approximated by corresponding EIF-type networks, with the approximation being at least statistically accurate over a broad range of Poisson rates of the external drive. For the form of external drive resembling realistic, AMPA-like synaptic conductance response to incoming action potentials, the EIF model affords great savings of computation time as compared with the corresponding HH-type model. Our work shows that the EIF model with additional slow currents is well suited for use in large-scale, point-neuron models in which spike-frequency adaptation is important.
The dynamics of socio-psychological adaptation of adolescents engaged in artistic creativity
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Chernaya Yu.S.
2017-07-01
Full Text Available this article presents a study of the dynamics of socio-psychological adaptation in adolescents during the course of pictorial arts. 60 teenagers aged 13 to 17 years have been participating in a longitudinal study for three years, systematically involved and not involved in pictorial art. It has been found that the creative adolescents have lower level of neuro-psychological adaptation and higher level of subjective feelings of loneliness than non-creative adolescents. But creative teenagers have significantly higher self-esteem, level of aspiration and satisfaction in achieving success and lower anxiety in relationships with adults. The influence of the creative group reflected on such personal qualities as: self-confidence, credibility among peers, ability to do things with their hands, social identity, loneliness, frustration needs in achieving success, problems and fears in relations with adults. The personal characteristics of creative adolescents have been identified. These characteristics distinguish them from others teenagers, and the effect of the creative group and creative activity indirectly on the personal qualities of adolescents.
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Matos Margarida
2009-06-01
Full Text Available Abstract Here we present a correction to our article "Evolutionary dynamics of molecular markers during local adaptation: a case study in Drosophila subobscura". We have recently detected an error concerning the application of the Ln RH formula – a test to detect positive selection – to our microsatellite data. Here we provide the corrected data and discuss its implications for our overall findings. The corrections presented here have produced some changes relative to our previous results, namely in a locus (dsub14 that presents indications of being affected by positive selection. In general, our populations present less consistent indications of positive selection for this particular locus in both periods studied – between generations 3 and 14 and between generation 14 and 40 of laboratory adaptation. Despite this, the main findings of our study regarding the possibility of positive selection acting on that particular microsatellite still hold. As previously concluded in our article, further studies should be performed on this specific microsatellite locus (and neighboring areas to elucidate in greater detail the evolutionary forces acting on this specific region of the O chromosome of Drosophila subobscura.
Manor, Brad; Costa, Madalena D; Hu, Kun; Newton, Elizabeth; Starobinets, Olga; Kang, Hyun Gu; Peng, C K; Novak, Vera; Lipsitz, Lewis A
2010-12-01
The degree of multiscale complexity in human behavioral regulation, such as that required for postural control, appears to decrease with advanced aging or disease. To help delineate causes and functional consequences of complexity loss, we examined the effects of visual and somatosensory impairment on the complexity of postural sway during quiet standing and its relationship to postural adaptation to cognitive dual tasking. Participants of the MOBILIZE Boston Study were classified into mutually exclusive groups: controls [intact vision and foot somatosensation, n = 299, 76 ± 5 (SD) yr old], visual impairment only (Postural sway (i.e., center-of-pressure) dynamics were assessed during quiet standing and cognitive dual tasking, and a complexity index was quantified using multiscale entropy analysis. Postural sway speed and area, which did not correlate with complexity, were also computed. During quiet standing, the complexity index (mean ± SD) was highest in controls (9.5 ± 1.2) and successively lower in the visual (9.1 ± 1.1), somatosensory (8.6 ± 1.6), and combined (7.8 ± 1.3) impairment groups (P = 0.001). Dual tasking resulted in increased sway speed and area but reduced complexity (P postural sway speed from quiet standing to dual-tasking conditions. Sensory impairments contributed to decreased postural sway complexity, which reflected reduced adaptive capacity of the postural control system. Relatively low baseline complexity may, therefore, indicate control systems that are more vulnerable to cognitive and other stressors.
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Thuc Phi Duong
2015-07-01
Full Text Available To enable the geometrical freedom envisioned for wireless power transfer (WPT, fast dynamic adaptation to unpredictable changes in receiver position is needed. In this paper, we propose an adaptive impedance-searching system that achieves good impedance matching quickly. For fast and robust operation, the proposed method consists of three steps: system calibration, coarse search, and fine search. The proposed WPT system is characterized using distance variation and lateral and angular misalignment between coils. The measured results indicate that the proposed method significantly reduces searching time from a few minutes to approximately one second. Furthermore, the proposed system achieves impedance matching with good accuracy. The robust impedance-searching capability of the proposed system significantly improves power transfer efficiency. At 6.78 MHz, we achieve a maximum efficiency of 89.7% and a high efficiency of >80% up to a distance of 50 cm. When the center-to-center misalignment is 35 cm, the efficiency is improved from 48.4% to 74.1% with the proposed method. At a distance of 40 cm, the efficiency is higher than 74% for up to 60° of angular rotation. These results agree well with the simulated results obtained using a lumped-element circuit model.
Xu, Jun; Kong, Fan
2018-05-01
Extreme value distribution (EVD) evaluation is a critical topic in reliability analysis of nonlinear structural dynamic systems. In this paper, a new method is proposed to obtain the EVD. The maximum entropy method (MEM) with fractional moments as constraints is employed to derive the entire range of EVD. Then, an adaptive cubature formula is proposed for fractional moments assessment involved in MEM, which is closely related to the efficiency and accuracy for reliability analysis. Three point sets, which include a total of 2d2 + 1 integration points in the dimension d, are generated in the proposed formula. In this regard, the efficiency of the proposed formula is ensured. Besides, a "free" parameter is introduced, which makes the proposed formula adaptive with the dimension. The "free" parameter is determined by arranging one point set adjacent to the boundary of the hyper-sphere which contains the bulk of total probability. In this regard, the tail distribution may be better reproduced and the fractional moments could be evaluated with accuracy. Finally, the proposed method is applied to a ten-storey shear frame structure under seismic excitations, which exhibits strong nonlinearity. The numerical results demonstrate the efficacy of the proposed method.
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.
Dynamic Speed Adaptation for Path Tracking Based on Curvature Information and Speed Limits.
Gámez Serna, Citlalli; Ruichek, Yassine
2017-06-14
A critical concern of autonomous vehicles is safety. Different approaches have tried to enhance driving safety to reduce the number of fatal crashes and severe injuries. As an example, Intelligent Speed Adaptation (ISA) systems warn the driver when the vehicle exceeds the recommended speed limit. However, these systems only take into account fixed speed limits without considering factors like road geometry. In this paper, we consider road curvature with speed limits to automatically adjust vehicle's speed with the ideal one through our proposed Dynamic Speed Adaptation (DSA) method. Furthermore, 'curve analysis extraction' and 'speed limits database creation' are also part of our contribution. An algorithm that analyzes GPS information off-line identifies high curvature segments and estimates the speed for each curve. The speed limit database contains information about the different speed limit zones for each traveled path. Our DSA senses speed limits and curves of the road using GPS information and ensures smooth speed transitions between current and ideal speeds. Through experimental simulations with different control algorithms on real and simulated datasets, we prove that our method is able to significantly reduce lateral errors on sharp curves, to respect speed limits and consequently increase safety and comfort for the passenger.
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Muhammad Audy Bazly
2015-12-01
Full Text Available This paper aims to analyze Internet-based streaming video service in the communication media with variable bit rates. The proposed scheme on Dynamic Adaptive Streaming over HTTP (DASH using the internet network that adapts to the protocol Hyper Text Transfer Protocol (HTTP. DASH technology allows a video in the video segmentation into several packages that will distreamingkan. DASH initial stage is to compress the video source to lower the bit rate video codec uses H.26. Video compressed further in the segmentation using MP4Box generates streaming packets with the specified duration. These packages are assembled into packets in a streaming media format Presentation Description (MPD or known as MPEG-DASH. Streaming video format MPEG-DASH run on a platform with the player bitdash teritegrasi bitcoin. With this scheme, the video will have several variants of the bit rates that gave rise to the concept of scalability of streaming video services on the client side. The main target of the mechanism is smooth the MPEG-DASH streaming video display on the client. The simulation results show that the scheme based scalable video streaming MPEG- DASH able to improve the quality of image display on the client side, where the procedure bufering videos can be made constant and fine for the duration of video views
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Jooyoung Park
2015-05-01
Full Text Available Recently, the optimization of power flows in portable hybrid power-supply systems (HPSSs has become an important issue with the advent of a variety of mobile systems and hybrid energy technologies. In this paper, a control strategy is considered for dynamically managing power flows in portable HPSSs employing batteries and supercapacitors. Our dynamic power management strategy utilizes the concept of approximate dynamic programming (ADP. ADP methods are important tools in the fields of stochastic control and machine learning, and the utilization of these tools for practical engineering problems is now an active and promising research field. We propose an ADP-based procedure based on optimization under constraints including the iterated Bellman inequalities, which can be solved by convex optimization carried out offline, to find the optimal power management rules for portable HPSSs. The effectiveness of the proposed procedure is tested through dynamic simulations for smartphone workload scenarios, and simulation results show that the proposed strategy can successfully cope with uncertain workload demands.
Sugihardjo; Sutrisno, J.; Setyono, P.; Suntoro
2018-03-01
Farming activities are generally very sensitive to climate change variations. Global climate change will result in changes of patterns and distribution of rainfall. The impact of changing patterns and distribution of rainfall is the occurrence of early season shifts and periods of planting. Therefore, farmers need to adapt to the occurrence of climate change to avoid the decrease productivity on the farm land. This study aims to examine the impacts of climate change adaptation that farmers practiced on the farming productivity. The analysis is conducted dynamically using the Powersim 2.5. The result of analysis shows that the use of Planting Calendar and Integrated Crops Management technology can increase the rice productivity of certain area unity. Both technologies are the alternatives for farmers to adapt to climate change. Both farmers who adapt to climate change and do not adapt to climate change, experience an increase in rice production, time after time. However, farmers who adapt to climate change, increase their production faster than farmers who do not adapt to climate change. The use of the Planting Calendar and Integrated Crops Management strategy together as a farmers’ adaptation strategy is able to increase production compared to non-adaptive farmers.
Directory of Open Access Journals (Sweden)
Shaohua Luo
2014-01-01
Full Text Available This paper focuses on an adaptive dynamic surface control based on the Radial Basis Function Neural Network for a fourth-order permanent magnet synchronous motor system wherein the unknown parameters, disturbances, chaos, and uncertain time delays are presented. Neural Network systems are used to approximate the nonlinearities and an adaptive law is employed to estimate accurate parameters. Then, a simple and effective controller has been obtained by introducing dynamic surface control technique on the basis of first-order filters. Asymptotically tracking stability in the sense of uniformly ultimate boundedness is achieved in a short time. Finally, the performance of the proposed control has been illustrated through simulation results.
International Nuclear Information System (INIS)
Li, Lixiang; Li, Weiwei; Kurths, Jürgen; Luo, Qun; Yang, Yixian; Li, Shudong
2015-01-01
For the reason that the uncertain complex dynamic network with multi-link is quite close to various practical networks, there is superiority in the fields of research and application. In this paper, we focus upon pinning adaptive synchronization for uncertain complex dynamic networks with multi-link against network deterioration. The pinning approach can be applied to adapt uncertain coupling factors of deteriorated networks which can compensate effects of uncertainty. Several new synchronization criterions for networks with multi-link are derived, which ensure the synchronized states to be local or global stable with uncertainty and deterioration. Results of simulation are shown to demonstrate the feasibility and usefulness of our method
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
Optimization of decision rules based on dynamic programming approach
Zielosko, Beata
2014-01-14
This chapter is devoted to the study of an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure that is the difference between number of rows in a given decision table and the number of rows labeled with the most common decision for this table divided by the number of rows in the decision table. We fix a threshold γ, such that 0 ≤ γ < 1, and study so-called γ-decision rules (approximate decision rules) that localize rows in subtables which uncertainty is at most γ. Presented algorithm constructs a directed acyclic graph Δ γ T which nodes are subtables of the decision table T given by pairs "attribute = value". The algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The chapter contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2014 Springer International Publishing Switzerland.
Estimating Arrhenius parameters using temperature programmed molecular dynamics
International Nuclear Information System (INIS)
Imandi, Venkataramana; Chatterjee, Abhijit
2016-01-01
Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.
Estimating Arrhenius parameters using temperature programmed molecular dynamics
Energy Technology Data Exchange (ETDEWEB)
Imandi, Venkataramana; Chatterjee, Abhijit, E-mail: abhijit@che.iitb.ac.in [Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai 400076 (India)
2016-07-21
Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.
The sequence relay selection strategy based on stochastic dynamic programming
Zhu, Rui; Chen, Xihao; Huang, Yangchao
2017-07-01
Relay-assisted (RA) network with relay node selection is a kind of effective method to improve the channel capacity and convergence performance. However, most of the existing researches about the relay selection did not consider the statically channel state information and the selection cost. This shortage limited the performance and application of RA network in practical scenarios. In order to overcome this drawback, a sequence relay selection strategy (SRSS) was proposed. And the performance upper bound of SRSS was also analyzed in this paper. Furthermore, in order to make SRSS more practical, a novel threshold determination algorithm based on the stochastic dynamic program (SDP) was given to work with SRSS. Numerical results are also presented to exhibit the performance of SRSS with SDP.
Approximate dynamic programming approaches for appointment scheduling with patient preferences.
Li, Xin; Wang, Jin; Fung, Richard Y K
2018-04-01
During the appointment booking process in out-patient departments, the level of patient satisfaction can be affected by whether or not their preferences can be met, including the choice of physicians and preferred time slot. In addition, because the appointments are sequential, considering future possible requests is also necessary for a successful appointment system. This paper proposes a Markov decision process model for optimizing the scheduling of sequential appointments with patient preferences. In contrast to existing models, the evaluation of a booking decision in this model focuses on the extent to which preferences are satisfied. Characteristics of the model are analysed to develop a system for formulating booking policies. Based on these characteristics, two types of approximate dynamic programming algorithms are developed to avoid the curse of dimensionality. Experimental results suggest directions for further fine-tuning of the model, as well as improving the efficiency of the two proposed algorithms. Copyright © 2018 Elsevier B.V. All rights reserved.
Joiner, Wilsaan M; Ajayi, Obafunso; Sing, Gary C; Smith, Maurice A
2011-01-01
The ability to generalize learned motor actions to new contexts is a key feature of the motor system. For example, the ability to ride a bicycle or swing a racket is often first developed at lower speeds and later applied to faster velocities. A number of previous studies have examined the generalization of motor adaptation across movement directions and found that the learned adaptation decays in a pattern consistent with the existence of motor primitives that display narrow Gaussian tuning. However, few studies have examined the generalization of motor adaptation across movement speeds. Following adaptation to linear velocity-dependent dynamics during point-to-point reaching arm movements at one speed, we tested the ability of subjects to transfer this adaptation to short-duration higher-speed movements aimed at the same target. We found near-perfect linear extrapolation of the trained adaptation with respect to both the magnitude and the time course of the velocity profiles associated with the high-speed movements: a 69% increase in movement speed corresponded to a 74% extrapolation of the trained adaptation. The close match between the increase in movement speed and the corresponding increase in adaptation beyond what was trained indicates linear hypergeneralization. Computational modeling shows that this pattern of linear hypergeneralization across movement speeds is not compatible with previous models of adaptation in which motor primitives display isotropic Gaussian tuning of motor output around their preferred velocities. Instead, we show that this generalization pattern indicates that the primitives involved in the adaptation to viscous dynamics display anisotropic tuning in velocity space and encode the gain between motor output and motion state rather than motor output itself.
Vantomme, Ghislaine; Jiang, Shimei; Lehn, Jean-Marie
2014-07-02
Constitutional dynamic libraries of hydrazones (a)A(b)B and acylhydrazones (a)A(c)C undergo reorganization and adaptation in response to a chemical effector (metal cations) or a physical stimulus (light). The set of hydrazones [(1)A(1)B, (1)A(2)B, (2)A(1)B, (2)A(2)B] undergoes metalloselection on addition of zinc cations which drive the amplification of Zn((1)A(2)B)2 by selection of the fittest component (1)A(2)B. The set of acylhydrazones [E-(1)A(1)C, (1)A(2)C, (2)A(1)C, (2)A(2)C] undergoes photoselection by irradiation of the system, which causes photoisomerization of E-(1)A(1)C into Z-(1)A(1)C with amplification of the latter. The set of acyl hydrazones [E-(1)A(1)C, (1)A(3)C, (2)A(1)C, (2)A(3)C] undergoes a dual adaptation via component exchange and selection in response to two orthogonal external agents: a chemical effector, metal cations, and a physical stimulus, light irradiation. Metalloselection takes place on addition of zinc cations which drive the amplification of Zn((1)A(3)C)2 by selection of the fittest constituent (1)A(3)C. Photoselection is obtained on irradiation of the acylhydrazones that leads to photoisomerization from E-(1)A(1)C to Z-(1)A(1)C configuration with amplification of the latter. These changes may be represented by square constitutional dynamic networks that display up-regulation of the pairs of agonists ((1)A(2)B, (2)A(1)B), (Z-(1)A(1)C, (2)A(2)C), ((1)A(3)C, (2)A(1)C), (Z-(1)A(1)C, (2)A(3)C) and the simultaneous down-regulation of the pairs of antagonists ((1)A(1)B, (2)A(2)B), ((1)A(2)C, (2)A(1)C), (E-(1)A(1)C, (2)A(3)C), ((1)A(3)C, (2)A(1)C). The orthogonal dual adaptation undergone by the set of acylhydrazones amounts to a network switching process.
Lindsay, Sally; Hounsell, Kara Grace
2017-10-01
Youth with disabilities are under-represented in science, technology, engineering, and math (STEM) in school and in the workforce. One encouraging approach to engage youth's interest in STEM is through robotics; however, such programs are mostly for typically developing youth. The purpose of this study was to understand the development and implementation of an adapted robotics program for children and youth with disabilities and their experiences within it. Our mixed methods pilot study (pre- and post-workshop surveys, observations, and interviews) involved 41 participants including: 18 youth (aged 6-13), 12 parents and 11 key informants. The robotics program involved 6, two-hour workshops held at a paediatric hospital. Our findings showed that several adaptations made to the robotics program helped to enhance the participation of children with disabilities. Adaptations addressed the educational/curriculum, cognitive and learning, physical and social needs of the children. In regards to experiences within the adapted hospital program, our findings highlight that children enjoyed the program and learned about computer programming and building robots. Clinicians and educators should consider engaging youth with disabilities in robotics to enhance learning and interest in STEM. Implications for Rehabilitation Clinicians and educators should consider adapting curriculum content and mode of delivery of LEGO ® robotics programs to include youth with disabilities. Appropriate staffing including clinicians and educators who are knowledgeable about youth with disabilities and LEGO ® robotics are needed. Clinicians should consider engaging youth with disabilities in LEGO ® to enhance learning and interest in STEM.
The Glen Canyon Dam adaptive management program: progress and immediate challenges
Hamill, John F.; Melis, Theodore S.; Boon, Philip J.; Raven, Paul J.
2012-01-01
Adaptive management emerged as an important resource management strategy for major river systems in the United States (US) in the early 1990s. The Glen Canyon Dam Adaptive Management Program (‘the Program’) was formally established in 1997 to fulfill a statutory requirement in the 1992 Grand Canyon Protection Act (GCPA). The GCPA aimed to improve natural resource conditions in the Colorado River corridor in the Glen Canyon National Recreation Area and Grand Canyon National Park, Arizona that were affected by the Glen Canyon dam. The Program achieves this by using science and a variety of stakeholder perspectives to inform decisions about dam operations. Since the Program started the ecosystem is now much better understood and several biological and physical improvements have been achieved. These improvements include: (i) an estimated 50% increase in the adult population of endangered humpback chub (Gila cypha) between 2001 and 2008, following previous decline; (ii) a 90% decrease in non-native rainbow trout (Oncorhynchus mykiss), which are known to compete with and prey on native fish, as a result of removal experiments; and (iii) the widespread reappearance of sandbars in response to an experimental high-flow release of dam water in March 2008.Although substantial progress has been made, the Program faces several immediate challenges. These include: (i) defining specific, measurable objectives and desired future conditions for important natural, cultural and recreational attributes to inform science and management decisions; (ii) implementing structural and operational changes to improve collaboration among stakeholders; (iii) establishing a long-term experimental programme and management plan; and (iv) securing long-term funding for monitoring programmes to assess ecosystem and other responses to management actions. Addressing these challenges and building on recent progress will require strong and consistent leadership from the US Department of the Interior
Design and Analysis of Decision Rules via Dynamic Programming
Amin, Talha M.
2017-04-24
The areas of machine learning, data mining, and knowledge representation have many different formats used to represent information. Decision rules, amongst these formats, are the most expressive and easily-understood by humans. In this thesis, we use dynamic programming to design decision rules and analyze them. The use of dynamic programming allows us to work with decision rules in ways that were previously only possible for brute force methods. Our algorithms allow us to describe the set of all rules for a given decision table. Further, we can perform multi-stage optimization by repeatedly reducing this set to only contain rules that are optimal with respect to selected criteria. One way that we apply this study is to generate small systems with short rules by simulating a greedy algorithm for the set cover problem. We also compare maximum path lengths (depth) of deterministic and non-deterministic decision trees (a non-deterministic decision tree is effectively a complete system of decision rules) with regards to Boolean functions. Another area of advancement is the presentation of algorithms for constructing Pareto optimal points for rules and rule systems. This allows us to study the existence of “totally optimal” decision rules (rules that are simultaneously optimal with regards to multiple criteria). We also utilize Pareto optimal points to compare and rate greedy heuristics with regards to two criteria at once. Another application of Pareto optimal points is the study of trade-offs between cost and uncertainty which allows us to find reasonable systems of decision rules that strike a balance between length and accuracy.
A novel adaptive control scheme for dynamic performance improvement of DFIG-Based wind turbines
International Nuclear Information System (INIS)
Song, Zhanfeng; Shi, Tingna; Xia, Changliang; Chen, Wei
2012-01-01
A novel adaptive current controller for DFIG-based wind turbines is introduced in this paper. The attractiveness of the proposed strategy results from its ability to actively estimate and actively compensate for the plant dynamics and external disturbances in real time. Thus, the control strategy can successfully drive the rotor current to track the reference value, ensuring that the performance degradation caused by grid disturbances, cross-coupling terms and parameter uncertainties can be successfully suppressed. Besides, the two-parameter tuning feature makes the control strategy practical and easy to implement in commercial wind turbines. To quantify the controller performances, the transfer function description of the controller is derived. General disturbance rejection, robustness against parameter uncertainties, bandwidth and stability are also addressed. Simulation results, together with the time-domain responses, proved the stability and the strong robustness of the control system against parameter uncertainties and grid disturbances. Significant tracking and disturbance rejection performances are achieved. -- Highlights: ► The controller can compensate for plant dynamics and external disturbances. ► Performance degradation caused by disturbance can be successfully suppressed. ► General disturbance rejection of the proposed strategy is addressed. ► The stability and the strong robustness of the control system are proved.
International Nuclear Information System (INIS)
Fogarty, Aoife C.; Potestio, Raffaello; Kremer, Kurt
2015-01-01
A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydration shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations
An adaptively refined XFEM with virtual node polygonal elements for dynamic crack problems
Teng, Z. H.; Sun, F.; Wu, S. C.; Zhang, Z. B.; Chen, T.; Liao, D. M.
2018-02-01
By introducing the shape functions of virtual node polygonal (VP) elements into the standard extended finite element method (XFEM), a conforming elemental mesh can be created for the cracking process. Moreover, an adaptively refined meshing with the quadtree structure only at a growing crack tip is proposed without inserting hanging nodes into the transition region. A novel dynamic crack growth method termed as VP-XFEM is thus formulated in the framework of fracture mechanics. To verify the newly proposed VP-XFEM, both quasi-static and dynamic cracked problems are investigated in terms of computational accuracy, convergence, and efficiency. The research results show that the present VP-XFEM can achieve good agreement in stress intensity factor and crack growth path with the exact solutions or experiments. Furthermore, better accuracy, convergence, and efficiency of different models can be acquired, in contrast to standard XFEM and mesh-free methods. Therefore, VP-XFEM provides a suitable alternative to XFEM for engineering applications.
Kumar, Rajesh; Srivastava, Smriti; Gupta, J R P
2017-03-01
In this paper adaptive control of nonlinear dynamical systems using diagonal recurrent neural network (DRNN) is proposed. The structure of DRNN is a modification of fully connected recurrent neural network (FCRNN). Presence of self-recurrent neurons in the hidden layer of DRNN gives it an ability to capture the dynamic behaviour of the nonlinear plant under consideration (to be controlled). To ensure stability, update rules are developed using lyapunov stability criterion. These rules are then used for adjusting the various parameters of DRNN. The responses of plants obtained with DRNN are compared with those obtained when multi-layer feed forward neural network (MLFFNN) is used as a controller. Also, in example 4, FCRNN is also investigated and compared with DRNN and MLFFNN. Robustness of the proposed control scheme is also tested against parameter variations and disturbance signals. Four simulation examples including one-link robotic manipulator and inverted pendulum are considered on which the proposed controller is applied. The results so obtained show the superiority of DRNN over MLFFNN as a controller. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Fogarty, Aoife C., E-mail: fogarty@mpip-mainz.mpg.de; Potestio, Raffaello, E-mail: potestio@mpip-mainz.mpg.de; Kremer, Kurt, E-mail: kremer@mpip-mainz.mpg.de [Max Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz (Germany)
2015-05-21
A fully atomistic modelling of many biophysical and biochemical processes at biologically relevant length- and time scales is beyond our reach with current computational resources, and one approach to overcome this difficulty is the use of multiscale simulation techniques. In such simulations, when system properties necessitate a boundary between resolutions that falls within the solvent region, one can use an approach such as the Adaptive Resolution Scheme (AdResS), in which solvent particles change their resolution on the fly during the simulation. Here, we apply the existing AdResS methodology to biomolecular systems, simulating a fully atomistic protein with an atomistic hydration shell, solvated in a coarse-grained particle reservoir and heat bath. Using as a test case an aqueous solution of the regulatory protein ubiquitin, we first confirm the validity of the AdResS approach for such systems, via an examination of protein and solvent structural and dynamical properties. We then demonstrate how, in addition to providing a computational speedup, such a multiscale AdResS approach can yield otherwise inaccessible physical insights into biomolecular function. We use our methodology to show that protein structure and dynamics can still be correctly modelled using only a few shells of atomistic water molecules. We also discuss aspects of the AdResS methodology peculiar to biomolecular simulations.
Highly Dynamic and Adaptive Traffic Congestion Avoidance in Real-Time Inspired by Honey Bee Behavior
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.
High-dynamic range compressive spectral imaging by grayscale coded aperture adaptive filtering
Directory of Open Access Journals (Sweden)
Nelson Eduardo Diaz
2015-09-01
Full Text Available The coded aperture snapshot spectral imaging system (CASSI is an imaging architecture which senses the three dimensional informa-tion of a scene with two dimensional (2D focal plane array (FPA coded projection measurements. A reconstruction algorithm takes advantage of the compressive measurements sparsity to recover the underlying 3D data cube. Traditionally, CASSI uses block-un-block coded apertures (BCA to spatially modulate the light. In CASSI the quality of the reconstructed images depends on the design of these coded apertures and the FPA dynamic range. This work presents a new CASSI architecture based on grayscaled coded apertu-res (GCA which reduce the FPA saturation and increase the dynamic range of the reconstructed images. The set of GCA is calculated in a real-time adaptive manner exploiting the information from the FPA compressive measurements. Extensive simulations show the attained improvement in the quality of the reconstructed images when GCA are employed. In addition, a comparison between traditional coded apertures and GCA is realized with respect to noise tolerance.
The Glen Canyon Dam Adaptive Management Program: An experiment in science-based resource management
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
Energy Technology Data Exchange (ETDEWEB)
Erez, Mattan
2018-02-21
The Dynamic, Exascale Global Address Space programming environment (DEGAS) project will develop the next generation of programming models and runtime systems to meet the challenges of Exascale computing. Our approach is to provide an efficient and scalable programming model that can be adapted to application needs through the use of dynamic runtime features and domain-specific languages for computational kernels. We address the following technical challenges: Programmability: Rich set of programming constructs based on a Hierarchical Partitioned Global Address Space (HPGAS) model, demonstrated in UPC++. Scalability: Hierarchical locality control, lightweight communication (extended GASNet), and ef- ficient synchronization mechanisms (Phasers). Performance Portability: Just-in-time specialization (SEJITS) for generating hardware-specific code and scheduling libraries for domain-specific adaptive runtimes (Habanero). Energy Efficiency: Communication-optimal code generation to optimize energy efficiency by re- ducing data movement. Resilience: Containment Domains for flexible, domain-specific resilience, using state capture mechanisms and lightweight, asynchronous recovery mechanisms. Interoperability: Runtime and language interoperability with MPI and OpenMP to encourage broad adoption.
The selective adaptation of the alcoholics anonymous program by Gamblers Anonymous.
Browne, B R
1991-09-01
This paper is largely based on a year long observation study of Gamblers Anonymous and Alcoholics Anonymous meetings in northern California. The paper argues, contrary to popular assumption, that Gamblers Anonymous is significantly different from Alcoholics Anonymous. Differences, in members' consciousness for example, are discussed. The paper contends that although there is some12 step consciousness in G.A., the dominant consciousness ispage 17 consciousness. The significant differences are attributed to the selective adaptation of the Alcoholics Anonymous program. Several consequences of these differences, such as the central role of a language of the self in A.A. and not in G.A., are highlighted.
Dynamic Line Rating Oncor Electric Delivery Smart Grid Program
Energy Technology Data Exchange (ETDEWEB)
Johnson, Justin; Smith, Cale; Young, Mike; Donohoo, Ken; Owen, Ross; Clark, Eddit; Espejo, Raul; Aivaliotis, Sandy; Stelmak, Ron; Mohr, Ron; Barba, Cristian; Gonzalez, Guillermo; Malkin, Stuart; Dimitrova, Vessela; Ragsdale, Gary; Mitchem, Sean; Jeirath, Nakul; Loomis, Joe; Trevino, Gerardo; Syracuse, Steve; Hurst, Neil; Mereness, Matt; Johnson, Chad; Bivens, Carrie
2013-05-04
Electric transmission lines are the lifeline of the electric utility industry, delivering its product from source to consumer. This critical infrastructure is often constrained such that there is inadequate capacity on existing transmission lines to efficiently deliver the power to meet demand in certain areas or to transport energy from high-generation areas to high-consumption regions. When this happens, the cost of the energy rises; more costly sources of power are used to meet the demand or the system operates less reliably. These economic impacts are known as congestion, and they can amount to substantial dollars for any time frame of reference: hour, day or year. There are several solutions to the transmission constraint problem, including: construction of new generation, construction of new transmission facilities, rebuilding and reconductoring of existing transmission assets, and Dynamic Line Rating (DLR). All of these options except DLR are capital intensive, have long lead times and often experience strong public and regulatory opposition. The Smart Grid Demonstration Program (SGDP) project co-funded by the Department of Energy (DOE) and Oncor Electric Delivery Company developed and deployed the most extensive and advanced DLR installation to demonstrate that DLR technology is capable of resolving many transmission capacity constraint problems with a system that is reliable, safe and very cost competitive. The SGDP DLR deployment is the first application of DLR technology to feed transmission line real-time dynamic ratings directly into the system operation’s State Estimator and load dispatch program, which optimizes the matching of generation with load demand on a security, reliability and economic basis. The integrated Dynamic Line Rating (iDLR)1 collects transmission line parameters at remote locations on the lines, calculates the real-time line rating based on the equivalent conductor temperature, ambient temperature and influence of wind and solar
Geriatric education across 94 million acres: adapting conference programming in a rural state.
Murphy-Southwick, Colleen; McBride, Melen
2006-01-01
Montana, a predominantly rural state, with a unique blend of geography and history, low population density, and cultural diversity represents the challenges for program development and implementation across remote areas. The paper discusses two statewide multidisciplinary geriatric education programs for health professionals offered by the recently established Montana Geriatric Education Center (MTGEC); use of telecommunications technology; collaborations with Geriatric Education Centers (GECs) and the Montana Healthcare Telemedicine Alliance (MHTA); and training outcomes, insights, and implications for continuing education of health professionals who practice in hard-to-reach regions. In addition, data from a statewide needs assessment are presented specific to preferred format. The MTGEC training model that combined traditional classroom and videoconference increased attendance by twofold and may be adapted in other regions to train providers in remote areas of the U.S.
Placental adaptations to micronutrient dysregulation in the programming of chronic disease.
Hofstee, Pierre; McKeating, Daniel; Perkins, Anthony V; Cuffe, James S M
2018-04-21
Poor nutrition during pregnancy is known to impair foetal development and increase the risk of chronic disease in offspring. Both macronutrients and micronutrients are required for a healthy pregnancy although significantly less is understood about the role of micronutrients in the programming of chronic disease. This is despite the fact that modern calorie rich diets are often also deficient in key micronutrients. The importance of micronutrients in gestational disorders is clearly understood but how they impact long term disease in humans requires further investigation. In contrast, animal studies have demonstrated how diets high or low in specific micronutrients influence offspring physiology. Many of these studies highlight the importance of the placenta in determining disease risk. This review will explore the effects of individual vitamins, minerals and trace elements on offspring disease outcomes and discuss several key placental adaptations that are affected by multiple micronutrients. These placental adaptations include micronutrient induced dysregulation of oxidative stress, altered methyl donor availability and its impact on epigenetic mechanisms as well as endocrine dysfunction. Critical gaps in our current knowledge and the relative importance of different micronutrients at different gestational ages will also be highlighted. Finally, this review will discuss the need for further studies to characterise the micronutrient status of Australian women of reproductive age and correlate micronutrient status to placental adaptations, pregnancy complications and offspring disease. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Accardi, Luigi; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro
2016-07-01
Recently a novel quantum information formalism — quantum adaptive dynamics — was developed and applied to modelling of information processing by bio-systems including cognitive phenomena: from molecular biology (glucose-lactose metabolism for E.coli bacteria, epigenetic evolution) to cognition, psychology. From the foundational point of view quantum adaptive dynamics describes mutual adapting of the information states of two interacting systems (physical or biological) as well as adapting of co-observations performed by the systems. In this paper we apply this formalism to model unconscious inference: the process of transition from sensation to perception. The paper combines theory and experiment. Statistical data collected in an experimental study on recognition of a particular ambiguous figure, the Schröder stairs, support the viability of the quantum(-like) model of unconscious inference including modelling of biases generated by rotation-contexts. From the probabilistic point of view, we study (for concrete experimental data) the problem of contextuality of probability, its dependence on experimental contexts. Mathematically contextuality leads to non-Komogorovness: probability distributions generated by various rotation contexts cannot be treated in the Kolmogorovian framework. At the same time they can be embedded in a “big Kolmogorov space” as conditional probabilities. However, such a Kolmogorov space has too complex structure and the operational quantum formalism in the form of quantum adaptive dynamics simplifies the modelling essentially.
International Nuclear Information System (INIS)
Xu, Yancai; Liu, Derong; Wei, Qinglai
2015-01-01
Highlights: • The algorithm is developed in the two-household energy management environment. • We develop the absent energy penalty cost for the first time. • The algorithm has ability to keep adapting in real-time operations. • Its application can lower total costs and achieve better load balancing. - Abstract: Residential energy scheduling is a hot topic nowadays in the background of energy saving and environmental protection worldwide. To achieve this objective, a new residential energy scheduling algorithm is developed for energy management, based on action dependent heuristic dynamic programming. The algorithm works under the circumstance of residential real-time pricing and two adjacent housing units with energy inter-exchange, which can reduce the overall cost and enhance renewable energy efficiency after long-term operation. It is designed to obtain the optimal control policy to manage the directions and amounts of electricity energy flux. The algorithm’s architecture is mainly constructed based on neural networks, denoting the learned characteristics in the linkage of layers. To get close to real situations, many constraints such as maximum charging/discharging power of batteries are taken into account. The absent energy penalty cost is developed for the first time as a part of the performance index function. When the environment changes, the residential energy scheduling algorithm gains new features and keeps adapting in real-time operations. Simulation results show that the developed algorithm is beneficial to energy conversation
Janssen, M.; Voort, H. van der; Veenstra, A.F.E. van
2015-01-01
Many large transformation projects do not result in the outcomes desired or envisioned by the stakeholders. This type of project is characterised by dynamics which are both caused by and result of uncertainties and unexpected behaviour. In this paper a complex adaptive system (CAS) view was adopted
Di Rienzo, Marco; Castiglioni, Paolo; Iellamo, Ferdinando; Volterrani, Maurizio; Pagani, Massimo; Mancia, Giuseppe; Karemaker, John M.; Parati, Gianfranco
2008-01-01
Di Rienzo M, Castiglioni P, Iellamo F, Volterrani M, Pagani M, Mancia G, Karemaker JM, Parati G. Dynamic adaptation of cardiac baroreflex sensitivity to prolonged exposure to microgravity: data from a 16-day spaceflight. J Appl Physiol 105: 1569-1575, 2008. First published August 28, 2008;
Alzheimer's disease and natural cognitive aging may represent adaptive metabolism reduction programs
Directory of Open Access Journals (Sweden)
Reser Jared
2009-02-01
Full Text Available Abstract The present article examines several lines of converging evidence suggesting that the slow and insidious brain changes that accumulate over the lifespan, resulting in both natural cognitive aging and Alzheimer's disease (AD, represent a metabolism reduction program. A number of such adaptive programs are known to accompany aging and are thought to have decreased energy requirements for ancestral hunter-gatherers in their 30s, 40s and 50s. Foraging ability in modern hunter-gatherers declines rapidly, more than a decade before the average terminal age of 55 years. Given this, the human brain would have been a tremendous metabolic liability that must have been advantageously tempered by the early cellular and molecular changes of AD which begin to accumulate in all humans during early adulthood. Before the recent lengthening of life span, individuals in the ancestral environment died well before this metabolism reduction program resulted in clinical AD, thus there was never any selective pressure to keep adaptive changes from progressing to a maladaptive extent. Aging foragers may not have needed the same cognitive capacities as their younger counterparts because of the benefits of accumulated learning and life experience. It is known that during both childhood and adulthood metabolic rate in the brain decreases linearly with age. This trend is thought to reflect the fact that children have more to learn. AD "pathology" may be a natural continuation of this trend. It is characterized by decreasing cerebral metabolism, selective elimination of synapses and reliance on accumulating knowledge (especially implicit and procedural over raw brain power (working memory. Over decades of subsistence, the behaviors of aging foragers became routinized, their motor movements automated and their expertise ingrained to a point where they no longer necessitated the first-rate working memory they possessed when younger and learning actively. Alzheimer
Reser, Jared Edward
2009-02-28
The present article examines several lines of converging evidence suggesting that the slow and insidious brain changes that accumulate over the lifespan, resulting in both natural cognitive aging and Alzheimer's disease (AD), represent a metabolism reduction program. A number of such adaptive programs are known to accompany aging and are thought to have decreased energy requirements for ancestral hunter-gatherers in their 30s, 40s and 50s. Foraging ability in modern hunter-gatherers declines rapidly, more than a decade before the average terminal age of 55 years. Given this, the human brain would have been a tremendous metabolic liability that must have been advantageously tempered by the early cellular and molecular changes of AD which begin to accumulate in all humans during early adulthood. Before the recent lengthening of life span, individuals in the ancestral environment died well before this metabolism reduction program resulted in clinical AD, thus there was never any selective pressure to keep adaptive changes from progressing to a maladaptive extent.Aging foragers may not have needed the same cognitive capacities as their younger counterparts because of the benefits of accumulated learning and life experience. It is known that during both childhood and adulthood metabolic rate in the brain decreases linearly with age. This trend is thought to reflect the fact that children have more to learn. AD "pathology" may be a natural continuation of this trend. It is characterized by decreasing cerebral metabolism, selective elimination of synapses and reliance on accumulating knowledge (especially implicit and procedural) over raw brain power (working memory). Over decades of subsistence, the behaviors of aging foragers became routinized, their motor movements automated and their expertise ingrained to a point where they no longer necessitated the first-rate working memory they possessed when younger and learning actively. Alzheimer changes selectively and
TU-AB-303-01: A Feasibility Study for Dynamic Adaptive Therapy of Non-Small Cell Lung Cancer
Energy Technology Data Exchange (ETDEWEB)
Kim, M; Phillips, M [Univ Washington, Seattle, WA (United States)
2015-06-15
Purpose: To compare plans for NSCLC optimized using Dynamic Adaptive Therapy (DAT) with conventional IMRT optimization. DAT adapts plans based on changes in the target volume by using dynamic programing techniques to consider expected changes into the optimization process. Information gathered during treatment, e.g. from CBCT, is incorporated into the optimization. Methods and materials: DAT is formulated using stochastic control formalism, which minimizes the total expected number of tumor cells at the end of a treatment course subject to uncertainty inherent in the tumor response and organs-at-risk (OAR) dose constraints. This formulation allows for non-stationary dose distribution as well as non-stationary fractional dose as needed to achieve a series of optimal plans that are conformal to tumor over time. Sixteen phantom cases with various sizes and locations of tumors, and OAR geometries were generated. Each case was planned with DAT and conventional IMRT (60Gy/30fx). Tumor volume change over time was obtained by using, daily MVCT-based, two-level cell population model. Monte Carlo simulations have been performed for each treatment course to account for uncertainty in tumor response. Same OAR dose constraints were applied for both methods. The frequency of plan modification was varied to 1, 2, 5 (weekly), and 29 (daily). The final average tumor dose and OAR doses have been compared to quantify the potential benefit of DAT. Results: The average tumor max, min, mean, and D95 resulted from DAT were 124.0–125.2%, 102.1–114.7%, 113.7–123.4%, and 102.0–115.9% (range dependent on the frequency of plan modification) of those from conventional IMRT. Cord max, esophagus max, lung mean, heart mean, and unspecified tissue D05 resulted from AT were 84–102.4%, 99.8–106.9%, 66.9–85.6%, 58.2–78.8%, and 85.2–94.0% of those from conventional IMRT. Conclusions: Significant tumor dose increase and OAR dose reduction, especially with parallel OAR with mean or
Directory of Open Access Journals (Sweden)
H.Z. Igamberdiyev
2014-07-01
Full Text Available Dynamic systems condition estimation regularization algorithms in the conditions of signals and hindrances statistical characteristics aprioristic uncertainty are offered. Regular iterative algorithms of strengthening matrix factor elements of the Kalman filter, allowing to adapt the filter to changing hindrance-alarm conditions are developed. Steady adaptive estimation algorithms of a condition vector in the aprioristic uncertainty conditions of covariance matrixes of object noise and the measurements hindrances providing a certain roughness of filtration process in relation to changing statistical characteristics of signals information parameters are offered. Offered practical realization results of the dynamic systems condition estimation algorithms are given at the adaptive management systems synthesis problems solution by technological processes of granulation drying of an ammophos pulp and receiving ammonia.
1975-12-01
Frequency domain computer programs developed or acquired by TSC for the analysis of rail vehicle dynamics are described in two volumes. Volume I defines the general analytical capabilities required for computer programs applicable to single rail vehi...
Adaptive spacetime method using Riemann jump conditions for coupled atomistic-continuum dynamics
International Nuclear Information System (INIS)
Kraczek, B.; Miller, S.T.; Haber, R.B.; Johnson, D.D.
2010-01-01
We combine the Spacetime Discontinuous Galerkin (SDG) method for elastodynamics with the mathematically consistent Atomistic Discontinuous Galerkin (ADG) method in a new scheme that concurrently couples continuum and atomistic models of dynamic response in solids. The formulation couples non-overlapping continuum and atomistic models across sharp interfaces by weakly enforcing jump conditions, for both momentum balance and kinematic compatibility, using Riemann values to preserve the characteristic structure of the underlying hyperbolic system. Momentum balances to within machine-precision accuracy over every element, on each atom, and over the coupled system, with small, controllable energy dissipation in the continuum region that ensures numerical stability. When implemented on suitable unstructured spacetime grids, the continuum SDG model offers linear computational complexity in the number of elements and powerful adaptive analysis capabilities that readily bridge between atomic and continuum scales in both space and time. A special trace operator for the atomic velocities and an associated atomistic traction field enter the jump conditions at the coupling interface. The trace operator depends on parameters that specify, at the scale of the atomic spacing, the position of the coupling interface relative to the atoms. In a key finding, we demonstrate that optimizing these parameters suppresses spurious reflections at the coupling interface without the use of non-physical damping or special boundary conditions. We formulate the implicit SDG-ADG coupling scheme in up to three spatial dimensions, and describe an efficient iterative solution scheme that outperforms common explicit schemes, such as the Velocity Verlet integrator. Numerical examples, in 1dxtime and employing both linear and nonlinear potentials, demonstrate the performance of the SDG-ADG method and show how adaptive spacetime meshing reconciles disparate time steps and resolves atomic-scale signals in
Formative evaluation of an adaptive game for engaging learners of programming concepts in K-12
Directory of Open Access Journals (Sweden)
Renny S. N. Lindberg
2018-06-01
Full Text Available As the global demand for programmers is soaring, several countries have integrated programming into their K-12 curricula. Finding effective ways to engage children in programming education is an important objective. One effective method for this can be presenting learning materials via games, which are known to increase engagement and motivation. Current programming education games often focus on a single genre and offer one-size-fits-all experience to heterogeneous learners. In this study, we presented Minerva, a multi-genre (adventure, action, puzzle game to engage elementary school students in learning programming concepts. The game content is adapted to play and learning styles of the player to personalize the gameplay. We conducted a formative mixed-method evaluation of Minerva with 32 Korean 6th grade students who played the game and compared their learning outcomes with 32 6th grade students who studied the same concepts using handouts. The results indicated that, in terms of retention, learning was equally effective in both groups. Furthermore, the game was shown to facilitate engagement among the students. These results, together with uncovered issues, will guide Minerva’s further development.
Apostolos Chatzitomaris; Rudolf Hoermann; John E. Midgley; Steffen Hering; Aline Urban; Barbara Dietrich; Assjana Abood; Harald H. Klein; Harald H. Klein; Johannes W. Dietrich; Johannes W. Dietrich
2017-01-01
The hypothalamus–pituitary–thyroid feedback control is a dynamic, adaptive system. In situations of illness and deprivation of energy representing type 1 allostasis, the stress response operates to alter both its set point and peripheral transfer parameters. In contrast, type 2 allostatic load, typically effective in psychosocial stress, pregnancy, metabolic syndrome, and adaptation to cold, produces a nearly opposite phenotype of predictive plasticity. The non-thyroidal illness syndrome (NTI...
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…
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…
Directory of Open Access Journals (Sweden)
Emer Bernal
2017-01-01
Full Text Available In this paper we are presenting a method using fuzzy logic for dynamic parameter adaptation in the imperialist competitive algorithm, which is usually known by its acronym ICA. The ICA algorithm was initially studied in its original form to find out how it works and what parameters have more effect upon its results. Based on this study, several designs of fuzzy systems for dynamic adjustment of the ICA parameters are proposed. The experiments were performed on the basis of solving complex optimization problems, particularly applied to benchmark mathematical functions. A comparison of the original imperialist competitive algorithm and our proposed fuzzy imperialist competitive algorithm was performed. In addition, the fuzzy ICA was compared with another metaheuristic using a statistical test to measure the advantage of the proposed fuzzy approach for dynamic parameter adaptation.
De Colle, Fabio; Granot, Jonathan; López-Cámara, Diego; Ramirez-Ruiz, Enrico
2012-02-01
We report on the development of Mezcal-SRHD, a new adaptive mesh refinement, special relativistic hydrodynamics (SRHD) code, developed with the aim of studying the highly relativistic flows in gamma-ray burst sources. The SRHD equations are solved using finite-volume conservative solvers, with second-order interpolation in space and time. The correct implementation of the algorithms is verified by one-dimensional (1D) and multi-dimensional tests. The code is then applied to study the propagation of 1D spherical impulsive blast waves expanding in a stratified medium with ρvpropr -k , bridging between the relativistic and Newtonian phases (which are described by the Blandford-McKee and Sedov-Taylor self-similar solutions, respectively), as well as to a two-dimensional (2D) cylindrically symmetric impulsive jet propagating in a constant density medium. It is shown that the deceleration to nonrelativistic speeds in one dimension occurs on scales significantly larger than the Sedov length. This transition is further delayed with respect to the Sedov length as the degree of stratification of the ambient medium is increased. This result, together with the scaling of position, Lorentz factor, and the shock velocity as a function of time and shock radius, is explained here using a simple analytical model based on energy conservation. The method used for calculating the afterglow radiation by post-processing the results of the simulations is described in detail. The light curves computed using the results of 1D numerical simulations during the relativistic stage correctly reproduce those calculated assuming the self-similar Blandford-McKee solution for the evolution of the flow. The jet dynamics from our 2D simulations and the resulting afterglow light curves, including the jet break, are in good agreement with those presented in previous works. Finally, we show how the details of the dynamics critically depend on properly resolving the structure of the relativistic flow.
International Nuclear Information System (INIS)
De Colle, Fabio; Ramirez-Ruiz, Enrico; Granot, Jonathan; López-Cámara, Diego
2012-01-01
We report on the development of Mezcal-SRHD, a new adaptive mesh refinement, special relativistic hydrodynamics (SRHD) code, developed with the aim of studying the highly relativistic flows in gamma-ray burst sources. The SRHD equations are solved using finite-volume conservative solvers, with second-order interpolation in space and time. The correct implementation of the algorithms is verified by one-dimensional (1D) and multi-dimensional tests. The code is then applied to study the propagation of 1D spherical impulsive blast waves expanding in a stratified medium with ρ∝r –k , bridging between the relativistic and Newtonian phases (which are described by the Blandford-McKee and Sedov-Taylor self-similar solutions, respectively), as well as to a two-dimensional (2D) cylindrically symmetric impulsive jet propagating in a constant density medium. It is shown that the deceleration to nonrelativistic speeds in one dimension occurs on scales significantly larger than the Sedov length. This transition is further delayed with respect to the Sedov length as the degree of stratification of the ambient medium is increased. This result, together with the scaling of position, Lorentz factor, and the shock velocity as a function of time and shock radius, is explained here using a simple analytical model based on energy conservation. The method used for calculating the afterglow radiation by post-processing the results of the simulations is described in detail. The light curves computed using the results of 1D numerical simulations during the relativistic stage correctly reproduce those calculated assuming the self-similar Blandford-McKee solution for the evolution of the flow. The jet dynamics from our 2D simulations and the resulting afterglow light curves, including the jet break, are in good agreement with those presented in previous works. Finally, we show how the details of the dynamics critically depend on properly resolving the structure of the relativistic flow.
Stochastic dynamics of adaptive trait and neutral marker driven by eco-evolutionary feedbacks.
Billiard, Sylvain; Ferrière, Régis; Méléard, Sylvie; Tran, Viet Chi
2015-11-01
How the neutral diversity is affected by selection and adaptation is investigated in an eco-evolutionary framework. In our model, we study a finite population in continuous time, where each individual is characterized by a trait under selection and a completely linked neutral marker. Population dynamics are driven by births and deaths, mutations at birth, and competition between individuals. Trait values influence ecological processes (demographic events, competition), and competition generates selection on trait variation, thus closing the eco-evolutionary feedback loop. The demographic effects of the trait are also expected to influence the generation and maintenance of neutral variation. We consider a large population limit with rare mutation, under the assumption that the neutral marker mutates faster than the trait under selection. We prove the convergence of the stochastic individual-based process to a new measure-valued diffusive process with jumps that we call Substitution Fleming-Viot Process (SFVP). When restricted to the trait space this process is the Trait Substitution Sequence first introduced by Metz et al. (1996). During the invasion of a favorable mutation, a genetical bottleneck occurs and the marker associated with this favorable mutant is hitchhiked. By rigorously analysing the hitchhiking effect and how the neutral diversity is restored afterwards, we obtain the condition for a time-scale separation; under this condition, we show that the marker distribution is approximated by a Fleming-Viot distribution between two trait substitutions. We discuss the implications of the SFVP for our understanding of the dynamics of neutral variation under eco-evolutionary feedbacks and illustrate the main phenomena with simulations. Our results highlight the joint importance of mutations, ecological parameters, and trait values in the restoration of neutral diversity after a selective sweep.
Energy Technology Data Exchange (ETDEWEB)
De Colle, Fabio; Ramirez-Ruiz, Enrico [Astronomy and Astrophysics Department, University of California, Santa Cruz, CA 95064 (United States); Granot, Jonathan [Racah Institute of Physics, Hebrew University, Jerusalem 91904 (Israel); Lopez-Camara, Diego [Instituto de Ciencias Nucleares, Universidad Nacional Autonoma de Mexico, Ap. 70-543, 04510 D.F. (Mexico)
2012-02-20
We report on the development of Mezcal-SRHD, a new adaptive mesh refinement, special relativistic hydrodynamics (SRHD) code, developed with the aim of studying the highly relativistic flows in gamma-ray burst sources. The SRHD equations are solved using finite-volume conservative solvers, with second-order interpolation in space and time. The correct implementation of the algorithms is verified by one-dimensional (1D) and multi-dimensional tests. The code is then applied to study the propagation of 1D spherical impulsive blast waves expanding in a stratified medium with {rho}{proportional_to}r{sup -k}, bridging between the relativistic and Newtonian phases (which are described by the Blandford-McKee and Sedov-Taylor self-similar solutions, respectively), as well as to a two-dimensional (2D) cylindrically symmetric impulsive jet propagating in a constant density medium. It is shown that the deceleration to nonrelativistic speeds in one dimension occurs on scales significantly larger than the Sedov length. This transition is further delayed with respect to the Sedov length as the degree of stratification of the ambient medium is increased. This result, together with the scaling of position, Lorentz factor, and the shock velocity as a function of time and shock radius, is explained here using a simple analytical model based on energy conservation. The method used for calculating the afterglow radiation by post-processing the results of the simulations is described in detail. The light curves computed using the results of 1D numerical simulations during the relativistic stage correctly reproduce those calculated assuming the self-similar Blandford-McKee solution for the evolution of the flow. The jet dynamics from our 2D simulations and the resulting afterglow light curves, including the jet break, are in good agreement with those presented in previous works. Finally, we show how the details of the dynamics critically depend on properly resolving the structure of the
Arenas, I. A.; Tremblay, J.; Deslauriers, B.; Sandoval, J.; Šeda, O.; Gaudet, D.; Merlo, E.; Kotchen, T.; Cowley, A. W.
2013-01-01
Blood pressure (BP) is a dynamic phenotype that varies rapidly to adjust to changing environmental conditions. Standing upright is a recent evolutionary trait, and genetic factors that influence postural adaptations may contribute to BP variability. We studied the effect of posture on the genetics of BP and intermediate BP phenotypes. We included 384 sib-pairs in 64 sib-ships from families ascertained by early-onset hypertension and dyslipidemia. Blood pressure, three hemodynamic and seven neuroendocrine intermediate BP phenotypes were measured with subjects lying supine and standing upright. The effect of posture on estimates of heritability and genetic covariance was investigated in full pedigrees. Linkage was conducted on 196 candidate genes by sib-pair analyses, and empirical estimates of significance were obtained. A permutation algorithm was implemented to study the postural effect on linkage. ADRA1A, APO, CAST, CORIN, CRHR1, EDNRB, FGF2, GC, GJA1, KCNB2, MMP3, NPY, NR3C2, PLN, TGFBR2, TNFRSF6, and TRHR showed evidence of linkage with any phenotype in the supine position and not upon standing, whereas AKR1B1, CD36, EDNRA, F5, MMP9, PKD2, PON1, PPARG, PPARGC1A, PRKCA, and RET were specifically linked to standing phenotypes. Genetic profiling was undertaken to show genetic interactions among intermediate BP phenotypes and genes specific to each posture. When investigators perform genetic studies exclusively on a single posture, important genetic components of BP are missed. Supine and standing BPs have distinct genetic signatures. Standardized maneuvers influence the results of genetic investigations into BP, thus reflecting its dynamic regulation. PMID:23269701
DEFF Research Database (Denmark)
Goumas, Georgios; McKee, Sally A.; Själander, Magnus
2011-01-01
boundaries (walls) for applications which limit software development (parallel programming wall), performance (memory wall, communication wall) and viability (power wall). The only way to survive in such a demanding environment is by adaptation. In this paper we discuss how dynamic information collected...