Enhancing TSM&O strategies through life cycle benefit/cost analysis : life cycle benefit/cost analysis & life cycle assessment of adaptive traffic control systems and ramp metering systems.

DOT National Transportation Integrated Search

2015-05-01

The research team developed a comprehensive Benefit/Cost (B/C) analysis framework to evaluate existing and anticipated : intelligent transportation system (ITS) strategies, particularly, adaptive traffic control systems and ramp metering systems, : i...

Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering

PubMed Central

Carmena, Jose M.

2016-01-01

Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain’s behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user’s motor intention during CLDA—a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to parameter initialization. Finally, the architecture extended control to tasks beyond those used for CLDA training. These results have significant implications towards the development of clinically-viable neuroprosthetics. PMID:27035820

A Network Thermodynamic Framework for the Analysis and Control Design of Large-Scale Dynamical Systems

DTIC Science & Technology

2006-03-31

Nonnegative Dynamical Sys- tems................................................. 18 2.10. Adaptive Control for General Anesthesia and Intensive Care...Unit Sedation 20 2.11. Neural Network Adaptive Control for Intensive Care Unit Sedation and In- traoperative Anesthesia ...control for operating room hypnosis and intefisive care unit sedation. 1.3. Goals of this Report The main goal of this report is to summarize the

Effects of incomplete adaption and disturbance in adaptive control

NASA Technical Reports Server (NTRS)

Lindorff, D. P.

1972-01-01

This investigation focused attention on the fact that the synthesis of adaptive control systems has often been discussed in the framework of idealizations which may represent over simplifications. A condition for boundedness of the tracking error has been derived for the case in which incomplete adaption and disturbance are present. When using Parks' design it is shown that instability of the adaptive gains can result due to the presence of disturbance. The theory has been applied to a nontrivial example in order to illustrate the concepts involved.

Nonlinear discrete-time multirate adaptive control of non-linear vibrations of smart beams

NASA Astrophysics Data System (ADS)

Georgiou, Georgios; Foutsitzi, Georgia A.; Stavroulakis, Georgios E.

2018-06-01

The nonlinear adaptive digital control of a smart piezoelectric beam is considered. It is shown that in the case of a sampled-data context, a multirate control strategy provides an appropriate framework in order to achieve vibration regulation, ensuring the stability of the whole control system. Under parametric uncertainties in the model parameters (damping ratios, frequencies, levels of non linearities and cross coupling, control input parameters), the scheme is completed with an adaptation law deduced from hyperstability concepts. This results in the asymptotic satisfaction of the control objectives at the sampling instants. Simulation results are presented.

Encoder-Decoder Optimization for Brain-Computer Interfaces

PubMed Central

Merel, Josh; Pianto, Donald M.; Cunningham, John P.; Paninski, Liam

2015-01-01

Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages. PMID:26029919

Encoder-decoder optimization for brain-computer interfaces.

PubMed

Merel, Josh; Pianto, Donald M; Cunningham, John P; Paninski, Liam

2015-06-01

Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.

Adaptive change in corporate control practices.

PubMed

Alexander, J A

1991-03-01

Multidivisional organizations are not concerned with what structure to adopt but with how they should exercise control within the divisional form to achieve economic efficiencies. Using an information-processing framework, I examined control arrangements between the headquarters and operating divisions of such organizations and how managers adapted control practices to accommodate increasing environmental uncertainty. Also considered were the moderating effects of contextual attributes on such adaptive behavior. Analyses of panel data from 97 multihospital systems suggested that organizations generally practice selective decentralization under conditions of increasing uncertainty but that organizational age, dispersion, and initial control arrangements significantly moderate the direction and magnitude of such changes.

Dynamic optimization and adaptive controller design

NASA Astrophysics Data System (ADS)

Inamdar, S. R.

2010-10-01

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

Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems.

PubMed

González-Gutiérrez, Carlos; Santos, Jesús Daniel; Martínez-Zarzuela, Mario; Basden, Alistair G; Osborn, James; Díaz-Pernas, Francisco Javier; De Cos Juez, Francisco Javier

2017-06-02

Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named "CARMEN" are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances.

Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems

PubMed Central

González-Gutiérrez, Carlos; Santos, Jesús Daniel; Martínez-Zarzuela, Mario; Basden, Alistair G.; Osborn, James; Díaz-Pernas, Francisco Javier; De Cos Juez, Francisco Javier

2017-01-01

Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named “CARMEN” are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances. PMID:28574426

Experimental study of adaptive pointing and tracking for large flexible space structures

NASA Technical Reports Server (NTRS)

Boussalis, D.; Bayard, D. S.; Ih, C.; Wang, S. J.; Ahmed, A.

1991-01-01

This paper describes an experimental study of adaptive pointing and tracking control for flexible spacecraft conducted on a complex ground experiment facility. The algorithm used in this study is based on a multivariable direct model reference adaptive control law. Several experimental validation studies were performed earlier using this algorithm for vibration damping and robust regulation, with excellent results. The current work extends previous studies by addressing the pointing and tracking problem. As is consistent with an adaptive control framework, the plant is assumed to be poorly known to the extent that only system level knowledge of its dynamics is available. Explicit bounds on the steady-state pointing error are derived as functions of the adaptive controller design parameters. It is shown that good tracking performance can be achieved in an experimental setting by adjusting adaptive controller design weightings according to the guidelines indicated by the analytical expressions for the error.

On decentralized adaptive full-order sliding mode control of multiple UAVs.

PubMed

Xiang, Xianbo; Liu, Chao; Su, Housheng; Zhang, Qin

2017-11-01

In this study, a novel decentralized adaptive full-order sliding mode control framework is proposed for the robust synchronized formation motion of multiple unmanned aerial vehicles (UAVs) subject to system uncertainty. First, a full-order sliding mode surface in a decentralized manner is designed to incorporate both the individual position tracking error and the synchronized formation error while the UAV group is engaged in building a certain desired geometric pattern in three dimensional space. Second, a decentralized virtual plant controller is constructed which allows the embedded low-pass filter to attain the chattering free property of the sliding mode controller. In addition, robust adaptive technique is integrated in the decentralized chattering free sliding control design in order to handle unknown bounded uncertainties, without requirements for assuming a priori knowledge of bounds on the system uncertainties as stated in conventional chattering free control methods. Subsequently, system robustness as well as stability of the decentralized full-order sliding mode control of multiple UAVs is synthesized. Numerical simulation results illustrate the effectiveness of the proposed control framework to achieve robust 3D formation flight of the multi-UAV system. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

The Researching on Evaluation of Automatic Voltage Control Based on Improved Zoning Methodology

NASA Astrophysics Data System (ADS)

Xiao-jun, ZHU; Ang, FU; Guang-de, DONG; Rui-miao, WANG; De-fen, ZHU

2018-03-01

According to the present serious phenomenon of increasing size and structure of power system, hierarchically structured automatic voltage control(AVC) has been the researching spot. In the paper, the reduced control model is built and the adaptive reduced control model is researched to improve the voltage control effect. The theories of HCSD, HCVS, SKC and FCM are introduced and the effect on coordinated voltage regulation caused by different zoning methodologies is also researched. The generic framework for evaluating performance of coordinated voltage regulation is built. Finally, the IEEE-96 stsyem is used to divide the network. The 2383-bus Polish system is built to verify that the selection of a zoning methodology affects not only the coordinated voltage regulation operation, but also its robustness to erroneous data and proposes a comprehensive generic framework for evaluating its performance. The New England 39-bus network is used to verify the adaptive reduced control models’ performance.

Mission Data System Java Edition Version 7

NASA Technical Reports Server (NTRS)

Reinholtz, William K.; Wagner, David A.

2013-01-01

The Mission Data System framework defines closed-loop control system abstractions from State Analysis including interfaces for state variables, goals, estimators, and controllers that can be adapted to implement a goal-oriented control system. The framework further provides an execution environment that includes a goal scheduler, execution engine, and fault monitor that support the expression of goal network activity plans. Using these frameworks, adapters can build a goal-oriented control system where activity coordination is verified before execution begins (plan time), and continually during execution. Plan failures including violations of safety constraints expressed in the plan can be handled through automatic re-planning. This version optimizes a number of key interfaces and features to minimize dependencies, performance overhead, and improve reliability. Fault diagnosis and real-time projection capabilities are incorporated. This version enhances earlier versions primarily through optimizations and quality improvements that raise the technology readiness level. Goals explicitly constrain system states over explicit time intervals to eliminate ambiguity about intent, as compared to command-oriented control that only implies persistent intent until another command is sent. A goal network scheduling and verification process ensures that all goals in the plan are achievable before starting execution. Goal failures at runtime can be detected (including predicted failures) and handled by adapted response logic. Responses can include plan repairs (try an alternate tactic to achieve the same goal), goal shedding, ignoring the fault, cancelling the plan, or safing the system.

3D numerical simulations of oblique droplet impact onto a deep liquid pool

NASA Astrophysics Data System (ADS)

Gelderblom, Hanneke; Reijers, Sten A.; Gielen, Marise; Sleutel, Pascal; Lohse, Detlef; Xie, Zhihua; Pain, Christopher C.; Matar, Omar K.

2017-11-01

We study the fluid dynamics of three-dimensional oblique droplet impact, which results in phenomena that include splashing and cavity formation. An adaptive, unstructured mesh modelling framework is employed here, which can modify and adapt unstructured meshes to better represent the underlying physics of droplet dynamics, and reduce computational effort without sacrificing accuracy. The numerical framework consists of a mixed control-volume and finite-element formulation, a volume-of-fluid-type method for the interface-capturing based on a compressive control-volume advection method. The framework also features second-order finite-element methods, and a force-balanced algorithm for the surface tension implementation, minimising the spurious velocities often found in many simulations involving capillary-driven flows. The numerical results generated using this framework are compared with high-speed images of the interfacial shapes of the deformed droplet, and the cavity formed upon impact, yielding good agreement. EPSRC, UK, MEMPHIS program Grant (EP/K003976/1), RAEng Research Chair (OKM).

Adaptive PID formation control of nonholonomic robots without leader's velocity information.

PubMed

Shen, Dongbin; Sun, Weijie; Sun, Zhendong

2014-03-01

This paper proposes an adaptive proportional integral derivative (PID) algorithm to solve a formation control problem in the leader-follower framework where the leader robot's velocities are unknown for the follower robots. The main idea is first to design some proper ideal control law for the formation system to obtain a required performance, and then to propose the adaptive PID methodology to approach the ideal controller. As a result, the formation is achieved with much more enhanced robust formation performance. The stability of the closed-loop system is theoretically proved by Lyapunov method. Both numerical simulations and physical vehicle experiments are presented to verify the effectiveness of the proposed adaptive PID algorithm. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Using engineering control principles to inform the design of adaptive interventions: a conceptual introduction.

PubMed

Rivera, Daniel E; Pew, Michael D; Collins, Linda M

2007-05-01

The goal of this paper is to describe the role that control engineering principles can play in developing and improving the efficacy of adaptive, time-varying interventions. It is demonstrated that adaptive interventions constitute a form of feedback control system in the context of behavioral health. Consequently, drawing from ideas in control engineering has the potential to significantly inform the analysis, design, and implementation of adaptive interventions, leading to improved adherence, better management of limited resources, a reduction of negative effects, and overall more effective interventions. This article illustrates how to express an adaptive intervention in control engineering terms, and how to use this framework in a computer simulation to investigate the anticipated impact of intervention design choices on efficacy. The potential benefits of operationalizing decision rules based on control engineering principles are particularly significant for adaptive interventions that involve multiple components or address co-morbidities, situations that pose significant challenges to conventional clinical practice.

Using Engineering Control Principles to Inform the Design of Adaptive Interventions: A Conceptual Introduction

PubMed Central

Rivera, Daniel E.; Pew, Michael D.; Collins, Linda M.

2007-01-01

The goal of this paper is to describe the role that control engineering principles can play in developing and improving the efficacy of adaptive, time-varying interventions. It is demonstrated that adaptive interventions constitute a form of feedback control system in the context of behavioral health. Consequently, drawing from ideas in control engineering has the potential to significantly inform the analysis, design, and implementation of adaptive interventions, leading to improved adherence, better management of limited resources, a reduction of negative effects, and overall more effective interventions. This article illustrates how to express an adaptive intervention in control engineering terms, and how to use this framework in a computer simulation to investigate the anticipated impact of intervention design choices on efficacy. The potential benefits of operationalizing decision rules based on control engineering principles are particularly significant for adaptive interventions that involve multiple components or address co-morbidities, situations that pose significant challenges to conventional clinical practice. PMID:17169503

Robust adaptive control modeling of human arm movements subject to altered gravity and mechanical loads

NASA Astrophysics Data System (ADS)

Tryfonidis, Michail

It has been observed that during orbital spaceflight the absence of gravitation related sensory inputs causes incongruence between the expected and the actual sensory feedback resulting from voluntary movements. This incongruence results in a reinterpretation or neglect of gravity-induced sensory input signals. Over time, new internal models develop, gradually compensating for the loss of spatial reference. The study of adaptation of goal-directed movements is the main focus of this thesis. The hypothesis is that during the adaptive learning process the neural connections behave in ways that can be described by an adaptive control method. The investigation presented in this thesis includes two different sets of experiments. A series of dart throwing experiments took place onboard the space station Mir. Experiments also took place at the Biomechanics lab at MIT, where the subjects performed a series of continuous trajectory tracking movements while a planar robotic manipulandum exerted external torques on the subjects' moving arms. The experimental hypothesis for both experiments is that during the first few trials the subjects will perform poorly trying to follow a prescribed trajectory, or trying to hit a target. A theoretical framework is developed that is a modification of the sliding control method used in robotics. The new control framework is an attempt to explain the adaptive behavior of the subjects. Numerical simulations of the proposed framework are compared with experimental results and predictions from competitive models. The proposed control methodology extends the results of the sliding mode theory to human motor control. The resulting adaptive control model of the motor system is robust to external dynamics, even those of negative gain, uses only position and velocity feedback, and achieves bounded steady-state error without explicit knowledge of the system's nonlinearities. In addition, the experimental and modeling results demonstrate that visuomotor learning is important not only for error correction through internal model adaptation on ground or in microgravity, but also for the minimization of the total mean-square error in the presence of random variability. Thus human intelligent decision displays certain attributes that seem to conform to Bayesian statistical games. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)

Structure-based control of complex networks with nonlinear dynamics.

PubMed

Zañudo, Jorge Gomez Tejeda; Yang, Gang; Albert, Réka

2017-07-11

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.

A Novel Switching-Based Control Framework for Improved Task Performance in Teleoperation System With Asymmetric Time-Varying Delays.

PubMed

Zhai, Di-Hua; Xia, Yuanqing

2018-02-01

This paper addresses the adaptive control for task-space teleoperation systems with constrained predefined synchronization error, where a novel switched control framework is investigated. Based on multiple Lyapunov-Krasovskii functionals method, the stability of the resulting closed-loop system is established in the sense of state-independent input-to-output stability. Compared with previous work, the developed method can simultaneously handle the unknown kinematics/dynamics, asymmetric varying time delays, and prescribed performance control in a unified framework. It is shown that the developed controller can guarantee the prescribed transient-state and steady-state synchronization performances between the master and slave robots, which is demonstrated by the simulation study.

Patient adaptive control of end-effector based gait rehabilitation devices using a haptic control framework.

PubMed

Hussein, Sami; Kruger, Jörg

2011-01-01

Robot assisted training has proven beneficial as an extension of conventional therapy to improve rehabilitation outcome. Further facilitation of this positive impact is expected from the application of cooperative control algorithms to increase the patient's contribution to the training effort according to his level of ability. This paper presents an approach for cooperative training for end-effector based gait rehabilitation devices. Thereby it provides the basis to firstly establish sophisticated cooperative control methods in this class of devices. It uses a haptic control framework to synthesize and render complex, task specific training environments, which are composed of polygonal primitives. Training assistance is integrated as part of the environment into the haptic control framework. A compliant window is moved along a nominal training trajectory compliantly guiding and supporting the foot motion. The level of assistance is adjusted via the stiffness of the moving window. Further an iterative learning algorithm is used to automatically adjust this assistance level. Stable haptic rendering of the dynamic training environments and adaptive movement assistance have been evaluated in two example training scenarios: treadmill walking and stair climbing. Data from preliminary trials with one healthy subject is provided in this paper. © 2011 IEEE

Lyapunov function-based control laws for revolute robot arms - Tracking control, robustness, and adaptive control

NASA Technical Reports Server (NTRS)

Wen, John T.; Kreutz-Delgado, Kenneth; Bayard, David S.

1992-01-01

A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).

Adaptive management for subsurface pressure and plume control in application to geological CO2 storage

NASA Astrophysics Data System (ADS)

Gonzalez-Nicolas, A.; Cihan, A.; Birkholzer, J. T.; Petrusak, R.; Zhou, Q.; Riestenberg, D. E.; Trautz, R. C.; Godec, M.

2016-12-01

Industrial-scale injection of CO2 into the subsurface can cause reservoir pressure increases that must be properly controlled to prevent any potential environmental impact. Excessive pressure buildup in reservoir may result in ground water contamination stemming from leakage through conductive pathways, such as improperly plugged abandoned wells or distant faults, and the potential for fault reactivation and possibly seal breaching. Brine extraction is a viable approach for managing formation pressure, effective stress, and plume movement during industrial-scale CO2 injection projects. The main objectives of this study are to investigate suitable different pressure management strategies involving active brine extraction and passive pressure relief wells. Adaptive optimized management of CO2 storage projects utilizes the advanced automated optimization algorithms and suitable process models. The adaptive management integrates monitoring, forward modeling, inversion modeling and optimization through an iterative process. In this study, we employ an adaptive framework to understand primarily the effects of initial site characterization and frequency of the model update (calibration) and optimization calculations for controlling extraction rates based on the monitoring data on the accuracy and the success of the management without violating pressure buildup constraints in the subsurface reservoir system. We will present results of applying the adaptive framework to test appropriateness of different management strategies for a realistic field injection project.

Real-Time Minimization of Tracking Error for Aircraft Systems

NASA Technical Reports Server (NTRS)

Garud, Sumedha; Kaneshige, John T.; Krishnakumar, Kalmanje S.; Kulkarni, Nilesh V.; Burken, John

2013-01-01

This technology presents a novel, stable, discrete-time adaptive law for flight control in a Direct adaptive control (DAC) framework. Where errors are not present, the original control design has been tuned for optimal performance. Adaptive control works towards achieving nominal performance whenever the design has modeling uncertainties/errors or when the vehicle suffers substantial flight configuration change. The baseline controller uses dynamic inversion with proportional-integral augmentation. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to a dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. If the system senses that at least one aircraft component is experiencing an excursion and the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, then the neural network (NN) modeling of aircraft operation may be changed.

Structural Control of Metabolic Flux

PubMed Central

Sajitz-Hermstein, Max; Nikoloski, Zoran

2013-01-01

Organisms have to continuously adapt to changing environmental conditions or undergo developmental transitions. To meet the accompanying change in metabolic demands, the molecular mechanisms of adaptation involve concerted interactions which ultimately induce a modification of the metabolic state, which is characterized by reaction fluxes and metabolite concentrations. These state transitions are the effect of simultaneously manipulating fluxes through several reactions. While metabolic control analysis has provided a powerful framework for elucidating the principles governing this orchestrated action to understand metabolic control, its applications are restricted by the limited availability of kinetic information. Here, we introduce structural metabolic control as a framework to examine individual reactions' potential to control metabolic functions, such as biomass production, based on structural modeling. The capability to carry out a metabolic function is determined using flux balance analysis (FBA). We examine structural metabolic control on the example of the central carbon metabolism of Escherichia coli by the recently introduced framework of functional centrality (FC). This framework is based on the Shapley value from cooperative game theory and FBA, and we demonstrate its superior ability to assign “share of control” to individual reactions with respect to metabolic functions and environmental conditions. A comparative analysis of various scenarios illustrates the usefulness of FC and its relations to other structural approaches pertaining to metabolic control. We propose a Monte Carlo algorithm to estimate FCs for large networks, based on the enumeration of elementary flux modes. We further give detailed biological interpretation of FCs for production of lactate and ATP under various respiratory conditions. PMID:24367246

Exploring factors that influence the spread and sustainability of a dysphagia innovation: an instrumental case study.

PubMed

Ilott, Irene; Gerrish, Kate; Eltringham, Sabrina A; Taylor, Carolyn; Pownall, Sue

2016-08-18

Swallowing difficulties challenge patient safety due to the increased risk of malnutrition, dehydration and aspiration pneumonia. A theoretically driven study was undertaken to examine the spread and sustainability of a locally developed innovation that involved using the Inter-Professional Dysphagia Framework to structure education for the workforce. A conceptual framework with 3 spread strategies (hierarchical control, participatory adaptation and facilitated evolution) was blended with a processual approach to sustaining organisational change. The aim was to understand the processes, mechanism and outcomes associated with the spread and sustainability of this safety initiative. An instrumental case study, prospectively tracked a dysphagia innovation for 34 months (April 2011 to January 2014) in a large health care organisation in England. A train-the-trainer intervention (as participatory adaptation) was deployed on care pathways for stroke and fractured neck of femur. Data were collected at the organisational and clinical level through interviews (n = 30) and document review. The coding frame combined the processual approach with the spread mechanisms. Pre-determined outcomes included the number of staff trained about dysphagia and impact related to changes in practice. The features and processes associated with hierarchical control and participatory adaptation were identified. Leadership, critical junctures, temporality and making the innovation routine were aspects of hierarchical control. Participatory adaptation was evident on the care pathways through stakeholder responses, workload and resource pressures. Six of the 25 ward based trainers cascaded the dysphagia training. The expected outcomes were achieved when the top-down mandate (hierarchical control) was supplemented by local engagement and support (participatory adaptation). Frameworks for spread and sustainability were combined to create a 'small theory' that described the interventions, the processes and desired outcomes a priori. This novel methodological approach confirmed what is known about spread and sustainability, highlighted the particularity of change and offered new insights into the factors associated with hierarchical control and participatory adaptation. The findings illustrate the dualities of organisational change as universal and context specific; as particular and amendable to theoretical generalisation. Appreciating these dualities may contribute to understanding why many innovations fail to become routine.

XML in an Adaptive Framework for Instrument Control

NASA Technical Reports Server (NTRS)

Ames, Troy J.

2004-01-01

NASA Goddard Space Flight Center is developing an extensible framework for instrument command and control, known as Instrument Remote Control (IRC), that combines the platform independent processing capabilities of Java with the power of the Extensible Markup Language (XML). A key aspect of the architecture is software that is driven by an instrument description, written using the Instrument Markup Language (IML). IML is an XML dialect used to describe interfaces to control and monitor the instrument, command sets and command formats, data streams, communication mechanisms, and data processing algorithms.

Neural network robust tracking control with adaptive critic framework for uncertain nonlinear systems.

PubMed

Wang, Ding; Liu, Derong; Zhang, Yun; Li, Hongyi

2018-01-01

In this paper, we aim to tackle the neural robust tracking control problem for a class of nonlinear systems using the adaptive critic technique. The main contribution is that a neural-network-based robust tracking control scheme is established for nonlinear systems involving matched uncertainties. The augmented system considering the tracking error and the reference trajectory is formulated and then addressed under adaptive critic optimal control formulation, where the initial stabilizing controller is not needed. The approximate control law is derived via solving the Hamilton-Jacobi-Bellman equation related to the nominal augmented system, followed by closed-loop stability analysis. The robust tracking control performance is guaranteed theoretically via Lyapunov approach and also verified through simulation illustration. Copyright © 2017 Elsevier Ltd. All rights reserved.

The advantages and limitations of guideline adaptation frameworks.

PubMed

Wang, Zhicheng; Norris, Susan L; Bero, Lisa

2018-05-29

The implementation of evidence-based guidelines can improve clinical and public health outcomes by helping health professionals practice in the most effective manner, as well as assisting policy-makers in designing optimal programs. Adaptation of a guideline to suit the context in which it is intended to be applied can be a key step in the implementation process. Without taking the local context into account, certain interventions recommended in evidence-based guidelines may be infeasible under local conditions. Guideline adaptation frameworks provide a systematic way of approaching adaptation, and their use may increase transparency, methodological rigor, and the quality of the adapted guideline. This paper presents a number of adaptation frameworks that are currently available. We aim to compare the advantages and limitations of their processes, methods, and resource implications. These insights into adaptation frameworks can inform the future development of guidelines and systematic methods to optimize their adaptation. Recent adaptation frameworks show an evolution from adapting entire existing guidelines, to adapting specific recommendations extracted from an existing guideline, to constructing evidence tables for each recommendation that needs to be adapted. This is a move towards more recommendation-focused, context-specific processes and considerations. There are still many gaps in knowledge about guideline adaptation. Most of the frameworks reviewed lack any evaluation of the adaptation process and outcomes, including user satisfaction and resources expended. The validity, usability, and health impact of guidelines developed via an adaptation process have not been studied. Lastly, adaptation frameworks have not been evaluated for use in low-income countries. Despite the limitations in frameworks, a more systematic approach to adaptation based on a framework is valuable, as it helps to ensure that the recommendations stay true to the evidence while taking local needs into account. The utilization of frameworks in the guideline implementation process can be optimized by increasing the understanding and upfront estimation of resource and time needed, capacity building in adaptation methods, and increasing the adaptability of the source recommendation document.

An extensible and lightweight architecture for adaptive server applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gorton, Ian; Liu, Yan; Trivedi, Nihar

2008-07-10

Server applications augmented with behavioral adaptation logic can react to environmental changes, creating self-managing server applications with improved quality of service at runtime. However, developing adaptive server applications is challenging due to the complexity of the underlying server technologies and highly dynamic application environments. This paper presents an architecture framework, the Adaptive Server Framework (ASF), to facilitate the development of adaptive behavior for legacy server applications. ASF provides a clear separation between the implementation of adaptive behavior and the business logic of the server application. This means a server application can be extended with programmable adaptive features through the definitionmore » and implementation of control components defined in ASF. Furthermore, ASF is a lightweight architecture in that it incurs low CPU overhead and memory usage. We demonstrate the effectiveness of ASF through a case study, in which a server application dynamically determines the resolution and quality to scale an image based on the load of the server and network connection speed. The experimental evaluation demonstrates the erformance gains possible by adaptive behavior and the low overhead introduced by ASF.« less

Prediction and Control of Network Cascade: Example of Power Grid or Networking Adaptability from WMD Disruption and Cascading Failures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chertkov, Michael

2012-07-24

The goal of the DTRA project is to develop a mathematical framework that will provide the fundamental understanding of network survivability, algorithms for detecting/inferring pre-cursors of abnormal network behaviors, and methods for network adaptability and self-healing from cascading failures.

A Framework for the Development of Computerized Adaptive Tests

ERIC Educational Resources Information Center

Thompson, Nathan A.; Weiss, David J.

2011-01-01

A substantial amount of research has been conducted over the past 40 years on technical aspects of computerized adaptive testing (CAT), such as item selection algorithms, item exposure controls, and termination criteria. However, there is little literature providing practical guidance on the development of a CAT. This paper seeks to collate some…

An Approach for Autonomy: A Collaborative Communication Framework for Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Dufrene, Warren Russell, Jr.

2005-01-01

Research done during the last three years has studied the emersion properties of Complex Adaptive Systems (CAS). The deployment of Artificial Intelligence (AI) techniques applied to remote Unmanned Aerial Vehicles has led the author to investigate applications of CAS within the field of Autonomous Multi-Agent Systems. The core objective of current research efforts is focused on the simplicity of Intelligent Agents (IA) and the modeling of these agents within complex systems. This research effort looks at the communication, interaction, and adaptability of multi-agents as applied to complex systems control. The embodiment concept applied to robotics has application possibilities within multi-agent frameworks. A new framework for agent awareness within a virtual 3D world concept is possible where the vehicle is composed of collaborative agents. This approach has many possibilities for applications to complex systems. This paper describes the development of an approach to apply this virtual framework to the NASA Goddard Space Flight Center (GSFC) tetrahedron structure developed under the Autonomous Nano Technology Swarm (ANTS) program and the Super Miniaturized Addressable Reconfigurable Technology (SMART) architecture program. These projects represent an innovative set of novel concepts deploying adaptable, self-organizing structures composed of many tetrahedrons. This technology is pushing current applied Agents Concepts to new levels of requirements and adaptability.

Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.

PubMed

Aprasoff, Jonathan; Donchin, Opher

2012-04-01

Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.

Adaptive fixed-time trajectory tracking control of a stratospheric airship.

PubMed

Zheng, Zewei; Feroskhan, Mir; Sun, Liang

2018-05-01

This paper addresses the fixed-time trajectory tracking control problem of a stratospheric airship. By extending the method of adding a power integrator to a novel adaptive fixed-time control method, the convergence of a stratospheric airship to its reference trajectory is guaranteed to be achieved within a fixed time. The control algorithm is firstly formulated without the consideration of external disturbances to establish the stability of the closed-loop system in fixed-time and demonstrate that the convergence time of the airship is essentially independent of its initial conditions. Subsequently, a smooth adaptive law is incorporated into the proposed fixed-time control framework to provide the system with robustness to external disturbances. Theoretical analyses demonstrate that under the adaptive fixed-time controller, the tracking errors will converge towards a residual set in fixed-time. The results of a comparative simulation study with other recent methods illustrate the remarkable performance and superiority of the proposed control method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

PubMed Central

Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2014-01-01

Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

[Undue tobacco industry interference in tobacco control policies in Mexico].

PubMed

Madrazo-Lajous, Alejandro; Guerrero-Alcántara, Angela

2012-06-01

OBJECTIVO: To identify tobacco industry's strategies aimed at containing the full adoption of public health policies established by the Framework Convention on Tobacco Control. Tobacco industry interference in the design, adoption and implementation of tobacco control policies has intensified since the signing of the FCTC. However, it is back in 1997 when one can trace a shift in tobacco industry strategies, adapting to political change in Mexico. This adaptation has consisted mostly in identifying emerging veto points in the chain of public policy development. Tobacco industry's interfering strategies have successfully affected Mexican policies.

An Agent-Based Optimization Framework for Engineered Complex Adaptive Systems with Application to Demand Response in Electricity Markets

NASA Astrophysics Data System (ADS)

Haghnevis, Moeed

The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.

Adaptive Control Parameters for Dispersal of Multi-Agent Mobile Ad Hoc Network (MANET) Swarms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurt Derr; Milos Manic

A mobile ad hoc network is a collection of independent nodes that communicate wirelessly with one another. This paper investigates nodes that are swarm robots with communications and sensing capabilities. Each robot in the swarm may operate in a distributed and decentralized manner to achieve some goal. This paper presents a novel approach to dynamically adapting control parameters to achieve mesh configuration stability. The presented approach to robot interaction is based on spring force laws (attraction and repulsion laws) to create near-optimal mesh like configurations. In prior work, we presented the extended virtual spring mesh (EVSM) algorithm for the dispersionmore » of robot swarms. This paper extends the EVSM framework by providing the first known study on the effects of adaptive versus static control parameters on robot swarm stability. The EVSM algorithm provides the following novelties: 1) improved performance with adaptive control parameters and 2) accelerated convergence with high formation effectiveness. Simulation results show that 120 robots reach convergence using adaptive control parameters more than twice as fast as with static control parameters in a multiple obstacle environment.« less

Climate change adaptation frameworks: an evaluation of plans for coastal Suffolk, UK

NASA Astrophysics Data System (ADS)

Armstrong, J.; Wilby, R.; Nicholls, R. J.

2015-11-01

This paper asserts that three principal frameworks for climate change adaptation can be recognised in the literature: scenario-led (SL), vulnerability-led (VL) and decision-centric (DC) frameworks. A criterion is developed to differentiate these frameworks in recent adaptation projects. The criterion features six key hallmarks as follows: (1) use of climate model information; (2) analysis of metrics/units; (3) socio-economic knowledge; (4) stakeholder engagement; (5) adaptation of implementation mechanisms; (6) tier of adaptation implementation. The paper then tests the validity of this approach using adaptation projects on the Suffolk coast, UK. Fourteen adaptation plans were identified in an online survey. They were analysed in relation to the hallmarks outlined above and assigned to an adaptation framework. The results show that while some adaptation plans are primarily SL, VL or DC, the majority are hybrid, showing a mixture of DC/VL and DC/SL characteristics. Interestingly, the SL/VL combination is not observed, perhaps because the DC framework is intermediate and attempts to overcome weaknesses of both SL and VL approaches. The majority (57 %) of adaptation projects generated a risk assessment or advice notes. Further development of this type of framework analysis would allow better guidance on approaches for organisations when implementing climate change adaptation initiatives, and other similar proactive long-term planning.

Climate change adaptation frameworks: an evaluation of plans for coastal, Suffolk, UK

NASA Astrophysics Data System (ADS)

Armstrong, J.; Wilby, R.; Nicholls, R. J.

2015-06-01

This paper asserts that three principal frameworks for climate change adaptation can be recognised in the literature: Scenario-Led (SL), Vulnerability-Led (VL) and Decision-Centric (DC) frameworks. A criterion is developed to differentiate these frameworks in recent adaptation projects. The criterion features six key hallmarks as follows: (1) use of climate model information; (2) analysis metrics/units; (3) socio-economic knowledge; (4) stakeholder engagement; (5) adaptation implementation mechanisms; (6) tier of adaptation implementation. The paper then tests the validity of this approach using adaptation projects on the Suffolk coast, UK. Fourteen adaptation plans were identified in an online survey. They were analysed in relation to the hallmarks outlined above and assigned to an adaptation framework. The results show that while some adaptation plans are primarily SL, VL or DC, the majority are hybrid showing a mixture of DC/VL and DC/SL characteristics. Interestingly, the SL/VL combination is not observed, perhaps because the DC framework is intermediate and attempts to overcome weaknesses of both SL and VL approaches. The majority (57 %) of adaptation projects generated a risk assessment or advice notes. Further development of this type of framework analysis would allow better guidance on approaches for organisations when implementing climate change adaptation initiatives, and other similar proactive long-term planning.

A new class of energy based control laws for revolute robot arms - Tracking control, robustness enhancement and adaptive control

NASA Technical Reports Server (NTRS)

Wen, John T.; Kreutz, Kenneth; Bayard, David S.

1988-01-01

A class of joint-level control laws for all-revolute robot arms is introduced. The analysis is similar to the recently proposed energy Liapunov function approach except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. By using energy Liapunov functions with the modified potential energy, a much simpler analysis can be used to show closed-loop global asymptotic stability and local exponential stability. When Coulomb and viscous friction and model parameter errors are present, a sliding-mode-like modification of the control law is proposed to add a robustness-enhancing outer loop. Adaptive control is also addressed within the same framework. A linear-in-the-parameters formulation is adopted, and globally asymptotically stable adaptive control laws are derived by replacing the model parameters in the nonadaptive control laws by their estimates.

Event-triggered decentralized adaptive fault-tolerant control of uncertain interconnected nonlinear systems with actuator failures.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2018-06-01

This paper investigates the event-triggered decentralized adaptive tracking problem of a class of uncertain interconnected nonlinear systems with unexpected actuator failures. It is assumed that local control signals are transmitted to local actuators with time-varying faults whenever predefined conditions for triggering events are satisfied. Compared with the existing control-input-based event-triggering strategy for adaptive control of uncertain nonlinear systems, the aim of this paper is to propose a tracking-error-based event-triggering strategy in the decentralized adaptive fault-tolerant tracking framework. The proposed approach can relax drastic changes in control inputs caused by actuator faults in the existing triggering strategy. The stability of the proposed event-triggering control system is analyzed in the Lyapunov sense. Finally, simulation comparisons of the proposed and existing approaches are provided to show the effectiveness of the proposed theoretical result in the presence of actuator faults. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Verification and Tuning of an Adaptive Controller for an Unmanned Air Vehicle

NASA Technical Reports Server (NTRS)

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

2010-01-01

This paper focuses on the analysis and tuning of a controller based on the Adaptive Control Technology for Safe Flight (ACTS) architecture. The ACTS architecture consists of a nominal, non-adaptive controller that provides satisfactory performance under nominal flying conditions, and an adaptive controller that provides robustness under off-nominal ones. A framework unifying control verification and gain tuning is used to make the controller s ability to satisfy the closed-loop requirements more robust to uncertainty. In this paper we tune the gains of both controllers using this approach. Some advantages and drawbacks of adaptation are identified by performing a global robustness assessment of both the adaptive controller and its non-adaptive counterpart. The analyses used to determine these characteristics are based on evaluating the degradation in closed-loop performance resulting from uncertainties having increasing levels of severity. The specific adverse conditions considered can be grouped into three categories: aerodynamic uncertainties, structural damage, and actuator failures. These failures include partial and total loss of control effectiveness, locked-in-place control surface deflections, and engine out conditions. The requirements considered are the peak structural loading, the ability of the controller to track pilot commands, the ability of the controller to keep the aircraft s state within the reliable flight envelope, and the handling/riding qualities of the aircraft. The nominal controller resulting from these tuning strategies was successfully validated using the NASA GTM Flight Test Vehicle.

Runtime Assurance Framework Development for Highly Adaptive Flight Control Systems

DTIC Science & Technology

2015-12-01

performing a surveillance mission. The demonstration platform consisted of RTA systems for the inner- loop control, outer- loop guidance, ownship flight...For the inner- loop , the concept of employing multiple transition controllers in the reversionary control system was studied. For all feedback levels...5 RTA Protection Applied to Inner- Loop Control Systems .................................................61 5.1 General Description of Morphing Wing

Adaptive Behavior for Mobile Robots

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance

2009-01-01

The term "System for Mobility and Access to Rough Terrain" (SMART) denotes a theoretical framework, a control architecture, and an algorithm that implements the framework and architecture, for enabling a land-mobile robot to adapt to changing conditions. SMART is intended to enable the robot to recognize adverse terrain conditions beyond its optimal operational envelope, and, in response, to intelligently reconfigure itself (e.g., adjust suspension heights or baseline distances between suspension points) or adapt its driving techniques (e.g., engage in a crabbing motion as a switchback technique for ascending steep terrain). Conceived for original application aboard Mars rovers and similar autonomous or semi-autonomous mobile robots used in exploration of remote planets, SMART could also be applied to autonomous terrestrial vehicles to be used for search, rescue, and/or exploration on rough terrain.

Discrete-time entropy formulation of optimal and adaptive control problems

NASA Technical Reports Server (NTRS)

Tsai, Yweting A.; Casiello, Francisco A.; Loparo, Kenneth A.

1992-01-01

The discrete-time version of the entropy formulation of optimal control of problems developed by G. N. Saridis (1988) is discussed. Given a dynamical system, the uncertainty in the selection of the control is characterized by the probability distribution (density) function which maximizes the total entropy. The equivalence between the optimal control problem and the optimal entropy problem is established, and the total entropy is decomposed into a term associated with the certainty equivalent control law, the entropy of estimation, and the so-called equivocation of the active transmission of information from the controller to the estimator. This provides a useful framework for studying the certainty equivalent and adaptive control laws.

Adaptive Fuzzy Output Constrained Control Design for Multi-Input Multioutput Stochastic Nonstrict-Feedback Nonlinear Systems.

PubMed

Li, Yongming; Tong, Shaocheng

2017-12-01

In this paper, an adaptive fuzzy output constrained control design approach is addressed for multi-input multioutput uncertain stochastic nonlinear systems in nonstrict-feedback form. The nonlinear systems addressed in this paper possess unstructured uncertainties, unknown gain functions and unknown stochastic disturbances. Fuzzy logic systems are utilized to tackle the problem of unknown nonlinear uncertainties. The barrier Lyapunov function technique is employed to solve the output constrained problem. In the framework of backstepping design, an adaptive fuzzy control design scheme is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.

Adaptive management for ecosystem services (j/a) | Science ...

EPA Pesticide Factsheets

Management of natural resources for the production of ecosystem services, which are vital for human well-being, is necessary even when there is uncertainty regarding system response to management action. This uncertainty is the result of incomplete controllability, complex internal feedbacks, and non-linearity that often interferes with desired management outcomes, and insufficient understanding of nature and people. Adaptive management was developed to reduce such uncertainty. We present a framework for the application of adaptive management for ecosystem services that explicitly accounts for cross-scale tradeoffs in the production of ecosystem services. Our framework focuses on identifying key spatiotemporal scales (plot, patch, ecosystem, landscape, and region) that encompass dominant structures and processes in the system, and includes within- and cross-scale dynamics, ecosystem service tradeoffs, and management controllability within and across scales. Resilience theory recognizes that a limited set of ecological processes in a given system regulate ecosystem services, yet our understanding of these processes is poorly understood. If management actions erode or remove these processes, the system may shift into an alternative state unlikely to support the production of desired services. Adaptive management provides a process to assess the underlying within and cross-scale tradeoffs associated with production of ecosystem services while proceeding with manage

Method and apparatus for automatic control of a humanoid robot

NASA Technical Reports Server (NTRS)

Abdallah, Muhammad E (Inventor); Platt, Robert (Inventor); Wampler, II, Charles W. (Inventor); Sanders, Adam M (Inventor); Reiland, Matthew J (Inventor)

2013-01-01

A robotic system includes a humanoid robot having a plurality of joints adapted for force control with respect to an object acted upon by the robot, a graphical user interface (GUI) for receiving an input signal from a user, and a controller. The GUI provides the user with intuitive programming access to the controller. The controller controls the joints using an impedance-based control framework, which provides object level, end-effector level, and/or joint space-level control of the robot in response to the input signal. A method for controlling the robotic system includes receiving the input signal via the GUI, e.g., a desired force, and then processing the input signal using a host machine to control the joints via an impedance-based control framework. The framework provides object level, end-effector level, and/or joint space-level control of the robot, and allows for functional-based GUI to simplify implementation of a myriad of operating modes.

Adaptive Leadership Framework for Chronic Illness

PubMed Central

Anderson, Ruth A.; Bailey, Donald E.; Wu, Bei; Corazzini, Kirsten; McConnell, Eleanor S.; Thygeson, N. Marcus; Docherty, Sharron L.

2015-01-01

We propose the Adaptive Leadership Framework for Chronic Illness as a novel framework for conceptualizing, studying, and providing care. This framework is an application of the Adaptive Leadership Framework developed by Heifetz and colleagues for business. Our framework views health care as a complex adaptive system and addresses the intersection at which people with chronic illness interface with the care system. We shift focus from symptoms to symptoms and the challenges they pose for patients/families. We describe how providers and patients/families might collaborate to create shared meaning of symptoms and challenges to coproduce appropriate approaches to care. PMID:25647829

Modeling, Control, and Estimation of Flexible, Aerodynamic Structures

NASA Astrophysics Data System (ADS)

Ray, Cody W.

Engineers have long been inspired by nature’s flyers. Such animals navigate complex environments gracefully and efficiently by using a variety of evolutionary adaptations for high-performance flight. Biologists have discovered a variety of sensory adaptations that provide flow state feedback and allow flying animals to feel their way through flight. A specialized skeletal wing structure and plethora of robust, adaptable sensory systems together allow nature’s flyers to adapt to myriad flight conditions and regimes. In this work, motivated by biology and the successes of bio-inspired, engineered aerial vehicles, linear quadratic control of a flexible, morphing wing design is investigated, helping to pave the way for truly autonomous, mission-adaptive craft. The proposed control algorithm is demonstrated to morph a wing into desired positions. Furthermore, motivated specifically by the sensory adaptations organisms possess, this work transitions to an investigation of aircraft wing load identification using structural response as measured by distributed sensors. A novel, recursive estimation algorithm is utilized to recursively solve the inverse problem of load identification, providing both wing structural and aerodynamic states for use in a feedback control, mission-adaptive framework. The recursive load identification algorithm is demonstrated to provide accurate load estimate in both simulation and experiment.

Towards Validation of an Adaptive Flight Control Simulation Using Statistical Emulation

NASA Technical Reports Server (NTRS)

He, Yuning; Lee, Herbert K. H.; Davies, Misty D.

2012-01-01

Traditional validation of flight control systems is based primarily upon empirical testing. Empirical testing is sufficient for simple systems in which a.) the behavior is approximately linear and b.) humans are in-the-loop and responsible for off-nominal flight regimes. A different possible concept of operation is to use adaptive flight control systems with online learning neural networks (OLNNs) in combination with a human pilot for off-nominal flight behavior (such as when a plane has been damaged). Validating these systems is difficult because the controller is changing during the flight in a nonlinear way, and because the pilot and the control system have the potential to co-adapt in adverse ways traditional empirical methods are unlikely to provide any guarantees in this case. Additionally, the time it takes to find unsafe regions within the flight envelope using empirical testing means that the time between adaptive controller design iterations is large. This paper describes a new concept for validating adaptive control systems using methods based on Bayesian statistics. This validation framework allows the analyst to build nonlinear models with modal behavior, and to have an uncertainty estimate for the difference between the behaviors of the model and system under test.

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

PubMed

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.

Building capacity for implementation of the framework convention for tobacco control in Vietnam: lessons for developing countries

PubMed Central

Stillman, Frances A.; David, Annette M.; Kibria, Naseeb; Phan, Hai Thi

2014-01-01

Effective implementation of the WHO international Framework Convention on Tobacco Control (FCTC) is the key to controlling the tobacco epidemic. Within countries, strong national tobacco control capacity is the primary determinant for successful implementation of the FCTC. This case study of tobacco control policy describes the experience of building national tobacco control capacity in Vietnam under the Reduce Smoking in Vietnam Partnership project within a national capacity-building framework. In the Vietnam experience, four components of tobacco control capacity emerged as especially important to achieve ‘quality’ outputs and measurable outcomes at the implementation level: (i) organizational structure/infrastructure; (ii) leadership and expertise; (iii) partnerships and networks and (iv) data and evidence from research. The experience gained in this project helps in adapting our tobacco control capacity-building model, and the lessons that emerged from this country case study can provide guidance to global funders, tobacco control technical assistance providers and nations as governments endeavor to meet their commitment to the FCTC. PMID:23411160

Adaptive leadership framework for chronic illness: framing a research agenda for transforming care delivery.

PubMed

Anderson, Ruth A; Bailey, Donald E; Wu, Bei; Corazzini, Kirsten; McConnell, Eleanor S; Thygeson, N Marcus; Docherty, Sharron L

2015-01-01

We propose the Adaptive Leadership Framework for Chronic Illness as a novel framework for conceptualizing, studying, and providing care. This framework is an application of the Adaptive Leadership Framework developed by Heifetz and colleagues for business. Our framework views health care as a complex adaptive system and addresses the intersection at which people with chronic illness interface with the care system. We shift focus from symptoms to symptoms and the challenges they pose for patients/families. We describe how providers and patients/families might collaborate to create shared meaning of symptoms and challenges to coproduce appropriate approaches to care.

Adaptation of a U.S. evidence-based Positive Prevention intervention for youth living with HIV/AIDS in Kinshasa, Democratic Republic of the Congo

PubMed Central

Parker, L.; Maman, S.; Pettifor, A.; Chalachala, J.L.; Edmonds, A.; Golin, C.E.; Moracco, K.; Behets, F.

2013-01-01

Effective HIV prevention programs for people living with HIV/AIDS (PLWH) are important to reduce new infections and to ensure PLWH remain healthy. This paper describes the systematic adaptation of a U.S.-developed Evidence Based Intervention (EBI) using the Centers for Disease Control and Prevention (CDC) Map of Adaption Process for use at a Pediatric Hospital in Kinshasa, Democratic Republic of the Congo (DRC). The adapted intervention, Supporting Youth and Motivating Positive Action or SYMPA, a six-session risk reduction intervention targeted for youth living with HIV/AIDS (YLWH) in Kinshasa was adapted from the Healthy Living Project and guided by the Social Action Theory. This paper describes the process of implementing the first four steps of the ADAPT framework (Assess, Select, Prepare, and Pilot). Our study has shown that an EBI developed and implemented in the U.S. can be adapted successfully for a different target population in a low-resource context through an iterative process following the CDC ADAPT framework. This process included reviewing existing literature, adapting and adding components, and focusing on increasing staff capacity. This paper provides a rare, detailed description of the adaptation process and may aid organizations seeking to adapt and implement HIV prevention EBIs in sub-Saharan Africa and beyond. PMID:23063699

Instrument Remote Control Application Framework

NASA Technical Reports Server (NTRS)

Ames, Troy; Hostetter, Carl F.

2006-01-01

The Instrument Remote Control (IRC) architecture is a flexible, platform-independent application framework that is well suited for the control and monitoring of remote devices and sensors. IRC enables significant savings in development costs by utilizing extensible Markup Language (XML) descriptions to configure the framework for a specific application. The Instrument Markup Language (IML) is used to describe the commands used by an instrument, the data streams produced, the rules for formatting commands and parsing the data, and the method of communication. Often no custom code is needed to communicate with a new instrument or device. An IRC instance can advertise and publish a description about a device or subscribe to another device's description on a network. This simple capability of dynamically publishing and subscribing to interfaces enables a very flexible, self-adapting architecture for monitoring and control of complex instruments in diverse environments.

Deprived, but not depraved: Prosocial behavior is an adaptive response to lower socioeconomic status.

PubMed

Robinson, Angela R; Piff, Paul K

2017-01-01

Individuals of lower socioeconomic status (SES) display increased attentiveness to others and greater prosocial behavior compared to individuals of higher SES. We situate these effects within Pepper & Nettle's contextually appropriate response framework of SES. We argue that increased prosocial behavior is a contextually adaptive response for lower-SES individuals that serves to increase control over their more threatening social environments.

A dynamical framework for integrated corridor management.

DOT National Transportation Integrated Search

2016-01-11

We develop analysis and control synthesis tools for dynamic traffic flow over networks. Our analysis : relies on exploiting monotonicity properties of the dynamics, and on adapting relevant tools from : stochastic queuing networks. We develop proport...

Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems

PubMed Central

Xia, Feng; Ma, Longhua; Peng, Chen; Sun, Youxian; Dong, Jinxiang

2008-01-01

There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS) scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting cross-layer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An event-driven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN. PMID:27879934

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

PubMed Central

Liu, Jian; Liu, Kexin; Liu, Shutang

2017-01-01

In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results. PMID:28467431

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

PubMed

Liu, Jian; Liu, Kexin; Liu, Shutang

2017-01-01

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

Complex adaptive chronic care.

PubMed

Martin, Carmel; Sturmberg, Joachim

2009-06-01

The Chronic Care Model (CCM) is widely taken up as the universal operational framework for redesigning health systems to address the increasing chronic disease burden of an ageing population. Chronic care encompasses health promotion, prevention, self management, disease control, treatment and palliation to address 'chronicity' of long journeys through disease, illness and care in the varying contexts of complex health systems. Yet at an operational level, CCM activities are predominantly based on an evidence-base of discreet chronic disease interventions in specific settings; and their demonstrable impact is limited to processes of select disease management such as diabetes in specific disease management programs. This paper proposes a framework that makes sense of the nature of chronicity and its multiple dimensions beyond disease and argues for a set of building blocks and leverage points that should constitute the starting points for 'redesign'? Complex Adaptive Chronic Care is proposed as an idea for an explanatory and implementation framework for addressing chronicity in existing and future chronic care models. Chronicity is overtly conceptualized to encompass the phenomena of an individual journey, with simple and complicated, complex and chaotic phases, through long term asymptomatic disease to bodily dysfunction and illness, located in family and communities. Chronicity encompasses trajectories of self-care and health care, as health, illness and disease co-exist and co-evolve in the setting of primary care, local care networks and at times institutions. A systems approach to individuals in their multi-layered networks making sense of and optimizing experiences of their chronic illness would build on core values and agency around a local vision of health, empowerment of individuals and adaptive leadership, and it responds in line with the local values inherent in the community's disease-based knowledge and the local service's history and dynamics. Complex Adaptive Chronic Care exceeds the current notions of disease management as an endpoint. Primary care team members are system adaptors in partnership with individuals constructing their care and system leadership in response to chronic illness, and enable healthy resilience as well as personal healing and support. Outcomes of complex adaptive chronic care are the emergence of health in individuals and communities through adaptability, self-organization and empowerment. Chronic care reform from within a complex adaptive system framework is bottom up and emergent and stands in stark contrast to (but has to co-exist with) the prevailing protocol based disease care rewarding selective surrogate indicators of disease control. Frameworks such as the Chronic Care Model provide guidance, but do not replace individual experience, local adaptive leadership and responsiveness. The awareness of complexity means opening up problems to a different reality demanding different set of questions and approaches to answer them.

The insula: a critical neural substrate for craving and drug seeking under conflict and risk

PubMed Central

Naqvi, Nasir H.; Gaznick, Natassia; Tranel, Daniel; Bechara, Antoine

2014-01-01

Drug addiction is characterized by the inability to control drug use when it results in negative consequences or conflicts with more adaptive goals. Our previous work showed that damage to the insula disrupted addiction to cigarette smoking—the first time that the insula was shown to be a critical neural substrate for addiction. Here, we review those findings, as well as more recent studies that corroborate and extend them, demonstrating the role of the insula in (1) incentive motivational processes that drive addictive behavior, (2) control processes that moderate or inhibit addictive behavior, and (3) interoceptive processes that represent bodily states associated with drug use. We then describe a theoretical framework that attempts to integrate these seemingly disparate findings. In this framework, the insula functions in the recall of interoceptive drug effects during craving and drug seeking under specific conditions where drug taking is perceived as risky and/or where there is conflict between drug taking and more adaptive goals. We describe this framework in an evolutionary context and discuss its implications for understanding the mechanisms of behavior change in addiction treatments. PMID:24690001

Generating Adaptive Behaviour within a Memory-Prediction Framework

PubMed Central

Rawlinson, David; Kowadlo, Gideon

2012-01-01

The Memory-Prediction Framework (MPF) and its Hierarchical-Temporal Memory implementation (HTM) have been widely applied to unsupervised learning problems, for both classification and prediction. To date, there has been no attempt to incorporate MPF/HTM in reinforcement learning or other adaptive systems; that is, to use knowledge embodied within the hierarchy to control a system, or to generate behaviour for an agent. This problem is interesting because the human neocortex is believed to play a vital role in the generation of behaviour, and the MPF is a model of the human neocortex. We propose some simple and biologically-plausible enhancements to the Memory-Prediction Framework. These cause it to explore and interact with an external world, while trying to maximize a continuous, time-varying reward function. All behaviour is generated and controlled within the MPF hierarchy. The hierarchy develops from a random initial configuration by interaction with the world and reinforcement learning only. Among other demonstrations, we show that a 2-node hierarchy can learn to successfully play “rocks, paper, scissors” against a predictable opponent. PMID:22272231

Automatic Training of Rat Cyborgs for Navigation.

PubMed

Yu, Yipeng; Wu, Zhaohui; Xu, Kedi; Gong, Yongyue; Zheng, Nenggan; Zheng, Xiaoxiang; Pan, Gang

2016-01-01

A rat cyborg system refers to a biological rat implanted with microelectrodes in its brain, via which the outer electrical stimuli can be delivered into the brain in vivo to control its behaviors. Rat cyborgs have various applications in emergency, such as search and rescue in disasters. Prior to a rat cyborg becoming controllable, a lot of effort is required to train it to adapt to the electrical stimuli. In this paper, we build a vision-based automatic training system for rat cyborgs to replace the time-consuming manual training procedure. A hierarchical framework is proposed to facilitate the colearning between rats and machines. In the framework, the behavioral states of a rat cyborg are visually sensed by a camera, a parameterized state machine is employed to model the training action transitions triggered by rat's behavioral states, and an adaptive adjustment policy is developed to adaptively adjust the stimulation intensity. The experimental results of three rat cyborgs prove the effectiveness of our system. To the best of our knowledge, this study is the first to tackle automatic training of animal cyborgs.

Automatic Training of Rat Cyborgs for Navigation

PubMed Central

Yu, Yipeng; Wu, Zhaohui; Xu, Kedi; Gong, Yongyue; Zheng, Nenggan; Zheng, Xiaoxiang; Pan, Gang

2016-01-01

A rat cyborg system refers to a biological rat implanted with microelectrodes in its brain, via which the outer electrical stimuli can be delivered into the brain in vivo to control its behaviors. Rat cyborgs have various applications in emergency, such as search and rescue in disasters. Prior to a rat cyborg becoming controllable, a lot of effort is required to train it to adapt to the electrical stimuli. In this paper, we build a vision-based automatic training system for rat cyborgs to replace the time-consuming manual training procedure. A hierarchical framework is proposed to facilitate the colearning between rats and machines. In the framework, the behavioral states of a rat cyborg are visually sensed by a camera, a parameterized state machine is employed to model the training action transitions triggered by rat's behavioral states, and an adaptive adjustment policy is developed to adaptively adjust the stimulation intensity. The experimental results of three rat cyborgs prove the effectiveness of our system. To the best of our knowledge, this study is the first to tackle automatic training of animal cyborgs. PMID:27436999

Adaptive Failure Compensation for Aircraft Flight Control Using Engine Differentials: Regulation

NASA Technical Reports Server (NTRS)

Yu, Liu; Xidong, Tang; Gang, Tao; Joshi, Suresh M.

2005-01-01

The problem of using engine thrust differentials to compensate for rudder and aileron failures in aircraft flight control is addressed in this paper in a new framework. A nonlinear aircraft model that incorporates engine di erentials in the dynamic equations is employed and linearized to describe the aircraft s longitudinal and lateral motion. In this model two engine thrusts of an aircraft can be adjusted independently so as to provide the control flexibility for rudder or aileron failure compensation. A direct adaptive compensation scheme for asymptotic regulation is developed to handle uncertain actuator failures in the linearized system. A design condition is specified to characterize the system redundancy needed for failure compensation. The adaptive regulation control scheme is applied to the linearized model of a large transport aircraft in which the longitudinal and lateral motions are coupled as the result of using engine thrust differentials. Simulation results are presented to demonstrate the effectiveness of the adaptive compensation scheme.

Macroscopic description of complex adaptive networks coevolving with dynamic node states

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Naval Open Architecture Machinery Control Systems for Next Generation Integrated Power Systems

DTIC Science & Technology

2012-05-01

PORTABLE) OS / RTOS ADAPTATION MIDDLEWARE (FOR OS PORTABILITY) MACHINERY CONTROLLER FRAMEWORK MACHINERY CONTROL SYSTEM SERVICES POWER CONTROL SYSTEM...SERVICES SHIP SYSTEM SERVICES TTY 0 TTY N … OPERATING SYSTEM ( OS / RTOS ) COMPUTER HARDWARE UDP IP TCP RAW DEV 0 DEV N … POWER MANAGEMENT CONTROLLER...operating systems (DOS, Windows, Linux, OS /2, QNX, SCO Unix ...) COMPUTERS: ISA compatible motherboards, workstations and portables (Compaq, Dell

Rapid adaptation of invertebrate pests to climatic stress?

PubMed

Hoffmann, Ary A

2017-06-01

There is surprisingly little information on adaptive responses of pests and disease vectors to climatic stresses even though the short generation times and large population sizes associated with pests make rapid adaptation likely. Most evidence of adaptive differentiation has been obtained from geographic comparisons and these can directly or indirectly indicate rates of adaptation where historical data on invasions are available. There is very little information on adaptive shifts in pests detected through molecular comparisons even though the genomes of many pests are now available and can help to identify markers underlying adaptation. While the limited evidence available points to frequent rapid adaptation that can affect pest and disease vector control, constraints to adaptation are also evident and a predictive framework around the likelihood and limits of rapid adaptation is required. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

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

2018-01-21

A major challenge in community ecology is to understand how species respond to environmental changes. Previous studies have shown that the reorganization of interactions among co-occurring species can modulate their chances to adapt to novel environmental conditions. Moreover, empirical evidence has shown that these ecological dynamics typically facilitate the persistence of groups of species rather than entire communities. However, so far, we have no systematic methodology to identify those groups of species with the highest or lowest chances to adapt to new environments through a reorganization of their interactions. Yet, this could prove extremely valuable for developing new conservation strategies. Here, we introduce a theoretical framework to estimate the effect of the reorganization of interactions on the adaptability of a group of species, within a community, to novel environmental conditions. We introduce the concept of the adaptation space of a group of species based on a feasibility analysis of a population dynamics model. We define the adaptation space of a group as the set of environmental conditions that can be made compatible with its persistence thorough the reorganization of interactions among species within the group. The larger the adaptation space of a group, the larger its likelihood to adapt to a novel environment. We show that the interactions in the community outside a group can act as structural constraints and be used to quantitatively compare the size of the adaptation space among different groups of species within a community. To test our theoretical framework, we perform a data analysis on several pairs of natural and artificially perturbed ecological communities. Overall, we find that the groups of species present in both control and perturbed communities are among the ones with the largest adaptation space. We believe that the results derived from our framework point out towards new directions to understand and estimate the adaptability of species to changing environments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Designing for adaptation to novelty and change: functional information, emergent feature graphics, and higher-level control.

PubMed

Hajdukiewicz, John R; Vicente, Kim J

2002-01-01

Ecological interface design (EID) is a theoretical framework that aims to support worker adaptation to change and novelty in complex systems. Previous evaluations of EID have emphasized representativeness to enhance generalizability of results to operational settings. The research presented here is complementary, emphasizing experimental control to enhance theory building. Two experiments were conducted to test the impact of functional information and emergent feature graphics on adaptation to novelty and change in a thermal-hydraulic process control microworld. Presenting functional information in an interface using emergent features encouraged experienced participants to become perceptually coupled to the interface and thereby to exhibit higher-level control and more successful adaptation to unanticipated events. The absence of functional information or of emergent features generally led to lower-level control and less success at adaptation, the exception being a minority of participants who compensated by relying on analytical reasoning. These findings may have practical implications for shaping coordination in complex systems and fundamental implications for the development of a general unified theory of coordination for the technical, human, and social sciences. Actual or potential applications of this research include the design of human-computer interfaces that improve safety in complex sociotechnical systems.

Adaptive management for ecosystem services.

PubMed

Birgé, Hannah E; Allen, Craig R; Garmestani, Ahjond S; Pope, Kevin L

2016-12-01

Management of natural resources for the production of ecosystem services, which are vital for human well-being, is necessary even when there is uncertainty regarding system response to management action. This uncertainty is the result of incomplete controllability, complex internal feedbacks, and non-linearity that often interferes with desired management outcomes, and insufficient understanding of nature and people. Adaptive management was developed to reduce such uncertainty. We present a framework for the application of adaptive management for ecosystem services that explicitly accounts for cross-scale tradeoffs in the production of ecosystem services. Our framework focuses on identifying key spatiotemporal scales (plot, patch, ecosystem, landscape, and region) that encompass dominant structures and processes in the system, and includes within- and cross-scale dynamics, ecosystem service tradeoffs, and management controllability within and across scales. Resilience theory recognizes that a limited set of ecological processes in a given system regulate ecosystem services, yet our understanding of these processes is poorly understood. If management actions erode or remove these processes, the system may shift into an alternative state unlikely to support the production of desired services. Adaptive management provides a process to assess the underlying within and cross-scale tradeoffs associated with production of ecosystem services while proceeding with management designed to meet the demands of a growing human population. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Establishment of policy indicators of adaptation to the impact of climate change on the transmission of schistosomiasis and malaria in China].

PubMed

Qian, Ying-Jun; Li, Shi-Zhu; Xu, Jun-Fang; Zhang, Li; Fu, Qing; Zhou, Xiao-Nong

2013-12-01

To set up a framework of indicators for schistosomiasis and malaria to guide the formulation and evaluation of vector-borne disease control policies focusing on adaptation to the negative impact of climate change. A 2-level indicator framework was set up on the basis of literature review, and Delphi method was applied to a total of 22 and 19 experts working on schistosomiasis and malaria, respectively. The result was analyzed to calculate the weight of various indicators. A total of 41 questionnaires was delivered, and 38 with valid response (92.7%). The system included 4 indicators at first level, i.e. surveillance, scientific research, disease control and intervention, and adaptation capacity building, with 25 indicators for schistosomiasis and 21 for malaria at the second level. Among indicators at the first level, disease surveillance ranked first with a weight of 0.32. Among the indicators at the second level, vector monitoring scored the highest in terms of both schistosomiasis and malaria. The indicators set up by Delphi method are practical,universal and effective ones using in the field, which is also useful to technically support the establishment of adaptation to climate change in the field of public health.

Bayesian selective response-adaptive design using the historical control.

PubMed

Kim, Mi-Ok; Harun, Nusrat; Liu, Chunyan; Khoury, Jane C; Broderick, Joseph P

2018-06-13

High quality historical control data, if incorporated, may reduce sample size, trial cost, and duration. A too optimistic use of the data, however, may result in bias under prior-data conflict. Motivated by well-publicized two-arm comparative trials in stroke, we propose a Bayesian design that both adaptively incorporates historical control data and selectively adapt the treatment allocation ratios within an ongoing trial responsively to the relative treatment effects. The proposed design differs from existing designs that borrow from historical controls. As opposed to reducing the number of subjects assigned to the control arm blindly, this design does so adaptively to the relative treatment effects only if evaluation of cumulated current trial data combined with the historical control suggests the superiority of the intervention arm. We used the effective historical sample size approach to quantify borrowed information on the control arm and modified the treatment allocation rules of the doubly adaptive biased coin design to incorporate the quantity. The modified allocation rules were then implemented under the Bayesian framework with commensurate priors addressing prior-data conflict. Trials were also more frequently concluded earlier in line with the underlying truth, reducing trial cost, and duration and yielded parameter estimates with smaller standard errors. © 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons, Ltd.

Reliable Adaptive Video Streaming Driven by Perceptual Semantics for Situational Awareness

PubMed Central

Pimentel-Niño, M. A.; Saxena, Paresh; Vazquez-Castro, M. A.

2015-01-01

A novel cross-layer optimized video adaptation driven by perceptual semantics is presented. The design target is streamed live video to enhance situational awareness in challenging communications conditions. Conventional solutions for recreational applications are inadequate and novel quality of experience (QoE) framework is proposed which allows fully controlled adaptation and enables perceptual semantic feedback. The framework relies on temporal/spatial abstraction for video applications serving beyond recreational purposes. An underlying cross-layer optimization technique takes into account feedback on network congestion (time) and erasures (space) to best distribute available (scarce) bandwidth. Systematic random linear network coding (SRNC) adds reliability while preserving perceptual semantics. Objective metrics of the perceptual features in QoE show homogeneous high performance when using the proposed scheme. Finally, the proposed scheme is in line with content-aware trends, by complying with information-centric-networking philosophy and architecture. PMID:26247057

Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

NASA Astrophysics Data System (ADS)

Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Bao, Jie; Swiler, Laura

2017-12-01

In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic Amplitude Versus Angle and Controlled-Source Electromagnetic data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis and Adaptive Metropolis samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and Controlled-Source Electromagnetic data. The multi-chain Markov-chain Monte Carlo is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic Amplitude Versus Angle and Controlled-Source Electromagnetic joint inversion provides better estimation of reservoir saturations than the seismic Amplitude Versus Angle only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated - reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.

Distributed Adaptive Fuzzy Control for Nonlinear Multiagent Systems Via Sliding Mode Observers.

PubMed

Shen, Qikun; Shi, Peng; Shi, Yan

2016-12-01

In this paper, the problem of distributed adaptive fuzzy control is investigated for high-order uncertain nonlinear multiagent systems on directed graph with a fixed topology. It is assumed that only the outputs of each follower and its neighbors are available in the design of its distributed controllers. Equivalent output injection sliding mode observers are proposed for each follower to estimate the states of itself and its neighbors, and an observer-based distributed adaptive controller is designed for each follower to guarantee that it asymptotically synchronizes to a leader with tracking errors being semi-globally uniform ultimate bounded, in which fuzzy logic systems are utilized to approximate unknown functions. Based on algebraic graph theory and Lyapunov function approach, using Filippov-framework, the closed-loop system stability analysis is conducted. Finally, numerical simulations are provided to illustrate the effectiveness and potential of the developed design techniques.

The conceptual framework and assessment methodology for the systematic reviews of community-based interventions for the prevention and control of infectious diseases of poverty.

PubMed

Lassi, Zohra S; Salam, Rehana A; Das, Jai K; Bhutta, Zulfiqar A

2014-01-01

This paper describes the conceptual framework and the methodology used to guide the systematic reviews of community-based interventions (CBIs) for the prevention and control of infectious diseases of poverty (IDoP). We adapted the conceptual framework from the 3ie work on the 'Community-Based Intervention Packages for Preventing Maternal Morbidity and Mortality and Improving Neonatal Outcomes' to aid in the analyzing of the existing CBIs for IDoP. The conceptual framework revolves around objectives, inputs, processes, outputs, outcomes, and impacts showing the theoretical linkages between the delivery of the interventions targeting these diseases through various community delivery platforms and the consequent health impacts. We also describe the methodology undertaken to conduct the systematic reviews and the meta-analyses.

A Systems Approach to Manage Drinking Water Quality ...

EPA Pesticide Factsheets

Drinking water supplies can be vulnerable to impacts from short-term weather events, long-term changes in land-use and climate, and water quality controls in treatment and distribution. Disinfection by-product (DBP) formation in drinking water is a prominent example to illustrate the water supply vulnerability and examine technological options in adaptation. Total organic carbon (TOC) in surface water can vary significantly due to changes or a combination of changes in watershed land use, climate variability, and extreme meteorological events (e.g., hurricanes). On the other hand, water demand is known to vary temporarily and spatially leading to changes in water ages and hence DBP formation potential. Typically a drinking water facility is designed to operate within a projected range of influent water quality and water demand. When the variations exceed the design range, water supply becomes vulnerable in the compliance to Safe Drinking Water Act (SDWA) Stage-II disinfection by-product (DBP) rules. This paper describes a framework of systems-level modeling, monitoring and control in adaptive planning and system operation. The framework, built upon the integration of model projections, adaptive monitoring and systems control, has three primary functions. Its advantages and limitations will be discussed with the application examples in Cincinnati (Ohio, USA) and Las Vegas (Nevada, USA). At a conceptual level, an integrated land use and hydrological model

Compendium of Abstracts. Volume 2

DTIC Science & Technology

2011-08-01

Framework with Memristors for use in Biomimetic Locomotion Control Systems Albert, Stephen In the future of reconnaissance and combat, small unmanned...standards according to ASTM D1002-2006 and formulation of silane blends to control bonding strength. Once a statistical set of coupons is completed...architectures, Adaptive Control of Thought-Rational – Queueing Networks (ACTR-QN) and Soar. I then identified the aspects of each that can be used to

A methodological survey identified eight proposed frameworks for the adaptation of health related guidelines.

PubMed

Darzi, Andrea; Abou-Jaoude, Elias A; Agarwal, Arnav; Lakis, Chantal; Wiercioch, Wojtek; Santesso, Nancy; Brax, Hneine; El-Jardali, Fadi; Schünemann, Holger J; Akl, Elie A

2017-06-01

Our objective was to identify and describe published frameworks for adaptation of clinical, public health, and health services guidelines. We included reports describing methods of adaptation of guidelines in sufficient detail to allow its reproducibility. We searched Medline and EMBASE databases. We also searched personal files, as well manuals and handbooks of organizations and professional societies that proposed methods of adaptation and adoption of guidelines. We followed standard systematic review methodology. Our search captured 12,021 citations, out of which we identified eight proposed methods of guidelines adaptation: ADAPTE, Adapted ADAPTE, Alberta Ambassador Program adaptation phase, GRADE-ADOLOPMENT, MAGIC, RAPADAPTE, Royal College of Nursing (RCN), and Systematic Guideline Review (SGR). The ADAPTE framework consists of a 24-step process to adapt guidelines to a local context taking into consideration the needs, priorities, legislation, policies, and resources. The Alexandria Center for Evidence-Based Clinical Practice Guidelines updated one of ADAPTE's tools, modified three tools, and added three new ones. In addition, they proposed optionally using three other tools. The Alberta Ambassador Program adaptation phase consists of 11 steps and focused on adapting good-quality guidelines for nonspecific low back pain into local context. GRADE-ADOLOPMENT is an eight-step process based on the GRADE Working Group's Evidence to Decision frameworks and applied in 22 guidelines in the context of national guideline development program. The MAGIC research program developed a five-step adaptation process, informed by ADAPTE and the GRADE approach in the context of adapting thrombosis guidelines. The RAPADAPTE framework consists of 12 steps based on ADAPTE and using synthesized evidence databases, retrospectively derived from the experience of producing a high-quality guideline for the treatment of breast cancer with limited resources in Costa Rica. The RCN outlines five key steps strategy for adaptation of guidelines to the local context. The SGR method consists of nine steps and takes into consideration both methodological gaps and context-specific normative issues in source guidelines. We identified through searching personal files two abandoned methods. We identified and described eight proposed frameworks for the adaptation of health-related guidelines. There is a need to evaluate these different frameworks to assess rigor, efficiency, and transparency of their proposed processes. Copyright © 2017 Elsevier Inc. All rights reserved.

Carpet: Adaptive Mesh Refinement for the Cactus Framework

NASA Astrophysics Data System (ADS)

Schnetter, Erik; Hawley, Scott; Hawke, Ian

2016-11-01

Carpet is an adaptive mesh refinement and multi-patch driver for the Cactus Framework (ascl:1102.013). Cactus is a software framework for solving time-dependent partial differential equations on block-structured grids, and Carpet acts as driver layer providing adaptive mesh refinement, multi-patch capability, as well as parallelization and efficient I/O.

Building capacity for implementation of the framework convention for tobacco control in Vietnam: lessons for developing countries.

PubMed

Stillman, Frances A; David, Annette M; Kibria, Naseeb; Phan, Hai Thi

2014-09-01

Effective implementation of the WHO international Framework Convention on Tobacco Control (FCTC) is the key to controlling the tobacco epidemic. Within countries, strong national tobacco control capacity is the primary determinant for successful implementation of the FCTC. This case study of tobacco control policy describes the experience of building national tobacco control capacity in Vietnam under the Reduce Smoking in Vietnam Partnership project within a national capacity-building framework. In the Vietnam experience, four components of tobacco control capacity emerged as especially important to achieve 'quality' outputs and measurable outcomes at the implementation level: (i) organizational structure/infrastructure; (ii) leadership and expertise; (iii) partnerships and networks and (iv) data and evidence from research. The experience gained in this project helps in adapting our tobacco control capacity-building model, and the lessons that emerged from this country case study can provide guidance to global funders, tobacco control technical assistance providers and nations as governments endeavor to meet their commitment to the FCTC. © The Author (2013). Published by Oxford University Press.

Ecological Principles for Invasive Plant Management

USDA-ARS?s Scientific Manuscript database

Invasive annual grasses continue to advance at an alarming rate despite efforts of control by land managers. Ecologically-based invasive plant management (EBIPM) is a holistic framework that integrates ecosystem health assessment, knowledge of ecological processes and adaptive management into a succ...

Vulnerability Assessment and Adaptation Framework, Third Edition

DOT National Transportation Integrated Search

2017-11-01

The Federal Highway Administrations (FHWAs) Vulnerability Assessment and Adaptation Framework (the Framework), third edition, is a manual to help transportation agencies and their partners assess the vulnerability of transportation infrastructu...

Influence of porcelain firing and cementation on the marginal adaptation of metal-ceramic restorations prepared by different methods.

PubMed

Kaleli, Necati; Saraç, Duygu

2017-05-01

Marginal adaptation plays an important role in the survival of metal-ceramic restorations. Porcelain firings and cementation may affect the adaptation of restorations. Moreover, conventional casting procedures and casting imperfections may cause deteriorations in the marginal adaptation of metal-ceramic restorations. The purpose of this in vitro study was to compare the marginal adaptation after fabrication of the framework, porcelain application, and cementation of metal-ceramic restorations prepared by using the conventional lost-wax technique, milling, direct metal laser sintering (DMLS), and LaserCUSING, a direct process powder-bed system. Alterations in the marginal adaptation of the metal frameworks during the fabrication stages and the precision of fabrication methods were evaluated. Forty-eight metal dies simulating prepared premolar and molar abutment teeth were fabricated to investigate marginal adaptation. They were divided into 4 groups (n=12) according to the fabrication method used (group C serving as the control group: lost-wax method; group M: milling method; group LS: DMLS method; group DP: direct process powder-bed method). Sixty marginal discrepancy measurements were recorded separately on each abutment tooth after fabrication of the framework, porcelain application, and cementation by using a stereomicroscope. Thereafter, each group was divided into 3 subgroups according to the measurements recorded in each fabrication stage: subgroup F (framework), subgroup P (porcelain application), and subgroup C (cementation). Data were statistically analyzed with univariate analysis of variance (followed by 1-way ANOVA and Tamhane T2 test (α=.05). The lowest marginal discrepancy values were observed in restorations prepared by using the direct process powder-bed method, and this was significantly different (P<.001) from the other methods. The highest marginal discrepancy values were recorded after the cementation procedure in all groups. The results showed that the direct process powder-bed method is quite successful in terms of marginal adaptation. The marginal discrepancy increased after porcelain application and cementation. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Object-oriented philosophy in designing adaptive finite-element package for 3D elliptic deferential equations

NASA Astrophysics Data System (ADS)

Zhengyong, R.; Jingtian, T.; Changsheng, L.; Xiao, X.

2007-12-01

Although adaptive finite-element (AFE) analysis is becoming more and more focused in scientific and engineering fields, its efficient implementations are remain to be a discussed problem as its more complex procedures. In this paper, we propose a clear C++ framework implementation to show the powerful properties of Object-oriented philosophy (OOP) in designing such complex adaptive procedure. In terms of the modal functions of OOP language, the whole adaptive system is divided into several separate parts such as the mesh generation or refinement, a-posterior error estimator, adaptive strategy and the final post processing. After proper designs are locally performed on these separate modals, a connected framework of adaptive procedure is formed finally. Based on the general elliptic deferential equation, little efforts should be added in the adaptive framework to do practical simulations. To show the preferable properties of OOP adaptive designing, two numerical examples are tested. The first one is the 3D direct current resistivity problem in which the powerful framework is efficiently shown as only little divisions are added. And then, in the second induced polarization£¨IP£©exploration case, new adaptive procedure is easily added which adequately shows the strong extendibility and re-usage of OOP language. Finally we believe based on the modal framework adaptive implementation by OOP methodology, more advanced adaptive analysis system will be available in future.

Hybrid Model Predictive Control for Sequential Decision Policies in Adaptive Behavioral Interventions.

PubMed

Dong, Yuwen; Deshpande, Sunil; Rivera, Daniel E; Downs, Danielle S; Savage, Jennifer S

2014-06-01

Control engineering offers a systematic and efficient method to optimize the effectiveness of individually tailored treatment and prevention policies known as adaptive or "just-in-time" behavioral interventions. The nature of these interventions requires assigning dosages at categorical levels, which has been addressed in prior work using Mixed Logical Dynamical (MLD)-based hybrid model predictive control (HMPC) schemes. However, certain requirements of adaptive behavioral interventions that involve sequential decision making have not been comprehensively explored in the literature. This paper presents an extension of the traditional MLD framework for HMPC by representing the requirements of sequential decision policies as mixed-integer linear constraints. This is accomplished with user-specified dosage sequence tables, manipulation of one input at a time, and a switching time strategy for assigning dosages at time intervals less frequent than the measurement sampling interval. A model developed for a gestational weight gain (GWG) intervention is used to illustrate the generation of these sequential decision policies and their effectiveness for implementing adaptive behavioral interventions involving multiple components.

Adaptation, expertise, and giftedness: towards an understanding of cortical, subcortical, and cerebellar network contributions.

PubMed

Koziol, Leonard F; Budding, Deborah Ely; Chidekel, Dana

2010-12-01

Current cortico-centric models of cognition lack a cohesive neuroanatomic framework that sufficiently considers overlapping levels of function, from "pathological" through "normal" to "gifted" or exceptional ability. While most cognitive theories presume an evolutionary context, few actively consider the process of adaptation, including concepts of neurodevelopment. Further, the frequent co-occurrence of "gifted" and "pathological" function is difficult to explain from a cortico-centric point of view. This comprehensive review paper proposes a framework that includes the brain's vertical organization and considers "giftedness" from an evolutionary and neurodevelopmental vantage point. We begin by discussing the current cortico-centric model of cognition and its relationship to intelligence. We then review an integrated, dual-tiered model of cognition that better explains the process of adaptation by simultaneously allowing for both stimulus-based processing and higher-order cognitive control. We consider the role of the basal ganglia within this model, particularly in relation to reward circuitry and instrumental learning. We review the important role of white matter tracts in relation to speed of adaptation and development of behavioral mastery. We examine the cerebellum's critical role in behavioral refinement and in cognitive and behavioral automation, particularly in relation to expertise and giftedness. We conclude this integrated model of brain function by considering the savant syndrome, which we believe is best understood within the context of a dual-tiered model of cognition that allows for automaticity in adaptation as well as higher-order executive control.

Run-to-Run Optimization Control Within Exact Inverse Framework for Scan Tracking.

PubMed

Yeoh, Ivan L; Reinhall, Per G; Berg, Martin C; Chizeck, Howard J; Seibel, Eric J

2017-09-01

A run-to-run optimization controller uses a reduced set of measurement parameters, in comparison to more general feedback controllers, to converge to the best control point for a repetitive process. A new run-to-run optimization controller is presented for the scanning fiber device used for image acquisition and display. This controller utilizes very sparse measurements to estimate a system energy measure and updates the input parameterizations iteratively within a feedforward with exact-inversion framework. Analysis, simulation, and experimental investigations on the scanning fiber device demonstrate improved scan accuracy over previous methods and automatic controller adaptation to changing operating temperature. A specific application example and quantitative error analyses are provided of a scanning fiber endoscope that maintains high image quality continuously across a 20 °C temperature rise without interruption of the 56 Hz video.

A Framework for Evaluating Energy and Emissions of Connected and Automated Vehicles through Traffic Microsimulations

DOT National Transportation Integrated Search

2018-01-07

Connected and automated vehicles (CAV) are poised to transform surface transportation systems in the United States. Near-term CAV technologies like cooperative adaptive cruise control (CACC) have the potential to deliver energy efficiency and air qua...

An adaptive-management framework for optimal control of hiking near golden eagle nests in Denali National Park

USGS Publications Warehouse

Martin, Julien; Fackler, Paul L.; Nichols, James D.; Runge, Michael C.; McIntyre, Carol L.; Lubow, Bruce L.; McCluskie, Maggie C.; Schmutz, Joel A.

2011-01-01

Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive-management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles

An Adaptive Sensor Mining Framework for Pervasive Computing Applications

NASA Astrophysics Data System (ADS)

Rashidi, Parisa; Cook, Diane J.

Analyzing sensor data in pervasive computing applications brings unique challenges to the KDD community. The challenge is heightened when the underlying data source is dynamic and the patterns change. We introduce a new adaptive mining framework that detects patterns in sensor data, and more importantly, adapts to the changes in the underlying model. In our framework, the frequent and periodic patterns of data are first discovered by the Frequent and Periodic Pattern Miner (FPPM) algorithm; and then any changes in the discovered patterns over the lifetime of the system are discovered by the Pattern Adaptation Miner (PAM) algorithm, in order to adapt to the changing environment. This framework also captures vital context information present in pervasive computing applications, such as the startup triggers and temporal information. In this paper, we present a description of our mining framework and validate the approach using data collected in the CASAS smart home testbed.

General mental ability and two types of adaptation to unforeseen change: applying discontinuous growth models to the task-change paradigm.

PubMed

Lang, Jonas W B; Bliese, Paul D

2009-03-01

The present research provides new insights into the relationship between general mental ability (GMA) and adaptive performance by applying a discontinuous growth modeling framework to a study of unforeseen change on a complex decision-making task. The proposed framework provides a way to distinguish 2 types of adaptation (transition adaptation and reacquisition adaptation) from 2 common performance components (skill acquisition and basal task performance). Transition adaptation refers to an immediate loss of performance following a change, whereas reacquisition adaptation refers to the ability to relearn a changed task over time. Analyses revealed that GMA was negatively related to transition adaptation and found no evidence for a relationship between GMA and reacquisition adaptation. The results are integrated within the context of adaptability research, and implications of using the described discontinuous growth modeling framework to study adaptability are discussed. (c) 2009 APA, all rights reserved.

U.S.A.B.I.L.I.T.Y. Framework for Older Adults.

PubMed

Caboral-Stevens, Meriam; Whetsell, Martha V; Evangelista, Lorraine S; Cypress, Brigitte; Nickitas, Donna

2015-01-01

The purpose of the current study was to present a framework to determine potential usability of health websites by older adults. Review of the literature showed paucity of nursing theory related to the use of technology and usability, particularly in older adults. The Roy Adaptation Model, a widely used nursing theory, was chosen to provide framework for the new model. Technology constructs from the Technology Acceptance Model and United Theory of Acceptance and Use of Technology and behavioral control construct from the Theory of Planned Behavior were integrated into the construction of the derived model. The Use of Technology for Adaptation by Older Adults and/or Those With Limited Literacy (U.S.A.B.I.L.I.T.Y.) Model was constructed from the integration of diverse theoretical/conceptual perspectives. The four determinants of usability in the conceptual model include (a) efficiency, (b) learnability, (c) perceived user experience, and (d) perceived control. Because of the lack of well-validated survey questionnaires to measure these determinants, a U.S.A.B.I.L.I.T.Y. Survey was developed. A panel of experts evaluated face and content validity of the new instrument. Internal consistency of the new instrument was 0.96. Usability is key to accepting technology. The derived U.S.A.B.I.L.I.T.Y. framework could serve as a guide for nurses in formative evaluation of technology. Copyright 2015, SLACK Incorporated.

A New Powered Lower Limb Prosthesis Control Framework Based on Adaptive Dynamic Programming.

PubMed

Wen, Yue; Si, Jennie; Gao, Xiang; Huang, Stephanie; Huang, He Helen

2017-09-01

This brief presents a novel application of adaptive dynamic programming (ADP) for optimal adaptive control of powered lower limb prostheses, a type of wearable robots to assist the motor function of the limb amputees. Current control of these robotic devices typically relies on finite state impedance control (FS-IC), which lacks adaptability to the user's physical condition. As a result, joint impedance settings are often customized manually and heuristically in clinics, which greatly hinder the wide use of these advanced medical devices. This simulation study aimed at demonstrating the feasibility of ADP for automatic tuning of the twelve knee joint impedance parameters during a complete gait cycle to achieve balanced walking. Given that the accurate models of human walking dynamics are difficult to obtain, the model-free ADP control algorithms were considered. First, direct heuristic dynamic programming (dHDP) was applied to the control problem, and its performance was evaluated on OpenSim, an often-used dynamic walking simulator. For the comparison purposes, we selected another established ADP algorithm, the neural fitted Q with continuous action (NFQCA). In both cases, the ADP controllers learned to control the right knee joint and achieved balanced walking, but dHDP outperformed NFQCA in this application during a 200 gait cycle-based testing.

Multidimensional CAT Item Selection Methods for Domain Scores and Composite Scores with Item Exposure Control and Content Constraints

ERIC Educational Resources Information Center

Yao, Lihua

2014-01-01

The intent of this research was to find an item selection procedure in the multidimensional computer adaptive testing (CAT) framework that yielded higher precision for both the domain and composite abilities, had a higher usage of the item pool, and controlled the exposure rate. Five multidimensional CAT item selection procedures (minimum angle;…

Conflicts of thermal adaptation and fever--a cybernetic approach based on physiological experiments.

PubMed

Werner, J; Beckmann, U

1998-01-01

Cold adaptation aims primarily at a better economy, i.e., preservation of energy often at the cost of a lower mean body temperature during cold stress, whereas heat adaptation whether achieved by exposure to a hot environment or by endogenous heat produced by muscle exercise, often brings about a higher efficiency of control, i.e., a lower mean body temperature during heat stress, at the cost of a higher water loss. While cold adaptation is beneficial in a cold environment, it may constitute a detrimental factor for exposure to a hot environment, mainly because of morphological adaptation. Heat adaptation may be maladaptive for cold exposure, mainly because of functional adaptation. Heat adaptation clearly is best suited to avoid higher body temperatures in fever, no matter which environmental conditions prevail. On the other hand, cold adaptation is detrimental for coping with fever in hot environment. Yet, in the cold, preceding cold adaptation may, because of reduced metabolic heat production, result in lower febrile increase of body temperature. Apparently controversial effects and results may be analyzed in the framework of a cybernetic approach to the main mechanisms of thermal adaptation and fever. Morphological adaptations alter the properties of the heat transfer characteristics of the body ("passive system"), whereas functional adaptation and fever concern the subsystems of control, namely sensors, integrative centers and effectors. In a closed control-loop the two types of adaptation have totally different consequences. It is shown that the experimental results are consistent with the predictions of such an approach.

Cross Support Transfer Service (CSTS) Framework Library

NASA Technical Reports Server (NTRS)

Ray, Timothy

2014-01-01

Within the Consultative Committee for Space Data Systems (CCSDS), there is an effort to standardize data transfer between ground stations and control centers. CCSDS plans to publish a collection of transfer services that will each address the transfer of a particular type of data (e.g., tracking data). These services will be called Cross Support Transfer Services (CSTSs). All of these services will make use of a common foundation that is called the CSTS Framework. This library implements the User side of the CSTS Framework. "User side" means that the library performs the role that is typically expected of the control center. This library was developed in support of the Goddard Data Standards program. This technology could be applicable for control centers, and possibly for use in control center simulators needed to test ground station capabilities. The main advantages of this implementation are its flexibility and simplicity. It provides the framework capabilities, while allowing the library user to provide a wrapper that adapts the library to any particular environment. The main purpose of this implementation was to support the inter-operability testing required by CCSDS. In addition, it is likely that the implementation will be useful within the Goddard mission community (for use in control centers).

Test and evaluation of vehicle platooning proof-of-concept based on cooperative adaptive cruise control

DOT National Transportation Integrated Search

2017-04-01

This report presents a high-level test and evaluation framework for cooperative driving automation systems that have the potential to significantly improve mobility and enhance traffic flow stability with better safety. It focuses on the test and eva...

Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

DOE PAGES

Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan; ...

2017-10-17

In this paper we developed an efficient Bayesian inversion framework for interpreting marine seismic Amplitude Versus Angle and Controlled-Source Electromagnetic data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis and Adaptive Metropolis samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and Controlled-Source Electromagnetic data. The multi-chain Markov-chain Monte Carlo is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach ismore » used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic Amplitude Versus Angle and Controlled-Source Electromagnetic joint inversion provides better estimation of reservoir saturations than the seismic Amplitude Versus Angle only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated — reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.« less

Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan

In this paper we developed an efficient Bayesian inversion framework for interpreting marine seismic Amplitude Versus Angle and Controlled-Source Electromagnetic data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis and Adaptive Metropolis samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and Controlled-Source Electromagnetic data. The multi-chain Markov-chain Monte Carlo is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach ismore » used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic Amplitude Versus Angle and Controlled-Source Electromagnetic joint inversion provides better estimation of reservoir saturations than the seismic Amplitude Versus Angle only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated — reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.« less

Adaptive multimodal interaction in mobile augmented reality: A conceptual framework

NASA Astrophysics Data System (ADS)

Abidin, Rimaniza Zainal; Arshad, Haslina; Shukri, Saidatul A'isyah Ahmad

2017-10-01

Recently, Augmented Reality (AR) is an emerging technology in many mobile applications. Mobile AR was defined as a medium for displaying information merged with the real world environment mapped with augmented reality surrounding in a single view. There are four main types of mobile augmented reality interfaces and one of them are multimodal interfaces. Multimodal interface processes two or more combined user input modes (such as speech, pen, touch, manual gesture, gaze, and head and body movements) in a coordinated manner with multimedia system output. In multimodal interface, many frameworks have been proposed to guide the designer to develop a multimodal applications including in augmented reality environment but there has been little work reviewing the framework of adaptive multimodal interface in mobile augmented reality. The main goal of this study is to propose a conceptual framework to illustrate the adaptive multimodal interface in mobile augmented reality. We reviewed several frameworks that have been proposed in the field of multimodal interfaces, adaptive interface and augmented reality. We analyzed the components in the previous frameworks and measure which can be applied in mobile devices. Our framework can be used as a guide for designers and developer to develop a mobile AR application with an adaptive multimodal interfaces.

A Conceptual Framework for Planning Systemic Human Adaptation to Global Warming.

PubMed

Tait, Peter W; Hanna, Elizabeth G

2015-08-31

Human activity is having multiple, inter-related effects on ecosystems. Greenhouse gas emissions persisting along current trajectories threaten to significantly alter human society. At 0.85 °C of anthropogenic warming, deleterious human impacts are acutely evident. Additional warming of 0.5 °C-1.0 °C from already emitted CO₂ will further intensify extreme heat and damaging storm events. Failing to sufficiently address this trend will have a heavy human toll directly and indirectly on health. Along with mitigation efforts, societal adaptation to a warmer world is imperative. Adaptation efforts need to be significantly upscaled to prepare society to lessen the public health effects of rising temperatures. Modifying societal behaviour is inherently complex and presents a major policy challenge. We propose a social systems framework for conceptualizing adaptation that maps out three domains within the adaptation policy landscape: acclimatisation, behavioural adaptation and technological adaptation, which operate at societal and personal levels. We propose that overlaying this framework on a systems approach to societal change planning methods will enhance governments' capacity and efficacy in strategic planning for adaptation. This conceptual framework provides a policy oriented planning assessment tool that will help planners match interventions to the behaviours being targeted for change. We provide illustrative examples to demonstrate the framework's application as a planning tool.

Distributed adaptive neural network control for a class of heterogeneous nonlinear multi-agent systems subject to actuation failures

NASA Astrophysics Data System (ADS)

Cui, Bing; Zhao, Chunhui; Ma, Tiedong; Feng, Chi

2017-02-01

In this paper, the cooperative adaptive consensus tracking problem for heterogeneous nonlinear multi-agent systems on directed graph is addressed. Each follower is modelled as a general nonlinear system with the unknown and nonidentical nonlinear dynamics, disturbances and actuator failures. Cooperative fault tolerant neural network tracking controllers with online adaptive learning features are proposed to guarantee that all agents synchronise to the trajectory of one leader with bounded adjustable synchronisation errors. With the help of linear quadratic regulator-based optimal design, a graph-dependent Lyapunov proof provides error bounds that depend on the graph topology, one virtual matrix and some design parameters. Of particular interest is that if the control gain is selected appropriately, the proposed control scheme can be implemented in a unified framework no matter whether there are faults or not. Furthermore, the fault detection and isolation are not needed to implement. Finally, a simulation is given to verify the effectiveness of the proposed method.

Atmospheric Environment Vulnerability Cause Analysis for the Beijing-Tianjin-Hebei Metropolitan Region

PubMed Central

Zhang, Yang; Shen, Jing; Li, Yu

2018-01-01

Assessing and quantifying atmospheric vulnerability is a key issue in urban environmental protection and management. This paper integrated the Analytical hierarchy process (AHP), fuzzy synthesis evaluation and Geographic Information System (GIS) spatial analysis into an Exposure-Sensitivity-Adaptive capacity (ESA) framework to quantitatively assess atmospheric environment vulnerability in the Beijing-Tianjin-Hebei (BTH) region with spatial and temporal comparisons. The elaboration of the relationships between atmospheric environment vulnerability and indices of exposure, sensitivity, and adaptive capacity supports enable analysis of the atmospheric environment vulnerability. Our findings indicate that the atmospheric environment vulnerability of 13 cities in the BTH region exhibits obvious spatial heterogeneity, which is caused by regional diversity in exposure, sensitivity, and adaptive capacity indices. The results of atmospheric environment vulnerability assessment and the cause analysis can provide guidance to pick out key control regions and recognize vulnerable indicators for study sites. The framework developed in this paper can also be replicated at different spatial and temporal scales using context-specific datasets to support environmental management. PMID:29342852

Atmospheric Environment Vulnerability Cause Analysis for the Beijing-Tianjin-Hebei Metropolitan Region.

PubMed

Zhang, Yang; Shen, Jing; Li, Yu

2018-01-13

Assessing and quantifying atmospheric vulnerability is a key issue in urban environmental protection and management. This paper integrated the Analytical hierarchy process (AHP), fuzzy synthesis evaluation and Geographic Information System (GIS) spatial analysis into an Exposure-Sensitivity-Adaptive capacity (ESA) framework to quantitatively assess atmospheric environment vulnerability in the Beijing-Tianjin-Hebei (BTH) region with spatial and temporal comparisons. The elaboration of the relationships between atmospheric environment vulnerability and indices of exposure, sensitivity, and adaptive capacity supports enable analysis of the atmospheric environment vulnerability. Our findings indicate that the atmospheric environment vulnerability of 13 cities in the BTH region exhibits obvious spatial heterogeneity, which is caused by regional diversity in exposure, sensitivity, and adaptive capacity indices. The results of atmospheric environment vulnerability assessment and the cause analysis can provide guidance to pick out key control regions and recognize vulnerable indicators for study sites. The framework developed in this paper can also be replicated at different spatial and temporal scales using context-specific datasets to support environmental management.

[Going into the 21st century: should one dream or act?].

PubMed

Coosemans, M

1991-01-01

A historical review of vector control is made. Despite the available tools, vector borne diseases are still a priority in Public Health. Magic tools, like DDT, were often misused. Adapted strategies and structures for vector control are now required. Progress will mainly result from research and evaluation done in the framework of vector control programmes. Discovery of new tools will find in these operational programmes a point of fall for their application.

Bio-inspired adaptive feedback error learning architecture for motor control.

PubMed

Tolu, Silvia; Vanegas, Mauricio; Luque, Niceto R; Garrido, Jesús A; Ros, Eduardo

2012-10-01

This study proposes an adaptive control architecture based on an accurate regression method called Locally Weighted Projection Regression (LWPR) and on a bio-inspired module, such as a cerebellar-like engine. This hybrid architecture takes full advantage of the machine learning module (LWPR kernel) to abstract an optimized representation of the sensorimotor space while the cerebellar component integrates this to generate corrective terms in the framework of a control task. Furthermore, we illustrate how the use of a simple adaptive error feedback term allows to use the proposed architecture even in the absence of an accurate analytic reference model. The presented approach achieves an accurate control with low gain corrective terms (for compliant control schemes). We evaluate the contribution of the different components of the proposed scheme comparing the obtained performance with alternative approaches. Then, we show that the presented architecture can be used for accurate manipulation of different objects when their physical properties are not directly known by the controller. We evaluate how the scheme scales for simulated plants of high Degrees of Freedom (7-DOFs).

Adaptive nonlinear robust relative pose control of spacecraft autonomous rendezvous and proximity operations.

PubMed

Sun, Liang; Huo, Wei; Jiao, Zongxia

2017-03-01

This paper studies relative pose control for a rigid spacecraft with parametric uncertainties approaching to an unknown tumbling target in disturbed space environment. State feedback controllers for relative translation and relative rotation are designed in an adaptive nonlinear robust control framework. The element-wise and norm-wise adaptive laws are utilized to compensate the parametric uncertainties of chaser and target spacecraft, respectively. External disturbances acting on two spacecraft are treated as a lumped and bounded perturbation input for system. To achieve the prescribed disturbance attenuation performance index, feedback gains of controllers are designed by solving linear matrix inequality problems so that lumped disturbance attenuation with respect to the controlled output is ensured in the L 2 -gain sense. Moreover, in the absence of lumped disturbance input, asymptotical convergence of relative pose are proved by using the Lyapunov method. Numerical simulations are performed to show that position tracking and attitude synchronization are accomplished in spite of the presence of couplings and uncertainties. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A Roy model study of adapting to being HIV positive.

PubMed

Perrett, Stephanie E; Biley, Francis C

2013-10-01

Roy's adaptation model outlines a generic process of adaptation useful to nurses in any situation where a patient is facing change. To advance nursing practice, nursing theories and frameworks must be constantly tested and developed through research. This article describes how the results of a qualitative grounded theory study have been used to test components of the Roy adaptation model. A framework for "negotiating uncertainty" was the result of a grounded theory study exploring adaptation to HIV. This framework has been compared to the Roy adaptation model, strengthening concepts such as focal and contextual stimuli, Roy's definition of adaptation and her description of adaptive modes, while suggesting areas for further development including the role of perception. The comparison described in this article demonstrates the usefulness of qualitative research in developing nursing models, specifically highlighting opportunities to continue refining Roy's work.

Studying the clinical encounter with the Adaptive Leadership framework.

PubMed

Bailey, Donald E; Docherty, Sharron L; Adams, Judith A; Carthron, Dana L; Corazzini, Kirsten; Day, Jennifer R; Neglia, Elizabeth; Thygeson, Marcus; Anderson, Ruth A

2012-08-01

In this paper we discuss the concept of leadership as a personal capability, not contingent on one's position in a hierarchy. This type of leadership allows us to reframe both the care-giving and organizational roles of nurses and other front-line clinical staff. Little research has been done to explore what leadership means at the point of care, particularly in reference to the relationship between health care practitioners and patients and their family caregivers. The Adaptive Leadership framework, based on complexity science theory, provides a useful lens to explore practitioners' leadership behaviors at the point of care. This framework proposes that there are two broad categories of challenges that patients face: technical and adaptive. Whereas technical challenges are addressed with technical solutions that are delivered by practitioners, adaptive challenges require the patient (or family member) to adjust to a new situation and to do the work of adapting, learning, and behavior change. Adaptive leadership is the work that practitioners do to mobilize and support patients to do the adaptive work. The purpose of this paper is to describe this framework and demonstrate its application to nursing research. We demonstrate the framework's utility with five exemplars of nursing research problems that range from the individual to the system levels. The framework has the potential to guide researchers to ask new questions and to gain new insights into how practitioners interact with patients at the point of care to increase the patient's ability to tackle challenging problems and improve their own health care outcomes. It is a potentially powerful framework for developing and testing a new generation of interventions to address complex issues by harnessing and learning about the adaptive capabilities of patients within their life contexts.

Evolving Systems: Adaptive Key Component Control and Inheritance of Passivity and Dissipativity

NASA Technical Reports Server (NTRS)

Frost, S. A.; Balas, M. J.

2010-01-01

We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. Autonomous assembly of large, complex flexible structures in space is a target application for Evolving Systems. A critical requirement for autonomous assembling structures is that they remain stable during and after assembly. The fundamental topic of inheritance of stability, dissipativity, and passivity in Evolving Systems is the primary focus of this research. In this paper, we develop an adaptive key component controller to restore stability in Nonlinear Evolving Systems that would otherwise fail to inherit the stability traits of their components. We provide sufficient conditions for the use of this novel control method and demonstrate its use on an illustrative example.

Fully probabilistic control design in an adaptive critic framework.

PubMed

Herzallah, Randa; Kárný, Miroslav

2011-12-01

Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem; in particular, very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic control algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this paper. Copyright © 2011 Elsevier Ltd. All rights reserved.

Intelligent control and adaptive systems; Proceedings of the Meeting, Philadelphia, PA, Nov. 7, 8, 1989

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Editor)

1990-01-01

Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.

A Conceptual Model of Childhood Adaptation to Type 1 Diabetes

PubMed Central

Whittemore, Robin; Jaser, Sarah; Guo, Jia; Grey, Margaret

2010-01-01

The Childhood Adaptation Model to Chronic Illness: Diabetes Mellitus was developed to identify factors that influence childhood adaptation to type 1 diabetes (T1D). Since this model was proposed, considerable research has been completed. The purpose of this paper is to update the model on childhood adaptation to T1D using research conducted since the original model was proposed. The framework suggests that individual and family characteristics, such as age, socioeconomic status, and in children with T1D, treatment modality (pump vs. injections), psychosocial responses (depressive symptoms and anxiety), and individual and family responses (self-management, coping, self-efficacy, family functioning, social competence) influence the level of adaptation. Adaptation has both physiologic (metabolic control) and psychosocial (QOL) components. This revised model provides greater specificity to the factors that influence adaptation to chronic illness in children. Research and clinical implications are discussed. PMID:20934079

Genetically modified organisms: an analysis of the regulatory framework currently employed within the European Union.

PubMed

Gent, R N

1999-09-01

Genetic engineering technology is starting to bring many commercial products to the market. These genetically modified organisms (GMOs) and their derived products are subject to topical debate as to their benefits and risks. The strengths and weaknesses of the regulatory framework that controls their development and application is central to the question of whether this technology poses significant risk to the public health during this critical phase of its evolution. A critical review was carried out of the legal framework regulating the contained use, deliberate release and some aspects of consumer protection relevant to the control of GMOs in Europe and the United Kingdom. The current legal framework is failing to provide a speed of adaptation commensurate with the development of the science of genetic engineering; failing to properly respond to democratic control; failing to resolve significant conflict between the protection of free markets and protection of public health and the environment; and failing to implement obligations on biodiversity. The present legal framework must be replaced. Current European Union proposals for new standards of regulation are welcome, but provide only for further incremental change, and do not address some significant fundamental flaws in our current laws.

Development of a Resource Manager Framework for Adaptive Beamformer Selection

DTIC Science & Technology

2013-12-27

DEVELOPMENT OF A RESOURCE MANAGER FRAMEWORK FOR ADAPTIVE BEAMFORMER SELECTION DISSERTATION Jeremy P. Stringer, Major, USAF AFIT-ENG-DS-13-D-01...Force, the United States Department of Defense or the United States Government. AFIT-ENG-DS-13-D-01 DEVELOPMENT OF A RESOURCE MANAGER FRAMEWORK FOR...ADAPTIVE BEAMFORMER SELECTION DISSERTATION Presented to the Faculty Graduate School of Engineering and Management Air Force Institute of Technology Air

A framework to assess landscape structural capacity to provide regulating ecosystem services in West Africa.

PubMed

Inkoom, Justice Nana; Frank, Susanne; Greve, Klaus; Fürst, Christine

2018-03-01

The Sudanian savanna landscapes of West Africa are amongst the world's most vulnerable areas to climate change impacts. Inappropriate land use and agriculture management practices continuously impede the capacity of agricultural landscapes to provide ecosystem services (ES). Given the absence of practical assessment techniques to evaluate the landscape's capacity to provide regulating ES in this region, the goal of this paper is to propose an integrative assessment framework which combines remote sensing, geographic information systems, expert weighting and landscape metrics-based assessment. We utilized Analytical Hierarchical Process and Likert scale for the expert weighting of landscape capacity. In total, 56 experts from several land use and landscape management related departments participated in the assessment. Further, we adapted the hemeroby concept to define areas of naturalness while landscape metrics including Patch Density, Shannon's Diversity, and Shape Index were utilized for structural assessment. Lastly, we tested the reliability of expert weighting using certainty measurement rated by experts themselves. Our study focused on four regulating ES including flood control, pest and disease control, climate control, and wind erosion control. Our assessment framework was tested on four selected sites in the Vea catchment area of Ghana. The outcome of our study revealed that highly heterogeneous landscapes have a higher capacity to provide pest and disease control, while less heterogeneous landscapes have a higher potential to provide climate control. Further, we could show that the potential capacities to provide ecosystem services are underestimated by 15% if landscape structural aspects assessed through landscape metrics are not considered. We conclude that the combination of adapted land use and an optimized land use pattern could contribute considerably to lower climate change impacts in West African agricultural landscapes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adapting the coping in deliberation (CODE) framework: a multi-method approach in the context of familial ovarian cancer risk management.

PubMed

Witt, Jana; Elwyn, Glyn; Wood, Fiona; Rogers, Mark T; Menon, Usha; Brain, Kate

2014-11-01

To test whether the coping in deliberation (CODE) framework can be adapted to a specific preference-sensitive medical decision: risk-reducing bilateral salpingo-oophorectomy (RRSO) in women at increased risk of ovarian cancer. We performed a systematic literature search to identify issues important to women during deliberations about RRSO. Three focus groups with patients (most were pre-menopausal and untested for genetic mutations) and 11 interviews with health professionals were conducted to determine which issues mattered in the UK context. Data were used to adapt the generic CODE framework. The literature search yielded 49 relevant studies, which highlighted various issues and coping options important during deliberations, including mutation status, risks of surgery, family obligations, physician recommendation, peer support and reliable information sources. Consultations with UK stakeholders confirmed most of these factors as pertinent influences on deliberations. Questions in the generic framework were adapted to reflect the issues and coping options identified. The generic CODE framework was readily adapted to a specific preference-sensitive medical decision, showing that deliberations and coping are linked during deliberations about RRSO. Adapted versions of the CODE framework may be used to develop tailored decision support methods and materials in order to improve patient-centred care. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

CReaTE Excellence: Using a Teacher Framework to Maximize STEM Learning with Your Child

ERIC Educational Resources Information Center

Tassell, Janet; Maxwell, Margaret; Stobaugh, Rebecca

2013-01-01

Gifted children crave meaning through learning experiences, and they are naturally inquisitive. This article provides a teaching framework that parents can adapt for use with gifted children to help facilitate STEM knowledge and skills. The CReaTE Framework, adapted from an evolving lesson plan framework, can promote learning in a nontraditional,…

Grassland Smoke Emission Measurement Supporting Multi-Modeling Framework Simulation of Rangeland Burning Practices for the Kansas Flint Hills Fire Experiment

EPA Science Inventory

Historically, frequent wildfires were essential for the maintenance of native prairie fire adapted ecosystems. Today prescribed fires are used to control invasive woody species and potentially improve forage production in these same prairie ecosystems for the beef-cattle industry...

Insights for the assessment of the economic impact of endemic diseases: specific adaptation of economic frameworks using the case of bovine viral diarrhoea.

PubMed

Stott, A W; Gunn, G J

2017-04-01

Generic frameworks for the economic analysis of farm animal disease are now well established. The paper, therefore, uses bovine viral diarrhoea (BVD) as an example to explore how these frameworks need to be adapted to fit the characteristics of a particular disease and the specific objectives of the analysis. In the case of BVD, given the relative strength of tests available to correctly identify virus-positive animals, thus enabling them to be culled, the emphasis has been on cost-benefit analysis of regional and national certification/eradication schemes. Such analyses in turn raise interesting questions about farmer uptake and maintenance of certification schemes and the equity and cost-effective implementation of these schemes. The complex epidemiology of BVD virus infections and the long-term, widespread and often occult nature of BVD effects make economic analysis of the disease and its control particularly challenging. However, this has resulted in a wider whole-farm perspective that captures the influence of multiple decisions, not just those directly associated with disease prevention and control. There is a need to include management of reproduction, risk and enterprise mix in the research on farmer decision-making, as all these factors impinge on, and are affected by, the spread of BVD.

Science-based Forest Management in an Era of Climate Change

NASA Astrophysics Data System (ADS)

Swanston, C.; Janowiak, M.; Brandt, L.; Butler, P.; Handler, S.; Shannon, D.

2014-12-01

Recognizing the need to provide climate adaptation information, training, and tools to forest managers, the Forest Service joined with partners in 2009 to launch a comprehensive effort called the Climate Change Response Framework (www.forestadaptation.org). The Framework provides a structured approach to help managers integrate climate considerations into forest management plans and then implement adaptation actions on the ground. A planning tool, the Adaptation Workbook, is used in conjunction with vulnerability assessments and a diverse "menu" of adaptation approaches to generate site-specific adaptation actions that meet explicit management objectives. Additionally, a training course, designed around the Adaptation Workbook, leads management organizations through this process of designing on-the-ground adaptation tactics for their management projects. The Framework is now being actively pursued in 20 states in the Northwoods, Central Hardwoods, Central Appalachians, Mid-Atlantic, and New England. The Framework community includes over 100 science and management groups, dozens of whom have worked together to complete six ecoregional vulnerability assessments covering nearly 135 million acres. More than 75 forest and urban forest adaptation strategies and approaches were synthesized from peer-reviewed and gray literature, expert solicitation, and on-the-ground adaptation projects. These are being linked through the Adaptation Workbook process to on-the-ground adaptation tactics being planned and employed in more than 50 adaptation "demonstrations". This presentation will touch on the scientific and professional basis of the vulnerability assessments, and showcase efforts where adaptation actions are currently being implemented in forests.

Self-organizing network services with evolutionary adaptation.

PubMed

Nakano, Tadashi; Suda, Tatsuya

2005-09-01

This paper proposes a novel framework for developing adaptive and scalable network services. In the proposed framework, a network service is implemented as a group of autonomous agents that interact in the network environment. Agents in the proposed framework are autonomous and capable of simple behaviors (e.g., replication, migration, and death). In this paper, an evolutionary adaptation mechanism is designed using genetic algorithms (GAs) for agents to evolve their behaviors and improve their fitness values (e.g., response time to a service request) to the environment. The proposed framework is evaluated through simulations, and the simulation results demonstrate the ability of autonomous agents to adapt to the network environment. The proposed framework may be suitable for disseminating network services in dynamic and large-scale networks where a large number of data and services need to be replicated, moved, and deleted in a decentralized manner.

The Roy Adaptation Model: A Theoretical Framework for Nurses Providing Care to Individuals With Anorexia Nervosa.

PubMed

Jennings, Karen M

Using a nursing theoretical framework to understand, elucidate, and propose nursing research is fundamental to knowledge development. This article presents the Roy Adaptation Model as a theoretical framework to better understand individuals with anorexia nervosa during acute treatment, and the role of nursing assessments and interventions in the promotion of weight restoration. Nursing assessments and interventions situated within the Roy Adaptation Model take into consideration how weight restoration does not occur in isolation but rather reflects an adaptive process within external and internal environments, and has the potential for more holistic care.

Adaptive management of natural resources-framework and issues

USGS Publications Warehouse

Williams, B.K.

2011-01-01

Adaptive management, an approach for simultaneously managing and learning about natural resources, has been around for several decades. Interest in adaptive decision making has grown steadily over that time, and by now many in natural resources conservation claim that adaptive management is the approach they use in meeting their resource management responsibilities. Yet there remains considerable ambiguity about what adaptive management actually is, and how it is to be implemented by practitioners. The objective of this paper is to present a framework and conditions for adaptive decision making, and discuss some important challenges in its application. Adaptive management is described as a two-phase process of deliberative and iterative phases, which are implemented sequentially over the timeframe of an application. Key elements, processes, and issues in adaptive decision making are highlighted in terms of this framework. Special emphasis is given to the question of geographic scale, the difficulties presented by non-stationarity, and organizational challenges in implementing adaptive management. ?? 2010.

Adaptation of community health worker-delivered behavioral activation for torture survivors in Kurdistan, Iraq.

PubMed

Magidson, J F; Lejuez, C W; Kamal, T; Blevins, E J; Murray, L K; Bass, J K; Bolton, P; Pagoto, S

2015-12-01

Growing evidence supports the use of Western therapies for the treatment of depression, trauma, and stress delivered by community health workers (CHWs) in conflict-affected, resource-limited countries. A recent randomized controlled trial (Bolton et al . 2014 a ) supported the efficacy of two CHW-delivered interventions, cognitive processing therapy (CPT) and brief behavioral activation treatment for depression (BATD), for reducing depressive symptoms and functional impairment among torture survivors in the Kurdish region of Iraq. This study describes the adaptation of the CHW-delivered BATD approach delivered in this trial (Bolton et al .2014 a ), informed by the Assessment-Decision-Administration-Production-Topical experts-Integration-Training-Testing (ADAPT-ITT) framework for intervention adaptation (Wingood & DiClemente, 2008). Cultural modifications, adaptations for low-literacy, and tailored training and supervision for non-specialist CHWs are presented, along with two clinical case examples to illustrate delivery of the adapted intervention in this setting. Eleven CHWs, a study psychiatrist, and the CHW clinical supervisor were trained in BATD. The adaptation process followed the ADAPT-ITT framework and was iterative with significant input from the on-site supervisor and CHWs. Modifications were made to fit Kurdish culture, including culturally relevant analogies, use of stickers for behavior monitoring, cultural modifications to behavioral contracts, and including telephone-delivered sessions to enhance feasibility. BATD was delivered by CHWs in a resource-poor, conflict-affected area in Kurdistan, Iraq, with some important modifications, including low-literacy adaptations, increased cultural relevancy of clinical materials, and tailored training and supervision for CHWs. Barriers to implementation, lessons learned, and recommendations for future efforts to adapt behavioral therapies for resource-limited, conflict-affected areas are discussed.

A conceptual model of childhood adaptation to type 1 diabetes.

PubMed

Whittemore, Robin; Jaser, Sarah; Guo, Jia; Grey, Margaret

2010-01-01

The Childhood Adaptation Model to Chronic Illness: Diabetes Mellitus was developed to identify factors that influence childhood adaptation to type 1 diabetes (T1D). Since this model was proposed, considerable research has been completed. The purpose of this article is to update the model on childhood adaptation to T1D using research conducted since the original model was proposed. The framework suggests that, in individuals and families, characteristics such as age and socioeconomic status as well as the individuals' and families' responses (self-management, coping, self-efficacy, family functioning, social competence) influence the level of adaptation; in children with T1D, characteristics such as treatment modality (pump vs injections) and psychosocial responses (depressive symptoms and anxiety) also influence the level of adaptation. Adaptation has both physiologic (metabolic control) and psychosocial (Quality of Life [QOL]) components. This revised model provides greater specificity to the factors that influence adaptation to chronic illness in children. Research and clinical implications are discussed. Copyright © 2010 Mosby, Inc. All rights reserved.

Adaptive Approximation-Based Regulation Control for a Class of Uncertain Nonlinear Systems Without Feedback Linearizability.

PubMed

Wang, Ning; Sun, Jing-Chao; Han, Min; Zheng, Zhongjiu; Er, Meng Joo

2017-09-06

In this paper, for a general class of uncertain nonlinear (cascade) systems, including unknown dynamics, which are not feedback linearizable and cannot be solved by existing approaches, an innovative adaptive approximation-based regulation control (AARC) scheme is developed. Within the framework of adding a power integrator (API), by deriving adaptive laws for output weights and prediction error compensation pertaining to single-hidden-layer feedforward network (SLFN) from the Lyapunov synthesis, a series of SLFN-based approximators are explicitly constructed to exactly dominate completely unknown dynamics. By the virtue of significant advancements on the API technique, an adaptive API methodology is eventually established in combination with SLFN-based adaptive approximators, and it contributes to a recursive mechanism for the AARC scheme. As a consequence, the output regulation error can asymptotically converge to the origin, and all other signals of the closed-loop system are uniformly ultimately bounded. Simulation studies and comprehensive comparisons with backstepping- and API-based approaches demonstrate that the proposed AARC scheme achieves remarkable performance and superiority in dealing with unknown dynamics.

Design Framework for an Adaptive MOOC Enhanced by Blended Learning: Supplementary Training and Personalized Learning for Teacher Professional Development

ERIC Educational Resources Information Center

Gynther, Karsten

2016-01-01

The research project has developed a design framework for an adaptive MOOC that complements the MOOC format with blended learning. The design framework consists of a design model and a series of learning design principles which can be used to design in-service courses for teacher professional development. The framework has been evaluated by…

A modified theoretical framework to assess implementation fidelity of adaptive public health interventions.

PubMed

Pérez, Dennis; Van der Stuyft, Patrick; Zabala, Maríadel Carmen; Castro, Marta; Lefèvre, Pierre

2016-07-08

One of the major debates in implementation research turns around fidelity and adaptation. Fidelity is the degree to which an intervention is implemented as intended by its developers. It is meant to ensure that the intervention maintains its intended effects. Adaptation is the process of implementers or users bringing changes to the original design of an intervention. Depending on the nature of the modifications brought, adaptation could either be potentially positive or could carry the risk of threatening the theoretical basis of the intervention, resulting in a negative effect on expected outcomes. Adaptive interventions are those for which adaptation is allowed or even encouraged. Classical fidelity dimensions and conceptual frameworks do not address the issue of how to adapt an intervention while still maintaining its effectiveness. We support the idea that fidelity and adaptation co-exist and that adaptations can impact either positively or negatively on the intervention's effectiveness. For adaptive interventions, research should answer the question how an adequate fidelity-adaptation balance can be reached. One way to address this issue is by looking systematically at the aspects of an intervention that are being adapted. We conducted fidelity research on the implementation of an empowerment strategy for dengue prevention in Cuba. In view of the adaptive nature of the strategy, we anticipated that the classical fidelity dimensions would be of limited use for assessing adaptations. The typology we used in the assessment-implemented, not-implemented, modified, or added components of the strategy-also had limitations. It did not allow us to answer the question which of the modifications introduced in the strategy contributed to or distracted from outcomes. We confronted our empirical research with existing literature on fidelity, and as a result, considered that the framework for implementation fidelity proposed by Carroll et al. in 2007 could potentially meet our concerns. We propose modifications to the framework to assess both fidelity and adaptation. The modified Carroll et al.'s framework we propose may permit a comprehensive assessment of the implementation fidelity-adaptation balance required when implementing adaptive interventions, but more empirical research is needed to validate it.

Systematic evaluation of deep learning based detection frameworks for aerial imagery

NASA Astrophysics Data System (ADS)

Sommer, Lars; Steinmann, Lucas; Schumann, Arne; Beyerer, Jürgen

2018-04-01

Object detection in aerial imagery is crucial for many applications in the civil and military domain. In recent years, deep learning based object detection frameworks significantly outperformed conventional approaches based on hand-crafted features on several datasets. However, these detection frameworks are generally designed and optimized for common benchmark datasets, which considerably differ from aerial imagery especially in object sizes. As already demonstrated for Faster R-CNN, several adaptations are necessary to account for these differences. In this work, we adapt several state-of-the-art detection frameworks including Faster R-CNN, R-FCN, and Single Shot MultiBox Detector (SSD) to aerial imagery. We discuss adaptations that mainly improve the detection accuracy of all frameworks in detail. As the output of deeper convolutional layers comprise more semantic information, these layers are generally used in detection frameworks as feature map to locate and classify objects. However, the resolution of these feature maps is insufficient for handling small object instances, which results in an inaccurate localization or incorrect classification of small objects. Furthermore, state-of-the-art detection frameworks perform bounding box regression to predict the exact object location. Therefore, so called anchor or default boxes are used as reference. We demonstrate how an appropriate choice of anchor box sizes can considerably improve detection performance. Furthermore, we evaluate the impact of the performed adaptations on two publicly available datasets to account for various ground sampling distances or differing backgrounds. The presented adaptations can be used as guideline for further datasets or detection frameworks.

An evidence-based public health approach to climate change adaptation.

PubMed

Hess, Jeremy J; Eidson, Millicent; Tlumak, Jennifer E; Raab, Kristin K; Luber, George

2014-11-01

Public health is committed to evidence-based practice, yet there has been minimal discussion of how to apply an evidence-based practice framework to climate change adaptation. Our goal was to review the literature on evidence-based public health (EBPH), to determine whether it can be applied to climate change adaptation, and to consider how emphasizing evidence-based practice may influence research and practice decisions related to public health adaptation to climate change. We conducted a substantive review of EBPH, identified a consensus EBPH framework, and modified it to support an EBPH approach to climate change adaptation. We applied the framework to an example and considered implications for stakeholders. A modified EBPH framework can accommodate the wide range of exposures, outcomes, and modes of inquiry associated with climate change adaptation and the variety of settings in which adaptation activities will be pursued. Several factors currently limit application of the framework, including a lack of higher-level evidence of intervention efficacy and a lack of guidelines for reporting climate change health impact projections. To enhance the evidence base, there must be increased attention to designing, evaluating, and reporting adaptation interventions; standardized health impact projection reporting; and increased attention to knowledge translation. This approach has implications for funders, researchers, journal editors, practitioners, and policy makers. The current approach to EBPH can, with modifications, support climate change adaptation activities, but there is little evidence regarding interventions and knowledge translation, and guidelines for projecting health impacts are lacking. Realizing the goal of an evidence-based approach will require systematic, coordinated efforts among various stakeholders.

Evaluation of an Adaptive Game that Uses EEG Measures Validated during the Design Process as Inputs to a Biocybernetic Loop.

PubMed

Ewing, Kate C; Fairclough, Stephen H; Gilleade, Kiel

2016-01-01

Biocybernetic adaptation is a form of physiological computing whereby real-time data streaming from the brain and body is used by a negative control loop to adapt the user interface. This article describes the development of an adaptive game system that is designed to maximize player engagement by utilizing changes in real-time electroencephalography (EEG) to adjust the level of game demand. The research consists of four main stages: (1) the development of a conceptual framework upon which to model the interaction between person and system; (2) the validation of the psychophysiological inference underpinning the loop; (3) the construction of a working prototype; and (4) an evaluation of the adaptive game. Two studies are reported. The first demonstrates the sensitivity of EEG power in the (frontal) theta and (parietal) alpha bands to changing levels of game demand. These variables were then reformulated within the working biocybernetic control loop designed to maximize player engagement. The second study evaluated the performance of an adaptive game of Tetris with respect to system behavior and user experience. Important issues for the design and evaluation of closed-loop interfaces are discussed.

Evaluation of an Adaptive Game that Uses EEG Measures Validated during the Design Process as Inputs to a Biocybernetic Loop

PubMed Central

Ewing, Kate C.; Fairclough, Stephen H.; Gilleade, Kiel

2016-01-01

Biocybernetic adaptation is a form of physiological computing whereby real-time data streaming from the brain and body is used by a negative control loop to adapt the user interface. This article describes the development of an adaptive game system that is designed to maximize player engagement by utilizing changes in real-time electroencephalography (EEG) to adjust the level of game demand. The research consists of four main stages: (1) the development of a conceptual framework upon which to model the interaction between person and system; (2) the validation of the psychophysiological inference underpinning the loop; (3) the construction of a working prototype; and (4) an evaluation of the adaptive game. Two studies are reported. The first demonstrates the sensitivity of EEG power in the (frontal) theta and (parietal) alpha bands to changing levels of game demand. These variables were then reformulated within the working biocybernetic control loop designed to maximize player engagement. The second study evaluated the performance of an adaptive game of Tetris with respect to system behavior and user experience. Important issues for the design and evaluation of closed-loop interfaces are discussed. PMID:27242486

A Climate Change Adaptation Strategy for Management of ...

EPA Pesticide Factsheets

Sea level rise is causing shoreline erosion, increased coastal flooding, and marsh vulnerability to the impact of storms. Coastal marshes provide flood abatement, carbon and nutrient sequestration, water quality maintenance, and habitat for fish, shellfish, and wildlife, including species of concern, such as the saltmarsh sparrow (Ammodramus caudacutus). We present a climate change adaptation strategy (CCAS) adopted by scientific, management, and policy stakeholders for managing coastal marshes and enhancing system resiliency. A common adaptive management approach previously used for restoration projects was modified to identify climate-related vulnerabilities and plan climate change adaptive actions. As an example of implementation of the CCAS, we describe the stakeholder plans and management actions the US Fish and Wildlife Service and partners developed to build coastal resiliency in the Narrow River Estuary, RI, in the aftermath of Superstorm Sandy. When possible, an experimental BACI (before-after, control-impact) design, described as pre- and post-sampling at the impact site and one or more control sites, was incorporated into the climate change adaptation and implementation plans. Specific climate change adaptive actions and monitoring plans are described and include shoreline stabilization, restoring marsh drainage, increasing marsh elevation, and enabling upland marsh migration. The CCAS provides a framework and methodology for successfully managing coa

Frameworks and Tools for High-Confidence Design of Adaptive, Distributed Embedded Control Systems. Multi-University Research Initiative on High-Confidence Design for Distributed Embedded Systems

DTIC Science & Technology

2009-01-01

controllers (currently using the Robostix+Gumstix pair ). The interface between the plant simulator and the controller is ‘hard real-time’, and the xPC box... simulation ) on aerobatic maneuver design for the STARMAC quadrotor helicopter testbed. In related work, we have developed a new optimization scheme...for scheduling hybrid systems, and have demonstrated the results on an autonomous car simulation testbed. We are focusing efforts this summer for

Managing urban water systems with significant adaptation deficits - a unified framework for secondary cities

NASA Astrophysics Data System (ADS)

Pathirana, A.; Radhakrishnan, M.; Zevenbergen, C.; Quan, N. H.

2016-12-01

The need to address the shortcomings of urban systems - adaptation deficit - and shortcomings in response to climate change - `adaptation gap' - are both major challenges in maintaining the livability and sustainability of cities. However, the adaptation actions defined in terms of type I (addressing adaptation deficits) and type II (addressing adaptation gaps), often compete and conflict each other in the secondary cities of the global south. Extending the concept of the environmental Kuznets curve, this paper argues that a unified framework that calls for synergistic action on type I and type II adaptation is essential in order for these cities to maintain their livability, sustainability and resilience facing extreme rates of urbanization and rapid onset of climate change. The proposed framework has been demonstrated in Can Tho, Vietnam, where there are significant adaptation deficits due to rapid urbanisation and adaptation gaps due to climate change and socio-economic changes. The analysis in Can Tho reveals the lack of integration between type I and type II measures that could be overcome by closer integration between various stakeholders in terms of planning, prioritising and implementing the adaptation measures.

IMHOTEP: virtual reality framework for surgical applications.

PubMed

Pfeiffer, Micha; Kenngott, Hannes; Preukschas, Anas; Huber, Matthias; Bettscheider, Lisa; Müller-Stich, Beat; Speidel, Stefanie

2018-05-01

The data which is available to surgeons before, during and after surgery is steadily increasing in quantity as well as diversity. When planning a patient's treatment, this large amount of information can be difficult to interpret. To aid in processing the information, new methods need to be found to present multimodal patient data, ideally combining textual, imagery, temporal and 3D data in a holistic and context-aware system. We present an open-source framework which allows handling of patient data in a virtual reality (VR) environment. By using VR technology, the workspace available to the surgeon is maximized and 3D patient data is rendered in stereo, which increases depth perception. The framework organizes the data into workspaces and contains tools which allow users to control, manipulate and enhance the data. Due to the framework's modular design, it can easily be adapted and extended for various clinical applications. The framework was evaluated by clinical personnel (77 participants). The majority of the group stated that a complex surgical situation is easier to comprehend by using the framework, and that it is very well suited for education. Furthermore, the application to various clinical scenarios-including the simulation of excitation propagation in the human atrium-demonstrated the framework's adaptability. As a feasibility study, the framework was used during the planning phase of the surgical removal of a large central carcinoma from a patient's liver. The clinical evaluation showed a large potential and high acceptance for the VR environment in a medical context. The various applications confirmed that the framework is easily extended and can be used in real-time simulation as well as for the manipulation of complex anatomical structures.

The Role of Perceived Parental Autonomy Support in Academic Achievement of Asian and Latino American Adolescents

ERIC Educational Resources Information Center

Jiang, Ying Hong; Yau, Jenny; Bonner, Patricia; Chiang, Linda

2011-01-01

Introduction: Driven by an overarching conceptual framework adapted from Self-Determination Theory, this study tested the direct and indirect effects of perceived parental academia autonomy support vs. academic planning control on the interrelated variables of adolescents' self-esteem, academic motivation, and academic achievement, using…

Lifespan Development of Neuromodulation of Adaptive Control and Motivation as an Ontogenetic Mechanism for Developmental Niche Construction

ERIC Educational Resources Information Center

Li, Shu-Chen

2013-01-01

Instead of viewing organisms and individuals as passive recipients of their biological, ecological, and cultural inheritances, the developmental niche construction theory and the biocultural co-construction framework both emphasize that the individual's agency plays a key role in regulating how environmental and sociocontextual influences may…

Monitoring and evaluation framework for hypertension programs. A collaboration between the Pan American Health Organization and World Hypertension League.

PubMed

Campbell, Norm R C; Ordunez, Pedro; DiPette, Donald J; Giraldo, Gloria P; Angell, Sonia Y; Jaffe, Marc G; Lackland, Dan; Martinez, Ramón; Valdez, Yamilé; Maldonado Figueredo, Javier I; Paccot, Melanie; Santana, Maria J; Whelton, Paul K

2018-06-01

The Pan American Health Organization (PAHO)-World Hypertension League (WHL) Hypertension Monitoring and Evaluation Framework is summarized. Standardized indicators are provided for monitoring and evaluating national or subnational hypertension control programs. Five core indicators from the World Health Organization hearts initiative and a single PAHO-WHL core indicator are recommended to be used in all hypertension control programs. In addition, hypertension control programs are encouraged to select from 14 optional qualitative and 33 quantitative indicators to facilitate progress towards enhanced hypertension control. The intention is for hypertension programs to select quantitative indicators based on the current surveillance mechanisms that are available and what is feasible and to use the framework process indicators as a guide to program management. Programs may wish to increase or refine the number of indicators they use over time. With adaption the indicators can also be implemented at a community or clinic level. The standardized indicators are being pilot tested in Cuba, Colombia, Chile, and Barbados. ©2018 Wiley Periodicals, Inc.

Compression-based integral curve data reuse framework for flow visualization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hong, Fan; Bi, Chongke; Guo, Hanqi

Currently, by default, integral curves are repeatedly re-computed in different flow visualization applications, such as FTLE field computation, source-destination queries, etc., leading to unnecessary resource cost. We present a compression-based data reuse framework for integral curves, to greatly reduce their retrieval cost, especially in a resource-limited environment. In our design, a hierarchical and hybrid compression scheme is proposed to balance three objectives, including high compression ratio, controllable error, and low decompression cost. Specifically, we use and combine digitized curve sparse representation, floating-point data compression, and octree space partitioning to adaptively achieve the objectives. Results have shown that our data reusemore » framework could acquire tens of times acceleration in the resource-limited environment compared to on-the-fly particle tracing, and keep controllable information loss. Moreover, our method could provide fast integral curve retrieval for more complex data, such as unstructured mesh data.« less

A Novel Extreme Learning Control Framework of Unmanned Surface Vehicles.

PubMed

Wang, Ning; Sun, Jing-Chao; Er, Meng Joo; Liu, Yan-Cheng

2016-05-01

In this paper, an extreme learning control (ELC) framework using the single-hidden-layer feedforward network (SLFN) with random hidden nodes for tracking an unmanned surface vehicle suffering from unknown dynamics and external disturbances is proposed. By combining tracking errors with derivatives, an error surface and transformed states are defined to encapsulate unknown dynamics and disturbances into a lumped vector field of transformed states. The lumped nonlinearity is further identified accurately by an extreme-learning-machine-based SLFN approximator which does not require a priori system knowledge nor tuning input weights. Only output weights of the SLFN need to be updated by adaptive projection-based laws derived from the Lyapunov approach. Moreover, an error compensator is incorporated to suppress approximation residuals, and thereby contributing to the robustness and global asymptotic stability of the closed-loop ELC system. Simulation studies and comprehensive comparisons demonstrate that the ELC framework achieves high accuracy in both tracking and approximation.

Adaptive critic designs for optimal control of uncertain nonlinear systems with unmatched interconnections.

PubMed

Yang, Xiong; He, Haibo

2018-05-26

In this paper, we develop a novel optimal control strategy for a class of uncertain nonlinear systems with unmatched interconnections. To begin with, we present a stabilizing feedback controller for the interconnected nonlinear systems by modifying an array of optimal control laws of auxiliary subsystems. We also prove that this feedback controller ensures a specified cost function to achieve optimality. Then, under the framework of adaptive critic designs, we use critic networks to solve the Hamilton-Jacobi-Bellman equations associated with auxiliary subsystem optimal control laws. The critic network weights are tuned through the gradient descent method combined with an additional stabilizing term. By using the newly established weight tuning rules, we no longer need the initial admissible control condition. In addition, we demonstrate that all signals in the closed-loop auxiliary subsystems are stable in the sense of uniform ultimate boundedness by using classic Lyapunov techniques. Finally, we provide an interconnected nonlinear plant to validate the present control scheme. Copyright © 2018 Elsevier Ltd. All rights reserved.

Ecological mechanisms underpinning climate adaptation services.

PubMed

Lavorel, Sandra; Colloff, Matthew J; McIntyre, Sue; Doherty, Michael D; Murphy, Helen T; Metcalfe, Daniel J; Dunlop, Michael; Williams, Richard J; Wise, Russell M; Williams, Kristen J

2015-01-01

Ecosystem services are typically valued for their immediate material or cultural benefits to human wellbeing, supported by regulating and supporting services. Under climate change, with more frequent stresses and novel shocks, 'climate adaptation services', are defined as the benefits to people from increased social ability to respond to change, provided by the capability of ecosystems to moderate and adapt to climate change and variability. They broaden the ecosystem services framework to assist decision makers in planning for an uncertain future with new choices and options. We present a generic framework for operationalising the adaptation services concept. Four steps guide the identification of intrinsic ecological mechanisms that facilitate the maintenance and emergence of ecosystem services during periods of change, and so materialise as adaptation services. We applied this framework for four contrasted Australian ecosystems. Comparative analyses enabled by the operational framework suggest that adaptation services that emerge during trajectories of ecological change are supported by common mechanisms: vegetation structural diversity, the role of keystone species or functional groups, response diversity and landscape connectivity, which underpin the persistence of function and the reassembly of ecological communities under severe climate change and variability. Such understanding should guide ecosystem management towards adaptation planning. © 2014 John Wiley & Sons Ltd.

Adaptive tracking control for active suspension systems with non-ideal actuators

NASA Astrophysics Data System (ADS)

Pan, Huihui; Sun, Weichao; Jing, Xingjian; Gao, Huijun; Yao, Jianyong

2017-07-01

As a critical component of transportation vehicles, active suspension systems are instrumental in the improvement of ride comfort and maneuverability. However, practical active suspensions commonly suffer from parameter uncertainties (e.g., the variations of payload mass and suspension component parameters), external disturbances and especially the unknown non-ideal actuators (i.e., dead-zone and hysteresis nonlinearities), which always significantly deteriorate the control performance in practice. To overcome these issues, this paper synthesizes an adaptive tracking control strategy for vehicle suspension systems to achieve suspension performance improvements. The proposed control algorithm is formulated by developing a unified framework of non-ideal actuators rather than a separate way, which is a simple yet effective approach to remove the unexpected nonlinear effects. From the perspective of practical implementation, the advantages of the presented controller for active suspensions include that the assumptions on the measurable actuator outputs, the prior knowledge of nonlinear actuator parameters and the uncertain parameters within a known compact set are not required. Furthermore, the stability of the closed-loop suspension system is theoretically guaranteed by rigorous mathematical analysis. Finally, the effectiveness of the presented adaptive control scheme is confirmed using comparative numerical simulation validations.

A Conceptual Framework for Planning Systemic Human Adaptation to Global Warming

PubMed Central

Tait, Peter W.; Hanna, Elizabeth G.

2015-01-01

Human activity is having multiple, inter-related effects on ecosystems. Greenhouse gas emissions persisting along current trajectories threaten to significantly alter human society. At 0.85 °C of anthropogenic warming, deleterious human impacts are acutely evident. Additional warming of 0.5 °C–1.0 °C from already emitted CO2 will further intensify extreme heat and damaging storm events. Failing to sufficiently address this trend will have a heavy human toll directly and indirectly on health. Along with mitigation efforts, societal adaptation to a warmer world is imperative. Adaptation efforts need to be significantly upscaled to prepare society to lessen the public health effects of rising temperatures. Modifying societal behaviour is inherently complex and presents a major policy challenge. We propose a social systems framework for conceptualizing adaptation that maps out three domains within the adaptation policy landscape: acclimatisation, behavioural adaptation and technological adaptation, which operate at societal and personal levels. We propose that overlaying this framework on a systems approach to societal change planning methods will enhance governments’ capacity and efficacy in strategic planning for adaptation. This conceptual framework provides a policy oriented planning assessment tool that will help planners match interventions to the behaviours being targeted for change. We provide illustrative examples to demonstrate the framework’s application as a planning tool. PMID:26334285

High precision tracking of a piezoelectric nano-manipulator with parameterized hysteresis compensation

NASA Astrophysics Data System (ADS)

Yan, Peng; Zhang, Yangming

2018-06-01

High performance scanning of nano-manipulators is widely deployed in various precision engineering applications such as SPM (scanning probe microscope), where trajectory tracking of sophisticated reference signals is an challenging control problem. The situation is further complicated when rate dependent hysteresis of the piezoelectric actuators and the stress-stiffening induced nonlinear stiffness of the flexure mechanism are considered. In this paper, a novel control framework is proposed to achieve high precision tracking of a piezoelectric nano-manipulator subjected to hysteresis and stiffness nonlinearities. An adaptive parameterized rate-dependent Prandtl-Ishlinskii model is constructed and the corresponding adaptive inverse model based online compensation is derived. Meanwhile a robust adaptive control architecture is further introduced to improve the tracking accuracy and robustness of the compensated system, where the parametric uncertainties of the nonlinear dynamics can be well eliminated by on-line estimations. Comparative experimental studies of the proposed control algorithm are conducted on a PZT actuated nano-manipulating stage, where hysteresis modeling accuracy and excellent tracking performance are demonstrated in real-time implementations, with significant improvement over existing results.

Intelligent Control of a Sensor-Actuator System via Kernelized Least-Squares Policy Iteration

PubMed Central

Liu, Bo; Chen, Sanfeng; Li, Shuai; Liang, Yongsheng

2012-01-01

In this paper a new framework, called Compressive Kernelized Reinforcement Learning (CKRL), for computing near-optimal policies in sequential decision making with uncertainty is proposed via incorporating the non-adaptive data-independent Random Projections and nonparametric Kernelized Least-squares Policy Iteration (KLSPI). Random Projections are a fast, non-adaptive dimensionality reduction framework in which high-dimensionality data is projected onto a random lower-dimension subspace via spherically random rotation and coordination sampling. KLSPI introduce kernel trick into the LSPI framework for Reinforcement Learning, often achieving faster convergence and providing automatic feature selection via various kernel sparsification approaches. In this approach, policies are computed in a low-dimensional subspace generated by projecting the high-dimensional features onto a set of random basis. We first show how Random Projections constitute an efficient sparsification technique and how our method often converges faster than regular LSPI, while at lower computational costs. Theoretical foundation underlying this approach is a fast approximation of Singular Value Decomposition (SVD). Finally, simulation results are exhibited on benchmark MDP domains, which confirm gains both in computation time and in performance in large feature spaces. PMID:22736969

Explicit and implicit emotion regulation: a multi-level framework

PubMed Central

Braunstein, Laura Martin; Gross, James J

2017-01-01

Abstract The ability to adaptively regulate emotion is essential for mental and physical well-being. How should we organize the myriad ways people attempt to regulate their emotions? We explore the utility of a framework that distinguishes among four fundamental classes of emotion regulation strategies. The framework describes each strategy class in terms their behavioral characteristics, underlying psychological processes and supporting neural systems. A key feature of this multi-level framework is its conceptualization of the psychological processes in terms of two orthogonal dimensions that describe (i) the nature of the emotion regulation goal (ranging from to implicit to explicit) and (ii) the nature of the emotion change process (ranging from more automatic to more controlled). After describing the core elements of the framework, we use it to review human and animal research on the neural bases of emotion regulation and to suggest key directions for future research on emotion regulation. PMID:28981910

Examining household asthma management behavior through a microeconomic framework.

PubMed

Magzamen, Sheryl; Brandt, Sylvia J; Tager, Ira B

2014-12-01

National guidelines on the effective management of pediatric asthma have been promoted for over 20 years, yet asthma-related morbidity among low-income children remains disproportionately high. To date, household and clinical interventions designed to remediate these differences have been informed largely by a health behavior framework. However, these programs have not resulted in consistent sustained improvements in targeted populations. The continued funding and implementation of programs based on the health behavior framework leads us to question if traditional behavioral models are sufficient to understand and promote adaptation of positive health management behaviors. We introduce the application of the microeconomic framework to investigate potential mechanisms that can lead to positive management behaviors to improve asthma-related morbidity. We provide examples from the literature on health production, preferences, trade-offs and time horizons to illustrate how economic constructs can potentially add to understanding of disease management. The economic framework, which can be empirically observed, tested, and quantified, can explicate the engagement in household-level activities that would affect health and well-being. The inclusion of a microeconomic perspective in intervention research may lead to identification of mechanisms that lead to household decisions with regard to asthma management strategies and behavior. The inclusion of the microeconomic framework to understand the production of health may provide a novel theoretical framework to investigate the underlying causal behavioral mechanisms related to asthma management and control. Adaptation of an economic perspective may provide new insight into the design and implementation of interventions to improve asthma-related morbidity in susceptible populations. © 2014 Society for Public Health Education.

An environmental decision framework applied to marine engine control technologies.

PubMed

Corbett, James J; Chapman, David

2006-06-01

This paper develops a decision framework for considering emission control technologies on marine engines, informed by standard decision theory, with an open structure that may be adapted by operators with specific vessel and technology attributes different from those provided here. Attributes relate objectives important to choosing control technologies with specific alternatives that may meet several of the objectives differently. The transparent framework enables multiple stakeholders to understand how different subjective judgments and varying attribute properties may result in different technology choices. Standard scoring techniques ensure that attributes are not biased by subjective scoring and that weights are the primary quantitative input where subjective preferences are exercised. An expected value decision structure is adopted that considers probabilities (likelihood) that a given alternative can meet its claims; alternative decision criteria are discussed. Capital and annual costs are combined using a net present value approach. An iterative approach is advocated that allows for screening and disqualifying alternatives that do not meet minimum conditions for acceptance, such as engine warranty or U.S. Coast Guard requirements. This decision framework assists vessel operators in considering explicitly important attributes and in representing choices clearly to other stakeholders concerned about reducing air pollution from vessels. This general decision structure may also be applied similarly to other environmental controls in marine applications.

Water Hyacinth in China: A Sustainability Science-Based Management Framework

NASA Astrophysics Data System (ADS)

Lu, Jianbo; Wu, Jianguo; Fu, Zhihui; Zhu, Lei

2007-12-01

The invasion of water hyacinth ( Eichhornia crassipes) has resulted in enormous ecological and economic consequences worldwide. Although the spread of this weed in Africa, Australia, and North America has been well documented, its invasion in China is yet to be fully documented. Here we report that since its introduction about seven decades ago, water hyacinth has infested many water bodies across almost half of China’s territory, causing a decline of native biodiversity, alteration of ecosystem services, deterioration of aquatic environments, and spread of diseases affecting human health. Water hyacinth infestations have also led to enormous economic losses in China by impeding water flows, paralyzing navigation, and damaging irrigation and hydroelectricity facilities. To effectively control the rampage of water hyacinth in China, we propose a sustainability science-based management framework that explicitly incorporates principles from landscape ecology and Integrated Pest Management. This framework emphasizes multiple-scale long-term monitoring and research, integration among different control techniques, combination of control with utilization, and landscape-level adaptive management. Sustainability science represents a new, transdisciplinary paradigm that integrates scientific research, technological innovation, and socioeconomic development of particular regions. Our proposed management framework is aimed to broaden the currently dominant biological control-centered view in China and to illustrate how sustainability science can be used to guide the research and management of water hyacinth.

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

PubMed Central

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

2015-01-01

The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that “Everything is everywhere, but the environment selects”, we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean. PMID:25852217

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

PubMed

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

2015-01-01

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

Motivation and engagement in music and sport: testing a multidimensional framework in diverse performance settings.

PubMed

Martin, Andrew J

2008-02-01

The present study assessed the application of a multidimensional model of motivation and engagement (the Motivation and Engagement Wheel) and its accompanying instrumentation (the Motivation and Engagement Scale) to the music and sport domains. Participants were 463 young classical musicians (N=224) and sportspeople (N=239). In both music and sport samples, the data confirmed the good fit of the four hypothesized higher-order dimensions and their 11 first-order dimensions: adaptive cognitions (self-efficacy, valuing, mastery orientation), adaptive behaviors (planning, task management, persistence), impeding/maladaptive cognitions (uncertain control, anxiety, failure avoidance), and maladaptive behaviors (self-handicapping, disengagement). Multigroup tests of factor invariance showed that in terms of underlying motivational constructs and the composition of and relationships among these constructs, key subsamples are not substantially different. Moreover-and of particular relevance to issues around the generalizability of the framework-the factor structure for music and sport samples was predominantly invariant.

Spatial, Hysteretic, and Adaptive Host-Guest Chemistry in a Metal-Organic Framework with Open Watson-Crick Sites.

PubMed

Cai, Hong; Li, Mian; Lin, Xiao-Rong; Chen, Wei; Chen, Guang-Hui; Huang, Xiao-Chun; Li, Dan

2015-09-01

Biological and artificial molecules and assemblies capable of supramolecular recognition, especially those with nucleobase pairing, usually rely on autonomous or collective binding to function. Advanced site-specific recognition takes advantage of cooperative spatial effects, as in local folding in protein-DNA binding. Herein, we report a new nucleobase-tagged metal-organic framework (MOF), namely ZnBTCA (BTC=benzene-1,3,5-tricarboxyl, A=adenine), in which the exposed Watson-Crick faces of adenine residues are immobilized periodically on the interior crystalline surface. Systematic control experiments demonstrated the cooperation of the open Watson-Crick sites and spatial effects within the nanopores, and thermodynamic and kinetic studies revealed a hysteretic host-guest interaction attributed to mild chemisorption. We further exploited this behavior for adenine-thymine binding within the constrained pores, and a globally adaptive response of the MOF host was observed. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ActiveTutor: Towards More Adaptive Features in an E-Learning Framework

ERIC Educational Resources Information Center

Fournier, Jean-Pierre; Sansonnet, Jean-Paul

2008-01-01

Purpose: This paper aims to sketch the emerging notion of auto-adaptive software when applied to e-learning software. Design/methodology/approach: The study and the implementation of the auto-adaptive architecture are based on the operational framework "ActiveTutor" that is used for teaching the topic of computer science programming in first-grade…

A study of an adaptive replication framework for orchestrated composite web services.

PubMed

Mohamed, Marwa F; Elyamany, Hany F; Nassar, Hamed M

2013-01-01

Replication is considered one of the most important techniques to improve the Quality of Services (QoS) of published Web Services. It has achieved impressive success in managing resource sharing and usage in order to moderate the energy consumed in IT environments. For a robust and successful replication process, attention should be paid to suitable time as well as the constraints and capabilities in which the process runs. The replication process is time-consuming since outsourcing some new replicas into other hosts is lengthy. Furthermore, nowadays, most of the business processes that might be implemented over the Web are composed of multiple Web services working together in two main styles: Orchestration and Choreography. Accomplishing a replication over such business processes is another challenge due to the complexity and flexibility involved. In this paper, we present an adaptive replication framework for regular and orchestrated composite Web services. The suggested framework includes a number of components for detecting unexpected and unhappy events that might occur when consuming the original published web services including failure or overloading. It also includes a specific replication controller to manage the replication process and select the best host that would encapsulate a new replica. In addition, it includes a component for predicting the incoming load in order to decrease the time needed for outsourcing new replicas, enhancing the performance greatly. A simulation environment has been created to measure the performance of the suggested framework. The results indicate that adaptive replication with prediction scenario is the best option for enhancing the performance of the replication process in an online business environment.

The Complex Nature of Bilinguals' Language Usage Modulates Task-Switching Outcomes

PubMed Central

Yang, Hwajin; Hartanto, Andree; Yang, Sujin

2016-01-01

In view of inconsistent findings regarding bilingual advantages in executive functions (EF), we reviewed the literature to determine whether bilinguals' different language usage causes measureable changes in the shifting aspects of EF. By drawing on the theoretical framework of the adaptive control hypothesis—which postulates a critical link between bilinguals' varying demands on language control and adaptive cognitive control (Green and Abutalebi, 2013), we examined three factors that characterize bilinguals' language-switching experience: (a) the interactional context of conversational exchanges, (b) frequency of language switching, and (c) typology of code-switching. We also examined whether methodological variations in previous task-switching studies modulate task-specific demands on control processing and lead to inconsistencies in the literature. Our review demonstrates that not only methodological rigor but also a more finely grained, theory-based approach will be required to understand the cognitive consequences of bilinguals' varied linguistic practices in shifting EF. PMID:27199800

Online human training of a myoelectric prosthesis controller via actor-critic reinforcement learning.

PubMed

Pilarski, Patrick M; Dawson, Michael R; Degris, Thomas; Fahimi, Farbod; Carey, Jason P; Sutton, Richard S

2011-01-01

As a contribution toward the goal of adaptable, intelligent artificial limbs, this work introduces a continuous actor-critic reinforcement learning method for optimizing the control of multi-function myoelectric devices. Using a simulated upper-arm robotic prosthesis, we demonstrate how it is possible to derive successful limb controllers from myoelectric data using only a sparse human-delivered training signal, without requiring detailed knowledge about the task domain. This reinforcement-based machine learning framework is well suited for use by both patients and clinical staff, and may be easily adapted to different application domains and the needs of individual amputees. To our knowledge, this is the first my-oelectric control approach that facilitates the online learning of new amputee-specific motions based only on a one-dimensional (scalar) feedback signal provided by the user of the prosthesis. © 2011 IEEE

Active Inference, homeostatic regulation and adaptive behavioural control

PubMed Central

Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl

2015-01-01

We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference. PMID:26365173

Building the framework for climate change adaptation in the urban areas using participatory approach: the Czech Republic experience

NASA Astrophysics Data System (ADS)

Emmer, Adam; Hubatová, Marie; Lupač, Miroslav; Pondělíček, Michael; Šafařík, Miroslav; Šilhánková, Vladimíra; Vačkář, David

2016-04-01

The Czech Republic has experienced numerous extreme hydrometeorological / climatological events such as floods (significant ones in 1997, 2002, 2010, 2013), droughts (2013, 2015), heat waves (2015) and windstorms (2007) during past decades. These events are generally attributed to the ongoing climate change and caused loss of lives and significant material damages (up to several % of GDP in some years), especially in urban areas. To initiate the adaptation process of urban areas, the main objective was to prepare a framework for creating climate change adaptation strategies of individual cities reflecting physical-geographical and socioeconomical conditions of the Czech Republic. Three pilot cities (Hradec Králové, Žďár nad Sázavou, Dobru\\vska) were used to optimize entire procedure. Two sets of participatory seminars were organised in order to involve all key stakeholders (the city council, department of the environment, department of the crisis management, hydrometeorological institute, local experts, ...) into the process of creation of the adaptation strategy from its early stage. Lesson learned for the framework were related especially to its applicability on a local level, which is largely a matter of the understandability of the concept. Finally, this illustrative and widely applicable framework (so called 'road map to adaptation strategy') includes five steps: (i) analysis of existing strategies and plans on national, regional and local levels; (ii) analysing climate-change related hazards and key vulnerabilities; (iii) identification of adaptation needs, evaluation of existing adaptation capacity and formulation of future adaptation priorities; (iv) identification of limits and barriers for the adaptation (economical, environmental, ...); and (v) selection of specific types of adaptation measures reflecting identified adaptation needs and formulated adaptation priorities. Keywords: climate change adaptation (CCA); urban areas; participatory approach; road map

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

PubMed

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

2015-01-01

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

Adaptive acoustic energy delivery to near and far fields using foldable, tessellated star transducers

NASA Astrophysics Data System (ADS)

Zou, Chengzhe; Harne, Ryan L.

2017-05-01

Methods of guiding acoustic energy arbitrarily through space have long relied on digital controls to meet performance needs. Yet, more recent attention to adaptive structures with unique spatial configurations has motivated mechanical signal processing (MSP) concepts that may not be subjected to the same functional and performance limitations as digital acoustic beamforming counterparts. The periodicity of repeatable structural reconfiguration enabled by origami-inspired tessellated architectures turns attention to foldable platforms as frameworks for MSP development. This research harnesses principles of MSP to study a tessellated, star-shaped acoustic transducer constituent that provides on-demand control of acoustic energy guiding via folding-induced shape reconfiguration. An analytical framework is established to probe the roles of mechanical and acoustic geometry on the far field directivity and near field focusing of sound energy. Following validation by experiments and verification by simulations, parametric studies are undertaken to uncover relations between constituent topology and acoustic energy delivery to arbitrary points in the free field. The adaptations enabled by folding of the star-shaped transducer reveal capability for restricting sound energy to angular regions in the far field while also introducing means to modulate sound energy by three orders-of-magnitude to locations near to the transducer surface. In addition, the modeling philosophy devised here provides a valuable approach to solve general sound radiation problems for foldable, tessellated acoustic transducer constituents of arbitrary geometry.

Patch models and their applications to multivehicle command and control.

PubMed

Rao, Venkatesh G; D'Andrea, Raffaello

2007-06-01

We introduce patch models, a computational modeling formalism for multivehicle combat domains, based on spatiotemporal abstraction methods developed in the computer science community. The framework yields models that are expressive enough to accommodate nontrivial controlled vehicle dynamics while being within the representational capabilities of common artificial intelligence techniques used in the construction of autonomous systems. The framework allows several key design requirements of next-generation network-centric command and control systems, such as maintenance of shared situation awareness, to be achieved. Major features include support for multiple situation models at each decision node and rapid mission plan adaptation. We describe the formal specification of patch models and our prototype implementation, i.e., Patchworks. The capabilities of patch models are validated through a combat mission simulation in Patchworks, which involves two defending teams protecting a camp from an enemy attacking team.

Adaptive NN controller design for a class of nonlinear MIMO discrete-time systems.

PubMed

Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip

2015-05-01

An adaptive neural network tracking control is studied for a class of multiple-input multiple-output (MIMO) nonlinear systems. The studied systems are in discrete-time form and the discretized dead-zone inputs are considered. In addition, the studied MIMO systems are composed of N subsystems, and each subsystem contains unknown functions and external disturbance. Due to the complicated framework of the discrete-time systems, the existence of the dead zone and the noncausal problem in discrete-time, it brings about difficulties for controlling such a class of systems. To overcome the noncausal problem, by defining the coordinate transformations, the studied systems are transformed into a special form, which is suitable for the backstepping design. The radial basis functions NNs are utilized to approximate the unknown functions of the systems. The adaptation laws and the controllers are designed based on the transformed systems. By using the Lyapunov method, it is proved that the closed-loop system is stable in the sense that the semiglobally uniformly ultimately bounded of all the signals and the tracking errors converge to a bounded compact set. The simulation examples and the comparisons with previous approaches are provided to illustrate the effectiveness of the proposed control algorithm.

Experiments in Nonlinear Adaptive Control of Multi-Manipulator, Free-Flying Space Robots

NASA Technical Reports Server (NTRS)

Chen, Vincent Wei-Kang

1992-01-01

Sophisticated robots can greatly enhance the role of humans in space by relieving astronauts of low level, tedious assembly and maintenance chores and allowing them to concentrate on higher level tasks. Robots and astronauts can work together efficiently, as a team; but the robot must be capable of accomplishing complex operations and yet be easy to use. Multiple cooperating manipulators are essential to dexterity and can broaden greatly the types of activities the robot can achieve; adding adaptive control can ease greatly robot usage by allowing the robot to change its own controller actions, without human intervention, in response to changes in its environment. Previous work in the Aerospace Robotics Laboratory (ARL) have shown the usefulness of a space robot with cooperating manipulators. The research presented in this dissertation extends that work by adding adaptive control. To help achieve this high level of robot sophistication, this research made several advances to the field of nonlinear adaptive control of robotic systems. A nonlinear adaptive control algorithm developed originally for control of robots, but requiring joint positions as inputs, was extended here to handle the much more general case of manipulator endpoint-position commands. A new system modelling technique, called system concatenation was developed to simplify the generation of a system model for complicated systems, such as a free-flying multiple-manipulator robot system. Finally, the task-space concept was introduced wherein the operator's inputs specify only the robot's task. The robot's subsequent autonomous performance of each task still involves, of course, endpoint positions and joint configurations as subsets. The combination of these developments resulted in a new adaptive control framework that is capable of continuously providing full adaptation capability to the complex space-robot system in all modes of operation. The new adaptive control algorithm easily handles free-flying systems with multiple, interacting manipulators, and extends naturally to even larger systems. The new adaptive controller was experimentally demonstrated on an ideal testbed in the ARL-A first-ever experimental model of a multi-manipulator, free-flying space robot that is capable of capturing and manipulating free-floating objects without requiring human assistance. A graphical user interface enhanced the robot usability: it enabled an operator situated at a remote location to issue high-level task description commands to the robot, and to monitor robot activities as it then carried out each assignment autonomously.

Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir

Treesearch

Nicholas C. Wheeler; Kathleen D. Jermstad; Konstantin V. Krutovsky; Sally N. Aitken; Glenn T. Howe; Jodie Krakowski; David B. Neale

2005-01-01

Quantitative trait locus (QTL) analyses are used by geneticists to characterize the genetic architecture of quantitative traits, provide a foundation for marker-aided-selection (MAS), and provide a framework for positional selection of candidate genes. The most useful QTL for breeding applications are those that have been verified in time, space, and/or genetic...

Making Healthy Eating and Physical Activity Policy Practice: Process Evaluation of a Group Randomized Controlled Intervention in Afterschool Programs

ERIC Educational Resources Information Center

Weaver, R. Glenn; Beets, Michael W.; Hutto, Brent; Saunders, Ruth P.; Moore, Justin B.; Turner-McGrievy, Gabrielle; Huberty, Jennifer L.; Ward, Dianne S.; Pate, Russell R.; Beighle, Aaron; Freedman, Darcy

2015-01-01

This study describes the link between level of implementation and outcomes from an intervention to increase afterschool programs' (ASPs) achievement of healthy eating and physical activity (HE-PA) Standards. Ten intervention ASPs implemented the Strategies-To-Enhance-Practice (STEPs), a multi-component, adaptive intervention framework identifying…

Multivariable adaptive closed-loop control of an artificial pancreas without meal and activity announcement.

PubMed

Turksoy, Kamuran; Bayrak, Elif Seyma; Quinn, Lauretta; Littlejohn, Elizabeth; Cinar, Ali

2013-05-01

Accurate closed-loop control is essential for developing artificial pancreas (AP) systems that adjust insulin infusion rates from insulin pumps. Glucose concentration information from continuous glucose monitoring (CGM) systems is the most important information for the control system. Additional physiological measurements can provide valuable information that can enhance the accuracy of the control system. Proportional-integral-derivative control and model predictive control have been popular in AP development. Their implementations to date rely on meal announcements (e.g., bolus insulin dose based on insulin:carbohydrate ratios) by the user. Adaptive control techniques provide a powerful alternative that do not necessitate any meal or activity announcements. Adaptive control systems based on the generalized predictive control framework are developed by extending the recursive modeling techniques. Physiological signals such as energy expenditure and galvanic skin response are used along with glucose measurements to generate a multiple-input-single-output model for predicting future glucose concentrations used by the controller. Insulin-on-board (IOB) is also estimated and used in control decisions. The controllers were tested with clinical studies that include seven cases with three different patients with type 1 diabetes for 32 or 60 h without any meal or activity announcements. The adaptive control system kept glucose concentration in the normal preprandial and postprandial range (70-180 mg/dL) without any meal or activity announcements during the test period. After IOB estimation was added to the control system, mild hypoglycemic episodes were observed only in one of the four experiments. This was reflected in a plasma glucose value of 56 mg/dL (YSI 2300 STAT; Yellow Springs Instrument, Yellow Springs, OH) and a CGM value of 63 mg/dL). Regulation of blood glucose concentration with an AP using adaptive control techniques was successful in clinical studies, even without any meal and physical activity announcement.

CDP - Adaptive Supervisory Control and Data Acquisition (SCADA) Technology for Infrastructure Protection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marco Carvalho; Richard Ford

2012-05-14

Supervisory Control and Data Acquisition (SCADA) Systems are a type of Industrial Control System characterized by the centralized (or hierarchical) monitoring and control of geographically dispersed assets. SCADA systems combine acquisition and network components to provide data gathering, transmission, and visualization for centralized monitoring and control. However these integrated capabilities, especially when built over legacy systems and protocols, generally result in vulnerabilities that can be exploited by attackers, with potentially disastrous consequences. Our research project proposal was to investigate new approaches for secure and survivable SCADA systems. In particular, we were interested in the resilience and adaptability of large-scale mission-criticalmore » monitoring and control infrastructures. Our research proposal was divided in two main tasks. The first task was centered on the design and investigation of algorithms for survivable SCADA systems and a prototype framework demonstration. The second task was centered on the characterization and demonstration of the proposed approach in illustrative scenarios (simulated or emulated).« less

The Vulnerability of Threatened Species: Adaptive Capability and Adaptation Opportunity

PubMed Central

Berry, Pam; Ogawa-Onishi, Yuko; McVey, Andrew

2013-01-01

Global targets to halt the loss of biodiversity have not been met, and there is now an additional Aichi target for preventing the extinction of known threatened species and improving their conservation status. Climate change increasingly needs to be factored in to these, and thus there is a need to identify the extent to which it could increase species vulnerability. This paper uses the exposure, sensitivity, and adaptive capacity framework to assess the vulnerability of a selection of WWF global priority large mammals and marine species to climate change. However, it divides adaptive capacity into adaptive capability and adaptation opportunity, in order to identify whether adaptation is more constrained by the biology of the species or by its environmental setting. Lack of evidence makes it difficult to apply the framework consistently across the species, but it was found that, particularly for the terrestrial mammals, adaptation opportunities seems to be the greater constraint. This framework and analysis could be used by conservationists and those wishing to enhance the resilience of species to climate change. PMID:24833051

Legal and institutional foundations of adaptive environmental governance

PubMed Central

DeCaro, Daniel A.; Chaffin, Brian C.; Schlager, Edella; Garmestani, Ahjond S.; Ruhl, J.B.

2018-01-01

Legal and institutional structures fundamentally shape opportunities for adaptive governance of environmental resources at multiple ecological and societal scales. Properties of adaptive governance are widely studied. However, these studies have not resulted in consolidated frameworks for legal and institutional design, limiting our ability to promote adaptation and social-ecological resilience. We develop an overarching framework that describes the current and potential role of law in enabling adaptation. We apply this framework to different social-ecological settings, centers of activity, and scales, illustrating the multidimensional and polycentric nature of water governance. Adaptation typically emerges organically among multiple centers of agency and authority in society as a relatively self-organized or autonomous process marked by innovation, social learning, and political deliberation. This self-directed and emergent process is difficult to create in an exogenous, top-down fashion. However, traditional centers of authority may establish enabling conditions for adaptation using a suite of legal, economic, and democratic tools to legitimize and facilitate self-organization, coordination, and collaboration across scales. The principles outlined here provide preliminary legal and institutional foundations for adaptive environmental governance, which may inform institutional design and guide future scholarship. PMID:29780428

Legal and institutional foundations of adaptive environmental governance.

PubMed

DeCaro, Daniel A; Chaffin, Brian C; Schlager, Edella; Garmestani, Ahjond S; Ruhl, J B

2017-03-17

Legal and institutional structures fundamentally shape opportunities for adaptive governance of environmental resources at multiple ecological and societal scales. Properties of adaptive governance are widely studied. However, these studies have not resulted in consolidated frameworks for legal and institutional design, limiting our ability to promote adaptation and social-ecological resilience. We develop an overarching framework that describes the current and potential role of law in enabling adaptation. We apply this framework to different social-ecological settings, centers of activity, and scales, illustrating the multidimensional and polycentric nature of water governance. Adaptation typically emerges organically among multiple centers of agency and authority in society as a relatively self-organized or autonomous process marked by innovation, social learning, and political deliberation. This self-directed and emergent process is difficult to create in an exogenous, top-down fashion. However, traditional centers of authority may establish enabling conditions for adaptation using a suite of legal, economic, and democratic tools to legitimize and facilitate self-organization, coordination, and collaboration across scales. The principles outlined here provide preliminary legal and institutional foundations for adaptive environmental governance, which may inform institutional design and guide future scholarship.

Soliciting scientific information and beliefs in predictive modeling and adaptive management

NASA Astrophysics Data System (ADS)

Glynn, P. D.; Voinov, A. A.; Shapiro, C. D.

2015-12-01

Post-normal science requires public engagement and adaptive corrections in addressing issues with high complexity and uncertainty. An adaptive management framework is presented for the improved management of natural resources and environments through a public participation process. The framework solicits the gathering and transformation and/or modeling of scientific information but also explicitly solicits the expression of participant beliefs. Beliefs and information are compared, explicitly discussed for alignments or misalignments, and ultimately melded back together as a "knowledge" basis for making decisions. An effort is made to recognize the human or participant biases that may affect the information base and the potential decisions. In a separate step, an attempt is made to recognize and predict the potential "winners" and "losers" (perceived or real) of any decision or action. These "winners" and "losers" include present human communities with different spatial, demographic or socio-economic characteristics as well as more dispersed or more diffusely characterized regional or global communities. "Winners" and "losers" may also include future human communities as well as communities of other biotic species. As in any adaptive management framework, assessment of predictions, iterative follow-through and adaptation of policies or actions is essential, and commonly very difficult or impossible to achieve. Recognizing beforehand the limits of adaptive management is essential. More generally, knowledge of the behavioral and economic sciences and of ethics and sociology will be key to a successful implementation of this adaptive management framework. Knowledge of biogeophysical processes will also be essential, but by definition of the issues being addressed, will always be incomplete and highly uncertain. The human dimensions of the issues addressed and the participatory processes used carry their own complexities and uncertainties. Some ideas and principles are provided that may help guide and implement the proposed adaptive management framework and its public and stakeholder engagement processes. Examples and characteristics of issues that could be beneficially addressed through the proposed framework will also be presented.

A framework for developing an evidence-based, comprehensive tobacco control program

PubMed Central

2010-01-01

Background Tobacco control is an area where the translation of evidence into policy would seem to be straightforward, given the wealth of epidemiological, behavioural and other types of research available. Yet, even here challenges exist. These include information overload, concealment of key (industry-funded) evidence, contextualization, assessment of population impact, and the changing nature of the threat. Methods In the context of Israel's health targeting initiative, Healthy Israel 2020, we describe the steps taken to develop a comprehensive tobacco control strategy. We elaborate on the following: a) scientific issues influencing the choice of tobacco control strategies; b) organization of existing evidence of effectiveness of interventions into a manageable form, and c) consideration of relevant philosophical and political issues. We propose a framework for developing a plan and illustrate this process with a case study in Israel. Results Broad consensus exists regarding the effectiveness of most interventions, but current recommendations differ in the emphasis they place on different strategies. Scientific challenges include integration of complex and sometimes conflicting information from authoritative sources, and lack of estimates of population impact of interventions. Philosophical and political challenges include the use of evidence-based versus innovative policymaking, the importance of individual versus governmental responsibility, and whether and how interventions should be prioritized. The proposed framework includes: 1) compilation of a list of potential interventions 2) modification of that list based on local needs and political constraints; 3) streamlining the list by categorizing interventions into broad groupings of related interventions; together these groupings form the basis of a comprehensive plan; and 4) refinement of the plan by comparing it to existing comprehensive plans. Conclusions Development of a comprehensive tobacco control plan is a complex endeavour, involving crucial decisions regarding intervention components. "Off the shelf" plans, which need to be adapted to local settings, are available from a variety of sources, and a multitude of individual recommendations are available. The proposed framework for adapting existing approaches to the local social and political climate may assist others planning for smoke-free societies. Additionally, this experience has implications for development of evidence-based health plans addressing other risk factors. PMID:20507612

A framework for developing an evidence-based, comprehensive tobacco control program.

PubMed

Rosen, Laura; Rosenberg, Elliot; McKee, Martin; Gan-Noy, Shosh; Levin, Diane; Mayshar, Elana; Shacham, Galia; Borowski, John; Nun, Gabi Bin; Lev, Boaz

2010-05-27

Tobacco control is an area where the translation of evidence into policy would seem to be straightforward, given the wealth of epidemiological, behavioural and other types of research available. Yet, even here challenges exist. These include information overload, concealment of key (industry-funded) evidence, contextualization, assessment of population impact, and the changing nature of the threat. In the context of Israel's health targeting initiative, Healthy Israel 2020, we describe the steps taken to develop a comprehensive tobacco control strategy. We elaborate on the following: a) scientific issues influencing the choice of tobacco control strategies; b) organization of existing evidence of effectiveness of interventions into a manageable form, and c) consideration of relevant philosophical and political issues. We propose a framework for developing a plan and illustrate this process with a case study in Israel. Broad consensus exists regarding the effectiveness of most interventions, but current recommendations differ in the emphasis they place on different strategies. Scientific challenges include integration of complex and sometimes conflicting information from authoritative sources, and lack of estimates of population impact of interventions. Philosophical and political challenges include the use of evidence-based versus innovative policymaking, the importance of individual versus governmental responsibility, and whether and how interventions should be prioritized.The proposed framework includes: 1) compilation of a list of potential interventions 2) modification of that list based on local needs and political constraints; 3) streamlining the list by categorizing interventions into broad groupings of related interventions; together these groupings form the basis of a comprehensive plan; and 4) refinement of the plan by comparing it to existing comprehensive plans. Development of a comprehensive tobacco control plan is a complex endeavour, involving crucial decisions regarding intervention components. "Off the shelf" plans, which need to be adapted to local settings, are available from a variety of sources, and a multitude of individual recommendations are available. The proposed framework for adapting existing approaches to the local social and political climate may assist others planning for smoke-free societies. Additionally, this experience has implications for development of evidence-based health plans addressing other risk factors.

An Evidence-Based Public Health Approach to Climate Change Adaptation

PubMed Central

Eidson, Millicent; Tlumak, Jennifer E.; Raab, Kristin K.; Luber, George

2014-01-01

Background: Public health is committed to evidence-based practice, yet there has been minimal discussion of how to apply an evidence-based practice framework to climate change adaptation. Objectives: Our goal was to review the literature on evidence-based public health (EBPH), to determine whether it can be applied to climate change adaptation, and to consider how emphasizing evidence-based practice may influence research and practice decisions related to public health adaptation to climate change. Methods: We conducted a substantive review of EBPH, identified a consensus EBPH framework, and modified it to support an EBPH approach to climate change adaptation. We applied the framework to an example and considered implications for stakeholders. Discussion: A modified EBPH framework can accommodate the wide range of exposures, outcomes, and modes of inquiry associated with climate change adaptation and the variety of settings in which adaptation activities will be pursued. Several factors currently limit application of the framework, including a lack of higher-level evidence of intervention efficacy and a lack of guidelines for reporting climate change health impact projections. To enhance the evidence base, there must be increased attention to designing, evaluating, and reporting adaptation interventions; standardized health impact projection reporting; and increased attention to knowledge translation. This approach has implications for funders, researchers, journal editors, practitioners, and policy makers. Conclusions: The current approach to EBPH can, with modifications, support climate change adaptation activities, but there is little evidence regarding interventions and knowledge translation, and guidelines for projecting health impacts are lacking. Realizing the goal of an evidence-based approach will require systematic, coordinated efforts among various stakeholders. Citation: Hess JJ, Eidson M, Tlumak JE, Raab KK, Luber G. 2014. An evidence-based public health approach to climate change adaptation. Environ Health Perspect 122:1177–1186; http://dx.doi.org/10.1289/ehp.1307396 PMID:25003495

A framework for understanding shared substrates of airway protection

PubMed Central

TROCHE, Michelle Shevon; BRANDIMORE, Alexandra Essman; GODOY, Juliana; HEGLAND, Karen Wheeler

2014-01-01

Deficits of airway protection can have deleterious effects to health and quality of life. Effective airway protection requires a continuum of behaviors including swallowing and cough. Swallowing prevents material from entering the airway and coughing ejects endogenous material from the airway. There is significant overlap between the control mechanisms for swallowing and cough. In this review we will present the existing literature to support a novel framework for understanding shared substrates of airway protection. This framework was originally adapted from Eccles' model of cough28 (2009) by Hegland, et al.42 (2012). It will serve to provide a basis from which to develop future studies and test specific hypotheses that advance our field and ultimately improve outcomes for people with airway protective deficits. PMID:25141195

Framework for managing mycotoxin risks in the food industry.

PubMed

Baker, Robert C; Ford, Randall M; Helander, Mary E; Marecki, Janusz; Natarajan, Ramesh; Ray, Bonnie

2014-12-01

We propose a methodological framework for managing mycotoxin risks in the food processing industry. Mycotoxin contamination is a well-known threat to public health that has economic significance for the food processing industry; it is imperative to address mycotoxin risks holistically, at all points in the procurement, processing, and distribution pipeline, by tracking the relevant data, adopting best practices, and providing suitable adaptive controls. The proposed framework includes (i) an information and data repository, (ii) a collaborative infrastructure with analysis and simulation tools, (iii) standardized testing and acceptance sampling procedures, and (iv) processes that link the risk assessments and testing results to the sourcing, production, and product release steps. The implementation of suitable acceptance sampling protocols for mycotoxin testing is considered in some detail.

Knowledge representation into Ada parallel processing

NASA Technical Reports Server (NTRS)

Masotto, Tom; Babikyan, Carol; Harper, Richard

1990-01-01

The Knowledge Representation into Ada Parallel Processing project is a joint NASA and Air Force funded project to demonstrate the execution of intelligent systems in Ada on the Charles Stark Draper Laboratory fault-tolerant parallel processor (FTPP). Two applications were demonstrated - a portion of the adaptive tactical navigator and a real time controller. Both systems are implemented as Activation Framework Objects on the Activation Framework intelligent scheduling mechanism developed by Worcester Polytechnic Institute. The implementations, results of performance analyses showing speedup due to parallelism and initial efficiency improvements are detailed and further areas for performance improvements are suggested.

Optimal control of underactuated mechanical systems: A geometric approach

NASA Astrophysics Data System (ADS)

Colombo, Leonardo; Martín De Diego, David; Zuccalli, Marcela

2010-08-01

In this paper, we consider a geometric formalism for optimal control of underactuated mechanical systems. Our techniques are an adaptation of the classical Skinner and Rusk approach for the case of Lagrangian dynamics with higher-order constraints. We study a regular case where it is possible to establish a symplectic framework and, as a consequence, to obtain a unique vector field determining the dynamics of the optimal control problem. These developments will allow us to develop a new class of geometric integrators based on discrete variational calculus.

Legal and Institutional Foundations of Adaptive Environmental ...

EPA Pesticide Factsheets

Legal and institutional structures fundamentally shape opportunities for adaptive governance of environmental resources at multiple ecological and societal scales. Properties of adaptive governance are widely studied. However, these studies have not resulted in consolidated frameworks for legal and institutional design, limiting our ability to promote adaptation and social-ecological resilience. We develop an overarching framework that describes the current and potential role of law in enabling adaptation. We apply this framework to different social-ecological settings, centers of activity, and scales, illustrating the multidimensional and polycentric nature of water governance. Adaptation typically emerges organically among multiple centers of agency and authority in society as a relatively self-organized or autonomous process marked by innovation, social learning, and political deliberation. This self-directed and emergent process is difficult to create in an exogenous, top-down fashion. However, traditional centers of authority may establish enabling conditions for adaptation using a suite of legal, economic, and democratic tools to legitimize and facilitate self-organization, coordination, and collaboration across scales. The principles outlined here provide preliminary legal and institutional foundations for adaptive environmental governance, which may inform institutional design and guide future scholarship. Adaptation typically emerges organically among m

A locally p-adaptive approach for Large Eddy Simulation of compressible flows in a DG framework

NASA Astrophysics Data System (ADS)

Tugnoli, Matteo; Abbà, Antonella; Bonaventura, Luca; Restelli, Marco

2017-11-01

We investigate the possibility of reducing the computational burden of LES models by employing local polynomial degree adaptivity in the framework of a high-order DG method. A novel degree adaptation technique especially featured to be effective for LES applications is proposed and its effectiveness is compared to that of other criteria already employed in the literature. The resulting locally adaptive approach allows to achieve significant reductions in computational cost of representative LES computations.

Communication about life-sustaining therapy: insights from the Adaptive Leadership Framework

PubMed Central

Neglia, Elizabeth; Anderson, Ruth A.; Brandon, Debra; Docherty, Sharron L.

2014-01-01

Objective Effective provider and caregiver communication is central to quality care during treatment for life-threatening illnesses. The study aim was to analyze communication patterns between providers and a parent of an infant with a life-threatening disease using the Adaptive Leadership Framework, which is an activity that involves mobilizing others to adapt to a difficult situation. Method A secondary analysis was conducted on one case using 23 interviews with providers and mother of an infant diagnosed with Hurler’s syndrome. The interviews focused on decision-making challenges in regard to the infant’s treatment and were conducted over a 1-year period (pre-transplant, study entry, monthly, after a life-threatening event or substantial change in treatment and at 1-year post enrollment). Content analysis was used to identify and categorize communication patterns using concepts from the Adaptive Leadership Framework. Results Infant illness events and parent-provider caregiving were chronicled across a 1-year trajectory. Despite the life-threatening nature of Hurler’s disease, the parent and providers did not discuss palliative care or end-of-life. The parent sought direction and answers from the providers. The Adaptive Leadership Framework suggested how communication approaches were often mismatched with the needs of the parent. Discussion The results of the study accentuate the need to improve communication between provider and parents about end-of-life for their child. Adaptive Leadership illuminates how providers can influence a parent’s behavior when facing a challenging situation. This study suggests that Adaptive Leadership is a useful framework to guide research about healthcare communication in dealing with challenging issues. PMID:25309745

An optimization-based framework for anisotropic simplex mesh adaptation

NASA Astrophysics Data System (ADS)

Yano, Masayuki; Darmofal, David L.

2012-09-01

We present a general framework for anisotropic h-adaptation of simplex meshes. Given a discretization and any element-wise, localizable error estimate, our adaptive method iterates toward a mesh that minimizes error for a given degrees of freedom. Utilizing mesh-metric duality, we consider a continuous optimization problem of the Riemannian metric tensor field that provides an anisotropic description of element sizes. First, our method performs a series of local solves to survey the behavior of the local error function. This information is then synthesized using an affine-invariant tensor manipulation framework to reconstruct an approximate gradient of the error function with respect to the metric tensor field. Finally, we perform gradient descent in the metric space to drive the mesh toward optimality. The method is first demonstrated to produce optimal anisotropic meshes minimizing the L2 projection error for a pair of canonical problems containing a singularity and a singular perturbation. The effectiveness of the framework is then demonstrated in the context of output-based adaptation for the advection-diffusion equation using a high-order discontinuous Galerkin discretization and the dual-weighted residual (DWR) error estimate. The method presented provides a unified framework for optimizing both the element size and anisotropy distribution using an a posteriori error estimate and enables efficient adaptation of anisotropic simplex meshes for high-order discretizations.

Adaptive control of periodic systems

NASA Astrophysics Data System (ADS)

Tian, Zhiling

2009-12-01

Adaptive control is needed to cope with parametric uncertainty in dynamical systems. The adaptive control of LTI systems in both discrete and continuous time has been studied for four decades and the results are currently used widely in many different fields. In recent years, interest has shifted to the adaptive control of time-varying systems. It is known that the adaptive control of arbitrarily rapidly time-varying systems is in general intractable, but systems with periodically time-varying parameters (LTP systems) which have much more structure, are amenable to mathematical analysis. Further, there is also a need for such control in practical problems which have arisen in industry during the past twenty years. This thesis is the first attempt to deal with the adaptive control of LTP systems. Adaptive Control involves estimation of unknown parameters, adjusting the control parameters based on the estimates, and demonstrating that the overall system is stable. System theoretic properties such as stability, controllability, and observability play an important role both in formulating of the problems, as well as in generating solutions for them. For LTI systems, these properties have been studied since 1960s, and algebraic conditions that have to be satisfied to assure these properties are now well established. In the case of LTP systems, these properties can be expressed only in terms of transition matrices that are much more involved than those for LTI systems. Since adaptive control problems can be formulated only when these properties are well understood, it is not surprising that systematic efforts have not been made thus far for formulating and solving adaptive control problems that arise in LTP systems. Even in the case of LTI systems, it is well recognized that problems related to adaptive discrete-time system are not as difficult as those that arise in the continuous-time systems. This is amply evident in the solutions that were derived in the 1980s and 1990s for all the important problems. These differences are even more amplified in the LTP case; some problems in continuous time cannot even be formulated precisely. This thesis consequently focuses primarily on the adaptive identification and control of discrete-time systems, and derives most of the results that currently exist in the literature for LTI systems. Based on these investigations of discrete-time adaptive systems, attempts are made in the thesis to examine their continuous-time counterparts, and discuss the principal difficulties encountered. The dissertation examines critically the system theoretic properties of LTP systems in Chapter 2, and the mathematical framework provided for their analysis by Floquet theory in Chapter 3. Assuming that adaptive identification and control problems can be formulated precisely, a unified method of developing stable adaptive laws using error models is treated in Chapter 4. Chapter 5 presents a detailed study of the adaptation in SISO discrete-time LTP systems, and represents the core of the thesis. The important problems of identification, stabilization, regulation, and tracking of arbitrary signals are investigated, and practically implementable stable adaptive laws are derived. The dissertation concludes with a discussion of continuous-time adaptive control in Chapter 6 and discrete multivariable systems in Chapter 7. Directions for future research are indicated towards the end of the dissertation.

An FPGA- Based General-Purpose Data Acquisition Controller

NASA Astrophysics Data System (ADS)

Robson, C. C. W.; Bousselham, A.; Bohm

2006-08-01

System development in advanced FPGAs allows considerable flexibility, both during development and in production use. A mixed firmware/software solution allows the developer to choose what shall be done in firmware or software, and to make that decision late in the process. However, this flexibility comes at the cost of increased complexity. We have designed a modular development framework to help to overcome these issues of increased complexity. This framework comprises a generic controller that can be adapted for different systems by simply changing the software or firmware parts. The controller can use both soft and hard processors, with or without an RTOS, based on the demands of the system to be developed. The resulting system uses the Internet for both control and data acquisition. In our studies we developed the embedded system in a Xilinx Virtex-II Pro FPGA, where we used both PowerPC and MicroBlaze cores, http, Java, and LabView for control and communication, together with the MicroC/OS-II and OSE operating systems

A trajectory generation framework for modeling spacecraft entry in MDAO

NASA Astrophysics Data System (ADS)

D`Souza, Sarah N.; Sarigul-Klijn, Nesrin

2016-04-01

In this paper a novel trajectory generation framework was developed that optimizes trajectory event conditions for use in a Generalized Entry Guidance algorithm. The framework was developed to be adaptable via the use of high fidelity equations of motion and drag based analytical bank profiles. Within this framework, a novel technique was implemented that resolved the sensitivity of the bank profile to atmospheric non-linearities. The framework's adaptability was established by running two different entry bank conditions. Each case yielded a reference trajectory and set of transition event conditions that are flight feasible and implementable in a Generalized Entry Guidance algorithm.

Decentralized adaptive control designs and microstrip antennas for smart structures

NASA Astrophysics Data System (ADS)

Khorrami, Farshad; Jain, Sandeep; Das, Nirod K.

1996-05-01

Smart structures lend themselves naturally to a decentralized control design framework, especially with adaptation mechanisms. The main reason being that it is highly undesirable to connect all the sensors and actuators in a large structure to a central processor. It is rather desirable to have local decision-making at each smart patch. Furthermore, this local controllers should be easily `expandable' to `contractible.' This corresponds to the fact that addition/deletion of several smart patches should not require a total redesign of the control system. The decentralized control strategies advocated in this paper are of expandable/contractible type. On another front, we are considering utilization of micro-strip antennas for power transfer to and from smart structures. We have made preliminary contributions in this direction and further developments are underway. These approaches are being pursued for active vibration damping and noise cancellation via piezoelectric ceramics although the methodology is general enough to be applicable to other type of active structures.

The Development of the Croatian Competency Framework for Pharmacists.

PubMed

Mucalo, Iva; Hadžiabdić, Maja Ortner; Govorčinović, Tihana; Šarić, Martina; Bruno, Andreia; Bates, Ian

2016-10-25

Objective. To adjust and validate the Global Competency Framework (GbCF) to be relevant for Croatian community and hospital pharmacists. Methods. A descriptive study was conducted in three steps: translation, consensus development, and validation by an expert panel and public consultation. Panel members were representatives from community pharmacies, hospital pharmacies, regulatory and professional bodies, academia, and industry. Results. The adapted framework consists of 96 behavioral statements organized in four clusters: Pharmaceutical Public Health, Pharmaceutical Care, Organization and Management, and Personal and Professional Competencies. When mapped against the 100 statements listed in the GbCF, 27 matched, 39 were revised, 30 were introduced, and 24 were excluded from the original framework. Conclusions. The adaptation and validation proved that GbCF is adaptable to local needs, the Croatian Competency Framework that emerged from it being an example. Key amendments were made within Organization and Management and Pharmaceutical Care clusters, demonstrating that these issues can be country specific.

Systematic comparison of the response properties of protein and RNA mediated gene regulatory motifs.

PubMed

Iyengar, Bharat Ravi; Pillai, Beena; Venkatesh, K V; Gadgil, Chetan J

2017-05-30

We present a framework enabling the dissection of the effects of motif structure (feedback or feedforward), the nature of the controller (RNA or protein), and the regulation mode (transcriptional, post-transcriptional or translational) on the response to a step change in the input. We have used a common model framework for gene expression where both motif structures have an activating input and repressing regulator, with the same set of parameters, to enable a comparison of the responses. We studied the global sensitivity of the system properties, such as steady-state gain, overshoot, peak time, and peak duration, to parameters. We find that, in all motifs, overshoot correlated negatively whereas peak duration varied concavely with peak time. Differences in the other system properties were found to be mainly dependent on the nature of the controller rather than the motif structure. Protein mediated motifs showed a higher degree of adaptation i.e. a tendency to return to baseline levels; in particular, feedforward motifs exhibited perfect adaptation. RNA mediated motifs had a mild regulatory effect; they also exhibited a lower peaking tendency and mean overshoot. Protein mediated feedforward motifs showed higher overshoot and lower peak time compared to the corresponding feedback motifs.

Taylor bubbles at high viscosity ratios: experiments and numerical simulations

NASA Astrophysics Data System (ADS)

Hewakandamby, Buddhika; Hasan, Abbas; Azzopardi, Barry; Xie, Zhihua; Pain, Chris; Matar, Omar

2015-11-01

The Taylor bubble is a single long bubble which nearly fills the entire cross section of a liquid-filled circular tube, often occurring in gas-liquid slug flows in many industrial applications, particularly oil and gas production. The objective of this study is to investigate the fluid dynamics of three-dimensional Taylor bubble rising in highly viscous silicone oil in a vertical pipe. An adaptive unstructured mesh modelling framework is adopted here which can modify and adapt anisotropic unstructured meshes to better represent the underlying physics of bubble rising and reduce computational effort without sacrificing accuracy. The numerical framework consists of a mixed control volume and finite element formulation, a `volume of fluid'-type method for the interface-capturing based on a compressive control volume advection method, and a force-balanced algorithm for the surface tension implementation. Experimental results for the Taylor bubble shape and rise velocity are presented, together with numerical results for the dynamics of the bubbles. A comparison of the simulation predictions with experimental data available in the literature is also presented to demonstrate the capabilities of our numerical method. EPSRC Programme Grant, MEMPHIS, EP/K0039761/1.

Assessment of urban pluvial flood risk and efficiency of adaptation options through simulations - A new generation of urban planning tools

NASA Astrophysics Data System (ADS)

Löwe, Roland; Urich, Christian; Sto. Domingo, Nina; Mark, Ole; Deletic, Ana; Arnbjerg-Nielsen, Karsten

2017-07-01

We present a new framework for flexible testing of flood risk adaptation strategies in a variety of urban development and climate scenarios. This framework couples the 1D-2D hydrodynamic simulation package MIKE FLOOD with the agent-based urban development model DAnCE4Water and provides the possibility to systematically test various flood risk adaptation measures ranging from large infrastructure changes over decentralised water management to urban planning policies. We have tested the framework in a case study in Melbourne, Australia considering 9 scenarios for urban development and climate and 32 potential combinations of flood adaptation measures. We found that the performance of adaptation measures strongly depended on the considered climate and urban development scenario and the other implementation measures implemented, suggesting that adaptive strategies are preferable over one-off investments. Urban planning policies proved to be an efficient means for the reduction of flood risk, while implementing property buyback and pipe increases in a guideline-oriented manner was too costly. Random variations in location and time point of urban development could have significant impact on flood risk and would in some cases outweigh the benefits of less efficient adaptation strategies. The results of our setup can serve as an input for robust decision making frameworks and thus support the identification of flood risk adaptation measures that are economically efficient and robust to variations of climate and urban layout.

Mingus Discontinuous Multiphysics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pat Notz, Dan Turner

Mingus provides hybrid coupled local/non-local mechanics analysis capabilities that extend several traditional methods to applications with inherent discontinuities. Its primary features include adaptations of solid mechanics, fluid dynamics and digital image correlation that naturally accommodate dijointed data or irregular solution fields by assimilating a variety of discretizations (such as control volume finite elements, peridynamics and meshless control point clouds). The goal of this software is to provide an analysis framework form multiphysics engineering problems with an integrated image correlation capability that can be used for experimental validation and model

A junction-tree based learning algorithm to optimize network wide traffic control: A coordinated multi-agent framework

DOE PAGES

Zhu, Feng; Aziz, H. M. Abdul; Qian, Xinwu; ...

2015-01-31

Our study develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm (JTA) based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. Moreover, the algorithm is implemented and tested with a network containing 18 signalized intersections in VISSIM. Finally, our results show that the JTA based algorithm outperforms independent learning (Q-learning), real-time adaptive learning, and fixed timing plansmore » in terms of average delay, number of stops, and vehicular emissions at the network level.« less

Decentralized adaptive robust control based on sliding mode and nonlinear compensator for the control of ankle movement using functional electrical stimulation of agonist-antagonist muscles

NASA Astrophysics Data System (ADS)

Kobravi, Hamid-Reza; Erfanian, Abbas

2009-08-01

A decentralized control methodology is designed for the control of ankle dorsiflexion and plantarflexion in paraplegic subjects with electrical stimulation of tibialis anterior and calf muscles. Each muscle joint is considered as a subsystem and individual controllers are designed for each subsystem. Each controller operates solely on its associated subsystem, with no exchange of information between the subsystems. The interactions between the subsystems are taken as external disturbances for each isolated subsystem. In order to achieve robustness with respect to external disturbances, unmodeled dynamics, model uncertainty and time-varying properties of muscle-joint dynamics, a robust control framework is proposed which is based on the synergistic combination of an adaptive nonlinear compensator with a sliding mode control and is referred to as an adaptive robust control. Extensive simulations and experiments on healthy and paraplegic subjects were performed to demonstrate the robustness against the time-varying properties of muscle-joint dynamics, day-to-day variations, subject-to-subject variations, fast convergence, stability and tracking accuracy of the proposed method. The results indicate that the decentralized robust control provides excellent tracking control for different reference trajectories and can generate control signals to compensate the muscle fatigue and reject the external disturbance. Moreover, the controller is able to automatically regulate the interaction between agonist and antagonist muscles under different conditions of operating without any preprogrammed antagonist activities.

Decentralized adaptive robust control based on sliding mode and nonlinear compensator for the control of ankle movement using functional electrical stimulation of agonist-antagonist muscles.

PubMed

Kobravi, Hamid-Reza; Erfanian, Abbas

2009-08-01

A decentralized control methodology is designed for the control of ankle dorsiflexion and plantarflexion in paraplegic subjects with electrical stimulation of tibialis anterior and calf muscles. Each muscle joint is considered as a subsystem and individual controllers are designed for each subsystem. Each controller operates solely on its associated subsystem, with no exchange of information between the subsystems. The interactions between the subsystems are taken as external disturbances for each isolated subsystem. In order to achieve robustness with respect to external disturbances, unmodeled dynamics, model uncertainty and time-varying properties of muscle-joint dynamics, a robust control framework is proposed which is based on the synergistic combination of an adaptive nonlinear compensator with a sliding mode control and is referred to as an adaptive robust control. Extensive simulations and experiments on healthy and paraplegic subjects were performed to demonstrate the robustness against the time-varying properties of muscle-joint dynamics, day-to-day variations, subject-to-subject variations, fast convergence, stability and tracking accuracy of the proposed method. The results indicate that the decentralized robust control provides excellent tracking control for different reference trajectories and can generate control signals to compensate the muscle fatigue and reject the external disturbance. Moreover, the controller is able to automatically regulate the interaction between agonist and antagonist muscles under different conditions of operating without any preprogrammed antagonist activities.

Reinforcement learning for adaptive optimal control of unknown continuous-time nonlinear systems with input constraints

NASA Astrophysics Data System (ADS)

Yang, Xiong; Liu, Derong; Wang, Ding

2014-03-01

In this paper, an adaptive reinforcement learning-based solution is developed for the infinite-horizon optimal control problem of constrained-input continuous-time nonlinear systems in the presence of nonlinearities with unknown structures. Two different types of neural networks (NNs) are employed to approximate the Hamilton-Jacobi-Bellman equation. That is, an recurrent NN is constructed to identify the unknown dynamical system, and two feedforward NNs are used as the actor and the critic to approximate the optimal control and the optimal cost, respectively. Based on this framework, the action NN and the critic NN are tuned simultaneously, without the requirement for the knowledge of system drift dynamics. Moreover, by using Lyapunov's direct method, the weights of the action NN and the critic NN are guaranteed to be uniformly ultimately bounded, while keeping the closed-loop system stable. To demonstrate the effectiveness of the present approach, simulation results are illustrated.

Ecohydrology frameworks for green infrastructure design and ecosystem service provision

NASA Astrophysics Data System (ADS)

Pavao-Zuckerman, M.; Knerl, A.; Barron-Gafford, G.

2014-12-01

Urbanization is a dominant form of landscape change that affects the structure and function of ecosystems and alters control points in biogeochemical and hydrologic cycles. Green infrastructure (GI) has been proposed as a solution to many urban environmental challenges and may be a way to manage biogeochemical control points. Despite this promise, there has been relatively limited empirical focus to evaluate the efficacy of GI, relationships between design and function, and the ability of GI to provide ecosystem services in cities. This work has been driven by goals of adapting GI approaches to dryland cities and to harvest rain and storm water for providing ecosystem services related to storm water management and urban heat island mitigation, as well as other co-benefits. We will present a modification of ecohydrologic theory for guiding the design and function of green infrastructure for dryland systems that highlights how GI functions in context of Trigger - Transfer - Reserve - Pulse (TTRP) dynamic framework. Here we also apply this TTRP framework to observations of established street-scape green infrastructure in Tucson, AZ, and an experimental installation of green infrastructure basins on the campus of Biosphere 2 (Oracle, AZ) where we have been measuring plant performance and soil biogeochemical functions. We found variable sensitivity of microbial activity, soil respiration, N-mineralization, photosynthesis and respiration that was mediated both by elements of basin design (soil texture and composition, choice of surface mulches) and antecedent precipitation inputs and soil moisture conditions. The adapted TTRP framework and field studies suggest that there are strong connections between design and function that have implications for stormwater management and ecosystem service provision in dryland cities.

A Formal Valuation Framework for Emotions and Their Control.

PubMed

Huys, Quentin J M; Renz, Daniel

2017-09-15

Computational psychiatry aims to apply mathematical and computational techniques to help improve psychiatric care. To achieve this, the phenomena under scrutiny should be within the scope of formal methods. As emotions play an important role across many psychiatric disorders, such computational methods must encompass emotions. Here, we consider formal valuation accounts of emotions. We focus on the fact that the flexibility of emotional responses and the nature of appraisals suggest the need for a model-based valuation framework for emotions. However, resource limitations make plain model-based valuation impossible and require metareasoning strategies to apportion cognitive resources adaptively. We argue that emotions may implement such metareasoning approximations by restricting the range of behaviors and states considered. We consider the processes that guide the deployment of the approximations, discerning between innate, model-free, heuristic, and model-based controllers. A formal valuation and metareasoning framework may thus provide a principled approach to examining emotions. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Using a social justice and health framework to assess European climate change adaptation strategies.

PubMed

Boeckmann, Melanie; Zeeb, Hajo

2014-11-28

Climate change puts pressure on existing health vulnerabilities through higher frequency of extreme weather events, changes in disease vector distribution or exacerbated air pollution. Climate change adaptation policies may hold potential to reduce societal inequities. We assessed the role of public health and social justice in European climate change adaptation using a three-fold approach: a document analysis, a critical discourse analysis of a subgroup of strategies, and a ranking of strategies against our social justice framework. The ranking approach favored planning that includes various adaptation types, social issues and infrastructure changes. Themes on values identified in the five subgroup documents showed that risks are perceived as contradictory, technology is viewed as savior, responsibilities need to be negotiated, and social justice is advocated by only a few countries. Of 21 strategy documents assessed overall, those from Austria, England and Sweden received the highest scores in the ranking. Our qualitative assessment showed that in European adaptation planning, progress could still be made through community involvement into adaptation decisions, consistent consideration of social and demographic determinants, and a stronger link between infrastructural adaptation and the health sector. Overall, a social justice framework can serve as an evaluation guideline for adaptation policy documents.

Multilevel Optimization Framework for Hierarchical Stiffened Shells Accelerated by Adaptive Equivalent Strategy

NASA Astrophysics Data System (ADS)

Wang, Bo; Tian, Kuo; Zhao, Haixin; Hao, Peng; Zhu, Tianyu; Zhang, Ke; Ma, Yunlong

2017-06-01

In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy.

Managing for climate change on protected areas: An adaptive management decision making framework.

PubMed

Tanner-McAllister, Sherri L; Rhodes, Jonathan; Hockings, Marc

2017-12-15

Current protected area management is becoming more challenging with advancing climate change and current park management techniques may not be adequate to adapt for effective management into the future. The framework presented here provides an adaptive management decision making process to assist protected area managers with adapting on-park management to climate change. The framework sets out a 4 step process. One, a good understanding of the park's context within climate change. Secondly, a thorough understanding of the park management systems including governance, planning and management systems. Thirdly, a series of management options set out as an accept/prevent change style structure, including a systematic assessment of those options. The adaptive approaches are defined as acceptance of anthropogenic climate change impact and attempt to adapt to a new climatic environment or prevention of change and attempt to maintain current systems under new climatic variations. Last, implementation and monitoring of long term trends in response to ecological responses to management interventions and assessing management effectiveness. The framework addresses many issues currently with park management in dealing with climate change including the considerable amount of research focussing on 'off-reserve' strategies, and threats and stress focused in situ park management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development and Flight Testing of an Adaptable Vehicle Health-Monitoring Architecture

NASA Technical Reports Server (NTRS)

Woodard, Stanley E.; Coffey, Neil C.; Gonzalez, Guillermo A.; Woodman, Keith L.; Weathered, Brenton W.; Rollins, Courtney H.; Taylor, B. Douglas; Brett, Rube R.

2003-01-01

Development and testing of an adaptable wireless health-monitoring architecture for a vehicle fleet is presented. It has three operational levels: one or more remote data acquisition units located throughout the vehicle; a command and control unit located within the vehicle; and a terminal collection unit to collect analysis results from all vehicles. Each level is capable of performing autonomous analysis with a trained adaptable expert system. The remote data acquisition unit has an eight channel programmable digital interface that allows the user discretion for choosing type of sensors; number of sensors, sensor sampling rate, and sampling duration for each sensor. The architecture provides framework for a tributary analysis. All measurements at the lowest operational level are reduced to provide analysis results necessary to gauge changes from established baselines. These are then collected at the next level to identify any global trends or common features from the prior level. This process is repeated until the results are reduced at the highest operational level. In the framework, only analysis results are forwarded to the next level to reduce telemetry congestion. The system's remote data acquisition hardware and non-analysis software have been flight tested on the NASA Langley B757's main landing gear.

Transmission models and management of lymphatic filariasis elimination.

PubMed

Michael, Edwin; Gambhir, Manoj

2010-01-01

The planning and evaluation of parasitic control programmes are complicated by the many interacting population dynamic and programmatic factors that determine infection trends under different control options. A key need is quantification about the status of the parasite system state at any one given timepoint and the dynamic change brought upon that state as an intervention program proceeds. Here, we focus on the control and elimination of the vector-borne disease, lymphatic filariasis, to show how mathematical models of parasite transmission can provide a quantitative framework for aiding the design of parasite elimination and monitoring programs by their ability to support (1) conducting rational analysis and definition of endpoints for different programmatic aims or objectives, including transmission endpoints for disease elimination, (2) undertaking strategic analysis to aid the optimal design of intervention programs to meet set endpoints under different endemic settings and (3) providing support for performing informed evaluations of ongoing programs, including aiding the formation of timely adaptive management strategies to correct for any observed deficiencies in program effectiveness. The results also highlight how the use of a model-based framework will be critical to addressing the impacts of ecological complexities, heterogeneities and uncertainties on effective parasite management and thereby guiding the development of strategies to resolve and overcome such real-world complexities. In particular, we underscore how this approach can provide a link between ecological science and policy by revealing novel tools and measures to appraise and enhance the biological controllability or eradicability of parasitic diseases. We conclude by emphasizing an urgent need to develop and apply flexible adaptive management frameworks informed by mathematical models that are based on learning and reducing uncertainty using monitoring data, apply phased or sequential decision-making to address extant uncertainty and focus on developing ecologically resilient management strategies, in ongoing efforts to control or eliminate filariasis and other parasitic diseases in resource-poor communities.

Implementation and dissemination of a transition of care program for rural veterans: a controlled before and after study.

PubMed

Leonard, Chelsea; Lawrence, Emily; McCreight, Marina; Lippmann, Brandi; Kelley, Lynette; Mayberry, Ashlea; Ladebue, Amy; Gilmartin, Heather; Côté, Murray J; Jones, Jacqueline; Rabin, Borsika A; Ho, P Michael; Burke, Robert

2017-10-23

Adapting promising health care interventions to local settings is a critical component in the dissemination and implementation process. The Veterans Health Administration (VHA) rural transitions nurse program (TNP) is a nurse-led, Veteran-centered intervention designed to improve transitional care for rural Veterans funded by VA national offices for dissemination to other VA sites serving a predominantly rural Veteran population. Here, we describe our novel approach to the implementation and evaluation = the TNP. This is a controlled before and after study that assesses both implementation and intervention outcomes. During pre-implementation, we assessed site context using a mixed method approach with data from diverse sources including facility-level quantitative data, key informant and Veteran interviews, observations of the discharge process, and a group brainstorming activity. We used the Practical Robust Implementation and Sustainability Model (PRISM) to inform our inquiries, to integrate data from all sources, and to identify factors that may affect implementation. In the implementation phase, we will use internal and external facilitation, paired with audit and feedback, to encourage appropriate contextual adaptations. We will use a modified Stirman framework to document adaptations. During the evaluation phase, we will measure intervention and implementation outcomes at each site using the RE-AIM framework (Reach, Effectiveness, Adoption, Implementation, and Maintenance). We will conduct a difference-in-differences analysis with propensity-matched Veterans and VA facilities as a control. Our primary intervention outcome is 30-day readmission and Emergency Department visit rates. We will use our findings to develop an implementation toolkit that will inform the larger scale-up of the TNP across the VA. The use of PRISM to inform pre-implementation evaluation and synthesize data from multiple sources, coupled with internal and external facilitation, is a novel approach to engaging sites in adapting interventions while promoting fidelity to the intervention. Our application of PRISM to pre-implementation and midline evaluation, as well as documentation of adaptations, provides an opportunity to identify and address contextual factors that may impede or enhance implementation and sustainability of health interventions and inform dissemination.

Adaptive management for soil ecosystem services

USGS Publications Warehouse

Birge, Hannah E.; Bevans, Rebecca A.; Allen, Craig R.; Angeler, David G.; Baer, Sara G.; Wall, Diana H.

2016-01-01

Ecosystem services provided by soil include regulation of the atmosphere and climate, primary (including agricultural) production, waste processing, decomposition, nutrient conservation, water purification, erosion control, medical resources, pest control, and disease mitigation. The simultaneous production of these multiple services arises from complex interactions among diverse aboveground and belowground communities across multiple scales. When a system is mismanaged, non-linear and persistent losses in ecosystem services can arise. Adaptive management is an approach to management designed to reduce uncertainty as management proceeds. By developing alternative hypotheses, testing these hypotheses and adjusting management in response to outcomes, managers can probe dynamic mechanistic relationships among aboveground and belowground soil system components. In doing so, soil ecosystem services can be preserved and critical ecological thresholds avoided. Here, we present an adaptive management framework designed to reduce uncertainty surrounding the soil system, even when soil ecosystem services production is not the explicit management objective, so that managers can reach their management goals without undermining soil multifunctionality or contributing to an irreversible loss of soil ecosystem services.

An auto-adaptive optimization approach for targeting nonpoint source pollution control practices.

PubMed

Chen, Lei; Wei, Guoyuan; Shen, Zhenyao

2015-10-21

To solve computationally intensive and technically complex control of nonpoint source pollution, the traditional genetic algorithm was modified into an auto-adaptive pattern, and a new framework was proposed by integrating this new algorithm with a watershed model and an economic module. Although conceptually simple and comprehensive, the proposed algorithm would search automatically for those Pareto-optimality solutions without a complex calibration of optimization parameters. The model was applied in a case study in a typical watershed of the Three Gorges Reservoir area, China. The results indicated that the evolutionary process of optimization was improved due to the incorporation of auto-adaptive parameters. In addition, the proposed algorithm outperformed the state-of-the-art existing algorithms in terms of convergence ability and computational efficiency. At the same cost level, solutions with greater pollutant reductions could be identified. From a scientific viewpoint, the proposed algorithm could be extended to other watersheds to provide cost-effective configurations of BMPs.

Adaptive notification framework for smart nursing home.

PubMed

Betge-Brezetz, S; Dupont, M P; Ghorbel, M; Kamga, G B; Piekarec, S

2009-01-01

This paper presents an adaptive notification framework which allows to optimally deliver and handle multimedia requests and alerts in a nursing home. This framework is operated with various applications (e.g., health alert, medicine reminder, and activity proposition) and has been evaluated with different real end-users (elderly resident and medical staff) in a pilot site. Results of these evaluations are presented and highlight the added value of the framework technology to enhance the quality of life of elderly people as well as the efficiency of the medical staff.

A comparison of item response models for accuracy and speed of item responses with applications to adaptive testing.

PubMed

van Rijn, Peter W; Ali, Usama S

2017-05-01

We compare three modelling frameworks for accuracy and speed of item responses in the context of adaptive testing. The first framework is based on modelling scores that result from a scoring rule that incorporates both accuracy and speed. The second framework is the hierarchical modelling approach developed by van der Linden (2007, Psychometrika, 72, 287) in which a regular item response model is specified for accuracy and a log-normal model for speed. The third framework is the diffusion framework in which the response is assumed to be the result of a Wiener process. Although the three frameworks differ in the relation between accuracy and speed, one commonality is that the marginal model for accuracy can be simplified to the two-parameter logistic model. We discuss both conditional and marginal estimation of model parameters. Models from all three frameworks were fitted to data from a mathematics and spelling test. Furthermore, we applied a linear and adaptive testing mode to the data off-line in order to determine differences between modelling frameworks. It was found that a model from the scoring rule framework outperformed a hierarchical model in terms of model-based reliability, but the results were mixed with respect to correlations with external measures. © 2017 The British Psychological Society.

Network support for turn-taking in multimedia collaboration

NASA Astrophysics Data System (ADS)

Dommel, Hans-Peter; Garcia-Luna-Aceves, Jose J.

1997-01-01

The effectiveness of collaborative multimedia systems depends on the regulation of access to their shared resources, such as continuous media or instruments used concurrently by multiple parties. Existing applications use only simple protocols to mediate such resource contention. Their cooperative rules follow a strict agenda and are largely application-specific. The inherent problem of floor control lacks a systematic methodology. This paper presents a general model on floor control for correct, scalable, fine-grained and fair resource sharing that integrates user interaction with network conditions, and adaptation to various media types. The motion of turn-taking known from psycholinguistics in studies on discourse structure is adapted for this framework. Viewed as a computational analogy to speech communication, online collaboration revolves around dynamically allocated access permissions called floors. The control semantics of floors derives from concurrently control methodology. An explicit specification and verification of a novel distributed Floor Control Protocol are presented. Hosts assume sharing roles that allow for efficient dissemination of control information, agreeing on a floor holder which is granted mutually exclusive access to a resource. Performance analytic aspects of floor control protocols are also briefly discussed.

Fitness trade-offs in pest management and intercropping with colour: an evolutionary framework and potential application

PubMed Central

Farkas, Timothy E

2015-01-01

An important modern goal of plant science research is to develop tools for agriculturalists effective at curbing yield losses to insect herbivores, but resistance evolution continuously threatens the efficacy of pest management strategies. The high-dose/refuge strategy has been employed with some success to curb pest adaptation, and has been shown to be most effective when fitness costs (fitness trade-offs) of resistance are high. Here, I use eco-evolutionary reasoning to demonstrate the general importance of fitness trade-offs for pest control, showing that strong fitness trade-offs mitigate the threat of pest adaptation, even if adaptation were to occur. I argue that novel pest management strategies evoking strong fitness trade-offs are the most likely to persist in the face of unbridled pest adaptation, and offer the manipulation of crop colours as a worked example of one potentially effective strategy against insect herbivores. PMID:26495038

Fitness trade-offs in pest management and intercropping with colour: an evolutionary framework and potential application.

PubMed

Farkas, Timothy E

2015-10-01

An important modern goal of plant science research is to develop tools for agriculturalists effective at curbing yield losses to insect herbivores, but resistance evolution continuously threatens the efficacy of pest management strategies. The high-dose/refuge strategy has been employed with some success to curb pest adaptation, and has been shown to be most effective when fitness costs (fitness trade-offs) of resistance are high. Here, I use eco-evolutionary reasoning to demonstrate the general importance of fitness trade-offs for pest control, showing that strong fitness trade-offs mitigate the threat of pest adaptation, even if adaptation were to occur. I argue that novel pest management strategies evoking strong fitness trade-offs are the most likely to persist in the face of unbridled pest adaptation, and offer the manipulation of crop colours as a worked example of one potentially effective strategy against insect herbivores.

Selecting, adapting, and sustaining programs in health care systems

PubMed Central

Zullig, Leah L; Bosworth, Hayden B

2015-01-01

Practitioners and researchers often design behavioral programs that are effective for a specific population or problem. Despite their success in a controlled setting, relatively few programs are scaled up and implemented in health care systems. Planning for scale-up is a critical, yet often overlooked, element in the process of program design. Equally as important is understanding how to select a program that has already been developed, and adapt and implement the program to meet specific organizational goals. This adaptation and implementation requires attention to organizational goals, available resources, and program cost. We assert that translational behavioral medicine necessitates expanding successful programs beyond a stand-alone research study. This paper describes key factors to consider when selecting, adapting, and sustaining programs for scale-up in large health care systems and applies the Knowledge to Action (KTA) Framework to a case study, illustrating knowledge creation and an action cycle of implementation and evaluation activities. PMID:25931825

Biological versus electronic adaptive coloration: how can one inform the other?

PubMed Central

Kreit, Eric; Mäthger, Lydia M.; Hanlon, Roger T.; Dennis, Patrick B.; Naik, Rajesh R.; Forsythe, Eric; Heikenfeld, Jason

2013-01-01

Adaptive reflective surfaces have been a challenge for both electronic paper (e-paper) and biological organisms. Multiple colours, contrast, polarization, reflectance, diffusivity and texture must all be controlled simultaneously without optical losses in order to fully replicate the appearance of natural surfaces and vividly communicate information. This review merges the frontiers of knowledge for both biological adaptive coloration, with a focus on cephalopods, and synthetic reflective e-paper within a consistent framework of scientific metrics. Currently, the highest performance approach for both nature and technology uses colourant transposition. Three outcomes are envisioned from this review: reflective display engineers may gain new insights from millions of years of natural selection and evolution; biologists will benefit from understanding the types of mechanisms, characterization and metrics used in synthetic reflective e-paper; all scientists will gain a clearer picture of the long-term prospects for capabilities such as adaptive concealment and signalling. PMID:23015522

Towards a Theoretical Framework for Educational Simulations.

ERIC Educational Resources Information Center

Winer, Laura R.; Vazquez-Abad, Jesus

1981-01-01

Discusses the need for a sustained and systematic effort toward establishing a theoretical framework for educational simulations, proposes the adaptation of models borrowed from the natural and applied sciences, and describes three simulations based on such a model adapted using Brunerian learning theory. Sixteen references are listed. (LLS)

The AgMIP Framework to Evaluate Agricultural Pathways

NASA Technical Reports Server (NTRS)

Ruane, Alex

2015-01-01

This talk will describe the community and research framework that AgMIP has built to enable evidence-based adaptation investment. We provide expertise on the ground and connect various disciplines in order to allow specific adaptations to be evaluated for their biophysical and socio-economic ramifications.

The Adaptation for Conservation Targets (ACT) framework: a tool for incorporating climate change into natural resource management.

PubMed

Cross, Molly S; Zavaleta, Erika S; Bachelet, Dominique; Brooks, Marjorie L; Enquist, Carolyn A F; Fleishman, Erica; Graumlich, Lisa J; Groves, Craig R; Hannah, Lee; Hansen, Lara; Hayward, Greg; Koopman, Marni; Lawler, Joshua J; Malcolm, Jay; Nordgren, John; Petersen, Brian; Rowland, Erika L; Scott, Daniel; Shafer, Sarah L; Shaw, M Rebecca; Tabor, Gary M

2012-09-01

As natural resource management agencies and conservation organizations seek guidance on responding to climate change, myriad potential actions and strategies have been proposed for increasing the long-term viability of some attributes of natural systems. Managers need practical tools for selecting among these actions and strategies to develop a tailored management approach for specific targets at a given location. We developed and present one such tool, the participatory Adaptation for Conservation Targets (ACT) framework, which considers the effects of climate change in the development of management actions for particular species, ecosystems and ecological functions. Our framework is based on the premise that effective adaptation of management to climate change can rely on local knowledge of an ecosystem and does not necessarily require detailed projections of climate change or its effects. We illustrate the ACT framework by applying it to an ecological function in the Greater Yellowstone Ecosystem (Montana, Wyoming, and Idaho, USA)--water flows in the upper Yellowstone River. We suggest that the ACT framework is a practical tool for initiating adaptation planning, and for generating and communicating specific management interventions given an increasingly altered, yet uncertain, climate.

The Adaptation for Conservation Targets (ACT) Framework: A tool for incorporating climate change into natural resource management

USGS Publications Warehouse

Cross, Molly S.; Zavaleta, Erika S.; Bachelet, Dominique; Brooks, Marjorie L.; Enquist, Carolyn A.F.; Fleishman, Erica; Graumlich, Lisa J.; Groves, Craig R.; Hannah, Lee; Hansen, Lara J.; Hayward, Gregory D.; Koopman, Marni; Lawler, Joshua J.; Malcolm, Jay; Nordgren, John R.; Petersen, Brian; Rowland, Erika; Scott, Daniel; Shafer, Sarah L.; Shaw, M. Rebecca; Tabor, Gary

2012-01-01

As natural resource management agencies and conservation organizations seek guidance on responding to climate change, myriad potential actions and strategies have been proposed for increasing the long-term viability of some attributes of natural systems. Managers need practical tools for selecting among these actions and strategies to develop a tailored management approach for specific targets at a given location. We developed and present one such tool, the participatory Adaptation for Conservation Targets (ACT) framework, which considers the effects of climate change in the development of management actions for particular species, ecosystems and ecological functions. Our framework is based on the premise that effective adaptation of management to climate change can rely on local knowledge of an ecosystem and does not necessarily require detailed projections of climate change or its effects. We illustrate the ACT framework by applying it to an ecological function in the Greater Yellowstone Ecosystem (Montana, Wyoming, and Idaho, USA)—water flows in the upper Yellowstone River. We suggest that the ACT framework is a practical tool for initiating adaptation planning, and for generating and communicating specific management interventions given an increasingly altered, yet uncertain, climate.

Beyond exposure, sensitivity and adaptive capacity: A response based ecological framework to assess species climate change vulnerability

USGS Publications Warehouse

Fortini, Lucas B.; Schubert, Olivia

2017-01-01

As the impacts of global climate change on species are increasingly evident, there is a clear need to adapt conservation efforts worldwide. Species vulnerability assessments (VAs) are increasingly used to summarize all relevant information to determine a species’ potential vulnerability to climate change and are frequently the first step in informing climate adaptation efforts. VAs commonly integrate multiple sources of information by utilizing a framework that distinguishes factors relevant to species exposure, sensitivity, and adaptive capacity. However, this framework was originally developed for human systems, and its use to evaluate species vulnerability has serious practical and theoretical limitations. By instead defining vulnerability as the degree to which a species is unable to exhibit any of the responses necessary for persistence under climate change (i.e., toleration of projected changes, migration to new climate-compatible areas, enduring in microrefugia, and evolutionary adaptation), we can bring VAs into the realm of ecological science without applying borrowed abstract concepts that have consistently challenged species-centric research and management. This response-based framework to assess species vulnerability to climate change allows better integration of relevant ecological data and past research, yielding results with much clearer implications for conservation and research prioritization.

A Systematic Review of Literature on Culturally Adapted Obesity Prevention Interventions for African American Youth.

PubMed

Lofton, Saria; Julion, Wrenetha A; McNaughton, Diane B; Bergren, Martha Dewey; Keim, Kathryn S

2016-02-01

Obesity and overweight prevalence in African American (AA) youth continues to be one of the highest of all major ethnic groups, which has led researchers to pursue culturally based approaches as a means to improve obesity prevention interventions. The purpose of this systematic review was to evaluate culturally adapted obesity prevention interventions targeting AA youth. A search of electronic databases, limited to multicomponent culturally adapted obesity prevention controlled trials from 2003 to 2013, was conducted for key terms. Eleven studies met inclusion criteria. We used the PEN-3 model to evaluate the strengths and weaknesses of interventions as well as to identify cultural adaptation strategies. The PEN-3 model highlighted the value of designing joint parent-youth interventions, building a relationship between AA mentors and youth, and emphasizing healthful activities that the youth preferred. The PEN-3 model shows promise as an overarching framework to develop culturally adapted obesity interventions. © The Author(s) 2015.

Adaptation problems with nursing home application for elderly persons: an application of the Roy adaptation nursing model.

PubMed

Farkas, L

1981-09-01

This study sought to identify adaptation problems on the part of elderly persons and significant others that were associated with nursing home applications for elderly persons. Within the framework of the Roy Adaptation Nursing Model, an ex post facto research design was utilized to identify these adaptation problems. The four adaptive modes in this model are: physiological, self-concept, role function, and interdependence. The study group (n = 22) and a control group of elderly persons living in Calgary, as well as their significant others, were administered a structured questionnaire. Five hypotheses relating to overall adaptation problems, powerlessness, role reversal, guilt, and knowledge and utilization of services were formulated and tested. Only the hypothesis indicating role reversal on the part of the significant others was accepted. Adaptation problems encountered by the elderly which were associated with nursing home applications occurred in the self-concept and interdependence adaptive modes. The adaptation problems perceived by the significant others, which were associated with nursing home applications for their elderly, occurred in the self-concept, role function, and interdependence modes. Adaptation problems from the significant others' perception rather than from the elderly persons' perception appear to be more significantly associated with nursing home applications.

Active Inference, homeostatic regulation and adaptive behavioural control.

PubMed

Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl

2015-11-01

We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Social Adaptation of New Immigrant Students: Cultural Scripts, Roles, and Symbolic Interactionism

ERIC Educational Resources Information Center

Ukasoanya, Grace

2014-01-01

It is important that counselors understand the socio-cultural dimensions of social adaptation among immigrant students. While many psychological theories could provide suitable frameworks for examining these, in this article, I argue that symbolic interactionism could provide an additional valuable framework for (a) exploring the intersections of…

The full spectrum of climate change adaptation: testing an analytical framework in Tyrolean mountain agriculture (Austria).

PubMed

Grüneis, Heidelinde; Penker, Marianne; Höferl, Karl-Michael

2016-01-01

Our scientific view on climate change adaptation (CCA) is unsatisfying in many ways: It is often dominated by a modernistic perspective of planned pro-active adaptation, with a selective focus on measures directly responding to climate change impacts and thus it is far from real-life conditions of those who are actually affected by climate change. Farmers have to simultaneously adapt to multiple changes. Therefore, also empirical climate change adaptation research needs a more integrative perspective on real-life climate change adaptations. This also has to consider "hidden" adaptations, which are not explicitly and directly motivated by CCA but actually contribute to the sector's adaptability to climate change. The aim of the present study is to develop and test an analytic framework that contributes to a broader understanding of CCA and to bridge the gap between scientific expertise and practical action. The framework distinguishes three types of CCA according to their climate related motivations: explicit adaptations, multi-purpose adaptations, and hidden adaptations. Although agriculture is among the sectors that are most affected by climate change, results from the case study of Tyrolean mountain agriculture show that climate change is ranked behind other more pressing "real-life-challenges" such as changing agricultural policies or market conditions. We identified numerous hidden adaptations which make a valuable contribution when dealing with climate change impacts. We conclude that these hidden adaptations have not only to be considered to get an integrative und more realistic view on CCA; they also provide a great opportunity for linking adaptation strategies to farmers' realities.

Building Resilience against Climate Effects—A Novel Framework to Facilitate Climate Readiness in Public Health Agencies

PubMed Central

Marinucci, Gino D.; Luber, George; Uejio, Christopher K.; Saha, Shubhayu; Hess, Jeremy J.

2014-01-01

Climate change is anticipated to have several adverse health impacts. Managing these risks to public health requires an iterative approach. As with many risk management strategies related to climate change, using modeling to project impacts, engaging a wide range of stakeholders, and regularly updating models and risk management plans with new information—hallmarks of adaptive management—are considered central tenets of effective public health adaptation. The Centers for Disease Control and Prevention has developed a framework, entitled Building Resilience Against Climate Effects, or BRACE, to facilitate this process for public health agencies. Its five steps are laid out here. Following the steps laid out in BRACE will enable an agency to use the best available science to project likely climate change health impacts in a given jurisdiction and prioritize interventions. Adopting BRACE will also reinforce public health’s established commitment to evidence-based practice and institutional learning, both of which will be central to successfully engaging the significant new challenges that climate change presents. PMID:24991665

Generating Models of Infinite-State Communication Protocols Using Regular Inference with Abstraction

NASA Astrophysics Data System (ADS)

Aarts, Fides; Jonsson, Bengt; Uijen, Johan

In order to facilitate model-based verification and validation, effort is underway to develop techniques for generating models of communication system components from observations of their external behavior. Most previous such work has employed regular inference techniques which generate modest-size finite-state models. They typically suppress parameters of messages, although these have a significant impact on control flow in many communication protocols. We present a framework, which adapts regular inference to include data parameters in messages and states for generating components with large or infinite message alphabets. A main idea is to adapt the framework of predicate abstraction, successfully used in formal verification. Since we are in a black-box setting, the abstraction must be supplied externally, using information about how the component manages data parameters. We have implemented our techniques by connecting the LearnLib tool for regular inference with the protocol simulator ns-2, and generated a model of the SIP component as implemented in ns-2.

Programming model for distributed intelligent systems

NASA Technical Reports Server (NTRS)

Sztipanovits, J.; Biegl, C.; Karsai, G.; Bogunovic, N.; Purves, B.; Williams, R.; Christiansen, T.

1988-01-01

A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.

Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets.

PubMed

Zhang, Jian-Hua; Xia, Jia-Jun; Garibaldi, Jonathan M; Groumpos, Petros P; Wang, Ru-Bin

2017-06-01

In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must be dynamically allocated in accordance with continuous-time fluctuation of psychophysiological functional status of the operator, so-called operator functional state (OFS). The behavior of the HM system is hybrid in nature due to the co-existence of discrete task-load (control) variable and continuous operator performance (system output) variable. Petri net is an effective tool for modeling discrete event systems, but for hybrid system involving discrete dynamics, generally Petri net model has to be extended. Instead of using different tools to represent continuous and discrete components of a hybrid system, this paper proposed a method of fuzzy inference Petri nets (FIPN) to represent the HM hybrid system comprising a Mamdani-type fuzzy model of OFS and a logical switching controller in a unified framework, in which the task-load level is dynamically reallocated between the operator and machine based on the model-predicted OFS. Furthermore, this paper used a multi-model approach to predict the operator performance based on three electroencephalographic (EEG) input variables (features) via the Wang-Mendel (WM) fuzzy modeling method. The membership function parameters of fuzzy OFS model for each experimental participant were optimized using artificial bee colony (ABC) evolutionary algorithm. Three performance indices, RMSE, MRE, and EPR, were computed to evaluate the overall modeling accuracy. Experiment data from six participants are analyzed. The results show that the proposed method (FIPN with adaptive task allocation) yields lower breakdown rate (from 14.8% to 3.27%) and higher human performance (from 90.30% to 91.99%). The simulation results of the FIPN-based adaptive HM (AHM) system on six experimental participants demonstrate that the FIPN framework provides an effective way to model and regulate/optimize the OFS in HM hybrid systems composed of continuous-time OFS model and discrete-event switching controller. Copyright © 2017 Elsevier B.V. All rights reserved.

The Stimuli-Actions-Effects-Responses (SAER)-framework for exploring perceived relationships between private and public climate change adaptation in agriculture.

PubMed

Mitter, Hermine; Schönhart, Martin; Larcher, Manuela; Schmid, Erwin

2018-03-01

Empirical findings on actors' roles and responsibilities in the climate change adaptation process are rare even though cooperation between private and public actors is perceived important to foster adaptation in agriculture. We therefore developed the framework SAER (Stimuli-Actions-Effects-Responses) to investigate perceived relationships between private and public climate change adaptation in agriculture at regional scale. In particular, we explore agricultural experts' perceptions on (i) climatic and non-climatic factors stimulating private adaptation, (ii) farm adaption actions, (iii) potential on-farm and off-farm effects from adaptation, and (iv) the relationships between private and public adaptation. The SAER-framework is built on a comprehensive literature review and empirical findings from semi-structured interviews with agricultural experts from two case study regions in Austria. We find that private adaptation is perceived as incremental, systemic or transformational. It is typically stimulated by a mix of bio-physical and socio-economic on-farm and off-farm factors. Stimulating factors related to climate change are perceived of highest relevance for systemic and transformational adaptation whereas already implemented adaptation is mostly perceived to be incremental. Perceived effects of private adaptation are related to the environment, weather and climate, quality and quantity of agricultural products as well as human, social and economic resources. Our results also show that public adaptation can influence factors stimulating private adaptation as well as adaptation effects through the design and development of the legal, policy and organizational environment as well as the provision of educational, informational, financial, and technical infrastructure. Hence, facilitating existing and new collaborations between private and public actors may enable farmers to adapt effectively to climate change. Copyright © 2018 Elsevier Ltd. All rights reserved.

AdaFF: Adaptive Failure-Handling Framework for Composite Web Services

NASA Astrophysics Data System (ADS)

Kim, Yuna; Lee, Wan Yeon; Kim, Kyong Hoon; Kim, Jong

In this paper, we propose a novel Web service composition framework which dynamically accommodates various failure recovery requirements. In the proposed framework called Adaptive Failure-handling Framework (AdaFF), failure-handling submodules are prepared during the design of a composite service, and some of them are systematically selected and automatically combined with the composite Web service at service instantiation in accordance with the requirement of individual users. In contrast, existing frameworks cannot adapt the failure-handling behaviors to user's requirements. AdaFF rapidly delivers a composite service supporting the requirement-matched failure handling without manual development, and contributes to a flexible composite Web service design in that service architects never care about failure handling or variable requirements of users. For proof of concept, we implement a prototype system of the AdaFF, which automatically generates a composite service instance with Web Services Business Process Execution Language (WS-BPEL) according to the users' requirement specified in XML format and executes the generated instance on the ActiveBPEL engine.

Teaching for adaptive expertise in biomedical engineering ethics.

PubMed

Martin, Taylor; Rayne, Karen; Kemp, Nate J; Hart, Jack; Diller, Kenneth R

2005-04-01

This paper considers an approach to teaching ethics in bioengineering based on the How People Learn (HPL) framework. Curricula based on this framework have been effective in mathematics and science instruction from the kindergarten to the college levels. This framework is well suited to teaching bioengineering ethics because it helps learners develop "adaptive expertise". Adaptive expertise refers to the ability to use knowledge and experience in a domain to learn in unanticipated situations. It differs from routine expertise, which requires using knowledge appropriately to solve routine problems. Adaptive expertise is an important educational objective for bioengineers because the regulations and knowledge base in the discipline are likely to change significantly over the course of their careers. This study compares the performance of undergraduate bioengineering students who learned about ethics for stem cell research using the HPL method of instruction to the performance of students who learned following a standard lecture sequence. Both groups learned the factual material equally well, but the HPL group was more prepared to act adaptively when presented with a novel situation.

Flexible real-time magnetic resonance imaging framework.

PubMed

Santos, Juan M; Wright, Graham A; Pauly, John M

2004-01-01

The extension of MR imaging to new applications has demonstrated the limitations of the architecture of current real-time systems. Traditional real-time implementations provide continuous acquisition of data and modification of basic sequence parameters on the fly. We have extended the concept of real-time MRI by designing a system that drives the examinations from a real-time localizer and then gets reconfigured for different imaging modes. Upon operator request or automatic feedback the system can immediately generate a new pulse sequence or change fundamental aspects of the acquisition such as gradient waveforms excitation pulses and scan planes. This framework has been implemented by connecting a data processing and control workstation to a conventional clinical scanner. Key components on the design of this framework are the data communication and control mechanisms, reconstruction algorithms optimized for real-time and adaptability, flexible user interface and extensible user interaction. In this paper we describe the various components that comprise this system. Some of the applications implemented in this framework include real-time catheter tracking embedded in high frame rate real-time imaging and immediate switching between real-time localizer and high-resolution volume imaging for coronary angiography applications.

Using a Social Justice and Health Framework to Assess European Climate Change Adaptation Strategies

PubMed Central

Boeckmann, Melanie; Zeeb, Hajo

2014-01-01

Climate change puts pressure on existing health vulnerabilities through higher frequency of extreme weather events, changes in disease vector distribution or exacerbated air pollution. Climate change adaptation policies may hold potential to reduce societal inequities. We assessed the role of public health and social justice in European climate change adaptation using a three-fold approach: a document analysis, a critical discourse analysis of a subgroup of strategies, and a ranking of strategies against our social justice framework. The ranking approach favored planning that includes various adaptation types, social issues and infrastructure changes. Themes on values identified in the five subgroup documents showed that risks are perceived as contradictory, technology is viewed as savior, responsibilities need to be negotiated, and social justice is advocated by only a few countries. Of 21 strategy documents assessed overall, those from Austria, England and Sweden received the highest scores in the ranking. Our qualitative assessment showed that in European adaptation planning, progress could still be made through community involvement into adaptation decisions, consistent consideration of social and demographic determinants, and a stronger link between infrastructural adaptation and the health sector. Overall, a social justice framework can serve as an evaluation guideline for adaptation policy documents. PMID:25464133

A graphics to scalable vector graphics adaptation framework for progressive remote line rendering on mobile devices

NASA Astrophysics Data System (ADS)

Le, Minh Tuan; Nguyen, Congdu; Yoon, Dae-Il; Jung, Eun Ku; Kim, Hae-Kwang

2007-12-01

In this paper, we introduce a graphics to Scalable Vector Graphics (SVG) adaptation framework with a mechanism of vector graphics transmission to overcome the shortcoming of real-time representation and interaction experiences of 3D graphics application running on mobile devices. We therefore develop an interactive 3D visualization system based on the proposed framework for rapidly representing a 3D scene on mobile devices without having to download it from the server. Our system scenario is composed of a client viewer and a graphic to SVG adaptation server. The client viewer offers the user to access to the same 3D contents with different devices according to consumer interactions.

Fully anisotropic goal-oriented mesh adaptation for 3D steady Euler equations

NASA Astrophysics Data System (ADS)

Loseille, A.; Dervieux, A.; Alauzet, F.

2010-04-01

This paper studies the coupling between anisotropic mesh adaptation and goal-oriented error estimate. The former is very well suited to the control of the interpolation error. It is generally interpreted as a local geometric error estimate. On the contrary, the latter is preferred when studying approximation errors for PDEs. It generally involves non local error contributions. Consequently, a full and strong coupling between both is hard to achieve due to this apparent incompatibility. This paper shows how to achieve this coupling in three steps. First, a new a priori error estimate is proved in a formal framework adapted to goal-oriented mesh adaptation for output functionals. This estimate is based on a careful analysis of the contributions of the implicit error and of the interpolation error. Second, the error estimate is applied to the set of steady compressible Euler equations which are solved by a stabilized Galerkin finite element discretization. A goal-oriented error estimation is derived. It involves the interpolation error of the Euler fluxes weighted by the gradient of the adjoint state associated with the observed functional. Third, rewritten in the continuous mesh framework, the previous estimate is minimized on the set of continuous meshes thanks to a calculus of variations. The optimal continuous mesh is then derived analytically. Thus, it can be used as a metric tensor field to drive the mesh adaptation. From a numerical point of view, this method is completely automatic, intrinsically anisotropic, and does not depend on any a priori choice of variables to perform the adaptation. 3D examples of steady flows around supersonic and transsonic jets are presented to validate the current approach and to demonstrate its efficiency.

SU-D-BRB-05: Quantum Learning for Knowledge-Based Response-Adaptive Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

El Naqa, I; Ten, R

Purpose: There is tremendous excitement in radiotherapy about applying data-driven methods to develop personalized clinical decisions for real-time response-based adaptation. However, classical statistical learning methods lack in terms of efficiency and ability to predict outcomes under conditions of uncertainty and incomplete information. Therefore, we are investigating physics-inspired machine learning approaches by utilizing quantum principles for developing a robust framework to dynamically adapt treatments to individual patient’s characteristics and optimize outcomes. Methods: We studied 88 liver SBRT patients with 35 on non-adaptive and 53 on adaptive protocols. Adaptation was based on liver function using a split-course of 3+2 fractions with amore » month break. The radiotherapy environment was modeled as a Markov decision process (MDP) of baseline and one month into treatment states. The patient environment was modeled by a 5-variable state represented by patient’s clinical and dosimetric covariates. For comparison of classical and quantum learning methods, decision-making to adapt at one month was considered. The MDP objective was defined by the complication-free tumor control (P{sup +}=TCPx(1-NTCP)). A simple regression model represented state-action mapping. Single bit in classical MDP and a qubit of 2-superimposed states in quantum MDP represented the decision actions. Classical decision selection was done using reinforcement Q-learning and quantum searching was performed using Grover’s algorithm, which applies uniform superposition over possible states and yields quadratic speed-up. Results: Classical/quantum MDPs suggested adaptation (probability amplitude ≥0.5) 79% of the time for splitcourses and 100% for continuous-courses. However, the classical MDP had an average adaptation probability of 0.5±0.22 while the quantum algorithm reached 0.76±0.28. In cases where adaptation failed, classical MDP yielded 0.31±0.26 average amplitude while the quantum approach averaged a more optimistic 0.57±0.4, but with high phase fluctuations. Conclusion: Our results demonstrate that quantum machine learning approaches provide a feasible and promising framework for real-time and sequential clinical decision-making in adaptive radiotherapy.« less

Cultural adaptation of preschool PATHS (Promoting Alternative Thinking Strategies) curriculum for Pakistani children.

PubMed

Inam, Ayesha; Tariq, Pervaiz N; Zaman, Sahira

2015-06-01

Cultural adaptation of evidence-based programmes has gained importance primarily owing to its perceived impact on the established effectiveness of a programme. To date, many researchers have proposed different frameworks for systematic adaptation process. This article presents the cultural adaptation of preschool Promoting Alternative Thinking Strategies (PATHS) curriculum for Pakistani children using the heuristic framework of adaptation (Barrera & Castro, 2006). The study was completed in four steps: information gathering, preliminary adaptation design, preliminary adaptation test and adaptation refinement. Feedbacks on programme content suggested universality of the core programme components. Suggested changes were mostly surface structure: language, presentation of materials, conceptual equivalence of concepts, training needs of implementation staff and frequency of programme delivery. In-depth analysis was done to acquire cultural equivalence. Pilot testing of the outcome measures showed strong internal consistency. The results were further discussed with reference to similar work undertaken in other cultures. © 2014 International Union of Psychological Science.

Committed, Face-Value, Hybrid or Mutual Adaptation? The Experiences of International Students in Australian Higher Education

ERIC Educational Resources Information Center

Tran, Ly Thi

2011-01-01

This paper explores the adaptation patterns of international Chinese and Vietnamese students in relation to academic writing practices in a higher education context. The study utilises a trans-disciplinary framework for interpreting students' and lecturers' practices within institutional structures. This framework has been developed by infusing a…

Using a Vulnerability-Stress-Adaptation Framework to Predict Physical Aggression Trajectories in Newlywed Marriage

ERIC Educational Resources Information Center

Langer, Amie; Lawrence, Erika; Barry, Robin A.

2008-01-01

The authors used a vulnerability-stress-adaptation framework to examine personality traits and chronic stress as predictors of the developmental course of physical aggression in the early years of marriage. Additionally, personality traits and physical aggression were examined as predictors of the developmental course of chronic stress. Data from…

A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

ERIC Educational Resources Information Center

Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

2016-01-01

Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

Can Survival Processing Enhance Story Memory? Testing the Generalizability of the Adaptive Memory Framework

ERIC Educational Resources Information Center

Seamon, John G.; Bohn, Justin M.; Coddington, Inslee E.; Ebling, Maritza C.; Grund, Ethan M.; Haring, Catherine T.; Jang, Sue-Jung; Kim, Daniel; Liong, Christopher; Paley, Frances M.; Pang, Luke K.; Siddique, Ashik H.

2012-01-01

Research from the adaptive memory framework shows that thinking about words in terms of their survival value in an incidental learning task enhances their free recall relative to other semantic encoding strategies and intentional learning (Nairne, Pandeirada, & Thompson, 2008). We found similar results. When participants used incidental…

Computational rationality: linking mechanism and behavior through bounded utility maximization.

PubMed

Lewis, Richard L; Howes, Andrew; Singh, Satinder

2014-04-01

We propose a framework for including information-processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of computational mechanism into the definition of rational action. Theories are specified as optimal program problems, defined by an adaptation environment, a bounded machine, and a utility function. Such theories yield different classes of explanation, depending on the extent to which they emphasize adaptation to bounds, and adaptation to some ecology that differs from the immediate local environment. We illustrate this variation with examples from three domains: visual attention in a linguistic task, manual response ordering, and reasoning. We explore the relation of this framework to existing "levels" approaches to explanation, and to other optimality-based modeling approaches. Copyright © 2014 Cognitive Science Society, Inc.

Justice and Equity Implications of Climate Change Adaptation: A Theoretical Evaluation Framework

PubMed Central

Boeckmann, Melanie; Zeeb, Hajo

2016-01-01

Climate change affects human health, and climate change adaptation aims to reduce these risks through infrastructural, behavioral, and technological measures. However, attributing direct human health effects to climate change adaptation is difficult, causing an ethical dilemma between the need for evidence of strategies and their precautionary implementation before such evidence has been generated. In the absence of conclusive evidence for individual adaptation strategies, alternative approaches to the measurement of adaptation effectiveness need to be developed. This article proposes a theoretical framework and a set of guiding questions to assess effects of adaptation strategies on seven domains of health determinants, including social, economic, infrastructure, institutional, community, environmental, and cultural determinants of health. Its focus on advancing gender equity and environmental justice concurrently with the implementation of health-related adaptation could serve as a template for policymakers and researchers. PMID:27618121

Toward city-scale water quality control: building a theory for smart stormwater systems

NASA Astrophysics Data System (ADS)

Kerkez, B.; Mullapudi, A. M.; Wong, B. P.

2016-12-01

Urban stormwater systems are rarely designed as actual systems. Rather, it is often assumed that individual Best Management Practices (BMPs) will add up to achieve desired watershed outcomes. Given the rise of BMPs and green infrastructure, we ask: does doing "best" at the local scale guarantee the "best" at the global scale? Existing studies suggest that the system-level performance of distributed stormwater practices may actually adversely impact watersheds by increasing downstream erosion and reducing water quality. Optimizing spatial placement may not be sufficient, however, since precipitation variability and other sources of uncertainty can drive the overall system into undesirable states. To that end, it is also important to control the temporal behavior of the system, which can be achieved by equipping stormwater elements (ponds, wetlands, basins, bioswales, etc.) with "smart" sensors and valves. Rather than building new infrastructure, this permits for existing assets to be repurposed and controlled to adapt to individual storm events. While we have learned how to build and deploy the necessary sensing and control technologies, we do not have a framework or theory that combines our knowledge of hydrology, hydraulics, water quality and control. We discuss the development of such a framework and investigate how existing water domain knowledge can be transferred into a system-theoretic context to enable real-time, city-scale stormwater control. We apply this framework to water quality control in an urban watershed in southeast Michigan, which has been heavily instrumented and retrofitted for control over the past year.

(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis.

PubMed

He, Fei; Fromion, Vincent; Westerhoff, Hans V

2013-11-21

Metabolic control analysis (MCA) and supply-demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply-demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. This study integrates control engineering and classical MCA augmented with supply-demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the 'integral control' (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of 'integral control' should rarely be expected to lead to the 'perfect adaptation': although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems biology, correspond to the 'perfect' regulatory structures designed by control engineering vis-à-vis optimal functions such as robustness. To the extent that they are not, the analyses suggest how they may become so and this in turn should facilitate synthetic biology and metabolic engineering.

Control software and electronics architecture design in the framework of the E-ELT instrumentation

NASA Astrophysics Data System (ADS)

Di Marcantonio, P.; Coretti, I.; Cirami, R.; Comari, M.; Santin, P.; Pucillo, M.

2010-07-01

During the last years the European Southern Observatory (ESO), in collaboration with other European astronomical institutes, has started several feasibility studies for the E-ELT (European-Extremely Large Telescope) instrumentation and post-focal adaptive optics. The goal is to create a flexible suite of instruments to deal with the wide variety of scientific questions astronomers would like to see solved in the coming decades. In this framework INAF-Astronomical Observatory of Trieste (INAF-AOTs) is currently responsible of carrying out the analysis and the preliminary study of the architecture of the electronics and control software of three instruments: CODEX (control software and electronics) and OPTIMOS-EVE/OPTIMOS-DIORAMAS (control software). To cope with the increased complexity and new requirements for stability, precision, real-time latency and communications among sub-systems imposed by these instruments, new solutions have been investigated by our group. In this paper we present the proposed software and electronics architecture based on a distributed common framework centered on the Component/Container model that uses OPC Unified Architecture as a standard layer to communicate with COTS components of three different vendors. We describe three working prototypes that have been set-up in our laboratory and discuss their performances, integration complexity and ease of deployment.

Opportunistic management of estuaries under climate change: A new adaptive decision-making framework and its practical application.

PubMed

Peirson, William; Davey, Erica; Jones, Alan; Hadwen, Wade; Bishop, Keith; Beger, Maria; Capon, Samantha; Fairweather, Peter; Creese, Bob; Smith, Timothy F; Gray, Leigh; Tomlinson, Rodger

2015-11-01

Ongoing coastal development and the prospect of severe climate change impacts present pressing estuary management and governance challenges. Robust approaches must recognise the intertwined social and ecological vulnerabilities of estuaries. Here, a new governance and management framework is proposed that recognises the integrated social-ecological systems of estuaries so as to permit transformative adaptation to climate change within these systems. The framework lists stakeholders and identifies estuarine uses and values. Goals are categorised that are specific to ecosystems, private property, public infrastructure, and human communities. Systematic adaptation management strategies are proposed with conceptual examples and associated governance approaches. Contrasting case studies are used to illustrate the practical application of these ideas. The framework will assist estuary managers worldwide to achieve their goals, minimise maladaptative responses, better identify competing interests, reduce stakeholder conflict and exploit opportunities for appropriate ecosystem restoration and sustainable development. Copyright © 2015 Elsevier Ltd. All rights reserved.

Optimal Fault-Tolerant Control for Discrete-Time Nonlinear Strict-Feedback Systems Based on Adaptive Critic Design.

PubMed

Wang, Zhanshan; Liu, Lei; Wu, Yanming; Zhang, Huaguang

2018-06-01

This paper investigates the problem of optimal fault-tolerant control (FTC) for a class of unknown nonlinear discrete-time systems with actuator fault in the framework of adaptive critic design (ACD). A pivotal highlight is the adaptive auxiliary signal of the actuator fault, which is designed to offset the effect of the fault. The considered systems are in strict-feedback forms and involve unknown nonlinear functions, which will result in the causal problem. To solve this problem, the original nonlinear systems are transformed into a novel system by employing the diffeomorphism theory. Besides, the action neural networks (ANNs) are utilized to approximate a predefined unknown function in the backstepping design procedure. Combined the strategic utility function and the ACD technique, a reinforcement learning algorithm is proposed to set up an optimal FTC, in which the critic neural networks (CNNs) provide an approximate structure of the cost function. In this case, it not only guarantees the stability of the systems, but also achieves the optimal control performance as well. In the end, two simulation examples are used to show the effectiveness of the proposed optimal FTC strategy.

Open-source framework for documentation of scientific software written on MATLAB-compatible programming languages

NASA Astrophysics Data System (ADS)

Konnik, Mikhail V.; Welsh, James

2012-09-01

Numerical simulators for adaptive optics systems have become an essential tool for the research and development of the future advanced astronomical instruments. However, growing software code of the numerical simulator makes it difficult to continue to support the code itself. The problem of adequate documentation of the astronomical software for adaptive optics simulators may complicate the development since the documentation must contain up-to-date schemes and mathematical descriptions implemented in the software code. Although most modern programming environments like MATLAB or Octave have in-built documentation abilities, they are often insufficient for the description of a typical adaptive optics simulator code. This paper describes a general cross-platform framework for the documentation of scientific software using open-source tools such as LATEX, mercurial, Doxygen, and Perl. Using the Perl script that translates M-files MATLAB comments into C-like, one can use Doxygen to generate and update the documentation for the scientific source code. The documentation generated by this framework contains the current code description with mathematical formulas, images, and bibliographical references. A detailed description of the framework components is presented as well as the guidelines for the framework deployment. Examples of the code documentation for the scripts and functions of a MATLAB-based adaptive optics simulator are provided.

Building health behavior models to guide the development of just-in-time adaptive interventions: A pragmatic framework

PubMed Central

Nahum-Shani, Inbal; Hekler, Eric B.; Spruijt-Metz, Donna

2016-01-01

Advances in wireless devices and mobile technology offer many opportunities for delivering just-in-time adaptive interventions (JITAIs)--suites of interventions that adapt over time to an individual’s changing status and circumstances with the goal to address the individual’s need for support, whenever this need arises. A major challenge confronting behavioral scientists aiming to develop a JITAI concerns the selection and integration of existing empirical, theoretical and practical evidence into a scientific model that can inform the construction of a JITAI and help identify scientific gaps. The purpose of this paper is to establish a pragmatic framework that can be used to organize existing evidence into a useful model for JITAI construction. This framework involves clarifying the conceptual purpose of a JITAI, namely the provision of just-in-time support via adaptation, as well as describing the components of a JITAI and articulating a list of concrete questions to guide the establishment of a useful model for JITAI construction. The proposed framework includes an organizing scheme for translating the relatively static scientific models underlying many health behavior interventions into a more dynamic model that better incorporates the element of time. This framework will help to guide the next generation of empirical work to support the creation of effective JITAIs. PMID:26651462

DyKOSMap: A framework for mapping adaptation between biomedical knowledge organization systems.

PubMed

Dos Reis, Julio Cesar; Pruski, Cédric; Da Silveira, Marcos; Reynaud-Delaître, Chantal

2015-06-01

Knowledge Organization Systems (KOS) and their associated mappings play a central role in several decision support systems. However, by virtue of knowledge evolution, KOS entities are modified over time, impacting mappings and potentially turning them invalid. This requires semi-automatic methods to maintain such semantic correspondences up-to-date at KOS evolution time. We define a complete and original framework based on formal heuristics that drives the adaptation of KOS mappings. Our approach takes into account the definition of established mappings, the evolution of KOS and the possible changes that can be applied to mappings. This study experimentally evaluates the proposed heuristics and the entire framework on realistic case studies borrowed from the biomedical domain, using official mappings between several biomedical KOSs. We demonstrate the overall performance of the approach over biomedical datasets of different characteristics and sizes. Our findings reveal the effectiveness in terms of precision, recall and F-measure of the suggested heuristics and methods defining the framework to adapt mappings affected by KOS evolution. The obtained results contribute and improve the quality of mappings over time. The proposed framework can adapt mappings largely automatically, facilitating thus the maintenance task. The implemented algorithms and tools support and minimize the work of users in charge of KOS mapping maintenance. Copyright © 2015 Elsevier Inc. All rights reserved.

Clinical effort against secondhand smoke exposure: development of framework and intervention.

PubMed

Winickoff, Jonathan P; Park, Elyse R; Hipple, Bethany J; Berkowitz, Anna; Vieira, Cecilia; Friebely, Joan; Healey, Erica A; Rigotti, Nancy A

2008-08-01

The purpose of this work was to describe a novel process and present results of formative research to develop a pediatric office intervention that uses available systems of care for addressing parental smoking. The scientific development of the intervention occurred in 3 stages. In stage 1, we designed an office system for parental tobacco control in the pediatric outpatient setting on the basis of complementary conceptual frameworks of preventive services delivery, conceptualized for the child health care setting through a process of key interviews with leaders in the field of implementing practice change; existing Public Health Service guidelines that had been shown effective in adult practices; and adaptation of an evidence-based adult office system for tobacco control. This was an iterative process that yielded a theoretically framed intervention prototype. In stage 2, we performed focus-group testing in pediatric practices with pediatricians, nurses, clinical assistants, and key office staff. Using qualitative methods, we adapted the intervention prototype on the basis of this feedback to include 5 key implementation steps for the child health care setting. In stage 3, we presented the intervention to breakout groups at 2 national meetings of pediatric practitioners for additional refinements. The main result was a theoretically grounded intervention that was responsive to the barriers and suggestions raised in the focus groups and at the national meetings. The Clinical Effort Against Secondhand Smoke Exposure intervention was designed to be flexible and adaptable to the particular practices' staffing, resources, and physical configuration. Practice staff can choose materials relevant to their own particular systems of care (www.ceasetobacco.org). Conceptually grounded and focus-group-tested strategies for parental tobacco control are now available for implementation in the pediatric outpatient setting. The tobacco-control intervention-development process might have particular relevance for other chronic pediatric conditions that have a strong evidence base and have available treatments or resources that are underused.

A theoretical stochastic control framework for adapting radiotherapy to hypoxia

NASA Astrophysics Data System (ADS)

Saberian, Fatemeh; Ghate, Archis; Kim, Minsun

2016-10-01

Hypoxia, that is, insufficient oxygen partial pressure, is a known cause of reduced radiosensitivity in solid tumors, and especially in head-and-neck tumors. It is thus believed to adversely affect the outcome of fractionated radiotherapy. Oxygen partial pressure varies spatially and temporally over the treatment course and exhibits inter-patient and intra-tumor variation. Emerging advances in non-invasive functional imaging offer the future possibility of adapting radiotherapy plans to this uncertain spatiotemporal evolution of hypoxia over the treatment course. We study the potential benefits of such adaptive planning via a theoretical stochastic control framework using computer-simulated evolution of hypoxia on computer-generated test cases in head-and-neck cancer. The exact solution of the resulting control problem is computationally intractable. We develop an approximation algorithm, called certainty equivalent control, that calls for the solution of a sequence of convex programs over the treatment course; dose-volume constraints are handled using a simple constraint generation method. These convex programs are solved using an interior point algorithm with a logarithmic barrier via Newton’s method and backtracking line search. Convexity of various formulations in this paper is guaranteed by a sufficient condition on radiobiological tumor-response parameters. This condition is expected to hold for head-and-neck tumors and for other similarly responding tumors where the linear dose-response parameter is larger than the quadratic dose-response parameter. We perform numerical experiments on four test cases by using a first-order vector autoregressive process with exponential and rational-quadratic covariance functions from the spatiotemporal statistics literature to simulate the evolution of hypoxia. Our results suggest that dynamic planning could lead to a considerable improvement in the number of tumor cells remaining at the end of the treatment course. Through these simulations, we also gain insights into when and why dynamic planning is likely to yield the largest benefits.

Development of a technical assistance framework for building organizational capacity of health programs in resource-limited settings.

PubMed

Reyes, E Michael; Sharma, Anjali; Thomas, Kate K; Kuehn, Chuck; Morales, José Rafael

2014-09-17

Little information exists on the technical assistance needs of local indigenous organizations charged with managing HIV care and treatment programs funded by the US President's Emergency Plan for AIDS Relief (PEPFAR). This paper describes the methods used to adapt the Primary Care Assessment Tool (PCAT) framework, which has successfully strengthened HIV primary care services in the US, into one that could strengthen the capacity of local partners to deliver priority health programs in resource-constrained settings by identifying their specific technical assistance needs. Qualitative methods and inductive reasoning approaches were used to conceptualize and adapt the new Clinical Assessment for Systems Strengthening (ClASS) framework. Stakeholder interviews, comparisons of existing assessment tools, and a pilot test helped determine the overall ClASS framework for use in low-resource settings. The framework was further refined one year post-ClASS implementation. Stakeholder interviews, assessment of existing tools, a pilot process and the one-year post- implementation assessment informed the adaptation of the ClASS framework for assessing and strengthening technical and managerial capacities of health programs at three levels: international partner, local indigenous partner, and local partner treatment facility. The PCAT focus on organizational strengths and systems strengthening was retained and implemented in the ClASS framework and approach. A modular format was chosen to allow the use of administrative, fiscal and clinical modules in any combination and to insert new modules as needed by programs. The pilot led to refined pre-visit planning, informed review team composition, increased visit duration, and restructured modules. A web-based toolkit was developed to capture three years of experiential learning; this kit can also be used for independent implementation of the ClASS framework. A systematic adaptation process has produced a qualitative framework that can inform implementation strategies in support of country led HIV care and treatment programs. The framework, as a well-received iterative process focused on technical assistance, may have broader utility in other global programs.

Combining analytical frameworks to assess livelihood vulnerability to climate change and analyse adaptation options.

PubMed

Reed, M S; Podesta, G; Fazey, I; Geeson, N; Hessel, R; Hubacek, K; Letson, D; Nainggolan, D; Prell, C; Rickenbach, M G; Ritsema, C; Schwilch, G; Stringer, L C; Thomas, A D

2013-10-01

Experts working on behalf of international development organisations need better tools to assist land managers in developing countries maintain their livelihoods, as climate change puts pressure on the ecosystem services that they depend upon. However, current understanding of livelihood vulnerability to climate change is based on a fractured and disparate set of theories and methods. This review therefore combines theoretical insights from sustainable livelihoods analysis with other analytical frameworks (including the ecosystem services framework, diffusion theory, social learning, adaptive management and transitions management) to assess the vulnerability of rural livelihoods to climate change. This integrated analytical framework helps diagnose vulnerability to climate change, whilst identifying and comparing adaptation options that could reduce vulnerability, following four broad steps: i) determine likely level of exposure to climate change, and how climate change might interact with existing stresses and other future drivers of change; ii) determine the sensitivity of stocks of capital assets and flows of ecosystem services to climate change; iii) identify factors influencing decisions to develop and/or adopt different adaptation strategies, based on innovation or the use/substitution of existing assets; and iv) identify and evaluate potential trade-offs between adaptation options. The paper concludes by identifying interdisciplinary research needs for assessing the vulnerability of livelihoods to climate change.

Combining analytical frameworks to assess livelihood vulnerability to climate change and analyse adaptation options☆

PubMed Central

Reed, M.S.; Podesta, G.; Fazey, I.; Geeson, N.; Hessel, R.; Hubacek, K.; Letson, D.; Nainggolan, D.; Prell, C.; Rickenbach, M.G.; Ritsema, C.; Schwilch, G.; Stringer, L.C.; Thomas, A.D.

2013-01-01

Experts working on behalf of international development organisations need better tools to assist land managers in developing countries maintain their livelihoods, as climate change puts pressure on the ecosystem services that they depend upon. However, current understanding of livelihood vulnerability to climate change is based on a fractured and disparate set of theories and methods. This review therefore combines theoretical insights from sustainable livelihoods analysis with other analytical frameworks (including the ecosystem services framework, diffusion theory, social learning, adaptive management and transitions management) to assess the vulnerability of rural livelihoods to climate change. This integrated analytical framework helps diagnose vulnerability to climate change, whilst identifying and comparing adaptation options that could reduce vulnerability, following four broad steps: i) determine likely level of exposure to climate change, and how climate change might interact with existing stresses and other future drivers of change; ii) determine the sensitivity of stocks of capital assets and flows of ecosystem services to climate change; iii) identify factors influencing decisions to develop and/or adopt different adaptation strategies, based on innovation or the use/substitution of existing assets; and iv) identify and evaluate potential trade-offs between adaptation options. The paper concludes by identifying interdisciplinary research needs for assessing the vulnerability of livelihoods to climate change. PMID:25844020

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

PubMed

Liu, Zitao; Hauskrecht, Milos

2017-11-01

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

Introduction of new technologies and decision making processes: a framework to adapt a Local Health Technology Decision Support Program for other local settings.

PubMed

Poulin, Paule; Austen, Lea; Scott, Catherine M; Poulin, Michelle; Gall, Nadine; Seidel, Judy; Lafrenière, René

2013-01-01

Introducing new health technologies, including medical devices, into a local setting in a safe, effective, and transparent manner is a complex process, involving many disciplines and players within an organization. Decision making should be systematic, consistent, and transparent. It should involve translating and integrating scientific evidence, such as health technology assessment (HTA) reports, with context-sensitive evidence to develop recommendations on whether and under what conditions a new technology will be introduced. However, the development of a program to support such decision making can require considerable time and resources. An alternative is to adapt a preexisting program to the new setting. We describe a framework for adapting the Local HTA Decision Support Program, originally developed by the Department of Surgery and Surgical Services (Calgary, AB, Canada), for use by other departments. The framework consists of six steps: 1) development of a program review and adaptation manual, 2) education and readiness assessment of interested departments, 3) evaluation of the program by individual departments, 4) joint evaluation via retreats, 5) synthesis of feedback and program revision, and 6) evaluation of the adaptation process. Nine departments revised the Local HTA Decision Support Program and expressed strong satisfaction with the adaptation process. Key elements for success were identified. Adaptation of a preexisting program may reduce duplication of effort, save resources, raise the health care providers' awareness of HTA, and foster constructive stakeholder engagement, which enhances the legitimacy of evidence-informed recommendations for introducing new health technologies. We encourage others to use this framework for program adaptation and to report their experiences.

Translating Knowledge into Action: Supporting Adaptation in Australia's Coastal Zone through Information Provision and Decision Support

NASA Astrophysics Data System (ADS)

Palutikof, J. P.; Rissik, D.; Tonmoy, F. N.; Boulter, S.

2015-12-01

Adaptation to risks from climate change and sea-level rise is particularly important in Australia, where 70% of the population live in major coastal cities and 85% within 50km of the coast. Adaptation activity focuses at local government level and, in the absence of strong leadership from central government, the extent to which local councils have taken action to adapt is highly variable across the nation. Also, although a number of councils have proceeded as far as identifying their exposure to risk and considering adaptation options, this fails to translate into action. A principal reason for this is concern over the response from coastal residents to actions which may affect property values, and fear of litigation. A project is underway to support councils to understand their risks, evaluate adaptation options and proceed to action. This support will consist of a three-pronged framework: provision of information, a tool to support decision-making, and a community forum. Delivery involves research to understand the barriers to adaptation and how these may be overcome, optimal methods for delivery of information, and the information needs of organizations, action-takers and communities. The presentation will focus on the results of consultation undertaken to understand users' information needs around content and delivery, and how understanding of these needs has translated into design of the framework. A strongly preference was expressed to learn from peers, and a challenge for the framework is to understand how to inject adaptation knowledge which is up-to-date and accurate into peer-to-peer conversations. The community forum is one mechanism to achieve this. The basic structure and delivery mechanisms of the framework are shown in the attached.

Autonomous watersheds: Reducing flooding and stream erosion through real-time control

NASA Astrophysics Data System (ADS)

Kerkez, B.; Wong, B. P.

2017-12-01

We introduce an analytical toolchain, based on dynamical system theory and feedback control, to determine how many control points (valves, gates, pumps, etc.) are needed to transform urban watersheds from static to adaptive. Advances and distributed sensing and control stand to fundamentally change how we manage urban watersheds. In lieu of new and costly infrastructure, the real-time control of stormwater systems will reduce flooding, mitigate stream erosion, and improve the treatment of polluted runoff. We discuss the how open source technologies, in the form of wireless sensor nodes and remotely-controllable valves (open-storm.org), have been deployed to build "smart" stormwater systems in the Midwestern US. Unlike "static" infrastructure, which cannot readily adapt to changing inputs and land uses, these distributed control assets allow entire watersheds to be reconfigured on a storm-by-storm basis. Our results show how the control of even just a few valves within urban catchments (1-10km^2) allows for the real-time "shaping" of hydrographs, which reduces downstream erosion and flooding. We also introduce an equivalence framework that can be used by decision-makers to objectively compare investments into "smart" system to more traditional solutions, such as gray and green stormwater infrastructure.

The Formative Method for Adapting Psychotherapy (FMAP): A community-based developmental approach to culturally adapting therapy

PubMed Central

Hwang, Wei-Chin

2010-01-01

How do we culturally adapt psychotherapy for ethnic minorities? Although there has been growing interest in doing so, few therapy adaptation frameworks have been developed. The majority of these frameworks take a top-down theoretical approach to adapting psychotherapy. The purpose of this paper is to introduce a community-based developmental approach to modifying psychotherapy for ethnic minorities. The Formative Method for Adapting Psychotherapy (FMAP) is a bottom-up approach that involves collaborating with consumers to generate and support ideas for therapy adaptation. It involves 5-phases that target developing, testing, and reformulating therapy modifications. These phases include: (a) generating knowledge and collaborating with stakeholders (b) integrating generated information with theory and empirical and clinical knowledge, (c) reviewing the initial culturally adapted clinical intervention with stakeholders and revising the culturally adapted intervention, (d) testing the culturally adapted intervention, and (e) finalizing the culturally adapted intervention. Application of the FMAP is illustrated using examples from a study adapting psychotherapy for Chinese Americans, but can also be readily applied to modify therapy for other ethnic groups. PMID:20625458

Visual Tracking Using 3D Data and Region-Based Active Contours

DTIC Science & Technology

2016-09-28

adaptive control strategies which explicitly take uncertainty into account. Filtering methods ranging from the classical Kalman filters valid for...linear systems to the much more general particle filters also fit into this framework in a very natural manner. In particular, the particle filtering ...the number of samples required for accurate filtering increases with the dimension of the system noise. In our approach, we approximate curve

PHIT for Duty, a Personal Health Intervention Tool for Psychological Health and Traumatic Brain Injury

DTIC Science & Technology

2016-06-01

smartphone or tablet computer platforms, including both Google Android™ and Apple iOS based devices. Recruiting for the pilot study was very...framework design.. 15. SUBJECT TERMS PTSD, post-traumatic stress disorder, mobile health, self-help, iOS , Android, mindfulness, relaxation... study and subsequent randomized controlled trial (RCT) with post-deployed personnel; and (5) adapting the developed system for several popular

Context-aware adaptive spelling in motor imagery BCI

NASA Astrophysics Data System (ADS)

Perdikis, S.; Leeb, R.; Millán, J. d. R.

2016-06-01

Objective. This work presents a first motor imagery-based, adaptive brain-computer interface (BCI) speller, which is able to exploit application-derived context for improved, simultaneous classifier adaptation and spelling. Online spelling experiments with ten able-bodied users evaluate the ability of our scheme, first, to alleviate non-stationarity of brain signals for restoring the subject’s performances, second, to guide naive users into BCI control avoiding initial offline BCI calibration and, third, to outperform regular unsupervised adaptation. Approach. Our co-adaptive framework combines the BrainTree speller with smooth-batch linear discriminant analysis adaptation. The latter enjoys contextual assistance through BrainTree’s language model to improve online expectation-maximization maximum-likelihood estimation. Main results. Our results verify the possibility to restore single-sample classification and BCI command accuracy, as well as spelling speed for expert users. Most importantly, context-aware adaptation performs significantly better than its unsupervised equivalent and similar to the supervised one. Although no significant differences are found with respect to the state-of-the-art PMean approach, the proposed algorithm is shown to be advantageous for 30% of the users. Significance. We demonstrate the possibility to circumvent supervised BCI recalibration, saving time without compromising the adaptation quality. On the other hand, we show that this type of classifier adaptation is not as efficient for BCI training purposes.

Context-aware adaptive spelling in motor imagery BCI.

PubMed

Perdikis, S; Leeb, R; Millán, J D R

2016-06-01

This work presents a first motor imagery-based, adaptive brain-computer interface (BCI) speller, which is able to exploit application-derived context for improved, simultaneous classifier adaptation and spelling. Online spelling experiments with ten able-bodied users evaluate the ability of our scheme, first, to alleviate non-stationarity of brain signals for restoring the subject's performances, second, to guide naive users into BCI control avoiding initial offline BCI calibration and, third, to outperform regular unsupervised adaptation. Our co-adaptive framework combines the BrainTree speller with smooth-batch linear discriminant analysis adaptation. The latter enjoys contextual assistance through BrainTree's language model to improve online expectation-maximization maximum-likelihood estimation. Our results verify the possibility to restore single-sample classification and BCI command accuracy, as well as spelling speed for expert users. Most importantly, context-aware adaptation performs significantly better than its unsupervised equivalent and similar to the supervised one. Although no significant differences are found with respect to the state-of-the-art PMean approach, the proposed algorithm is shown to be advantageous for 30% of the users. We demonstrate the possibility to circumvent supervised BCI recalibration, saving time without compromising the adaptation quality. On the other hand, we show that this type of classifier adaptation is not as efficient for BCI training purposes.

Refinement and evaluation of helicopter real-time self-adaptive active vibration controller algorithms

NASA Technical Reports Server (NTRS)

Davis, M. W.

1984-01-01

A Real-Time Self-Adaptive (RTSA) active vibration controller was used as the framework in developing a computer program for a generic controller that can be used to alleviate helicopter vibration. Based upon on-line identification of system parameters, the generic controller minimizes vibration in the fuselage by closed-loop implementation of higher harmonic control in the main rotor system. The new generic controller incorporates a set of improved algorithms that gives the capability to readily define many different configurations by selecting one of three different controller types (deterministic, cautious, and dual), one of two linear system models (local and global), and one or more of several methods of applying limits on control inputs (external and/or internal limits on higher harmonic pitch amplitude and rate). A helicopter rotor simulation analysis was used to evaluate the algorithms associated with the alternative controller types as applied to the four-bladed H-34 rotor mounted on the NASA Ames Rotor Test Apparatus (RTA) which represents the fuselage. After proper tuning all three controllers provide more effective vibration reduction and converge more quickly and smoothly with smaller control inputs than the initial RTSA controller (deterministic with external pitch-rate limiting). It is demonstrated that internal limiting of the control inputs a significantly improves the overall performance of the deterministic controller.

Communicable disease control programmes and health systems: an analytical approach to sustainability.

PubMed

Shigayeva, Altynay; Coker, Richard J

2015-04-01

There is renewed concern over the sustainability of disease control programmes, and re-emergence of policy recommendations to integrate programmes with general health systems. However, the conceptualization of this issue has remarkably received little critical attention. Additionally, the study of programmatic sustainability presents methodological challenges. In this article, we propose a conceptual framework to support analyses of sustainability of communicable disease programmes. Through this work, we also aim to clarify a link between notions of integration and sustainability. As a part of development of the conceptual framework, we conducted a systematic literature review of peer-reviewed literature on concepts, definitions, analytical approaches and empirical studies on sustainability in health systems. Identified conceptual proposals for analysis of sustainability in health systems lack an explicit conceptualization of what a health system is. Drawing upon theoretical concepts originating in sustainability sciences and our review here, we conceptualize a communicable disease programme as a component of a health system which is viewed as a complex adaptive system. We propose five programmatic characteristics that may explain a potential for sustainability: leadership, capacity, interactions (notions of integration), flexibility/adaptability and performance. Though integration of elements of a programme with other system components is important, its role in sustainability is context specific and difficult to predict. The proposed framework might serve as a basis for further empirical evaluations in understanding complex interplay between programmes and broader health systems in the development of sustainable responses to communicable diseases. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2014; all rights reserved.

Adaptive GSA-based optimal tuning of PI controlled servo systems with reduced process parametric sensitivity, robust stability and controller robustness.

PubMed

Precup, Radu-Emil; David, Radu-Codrut; Petriu, Emil M; Radac, Mircea-Bogdan; Preitl, Stefan

2014-11-01

This paper suggests a new generation of optimal PI controllers for a class of servo systems characterized by saturation and dead zone static nonlinearities and second-order models with an integral component. The objective functions are expressed as the integral of time multiplied by absolute error plus the weighted sum of the integrals of output sensitivity functions of the state sensitivity models with respect to two process parametric variations. The PI controller tuning conditions applied to a simplified linear process model involve a single design parameter specific to the extended symmetrical optimum (ESO) method which offers the desired tradeoff to several control system performance indices. An original back-calculation and tracking anti-windup scheme is proposed in order to prevent the integrator wind-up and to compensate for the dead zone nonlinearity of the process. The minimization of the objective functions is carried out in the framework of optimization problems with inequality constraints which guarantee the robust stability with respect to the process parametric variations and the controller robustness. An adaptive gravitational search algorithm (GSA) solves the optimization problems focused on the optimal tuning of the design parameter specific to the ESO method and of the anti-windup tracking gain. A tuning method for PI controllers is proposed as an efficient approach to the design of resilient control systems. The tuning method and the PI controllers are experimentally validated by the adaptive GSA-based tuning of PI controllers for the angular position control of a laboratory servo system.

Towards adaptive, streaming analysis of x-ray tomography data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, Mathew; Kleese van Dam, Kerstin; Marshall, Matthew J.

2015-03-04

Temporal and spatial resolution of chemical imaging methodologies such as x-ray tomography are rapidly increasing, leading to more complex experimental procedures and fast growing data volumes. Automated analysis pipelines and big data analytics are becoming essential to effectively evaluate the results of such experiments. Offering those data techniques in an adaptive, streaming environment can further substantially improve the scientific discovery process, by enabling experimental control and steering based on the evaluation of emerging phenomena as they are observed by the experiment. Pacific Northwest National Laboratory (PNNL)’ Chemical Imaging Initiative (CII - http://imaging.pnnl.gov/ ) has worked since 2011 towards developing amore » framework that allows users to rapidly compose and customize high throughput experimental analysis pipelines for multiple instrument types. The framework, named ‘Rapid Experimental Analysis’ (REXAN) Framework [1], is based on the idea of reusable component libraries and utilizes the PNNL developed collaborative data management and analysis environment ‘Velo’, to provide a user friendly analysis and data management environment for experimental facilities. This article will, discuss the capabilities established for X-Ray tomography, discuss lessons learned, and provide an overview of our more recent work in the Analysis in Motion Initiative (AIM - http://aim.pnnl.gov/ ) at PNNL to provide REXAN capabilities in a streaming environment.« less

Design of a Modular Monolithic Implicit Solver for Multi-Physics Applications

NASA Technical Reports Server (NTRS)

Carton De Wiart, Corentin; Diosady, Laslo T.; Garai, Anirban; Burgess, Nicholas; Blonigan, Patrick; Ekelschot, Dirk; Murman, Scott M.

2018-01-01

The design of a modular multi-physics high-order space-time finite-element framework is presented together with its extension to allow monolithic coupling of different physics. One of the main objectives of the framework is to perform efficient high- fidelity simulations of capsule/parachute systems. This problem requires simulating multiple physics including, but not limited to, the compressible Navier-Stokes equations, the dynamics of a moving body with mesh deformations and adaptation, the linear shell equations, non-re effective boundary conditions and wall modeling. The solver is based on high-order space-time - finite element methods. Continuous, discontinuous and C1-discontinuous Galerkin methods are implemented, allowing one to discretize various physical models. Tangent and adjoint sensitivity analysis are also targeted in order to conduct gradient-based optimization, error estimation, mesh adaptation, and flow control, adding another layer of complexity to the framework. The decisions made to tackle these challenges are presented. The discussion focuses first on the "single-physics" solver and later on its extension to the monolithic coupling of different physics. The implementation of different physics modules, relevant to the capsule/parachute system, are also presented. Finally, examples of coupled computations are presented, paving the way to the simulation of the full capsule/parachute system.

Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan

In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic amplitude versus angle (AVA) and controlled source electromagnetic (CSEM) data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo (MCMC) sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis (DREAM) and Adaptive Metropolis (AM) samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and CSEM data. The multi-chain MCMC is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration,more » the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic AVA and CSEM joint inversion provides better estimation of reservoir saturations than the seismic AVA-only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated – reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.« less

Adaptive Agent Modeling of Distributed Language: Investigations on the Effects of Cultural Variation and Internal Action Representations

ERIC Educational Resources Information Center

Cangelosi, Angelo

2007-01-01

In this paper we present the "grounded adaptive agent" computational framework for studying the emergence of communication and language. This modeling framework is based on simulations of population of cognitive agents that evolve linguistic capabilities by interacting with their social and physical environment (internal and external symbol…

Allocation of Public Resources for Psychological Therapy between Types of Mental Health Condition: Towards Structural Balance

ERIC Educational Resources Information Center

Tustin, Don

2009-01-01

This paper addresses issues of allocating public resources efficiently between mental health conditions that are associated with different levels of disability, and presents an adaptation of an established framework to help decision-making in this area. The adapted framework refers to psychological interventions that are universal, indicated,…

Framework for measuring adaptive knowledge-rich systems performance.

PubMed

Bushko, Renata G

2005-01-01

The universe is non repeatable in nature--most of events cannot be prestated and do not repeat themselves. The only way to create systems that are truly useful is to make them adaptive (able to reason by analogy and learn) and rich in knowledge (including common sense knowledge). Adaptive and knowledge-rich health management could get us closer to errorless health care where small incremental adjustments happen all the time preventing occurrence of an error. In the era of adaptive systems we need to have a way to evaluate their performance. Are they truly adaptive? How adaptive are they? Are they accurate enough? Are they fast enough? Are they cost effective? This chapter presents general framework for measuring adaptive knowledge-rich systems' performance and includes among others definitions of adaptiveness factor, britt (a unit of brittleness) and uso-quant (unit of usefulness of a piece of knowledge). Measuring adaptive knowledge-rich systems performance is one of the most important research areas that can have a big pay-off in healthcare now and in the future.

Assessing adaptation to the health risks of climate change: what guidance can existing frameworks provide?

PubMed

Füssel, Hans-Martin

2008-02-01

Climate change adaptation assessments aim at assisting policy-makers in reducing the health risks associated with climate change and variability. This paper identifies key characteristics of the climate-health relationship and of the adaptation decision problem that require consideration in climate change adaptation assessments. It then analyzes whether these characteristics are appropriately considered in existing guidelines for climate impact and adaptation assessment and in pertinent conceptual models from environmental epidemiology. The review finds three assessment guidelines based on a generalized risk management framework to be most useful for guiding adaptation assessments of human health. Since none of them adequately addresses all key challenges of the adaptation decision problem, actual adaptation assessments need to combine elements from different guidelines. Established conceptual models from environmental epidemiology are found to be of limited relevance for assessing and planning adaptation to climate change since the prevailing toxicological model of environmental health is not applicable to many climate-sensitive health risks.

Statistical physics of human beings in games: Controlled experiments

NASA Astrophysics Data System (ADS)

Liang, Yuan; Huang, Ji-Ping

2014-07-01

It is important to know whether the laws or phenomena in statistical physics for natural systems with non-adaptive agents still hold for social human systems with adaptive agents, because this implies whether it is possible to study or understand social human systems by using statistical physics originating from natural systems. For this purpose, we review the role of human adaptability in four kinds of specific human behaviors, namely, normal behavior, herd behavior, contrarian behavior, and hedge behavior. The approach is based on controlled experiments in the framework of market-directed resource-allocation games. The role of the controlled experiments could be at least two-fold: adopting the real human decision-making process so that the system under consideration could reflect the performance of genuine human beings; making it possible to obtain macroscopic physical properties of a human system by tuning a particular factor of the system, thus directly revealing cause and effect. As a result, both computer simulations and theoretical analyses help to show a few counterparts of some laws or phenomena in statistical physics for social human systems: two-phase phenomena or phase transitions, entropy-related phenomena, and a non-equilibrium steady state. This review highlights the role of human adaptability in these counterparts, and makes it possible to study or understand some particular social human systems by means of statistical physics coming from natural systems.

Systematic, Multimethod Assessment of Adaptations Across Four Diverse Health Systems Interventions.

PubMed

Rabin, Borsika A; McCreight, Marina; Battaglia, Catherine; Ayele, Roman; Burke, Robert E; Hess, Paul L; Frank, Joseph W; Glasgow, Russell E

2018-01-01

Many health outcomes and implementation science studies have demonstrated the importance of tailoring evidence-based care interventions to local context to improve fit. By adapting to local culture, history, resources, characteristics, and priorities, interventions are more likely to lead to improved outcomes. However, it is unclear how best to adapt evidence-based programs and promising innovations. There are few guides or examples of how to best categorize or assess health-care adaptations, and even fewer that are brief and practical for use by non-researchers. This study describes the importance and potential of assessing adaptations before, during, and after the implementation of health systems interventions. We present a promising multilevel and multimethod approach developed and being applied across four different health systems interventions. Finally, we discuss implications and opportunities for future research. The four case studies are diverse in the conditions addressed, interventions, and implementation strategies. They include two nurse coordinator-based transition of care interventions, a data and training-driven multimodal pain management project, and a cardiovascular patient-reported outcomes project, all of which are using audit and feedback. We used the same modified adaptation framework to document changes made to the interventions and implementation strategies. To create the modified framework, we started with the adaptation and modification model developed by Stirman and colleagues and expanded it by adding concepts from the RE-AIM framework. Our assessments address the intuitive domains of Who, How, When, What, and Why to classify and organize adaptations. For each case study, we discuss how the modified framework was operationalized, the multiple methods used to collect data, results to date and approaches utilized for data analysis. These methods include a real-time tracking system and structured interviews at key times during the intervention. We provide descriptive data on the types and categories of adaptations made and discuss lessons learned. The multimethod approaches demonstrate utility across diverse health systems interventions. The modified adaptations model adequately captures adaptations across the various projects and content areas. We recommend systematic documentation of adaptations in future clinical and public health research and have made our assessment materials publicly available.

Dynamic and scalable audio classification by collective network of binary classifiers framework: an evolutionary approach.

PubMed

Kiranyaz, Serkan; Mäkinen, Toni; Gabbouj, Moncef

2012-10-01

In this paper, we propose a novel framework based on a collective network of evolutionary binary classifiers (CNBC) to address the problems of feature and class scalability. The main goal of the proposed framework is to achieve a high classification performance over dynamic audio and video repositories. The proposed framework adopts a "Divide and Conquer" approach in which an individual network of binary classifiers (NBC) is allocated to discriminate each audio class. An evolutionary search is applied to find the best binary classifier in each NBC with respect to a given criterion. Through the incremental evolution sessions, the CNBC framework can dynamically adapt to each new incoming class or feature set without resorting to a full-scale re-training or re-configuration. Therefore, the CNBC framework is particularly designed for dynamically varying databases where no conventional static classifiers can adapt to such changes. In short, it is entirely a novel topology, an unprecedented approach for dynamic, content/data adaptive and scalable audio classification. A large set of audio features can be effectively used in the framework, where the CNBCs make appropriate selections and combinations so as to achieve the highest discrimination among individual audio classes. Experiments demonstrate a high classification accuracy (above 90%) and efficiency of the proposed framework over large and dynamic audio databases. Copyright © 2012 Elsevier Ltd. All rights reserved.

Nonparametric Online Learning Control for Soft Continuum Robot: An Enabling Technique for Effective Endoscopic Navigation

PubMed Central

Lee, Kit-Hang; Fu, Denny K.C.; Leong, Martin C.W.; Chow, Marco; Fu, Hing-Choi; Althoefer, Kaspar; Sze, Kam Yim; Yeung, Chung-Kwong

2017-01-01

Abstract Bioinspired robotic structures comprising soft actuation units have attracted increasing research interest. Taking advantage of its inherent compliance, soft robots can assure safe interaction with external environments, provided that precise and effective manipulation could be achieved. Endoscopy is a typical application. However, previous model-based control approaches often require simplified geometric assumptions on the soft manipulator, but which could be very inaccurate in the presence of unmodeled external interaction forces. In this study, we propose a generic control framework based on nonparametric and online, as well as local, training to learn the inverse model directly, without prior knowledge of the robot's structural parameters. Detailed experimental evaluation was conducted on a soft robot prototype with control redundancy, performing trajectory tracking in dynamically constrained environments. Advanced element formulation of finite element analysis is employed to initialize the control policy, hence eliminating the need for random exploration in the robot's workspace. The proposed control framework enabled a soft fluid-driven continuum robot to follow a 3D trajectory precisely, even under dynamic external disturbance. Such enhanced control accuracy and adaptability would facilitate effective endoscopic navigation in complex and changing environments. PMID:29251567

Nonparametric Online Learning Control for Soft Continuum Robot: An Enabling Technique for Effective Endoscopic Navigation.

PubMed

Lee, Kit-Hang; Fu, Denny K C; Leong, Martin C W; Chow, Marco; Fu, Hing-Choi; Althoefer, Kaspar; Sze, Kam Yim; Yeung, Chung-Kwong; Kwok, Ka-Wai

2017-12-01

Bioinspired robotic structures comprising soft actuation units have attracted increasing research interest. Taking advantage of its inherent compliance, soft robots can assure safe interaction with external environments, provided that precise and effective manipulation could be achieved. Endoscopy is a typical application. However, previous model-based control approaches often require simplified geometric assumptions on the soft manipulator, but which could be very inaccurate in the presence of unmodeled external interaction forces. In this study, we propose a generic control framework based on nonparametric and online, as well as local, training to learn the inverse model directly, without prior knowledge of the robot's structural parameters. Detailed experimental evaluation was conducted on a soft robot prototype with control redundancy, performing trajectory tracking in dynamically constrained environments. Advanced element formulation of finite element analysis is employed to initialize the control policy, hence eliminating the need for random exploration in the robot's workspace. The proposed control framework enabled a soft fluid-driven continuum robot to follow a 3D trajectory precisely, even under dynamic external disturbance. Such enhanced control accuracy and adaptability would facilitate effective endoscopic navigation in complex and changing environments.

Feasibility of Decentralized Linear-Quadratic-Gaussian Control of Autonomous Distributed Spacecraft

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell

1999-01-01

A distributed satellite formation, modeled as an arbitrary number of fully connected nodes in a network, could be controlled using a decentralized controller framework that distributes operations in parallel over the network. For such problems, a solution that minimizes data transmission requirements, in the context of linear-quadratic-Gaussian (LQG) control theory, was given by Speyer. This approach is advantageous because it is non-hierarchical, detected failures gracefully degrade system performance, fewer local computations are required than for a centralized controller, and it is optimal with respect to the standard LQG cost function. Disadvantages of the approach are the need for a fully connected communications network, the total operations performed over all the nodes are greater than for a centralized controller, and the approach is formulated for linear time-invariant systems. To investigate the feasibility of the decentralized approach to satellite formation flying, a simple centralized LQG design for a spacecraft orbit control problem is adapted to the decentralized framework. The simple design uses a fixed reference trajectory (an equatorial, Keplerian, circular orbit), and by appropriate choice of coordinates and measurements is formulated as a linear time-invariant system.

Return of the JITAI: Applying a Just-in-Time Adaptive Intervention Framework to the Development of m-Health Solutions for Addictive Behaviors

PubMed Central

Evans, Brittney C.; Flack, Daniel; Juarascio, Adrienne; Manasse, Stephanie; Zhang, Fengqing; Forman, Evan M.

2018-01-01

Purpose Lapses are strong indicators of later relapse among individuals with addictive disorders, and thus are an important intervention target. However, lapse behavior has proven resistant to change due to the complex interplay of lapse triggers that are present in everyday life. It could be possible to prevent lapses before they occur by using m-Health solutions to deliver interventions in real-time. Method Just-in-time adaptive intervention (JITAI) is an intervention design framework that could be delivered via mobile app to facilitate in-the-moment monitoring of triggers for lapsing, and deliver personalized coping strategies to the user to prevent lapses from occurring. An organized framework is key for successful development of a JITAI. Results Nahum-Shani and colleagues (2014) set forth six core elements of a JITAI and guidelines for designing each: distal outcomes, proximal outcomes, tailoring variables, decision points, decision rules, and intervention options. The primary aim of this paper is to illustrate the use of this framework as it pertains to developing a JITAI that targets lapse behavior among individuals following a weight control diet. Conclusion We will detail our approach to various decision points during the development phases, report on preliminary findings where applicable, identify problems that arose during development, and provide recommendations for researchers who are currently undertaking their own JITAI development efforts. Issues such as missing data, the rarity of lapses, advantages/disadvantages of machine learning, and user engagement are discussed. PMID:28083725

Return of the JITAI: Applying a Just-in-Time Adaptive Intervention Framework to the Development of m-Health Solutions for Addictive Behaviors.

PubMed

Goldstein, Stephanie P; Evans, Brittney C; Flack, Daniel; Juarascio, Adrienne; Manasse, Stephanie; Zhang, Fengqing; Forman, Evan M

2017-10-01

Lapses are strong indicators of later relapse among individuals with addictive disorders, and thus are an important intervention target. However, lapse behavior has proven resistant to change due to the complex interplay of lapse triggers that are present in everyday life. It could be possible to prevent lapses before they occur by using m-Health solutions to deliver interventions in real-time. Just-in-time adaptive intervention (JITAI) is an intervention design framework that could be delivered via mobile app to facilitate in-the-moment monitoring of triggers for lapsing, and deliver personalized coping strategies to the user to prevent lapses from occurring. An organized framework is key for successful development of a JITAI. Nahum-Shani and colleagues (2014) set forth six core elements of a JITAI and guidelines for designing each: distal outcomes, proximal outcomes, tailoring variables, decision points, decision rules, and intervention options. The primary aim of this paper is to illustrate the use of this framework as it pertains to developing a JITAI that targets lapse behavior among individuals following a weight control diet. We will detail our approach to various decision points during the development phases, report on preliminary findings where applicable, identify problems that arose during development, and provide recommendations for researchers who are currently undertaking their own JITAI development efforts. Issues such as missing data, the rarity of lapses, advantages/disadvantages of machine learning, and user engagement are discussed.

Climate Change: From Science to Practice.

PubMed

Wheeler, Nicola; Watts, Nick

2018-03-01

Climate change poses a significant threat to human health. Understanding how climate science can be translated into public health practice is an essential first step in enabling robust adaptation and improving resiliency to climate change. Recent research highlights the importance of iterative approaches to public health adaptation to climate change, enabling uncertainties of health impacts and barriers to adaptation to be accounted for. There are still significant barriers to adaptation, which are context-specific and thus present unique challenges to public health practice. The implementation of flexible adaptation approaches, using frameworks targeted for public health, is key to ensuring robust adaptation to climate change in public health practice. The BRACE framework provides an excellent approach for health adaptation to climate change. Combining this with the insights provided and by the adaptation pathways approach allows for more deliberate accounting of long-term uncertainties. The mainstreaming of climate change adaptation into public health practice and planning is important in facilitating this approach and overcoming the significant barriers to effective adaptation. Yet, the immediate and future limits to adaptation provide clear justification for urgent and accelerated efforts to mitigate climate change.

Data-based virtual unmodeled dynamics driven multivariable nonlinear adaptive switching control.

PubMed

Chai, Tianyou; Zhang, Yajun; Wang, Hong; Su, Chun-Yi; Sun, Jing

2011-12-01

For a complex industrial system, its multivariable and nonlinear nature generally make it very difficult, if not impossible, to obtain an accurate model, especially when the model structure is unknown. The control of this class of complex systems is difficult to handle by the traditional controller designs around their operating points. This paper, however, explores the concepts of controller-driven model and virtual unmodeled dynamics to propose a new design framework. The design consists of two controllers with distinct functions. First, using input and output data, a self-tuning controller is constructed based on a linear controller-driven model. Then the output signals of the controller-driven model are compared with the true outputs of the system to produce so-called virtual unmodeled dynamics. Based on the compensator of the virtual unmodeled dynamics, the second controller based on a nonlinear controller-driven model is proposed. Those two controllers are integrated by an adaptive switching control algorithm to take advantage of their complementary features: one offers stabilization function and another provides improved performance. The conditions on the stability and convergence of the closed-loop system are analyzed. Both simulation and experimental tests on a heavily coupled nonlinear twin-tank system are carried out to confirm the effectiveness of the proposed method.

Learning algorithms for human-machine interfaces.

PubMed

Danziger, Zachary; Fishbach, Alon; Mussa-Ivaldi, Ferdinando A

2009-05-01

The goal of this study is to create and examine machine learning algorithms that adapt in a controlled and cadenced way to foster a harmonious learning environment between the user and the controlled device. To evaluate these algorithms, we have developed a simple experimental framework. Subjects wear an instrumented data glove that records finger motions. The high-dimensional glove signals remotely control the joint angles of a simulated planar two-link arm on a computer screen, which is used to acquire targets. A machine learning algorithm was applied to adaptively change the transformation between finger motion and the simulated robot arm. This algorithm was either LMS gradient descent or the Moore-Penrose (MP) pseudoinverse transformation. Both algorithms modified the glove-to-joint angle map so as to reduce the endpoint errors measured in past performance. The MP group performed worse than the control group (subjects not exposed to any machine learning), while the LMS group outperformed the control subjects. However, the LMS subjects failed to achieve better generalization than the control subjects, and after extensive training converged to the same level of performance as the control subjects. These results highlight the limitations of coadaptive learning using only endpoint error reduction.

Learning Algorithms for Human–Machine Interfaces

PubMed Central

Fishbach, Alon; Mussa-Ivaldi, Ferdinando A.

2012-01-01

The goal of this study is to create and examine machine learning algorithms that adapt in a controlled and cadenced way to foster a harmonious learning environment between the user and the controlled device. To evaluate these algorithms, we have developed a simple experimental framework. Subjects wear an instrumented data glove that records finger motions. The high-dimensional glove signals remotely control the joint angles of a simulated planar two-link arm on a computer screen, which is used to acquire targets. A machine learning algorithm was applied to adaptively change the transformation between finger motion and the simulated robot arm. This algorithm was either LMS gradient descent or the Moore–Penrose (MP) pseudoinverse transformation. Both algorithms modified the glove-to-joint angle map so as to reduce the endpoint errors measured in past performance. The MP group performed worse than the control group (subjects not exposed to any machine learning), while the LMS group outperformed the control subjects. However, the LMS subjects failed to achieve better generalization than the control subjects, and after extensive training converged to the same level of performance as the control subjects. These results highlight the limitations of coadaptive learning using only endpoint error reduction. PMID:19203886

A Methodology for Evaluating the Hygroscopic Behavior of Wood in Adaptive Building Skins using Motion Grammar

NASA Astrophysics Data System (ADS)

El-Dabaa, Rana; Abdelmohsen, Sherif

2018-05-01

The challenge in designing kinetic architecture lies in the lack of applying computational design and human computer interaction to successfully design intelligent and interactive interfaces. The use of ‘programmable materials’ as specifically fabricated composite materials that afford motion upon stimulation is promising for low-cost low-tech systems for kinetic facades in buildings. Despite efforts to develop working prototypes, there has been no clear methodological framework for understanding and controlling the behavior of programmable materials or for using them for such purposes. This paper introduces a methodology for evaluating the motion acquired from programmed material – resulting from the hygroscopic behavior of wood – through ‘motion grammar’. Motion grammar typically allows for the explanation of desired motion control in a computationally tractable method. The paper analyzed and evaluated motion parameters related to the hygroscopic properties and behavior of wood, and introduce a framework for tracking and controlling wood as a programmable material for kinetic architecture.

From bricks to buildings: adapting the Medical Research Council framework to develop programs of research in simulation education and training for the health professions.

PubMed

Haji, Faizal A; Da Silva, Celina; Daigle, Delton T; Dubrowski, Adam

2014-08-01

Presently, health care simulation research is largely conducted on a study-by-study basis. Although such "project-based" research generates a plethora of evidence, it can be chaotic and contradictory. A move toward sustained, thematic, theory-based programs of research is necessary to advance knowledge in the field. Recognizing that simulation is a complex intervention, we present a framework for developing research programs in simulation-based education adapted from the Medical Research Council (MRC) guidance. This framework calls for an iterative approach to developing, refining, evaluating, and implementing simulation interventions. The adapted framework guidance emphasizes: (1) identification of theory and existing evidence; (2) modeling and piloting interventions to clarify active ingredients and identify mechanisms linking the context, intervention, and outcomes; and (3) evaluation of intervention processes and outcomes in both the laboratory and real-world setting. The proposed framework will aid simulation researchers in developing more robust interventions that optimize simulation-based education and advance our understanding of simulation pedagogy.

Antecedents of perceived coach interpersonal behaviors: the coaching environment and coach psychological well- and ill-being.

PubMed

Stebbings, Juliette; Taylor, Ian M; Spray, Christopher M; Ntoumanis, Nikos

2012-08-01

Embedded in the self-determination theory (Deci & Ryan, 2000) framework, we obtained self-report data from 418 paid and voluntary coaches from a variety of sports and competitive levels with the aim of exploring potential antecedents of coaches' perceived autonomy supportive and controlling behaviors. Controlling for socially desirable responses, structural equation modeling revealed that greater job security and opportunities for professional development, and lower work-life conflict were associated with psychological need satisfaction, which, in turn, was related to an adaptive process of psychological well-being and perceived autonomy support toward athletes. In contrast, higher work-life conflict and fewer opportunities for development were associated with a distinct maladaptive process of thwarted psychological needs, psychological ill-being, and perceived controlling interpersonal behavior. The results highlight how the coaching context may impact upon coaches' psychological health and their interpersonal behavior toward athletes. Moreover, evidence is provided for the independence of adaptive and maladaptive processes within the self-determination theory paradigm.

Enhancing Cultural and Contextual Intervention Strategies to Reduce HIV/AIDS Among African Americans

PubMed Central

2009-01-01

I describe 4 protective strategies that African Americans employ that may challenge current HIV prevention efforts: (1) an adaptive duality that protects identity, (2) personal control influenced by external factors, (3) long-established indirect communication patterns, and (4) a mistrust of “outsiders.” I propose the Sexual Health Model as a conceptual framework for HIV prevention interventions because it incorporates established adaptive coping strategies into new HIV-related protective skills. The Sexual Health Model promotes interconnectedness, sexual ownership, and body awareness, 3 concepts that represent the context of the African American historical and cultural experience and that enhance rather than contradict future prevention efforts. PMID:19762666

Intelligent FPGA Data Acquisition Framework

NASA Astrophysics Data System (ADS)

Bai, Yunpeng; Gaisbauer, Dominic; Huber, Stefan; Konorov, Igor; Levit, Dmytro; Steffen, Dominik; Paul, Stephan

2017-06-01

In this paper, we present the field programmable gate arrays (FPGA)-based framework intelligent FPGA data acquisition (IFDAQ), which is used for the development of DAQ systems for detectors in high-energy physics. The framework supports Xilinx FPGA and provides a collection of IP cores written in very high speed integrated circuit hardware description language, which use the common interconnect interface. The IP core library offers functionality required for the development of the full DAQ chain. The library consists of Serializer/Deserializer (SERDES)-based time-to-digital conversion channels, an interface to a multichannel 80-MS/s 10-b analog-digital conversion, data transmission, and synchronization protocol between FPGAs, event builder, and slow control. The functionality is distributed among FPGA modules built in the AMC form factor: front end and data concentrator. This modular design also helps to scale and adapt the DAQ system to the needs of the particular experiment. The first application of the IFDAQ framework is the upgrade of the read-out electronics for the drift chambers and the electromagnetic calorimeters (ECALs) of the COMPASS experiment at CERN. The framework will be presented and discussed in the context of this paper.

Adaptive management for soil ecosystem services.

PubMed

Birgé, Hannah E; Bevans, Rebecca A; Allen, Craig R; Angeler, David G; Baer, Sara G; Wall, Diana H

2016-12-01

Ecosystem services provided by soil include regulation of the atmosphere and climate, primary (including agricultural) production, waste processing, decomposition, nutrient conservation, water purification, erosion control, medical resources, pest control, and disease mitigation. The simultaneous production of these multiple services arises from complex interactions among diverse aboveground and belowground communities across multiple scales. When a system is mismanaged, non-linear and persistent losses in ecosystem services can arise. Adaptive management is an approach to management designed to reduce uncertainty as management proceeds. By developing alternative hypotheses, testing these hypotheses and adjusting management in response to outcomes, managers can probe dynamic mechanistic relationships among aboveground and belowground soil system components. In doing so, soil ecosystem services can be preserved and critical ecological thresholds avoided. Here, we present an adaptive management framework designed to reduce uncertainty surrounding the soil system, even when soil ecosystem services production is not the explicit management objective, so that managers can reach their management goals without undermining soil multifunctionality or contributing to an irreversible loss of soil ecosystem services. Copyright © 2016. Published by Elsevier Ltd.

Building oceanographic and atmospheric observation networks by composition: unmanned vehicles, communication networks, and planning and execution control frameworks

NASA Astrophysics Data System (ADS)

Sousa, J. T.; Pinto, J.; Martins, R.; Costa, M.; Ferreira, F.; Gomes, R.

2014-12-01

The problem of developing mobile oceanographic and atmospheric observation networks (MOAO) with coordinated air and ocean vehicles is discussed in the framework of the communications and control software tool chain developed at Underwater Systems and Technologies Laboratory (LSTS) from Porto University. This is done with reference to field experiments to illustrate key capabilities and to assess future MOAO operations. First, the motivation for building MOAO by "composition" of air and ocean vehicles, communication networks, and planning and execution control frameworks is discussed - in networked vehicle systems information and commands are exchanged among multiple vehicles and operators, and the roles, relative positions, and dependencies of these vehicles and operators change during operations. Second, the planning and execution control framework developed at LSTS for multi-vehicle systems is discussed with reference to key concepts such as autonomy, mixed-initiative interactions, and layered organization. Third, the LSTS tool software tool chain is presented to show how to develop MOAO by composition. The tool chain comprises the Neptus command and control framework for mixed initiative interactions, the underlying IMC messaging protocol, and the DUNE on-board software. Fourth, selected LSTS operational deployments illustrate MOAO capability building. In 2012 we demonstrated the use of UAS to "ferry" data from UUVs located beyond line of sight (BLOS). In 2013 we demonstrated coordinated observations of coastal fronts with small UAS and UUVs, "bent" BLOS through the use of UAS as communication relays, and UAS tracking of juvenile hammer-head sharks. In 2014 we demonstrated UUV adaptive sampling with the closed loop controller of the UUV residing on a UAS; this was done with the help of a Wave Glider ASV with a communications gateway. The results from these experiments provide a background for assessing potential future UAS operations in a compositional MOAO.

Enhancing climate Adaptation Capacity for Drinking Water ...

EPA Pesticide Factsheets

Journal article This paper considers the adaptation capacity of conventional water treatment systems. A modeling framework is used to illustrate climate adaptation mechanisms that could enable conventional treatment systems to accommodate water quality impairments.

Adaptation of Chain Event Graphs for use with Case-Control Studies in Epidemiology.

PubMed

Keeble, Claire; Thwaites, Peter Adam; Barber, Stuart; Law, Graham Richard; Baxter, Paul David

2017-09-26

Case-control studies are used in epidemiology to try to uncover the causes of diseases, but are a retrospective study design known to suffer from non-participation and recall bias, which may explain their decreased popularity in recent years. Traditional analyses report usually only the odds ratio for given exposures and the binary disease status. Chain event graphs are a graphical representation of a statistical model derived from event trees which have been developed in artificial intelligence and statistics, and only recently introduced to the epidemiology literature. They are a modern Bayesian technique which enable prior knowledge to be incorporated into the data analysis using the agglomerative hierarchical clustering algorithm, used to form a suitable chain event graph. Additionally, they can account for missing data and be used to explore missingness mechanisms. Here we adapt the chain event graph framework to suit scenarios often encountered in case-control studies, to strengthen this study design which is time and financially efficient. We demonstrate eight adaptations to the graphs, which consist of two suitable for full case-control study analysis, four which can be used in interim analyses to explore biases, and two which aim to improve the ease and accuracy of analyses. The adaptations are illustrated with complete, reproducible, fully-interpreted examples, including the event tree and chain event graph. Chain event graphs are used here for the first time to summarise non-participation, data collection techniques, data reliability, and disease severity in case-control studies. We demonstrate how these features of a case-control study can be incorporated into the analysis to provide further insight, which can help to identify potential biases and lead to more accurate study results.

Studying citizen science through adaptive management and learning feedbacks as mechanisms for improving conservation.

PubMed

Jordan, Rebecca; Gray, Steven; Sorensen, Amanda; Newman, Greg; Mellor, David; Newman, Greg; Hmelo-Silver, Cindy; LaDeau, Shannon; Biehler, Dawn; Crall, Alycia

2016-06-01

Citizen science has generated a growing interest among scientists and community groups, and citizen science programs have been created specifically for conservation. We examined collaborative science, a highly interactive form of citizen science, which we developed within a theoretically informed framework. In this essay, we focused on 2 aspects of our framework: social learning and adaptive management. Social learning, in contrast to individual-based learning, stresses collaborative and generative insight making and is well-suited for adaptive management. Adaptive-management integrates feedback loops that are informed by what is learned and is guided by iterative decision making. Participants engaged in citizen science are able to add to what they are learning through primary data collection, which can result in the real-time information that is often necessary for conservation. Our work is particularly timely because research publications consistently report a lack of established frameworks and evaluation plans to address the extent of conservation outcomes in citizen science. To illustrate how our framework supports conservation through citizen science, we examined how 2 programs enacted our collaborative science framework. Further, we inspected preliminary conservation outcomes of our case-study programs. These programs, despite their recent implementation, are demonstrating promise with regard to positive conservation outcomes. To date, they are independently earning funds to support research, earning buy-in from local partners to engage in experimentation, and, in the absence of leading scientists, are collecting data to test ideas. We argue that this success is due to citizen scientists being organized around local issues and engaging in iterative, collaborative, and adaptive learning. © 2016 Society for Conservation Biology.

Topographic and fire weather controls of fire refugia in forested ecosystems of northwestern North America

USGS Publications Warehouse

Krawchuk, Meg A.; Haire, Sandra L.; Coop, Jonathan D.; Parisien, Marc-Andre; Whitman, Ellen; Chong, Geneva W.; Miller, Carol

2016-01-01

for seven study fires that burned in conifer-dominated forested landscapes of the Western Cordillera of Canada between 2001 and 2014. We fit nine models, each for distinct levels of fire weather and terrain ruggedness. Our framework revealed that the predictability and abundance of fire refugia varied among these environmental settings. We observed highest predictability under moderate fire weather conditions and moderate terrain ruggedness (ROC-AUC = 0.77), and lowest predictability in flatter landscapes and under high fire weather conditions (ROC-AUC = 0.63–0.68). Catchment slope, local aspect, relative position, topographic wetness, topographic convergence, and local slope all contributed to discriminating where refugia occur but the relative importance of these topographic controls differed among environments. Our framework allows us to characterize the predictability of contemporary fire refugia across multiple environmental settings and provides important insights for ecosystem resilience, wildfire management, conservation planning, and climate change adaptation.

Iterative inversion of deformation vector fields with feedback control.

PubMed

Dubey, Abhishek; Iliopoulos, Alexandros-Stavros; Sun, Xiaobai; Yin, Fang-Fang; Ren, Lei

2018-05-14

Often, the inverse deformation vector field (DVF) is needed together with the corresponding forward DVF in four-dimesional (4D) reconstruction and dose calculation, adaptive radiation therapy, and simultaneous deformable registration. This study aims at improving both accuracy and efficiency of iterative algorithms for DVF inversion, and advancing our understanding of divergence and latency conditions. We introduce a framework of fixed-point iteration algorithms with active feedback control for DVF inversion. Based on rigorous convergence analysis, we design control mechanisms for modulating the inverse consistency (IC) residual of the current iterate, to be used as feedback into the next iterate. The control is designed adaptively to the input DVF with the objective to enlarge the convergence area and expedite convergence. Three particular settings of feedback control are introduced: constant value over the domain throughout the iteration; alternating values between iteration steps; and spatially variant values. We also introduce three spectral measures of the displacement Jacobian for characterizing a DVF. These measures reveal the critical role of what we term the nontranslational displacement component (NTDC) of the DVF. We carry out inversion experiments with an analytical DVF pair, and with DVFs associated with thoracic CT images of six patients at end of expiration and end of inspiration. The NTDC-adaptive iterations are shown to attain a larger convergence region at a faster pace compared to previous nonadaptive DVF inversion iteration algorithms. By our numerical experiments, alternating control yields smaller IC residuals and inversion errors than constant control. Spatially variant control renders smaller residuals and errors by at least an order of magnitude, compared to other schemes, in no more than 10 steps. Inversion results also show remarkable quantitative agreement with analysis-based predictions. Our analysis captures properties of DVF data associated with clinical CT images, and provides new understanding of iterative DVF inversion algorithms with a simple residual feedback control. Adaptive control is necessary and highly effective in the presence of nonsmall NTDCs. The adaptive iterations or the spectral measures, or both, may potentially be incorporated into deformable image registration methods. © 2018 American Association of Physicists in Medicine.

Nonlinear feedback drives homeostatic plasticity in H2O2 stress response

PubMed Central

Goulev, Youlian; Morlot, Sandrine; Matifas, Audrey; Huang, Bo; Molin, Mikael; Toledano, Michel B; Charvin, Gilles

2017-01-01

Homeostatic systems that rely on genetic regulatory networks are intrinsically limited by the transcriptional response time, which may restrict a cell’s ability to adapt to unanticipated environmental challenges. To bypass this limitation, cells have evolved mechanisms whereby exposure to mild stress increases their resistance to subsequent threats. However, the mechanisms responsible for such adaptive homeostasis remain largely unknown. Here, we used live-cell imaging and microfluidics to investigate the adaptive response of budding yeast to temporally controlled H2O2 stress patterns. We demonstrate that acquisition of tolerance is a systems-level property resulting from nonlinearity of H2O2 scavenging by peroxiredoxins and our study reveals that this regulatory scheme induces a striking hormetic effect of extracellular H2O2 stress on replicative longevity. Our study thus provides a novel quantitative framework bridging the molecular architecture of a cellular homeostatic system to the emergence of nonintuitive adaptive properties. DOI: http://dx.doi.org/10.7554/eLife.23971.001 PMID:28418333

Adaptive [theta]-methods for pricing American options

NASA Astrophysics Data System (ADS)

Khaliq, Abdul Q. M.; Voss, David A.; Kazmi, Kamran

2008-12-01

We develop adaptive [theta]-methods for solving the Black-Scholes PDE for American options. By adding a small, continuous term, the Black-Scholes PDE becomes an advection-diffusion-reaction equation on a fixed spatial domain. Standard implementation of [theta]-methods would require a Newton-type iterative procedure at each time step thereby increasing the computational complexity of the methods. Our linearly implicit approach avoids such complications. We establish a general framework under which [theta]-methods satisfy a discrete version of the positivity constraint characteristic of American options, and numerically demonstrate the sensitivity of the constraint. The positivity results are established for the single-asset and independent two-asset models. In addition, we have incorporated and analyzed an adaptive time-step control strategy to increase the computational efficiency. Numerical experiments are presented for one- and two-asset American options, using adaptive exponential splitting for two-asset problems. The approach is compared with an iterative solution of the two-asset problem in terms of computational efficiency.

People Capability Maturity Model. SM.

DTIC Science & Technology

1995-09-01

People Capability Maturity Model SM .^^^^_ -——’ Bill Curtis William E. ] Sally Mille] Hefley r Accesion For t NTIS DTIC...People CMM The P-CMM adapts the architecture and the maturity framework underlying the CMM for use with people-related improvement issues. The CMM...focuses on helping organizations improve their software development processes. By adapting the maturity framework and the CMM architecture

Use of intervention mapping to adapt a health behavior change intervention for endometrial cancer survivors: the shape-up following cancer treatment program.

PubMed

Koutoukidis, Dimitrios A; Lopes, Sonia; Atkins, Lou; Croker, Helen; Knobf, M Tish; Lanceley, Anne; Beeken, Rebecca J

2018-03-27

About 80% of endometrial cancer survivors (ECS) are overweight or obese and have sedentary behaviors. Lifestyle behavior interventions are promising for improving dietary and physical activity behaviors, but the constructs associated with their effectiveness are often inadequately reported. The aim of this study was to systematically adapt an evidence-based behavior change program to improve healthy lifestyle behaviors in ECS. Following a review of the literature, focus groups and interviews were conducted with ECS (n = 16). An intervention mapping protocol was used for the program adaptation, which consisted of six steps: a needs assessment, formulation of matrices of change objectives, selection of theoretical methods and practical applications, program production, adoption and implementation planning, and evaluation planning. Social Cognitive Theory and Control Theory guided the adaptation of the intervention. The process consisted of eight 90-min group sessions focusing on shaping outcome expectations, knowledge, self-efficacy, and goals about healthy eating and physical activity. The adapted performance objectives included establishment of regular eating, balanced diet, and portion sizes, reduction in sedentary behaviors, increase in lifestyle and organized activities, formulation of a discrepancy-reducing feedback loop for all above behaviors, and trigger management. Information on managing fatigue and bowel issues unique to ECS were added. Systematic intervention mapping provided a framework to design a cancer survivor-centered lifestyle intervention. ECS welcomed the intervention and provided essential feedback for its adaptation. The program has been evaluated through a randomized controlled trial.

The Resilience Assessment Framework: a common indicator for land management?

NASA Astrophysics Data System (ADS)

Cowie, Annette; Metternicht, Graciela; O'Connell, Deborah

2015-04-01

At the Rio+20 conference in June 2013, the United Nations Convention to Combat Desertification (UNCCD), the Convention on Biological Diversity (CBD), and the United Nations Framework Convention on Climate Change (UNFCCC) reinforced their mutual interests in building linkages between biodiversity conservation, sustainable land management, and climate change mitigation and adaptation. The UNCCD sees building resilience of agro-ecosystems as a common interest that could strengthen linkages between the conventions and deliver synergies in progressing goals of each of the conventions. Furthermore, enhancing resilience of productive agro-ecosystems is fundamental to food security and sustainable development, and thus aligns with the Sustainable Development Goals (SDGs). The Global Environment Facility (GEF) shares the interest of the conventions in building resilience in agro-ecosystems. Indicators of resilience are required for monitoring progress in these endeavors, application of a common indicator between the UNCCD, UNFCCC and CBD as a measure of both land-based adaptation and ecosystem resilience, could strengthen links between the conventions and increase attention to the broad benefits of improved land management. Consequently, the Scientific and Technical Advisory Panel (STAP) to the GEF commissioned the Commonwealth Scientific and Industrial Research Organisation (CSIRO) to produce a report reviewing the conceptual basis for resilience, and proposing an indicator approach that could meet the needs of the Conventions and the GEF for an indicator of agro-ecosystem resilience and land-based adaption. The paper presents a synthesis of scientific understanding of resilience in agro-ecosystems, reviews indicators that have been proposed, and, having concluded that none of the extant indicator approaches adequately assesses resilience of agro-ecosystems, proposes a new approach to the assessment of resilience. Recognizing that no single indicator of resilience is applicable to all agro-ecosystems, and that involvement of stakeholders is critical to discerning the critical variables to be assessed, the proposed framework uses an iterative participatory approach to characterise the system, considering also interactions across and within scales; identify the controlling variables, and assess proximity to thresholds, and adaptive capacity. The framework consists of four elements: Element A: System description; Element B Assessing the system; Element C Adaptive governance and management; Element D Participatory process. Element D is intended as a cross-cutting element, applying across Elements A to C, although Elements A and B can be applied as a desktop activity in a preliminary assessment. The results of the assessment are synthesised in "Resilience action indicators", that summarise the state of the system with respect to the need to adapt or transform. The presentation will summarise the framework and the responses of expert reviewers who identified strengths of the approach, and challenges for implementation, particularly at program and national scales. The presentation will emphasise the conceptual basis for the approach, and the role of scientists in testing, refining and operationalizing the approach.

Ventral striatum and the evaluation of memory retrieval strategies.

PubMed

Badre, David; Lebrecht, Sophie; Pagliaccio, David; Long, Nicole M; Scimeca, Jason M

2014-09-01

Adaptive memory retrieval requires mechanisms of cognitive control that facilitate the recovery of goal-relevant information. Frontoparietal systems are known to support control of memory retrieval. However, the mechanisms by which the brain acquires, evaluates, and adapts retrieval strategies remain unknown. Here, we provide evidence that ventral striatal activation tracks the success of a retrieval strategy and correlates with subsequent reliance on that strategy. Human participants were scanned with fMRI while performing a lexical decision task. A rule was provided that indicated the likely semantic category of a target word given the category of a preceding prime. Reliance on the rule improved decision-making, as estimated within a drift diffusion framework. Ventral striatal activation tracked the benefit that relying on the rule had on decision-making. Moreover, activation in ventral striatum correlated with a participant's subsequent reliance on the rule. Taken together, these results support a role for ventral striatum in learning and evaluating declarative retrieval strategies.

O(t-α)-synchronization and Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations.

PubMed

Chen, Jiejie; Chen, Boshan; Zeng, Zhigang

2018-04-01

This paper investigates O(t -α )-synchronization and adaptive Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations. Firstly, based on the framework of Filippov solution and differential inclusion theory, using a Razumikhin-type method, some sufficient conditions ensuring the global O(t -α )-synchronization of considered networks are established via a linear-type discontinuous control. Next, a new fractional differential inequality is established and two new discontinuous adaptive controller is designed to achieve Mittag-Leffler synchronization between the drive system and the response systems using this inequality. Finally, two numerical simulations are given to show the effectiveness of the theoretical results. Our approach and theoretical results have a leading significance in the design of synchronized fractional-order memristive neural networks circuits involving discontinuous activations and time-varying delays. Copyright © 2018 Elsevier Ltd. All rights reserved.

Programming adaptive control to evolve increased metabolite production.

PubMed

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.

Bayesian randomized clinical trials: From fixed to adaptive design.

PubMed

Yin, Guosheng; Lam, Chi Kin; Shi, Haolun

2017-08-01

Randomized controlled studies are the gold standard for phase III clinical trials. Using α-spending functions to control the overall type I error rate, group sequential methods are well established and have been dominating phase III studies. Bayesian randomized design, on the other hand, can be viewed as a complement instead of competitive approach to the frequentist methods. For the fixed Bayesian design, the hypothesis testing can be cast in the posterior probability or Bayes factor framework, which has a direct link to the frequentist type I error rate. Bayesian group sequential design relies upon Bayesian decision-theoretic approaches based on backward induction, which is often computationally intensive. Compared with the frequentist approaches, Bayesian methods have several advantages. The posterior predictive probability serves as a useful and convenient tool for trial monitoring, and can be updated at any time as the data accrue during the trial. The Bayesian decision-theoretic framework possesses a direct link to the decision making in the practical setting, and can be modeled more realistically to reflect the actual cost-benefit analysis during the drug development process. Other merits include the possibility of hierarchical modeling and the use of informative priors, which would lead to a more comprehensive utilization of information from both historical and longitudinal data. From fixed to adaptive design, we focus on Bayesian randomized controlled clinical trials and make extensive comparisons with frequentist counterparts through numerical studies. Copyright © 2017 Elsevier Inc. All rights reserved.

Building health behavior models to guide the development of just-in-time adaptive interventions: A pragmatic framework.

PubMed

Nahum-Shani, Inbal; Hekler, Eric B; Spruijt-Metz, Donna

2015-12-01

Advances in wireless devices and mobile technology offer many opportunities for delivering just-in-time adaptive interventions (JITAIs)-suites of interventions that adapt over time to an individual's changing status and circumstances with the goal to address the individual's need for support, whenever this need arises. A major challenge confronting behavioral scientists aiming to develop a JITAI concerns the selection and integration of existing empirical, theoretical and practical evidence into a scientific model that can inform the construction of a JITAI and help identify scientific gaps. The purpose of this paper is to establish a pragmatic framework that can be used to organize existing evidence into a useful model for JITAI construction. This framework involves clarifying the conceptual purpose of a JITAI, namely, the provision of just-in-time support via adaptation, as well as describing the components of a JITAI and articulating a list of concrete questions to guide the establishment of a useful model for JITAI construction. The proposed framework includes an organizing scheme for translating the relatively static scientific models underlying many health behavior interventions into a more dynamic model that better incorporates the element of time. This framework will help to guide the next generation of empirical work to support the creation of effective JITAIs. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

A Model Framework to Estimate Impact and Cost of Genetics-Based Sterile Insect Methods for Dengue Vector Control

PubMed Central

Alphey, Nina; Alphey, Luke; Bonsall, Michael B.

2011-01-01

Vector-borne diseases impose enormous health and economic burdens and additional methods to control vector populations are clearly needed. The Sterile Insect Technique (SIT) has been successful against agricultural pests, but is not in large-scale use for suppressing or eliminating mosquito populations. Genetic RIDL technology (Release of Insects carrying a Dominant Lethal) is a proposed modification that involves releasing insects that are homozygous for a repressible dominant lethal genetic construct rather than being sterilized by irradiation, and could potentially overcome some technical difficulties with the conventional SIT technology. Using the arboviral disease dengue as an example, we combine vector population dynamics and epidemiological models to explore the effect of a program of RIDL releases on disease transmission. We use these to derive a preliminary estimate of the potential cost-effectiveness of vector control by applying estimates of the costs of SIT. We predict that this genetic control strategy could eliminate dengue rapidly from a human community, and at lower expense (approximately US$ 2∼30 per case averted) than the direct and indirect costs of disease (mean US$ 86–190 per case of dengue). The theoretical framework has wider potential use; by appropriately adapting or replacing each component of the framework (entomological, epidemiological, vector control bio-economics and health economics), it could be applied to other vector-borne diseases or vector control strategies and extended to include other health interventions. PMID:21998654

Should the United Nations Framework Convention on Climate Change recognize climate migrants?

NASA Astrophysics Data System (ADS)

Gibb, Christine; Ford, James

2012-12-01

Climate change is expected to increase migration flows, especially from socially and environmentally vulnerable populations. These ‘climate migrants’ do not have any official protection under international law, which has implications for the human security of migrants. This work argues that the United Nations Framework Convention on Climate Change (UNFCCC) can and should recognize climate migrants, and is the most relevant international framework for doing so. While not legally binding, the acknowledgment of climate displacement, migration and planned relocation issues in the UNFCCC’s Cancun Adaptation Framework indicates a willingness to address the issue through an adaptation lens. Herein, the paper proposes a framework for setting the institutional groundwork for recognizing climate migrants, focusing on the most vulnerable, promoting targeted research and policy agendas, and situating policies within a comprehensive strategy.

Consolidating strategic planning and operational frameworks for integrated vector management in Eritrea.

PubMed

Chanda, Emmanuel; Ameneshewa, Birkinesh; Mihreteab, Selam; Berhane, Araia; Zehaie, Assefash; Ghebrat, Yohannes; Usman, Abdulmumini

2015-12-02

Contemporary malaria vector control relies on the use of insecticide-based, indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs). However, malaria-endemic countries, including Eritrea, have struggled to effectively deploy these tools due technical and operational challenges, including the selection of insecticide resistance in malaria vectors. This manuscript outlines the processes undertaken in consolidating strategic planning and operational frameworks for vector control to expedite malaria elimination in Eritrea. The effort to strengthen strategic frameworks for vector control in Eritrea was the 'case' for this study. The integrated vector management (IVM) strategy was developed in 2010 but was not well executed, resulting in a rise in malaria transmission, prompting a process to redefine and relaunch the IVM strategy with integration of other vector borne diseases (VBDs) as the focus. The information sources for this study included all available data and accessible archived documentary records on malaria vector control in Eritrea. Structured literature searches of published, peer-reviewed sources using online, scientific, bibliographic databases, Google Scholar, PubMed and WHO, and a combination of search terms were utilized to gather data. The literature was reviewed and adapted to the local context and translated into the consolidated strategic framework. In Eritrea, communities are grappling with the challenge of VBDs posing public health concerns, including malaria. The global fund financed the scale-up of IRS and LLIN programmes in 2014. Eritrea is transitioning towards malaria elimination and strategic frameworks for vector control have been consolidated by: developing an integrated vector management (IVM) strategy (2015-2019); updating IRS and larval source management (LSM) guidelines; developing training manuals for IRS and LSM; training of national staff in malaria entomology and vector control, including insecticide resistance monitoring techniques; initiating the global plan for insecticide resistance management; conducting needs' assessments and developing standard operating procedure for insectaries; developing a guidance document on malaria vector control based on eco-epidemiological strata, a vector surveillance plan and harmonized mapping, data collection and reporting tools. Eritrea has successfully consolidated strategic frameworks for vector control. Rational decision-making remains critical to ensure that the interventions are effective and their choice is evidence-based, and to optimize the use of resources for vector control. Implementation of effective IVM requires proper collaboration and coordination, consistent technical and financial capacity and support to offer greater benefits.

Optimal control of native predators

USGS Publications Warehouse

Martin, Julien; O'Connell, Allan F.; Kendall, William L.; Runge, Michael C.; Simons, Theodore R.; Waldstein, Arielle H.; Schulte, Shiloh A.; Converse, Sarah J.; Smith, Graham W.; Pinion, Timothy; Rikard, Michael; Zipkin, Elise F.

2010-01-01

We apply decision theory in a structured decision-making framework to evaluate how control of raccoons (Procyon lotor), a native predator, can promote the conservation of a declining population of American Oystercatchers (Haematopus palliatus) on the Outer Banks of North Carolina. Our management objective was to maintain Oystercatcher productivity above a level deemed necessary for population recovery while minimizing raccoon removal. We evaluated several scenarios including no raccoon removal, and applied an adaptive optimization algorithm to account for parameter uncertainty. We show how adaptive optimization can be used to account for uncertainties about how raccoon control may affect Oystercatcher productivity. Adaptive management can reduce this type of uncertainty and is particularly well suited for addressing controversial management issues such as native predator control. The case study also offers several insights that may be relevant to the optimal control of other native predators. First, we found that stage-specific removal policies (e.g., yearling versus adult raccoon removals) were most efficient if the reproductive values among stage classes were very different. Second, we found that the optimal control of raccoons would result in higher Oystercatcher productivity than the minimum levels recommended for this species. Third, we found that removing more raccoons initially minimized the total number of removals necessary to meet long term management objectives. Finally, if for logistical reasons managers cannot sustain a removal program by removing a minimum number of raccoons annually, managers may run the risk of creating an ecological trap for Oystercatchers.

IVHM Framework for Intelligent Integration for Vehicle Health Management

NASA Technical Reports Server (NTRS)

Paris, Deidre; Trevino, Luis C.; Watson, Michael D.

2005-01-01

Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, is the process of assessing, preserving, and restoring system functionality across flight and techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of Integrated Intelligent Vehicle Management (IIVM). These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, this framework integrates technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear that IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives. These systems include the following: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle Mission Planning, Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations.

Compromise-based Robust Prioritization of Climate Change Adaptation Strategies for Watershed Management

NASA Astrophysics Data System (ADS)

Kim, Y.; Chung, E. S.

2014-12-01

This study suggests a robust prioritization framework for climate change adaptation strategies under multiple climate change scenarios with a case study of selecting sites for reusing treated wastewater (TWW) in a Korean urban watershed. The framework utilizes various multi-criteria decision making techniques, including the VIKOR method and the Shannon entropy-based weights. In this case study, the sustainability of TWW use is quantified with indicator-based approaches with the DPSIR framework, which considers both hydro-environmental and socio-economic aspects of the watershed management. Under the various climate change scenarios, the hydro-environmental responses to reusing TWW in potential alternative sub-watersheds are determined using the Hydrologic Simulation Program in Fortran (HSPF). The socio-economic indicators are obtained from the statistical databases. Sustainability scores for multiple scenarios are estimated individually and then integrated with the proposed approach. At last, the suggested framework allows us to prioritize adaptation strategies in a robust manner with varying levels of compromise between utility-based and regret-based strategies.

Adapting cognitive behavioral therapy for psychosis for case managers: increasing access to services in a community mental health agency.

PubMed

Montesano, Vicki L; Sivec, Harry J; Munetz, Mark R; Pelton, Jeremy R; Turkington, Douglas

2014-03-01

The purpose of this article is twofold: (a) to describe the adaptation of an evidence-based practice and, (b) using a dissemination framework, to describe the process of implementing the practice at a community mental health agency. The authors describe the training concept and dissemination framework of implementing an emerging practice: high-yield cognitive behavioral techniques for psychosis, which is rooted in cognitive behavioral therapy. Thirteen case managers who represented teams from across the agency delivered the adapted practice at a community mental health agency. Implementation required buy in from all stakeholders, communication across disciplines, persistence, and flexibility. It appears that the use of a dissemination framework that is grounded in the literature, yet flexible, eases the process of implementing an adapted practice. Further research focusing on the effectiveness of this approach, along with the impact of implementing a full spectrum of cognitive behavioral therapy services for individuals with persistent psychotic symptoms, based on cognitive behavioral therapy principles, is indicated.

Applying a Theory-Driven Framework to Guide Quality Improvement Efforts in Nursing Homes: The LOCK Model.

PubMed

Mills, Whitney L; Pimentel, Camilla B; Palmer, Jennifer A; Snow, A Lynn; Wewiorski, Nancy J; Allen, Rebecca S; Hartmann, Christine W

2018-05-08

Implementing quality improvement (QI) programs in nursing homes continues to encounter significant challenges, despite recognized need. QI approaches provide nursing home staff with opportunities to collaborate on developing and testing strategies for improving care delivery. We present a theory-driven and user-friendly adaptable framework and facilitation package to overcome existing challenges and guide QI efforts in nursing homes. The framework is grounded in the foundational concepts of strengths-based learning, observation, relationship-based teams, efficiency, and organizational learning. We adapted these concepts to QI in the nursing home setting, creating the "LOCK" framework. The LOCK framework is currently being disseminated across the Veterans Health Administration. The LOCK framework has five tenets: (a) Look for the bright spots, (b) Observe, (c) Collaborate in huddles, (d) Keep it bite-sized, and (e) facilitation. Each tenet is described. We also present a case study documenting how a fictional nursing home can implement the LOCK framework as part of a QI effort to improve engagement between staff and residents. The case study describes sample observations, processes, and outcomes. We also discuss practical applications for nursing home staff, the adaptability of LOCK for different QI projects, the specific role of facilitation, and lessons learned. The proposed framework complements national efforts to improve quality of care and quality of life for nursing home residents and may be valuable across long-term care settings and QI project types.

Transformative governance of urban social-ecological systems

EPA Science Inventory

A central aspect of adaptive governance is a learning process that can help communities achieve environmental objectives. Adaptive governance is a framework for managing social-ecological systems, and is the precursor to transformative governance. Adaptive governance accounts for...

Adaptive optimization as a design and management methodology for coal-mining enterprise in uncertain and volatile market environment - the conceptual framework

NASA Astrophysics Data System (ADS)

Mikhalchenko, V. V.; Rubanik, Yu T.

2016-10-01

The work is devoted to the problem of cost-effective adaptation of coal mines to the volatile and uncertain market conditions. Conceptually it can be achieved through alignment of the dynamic characteristics of the coal mining system and power spectrum of market demand for coal product. In practical terms, this ensures the viability and competitiveness of coal mines. Transformation of dynamic characteristics is to be done by changing the structure of production system as well as corporate, logistics and management processes. The proposed methods and algorithms of control are aimed at the development of the theoretical foundations of adaptive optimization as basic methodology for coal mine enterprise management in conditions of high variability and uncertainty of economic and natural environment. Implementation of the proposed methodology requires a revision of the basic principles of open coal mining enterprises design.

Adaptive Nonparametric Kinematic Modeling of Concentric Tube Robots.

PubMed

Fagogenis, Georgios; Bergeles, Christos; Dupont, Pierre E

2016-10-01

Concentric tube robots comprise telescopic precurved elastic tubes. The robot's tip and shape are controlled via relative tube motions, i.e. tube rotations and translations. Non-linear interactions between the tubes, e.g. friction and torsion, as well as uncertainty in the physical properties of the tubes themselves, e.g. the Young's modulus, curvature, or stiffness, hinder accurate kinematic modelling. In this paper, we present a machine-learning-based methodology for kinematic modelling of concentric tube robots and in situ model adaptation. Our approach is based on Locally Weighted Projection Regression (LWPR). The model comprises an ensemble of linear models, each of which locally approximates the original complex kinematic relation. LWPR can accommodate for model deviations by adjusting the respective local models at run-time, resulting in an adaptive kinematics framework. We evaluated our approach on data gathered from a three-tube robot, and report high accuracy across the robot's configuration space.

Accountability for quality of care: Monitoring all aspects of quality across a framework adapted for action.

PubMed

Hulton, Louise; Matthews, Zoë; Bandali, Sarah; Izge, Abubakar; Daroda, Ramatu; Stones, William

2016-01-01

Quality of care is essential to maternal and newborn survival. The multidimensional nature of quality of care means that frameworks are useful for capturing it. The present paper proposes an adaptation to a widely used quality of care framework for maternity services. The framework subdivides quality into two inter-related dimensions-provision and experience of care-but suggests adaptations to reflect changes in the concept of quality over the past 15years. The application of the updated framework is presented in a case study, which uses it to measure and inform quality improvements in northern Nigeria across the reproductive, maternal, newborn, and child health continuum of care. Data from 231 sampled basic and comprehensive emergency obstetric and newborn care (BEmONC and CEmONC) facilities in six northern Nigerian states showed that only 35%-47% of facilities met minimum quality standards in infrastructure. Standards for human resources performed better with 49%-73% reaching minimum standards. A framework like this could form the basis for a certification scheme. Certification offers a practical and concrete opportunity to drive quality standards up and reward good performance. It also offers a mechanism to strengthen accountability. Copyright © 2015 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Feedback (F) Fueling Adaptation (A) Network Growth (N) and Self-Organization (S): A Complex Systems Design and Evaluation Approach to Professional Development

ERIC Educational Resources Information Center

Yoon, Susan A.; Klopfer, Eric

2006-01-01

This paper reports on the efficacy of a professional development framework premised on four complex systems design principles: Feedback, Adaptation, Network Growth and Self-organization (FANS). The framework is applied to the design and delivery of the first 2 years of a 3-year study aimed at improving teacher and student understanding of…

Applying the global RCP-SSP-SPA scenario framework at sub-national scale: A multi-scale and participatory scenario approach.

PubMed

Kebede, Abiy S; Nicholls, Robert J; Allan, Andrew; Arto, Iñaki; Cazcarro, Ignacio; Fernandes, Jose A; Hill, Chris T; Hutton, Craig W; Kay, Susan; Lázár, Attila N; Macadam, Ian; Palmer, Matthew; Suckall, Natalie; Tompkins, Emma L; Vincent, Katharine; Whitehead, Paul W

2018-09-01

To better anticipate potential impacts of climate change, diverse information about the future is required, including climate, society and economy, and adaptation and mitigation. To address this need, a global RCP (Representative Concentration Pathways), SSP (Shared Socio-economic Pathways), and SPA (Shared climate Policy Assumptions) (RCP-SSP-SPA) scenario framework has been developed by the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC-AR5). Application of this full global framework at sub-national scales introduces two key challenges: added complexity in capturing the multiple dimensions of change, and issues of scale. Perhaps for this reason, there are few such applications of this new framework. Here, we present an integrated multi-scale hybrid scenario approach that combines both expert-based and participatory methods. The framework has been developed and applied within the DECCMA 1 project with the purpose of exploring migration and adaptation in three deltas across West Africa and South Asia: (i) the Volta delta (Ghana), (ii) the Mahanadi delta (India), and (iii) the Ganges-Brahmaputra-Meghna (GBM) delta (Bangladesh/India). Using a climate scenario that encompasses a wide range of impacts (RCP8.5) combined with three SSP-based socio-economic scenarios (SSP2, SSP3, SSP5), we generate highly divergent and challenging scenario contexts across multiple scales against which robustness of the human and natural systems within the deltas are tested. In addition, we consider four distinct adaptation policy trajectories: Minimum intervention, Economic capacity expansion, System efficiency enhancement, and System restructuring, which describe alternative future bundles of adaptation actions/measures under different socio-economic trajectories. The paper highlights the importance of multi-scale (combined top-down and bottom-up) and participatory (joint expert-stakeholder) scenario methods for addressing uncertainty in adaptation decision-making. The framework facilitates improved integrated assessments of the potential impacts and plausible adaptation policy choices (including migration) under uncertain future changing conditions. The concept, methods, and processes presented are transferable to other sub-national socio-ecological settings with multi-scale challenges. Copyright © 2018. Published by Elsevier B.V.

Modular and Adaptive Control of Sound Processing

NASA Astrophysics Data System (ADS)

van Nort, Douglas

This dissertation presents research into the creation of systems for the control of sound synthesis and processing. The focus differs from much of the work related to digital musical instrument design, which has rightly concentrated on the physicality of the instrument and interface: sensor design, choice of controller, feedback to performer and so on. Often times a particular choice of sound processing is made, and the resultant parameters from the physical interface are conditioned and mapped to the available sound parameters in an exploratory fashion. The main goal of the work presented here is to demonstrate the importance of the space that lies between physical interface design and the choice of sound manipulation algorithm, and to present a new framework for instrument design that strongly considers this essential part of the design process. In particular, this research takes the viewpoint that instrument designs should be considered in a musical control context, and that both control and sound dynamics must be considered in tandem. In order to achieve this holistic approach, the work presented in this dissertation assumes complementary points of view. Instrument design is first seen as a function of musical context, focusing on electroacoustic music and leading to a view on gesture that relates perceived musical intent to the dynamics of an instrumental system. The important design concept of mapping is then discussed from a theoretical and conceptual point of view, relating perceptual, systems and mathematically-oriented ways of examining the subject. This theoretical framework gives rise to a mapping design space, functional analysis of pertinent existing literature, implementations of mapping tools, instrumental control designs and several perceptual studies that explore the influence of mapping structure. Each of these reflect a high-level approach in which control structures are imposed on top of a high-dimensional space of control and sound synthesis parameters. In this view, desired gestural dynamics and sonic response are achieved through modular construction of mapping layers that are themselves subject to parametric control. Complementing this view of the design process, the work concludes with an approach in which the creation of gestural control/sound dynamics are considered in the low-level of the underlying sound model. The result is an adaptive system that is specialized to noise-based transformations that are particularly relevant in an electroacoustic music context. Taken together, these different approaches to design and evaluation result in a unified framework for creation of an instrumental system. The key point is that this framework addresses the influence that mapping structure and control dynamics have on the perceived feel of the instrument. Each of the results illustrate this using either top-down or bottom-up approaches that consider musical control context, thereby pointing to the greater potential for refined sonic articulation that can be had by combining them in the design process.

Skeletal muscle mechanics, energetics and plasticity.

PubMed

Lieber, Richard L; Roberts, Thomas J; Blemker, Silvia S; Lee, Sabrina S M; Herzog, Walter

2017-10-23

The following papers by Richard Lieber (Skeletal Muscle as an Actuator), Thomas Roberts (Elastic Mechanisms and Muscle Function), Silvia Blemker (Skeletal Muscle has a Mind of its Own: a Computational Framework to Model the Complex Process of Muscle Adaptation) and Sabrina Lee (Muscle Properties of Spastic Muscle (Stroke and CP) are summaries of their representative contributions for the session on skeletal muscle mechanics, energetics and plasticity at the 2016 Biomechanics and Neural Control of Movement Conference (BANCOM 2016). Dr. Lieber revisits the topic of sarcomere length as a fundamental property of skeletal muscle contraction. Specifically, problems associated with sarcomere length non-uniformity and the role of sarcomerogenesis in diseases such as cerebral palsy are critically discussed. Dr. Roberts then makes us aware of the (often neglected) role of the passive tissues in muscles and discusses the properties of parallel elasticity and series elasticity, and their role in muscle function. Specifically, he identifies the merits of analyzing muscle deformations in three dimensions (rather than just two), because of the potential decoupling of the parallel elastic element length from the contractile element length, and reviews the associated implications for the architectural gear ratio of skeletal muscle contraction. Dr. Blemker then tackles muscle adaptation using a novel way of looking at adaptive processes and what might drive adaptation. She argues that cells do not have pre-programmed behaviors that are controlled by the nervous system. Rather, the adaptive responses of muscle fibers are determined by sub-cellular signaling pathways that are affected by mechanical and biochemical stimuli; an exciting framework with lots of potential. Finally, Dr. Lee takes on the challenging task of determining human muscle properties in vivo. She identifies the dilemma of how we can demonstrate the effectiveness of a treatment, specifically in cases of muscle spasticity following stroke or in children with cerebral palsy. She then discusses the merits of ultrasound based elastography, and the clinical possibilities this technique might hold. Overall, we are treated to a vast array of basic and clinical problems in skeletal muscle mechanics and physiology, with some solutions, and many suggestions for future research.

To Adapt or Not to Adapt: Navigating an Implementation Conundrum

ERIC Educational Resources Information Center

Leko, Melinda M.

2015-01-01

Maximizing the effectiveness of evidence-based practices (EBPs) requires an optimal balance of implementation fidelity and adaptation so EBPs fit local contexts and meet the individual learning needs of students with disabilities. The framework for classifying adaptations presented in this article can help educators make decisions about whether…

Adaptive mesh refinement and load balancing based on multi-level block-structured Cartesian mesh

NASA Astrophysics Data System (ADS)

Misaka, Takashi; Sasaki, Daisuke; Obayashi, Shigeru

2017-11-01

We developed a framework for a distributed-memory parallel computer that enables dynamic data management for adaptive mesh refinement and load balancing. We employed simple data structure of the building cube method (BCM) where a computational domain is divided into multi-level cubic domains and each cube has the same number of grid points inside, realising a multi-level block-structured Cartesian mesh. Solution adaptive mesh refinement, which works efficiently with the help of the dynamic load balancing, was implemented by dividing cubes based on mesh refinement criteria. The framework was investigated with the Laplace equation in terms of adaptive mesh refinement, load balancing and the parallel efficiency. It was then applied to the incompressible Navier-Stokes equations to simulate a turbulent flow around a sphere. We considered wall-adaptive cube refinement where a non-dimensional wall distance y+ near the sphere is used for a criterion of mesh refinement. The result showed the load imbalance due to y+ adaptive mesh refinement was corrected by the present approach. To utilise the BCM framework more effectively, we also tested a cube-wise algorithm switching where an explicit and implicit time integration schemes are switched depending on the local Courant-Friedrichs-Lewy (CFL) condition in each cube.

Face Adaptation Effects: Reviewing the Impact of Adapting Information, Time, and Transfer

PubMed Central

Strobach, Tilo; Carbon, Claus-Christian

2013-01-01

The ability to adapt is essential to live and survive in an ever-changing environment such as the human ecosystem. Here we review the literature on adaptation effects of face stimuli to give an overview of existing findings in this area, highlight gaps in its research literature, initiate new directions in face adaptation research, and help to design future adaptation studies. Furthermore, this review should lead to better understanding of the processing characteristics as well as the mental representations of face-relevant information. The review systematizes studies at a behavioral level in respect of a framework which includes three dimensions representing the major characteristics of studies in this field of research. These dimensions comprise (1) the specificity of adapting face information, e.g., identity, gender, or age aspects of the material to be adapted to (2) aspects of timing (e.g., the sustainability of adaptation effects) and (3) transfer relations between face images presented during adaptation and adaptation tests (e.g., images of the same or different identities). The review concludes with options for how to combine findings across different dimensions to demonstrate the relevance of our framework for future studies. PMID:23760550

Evidence-based librarianship: an overview.

PubMed

Eldredge, J D

2000-10-01

To demonstrate how the core characteristics of both evidence-based medicine (EBM) and evidence-based health care (EBHC) can be adapted to health sciences librarianship. Narrative review essay involving development of a conceptual framework. The author describes the central features of EBM and EBHC. Following each description of a central feature, the author then suggests ways that this feature applies to health sciences librarianship. First, the decision-making processes of EBM and EBHC are compatible with health sciences librarianship. Second, the EBM and EBHC values of favoring rigorously produced scientific evidence in decision making are congruent with the core values of librarianship. Third, the hierarchical levels of evidence can be applied to librarianship with some modifications. Library researchers currently favor descriptive-survey and case-study methods over systematic reviews, randomized controlled trials, or other higher levels of evidence. The library literature nevertheless contains diverse examples of randomized controlled trials, controlled-comparison studies, and cohort studies conducted by health sciences librarians. Health sciences librarians are confronted with making many practical decisions. Evidence-based librarianship offers a decision-making framework, which integrates the best available research evidence. By employing this framework and the higher levels of research evidence it promotes, health sciences librarians can lay the foundation for more collaborative and scientific endeavors.

Evidence-based librarianship: an overview

PubMed Central

Eldredge, Jonathan D.

2000-01-01

Objective: To demonstrate how the core characteristics of both evidence-based medicine (EBM) and evidence-based health care (EBHC) can be adapted to health sciences librarianship. Method: Narrative review essay involving development of a conceptual framework. The author describes the central features of EBM and EBHC. Following each description of a central feature, the author then suggests ways that this feature applies to health sciences librarianship. Results: First, the decision-making processes of EBM and EBHC are compatible with health sciences librarianship. Second, the EBM and EBHC values of favoring rigorously produced scientific evidence in decision making are congruent with the core values of librarianship. Third, the hierarchical levels of evidence can be applied to librarianship with some modifications. Library researchers currently favor descriptive-survey and case-study methods over systematic reviews, randomized controlled trials, or other higher levels of evidence. The library literature nevertheless contains diverse examples of randomized controlled trials, controlled-comparison studies, and cohort studies conducted by health sciences librarians. Conclusions: Health sciences librarians are confronted with making many practical decisions. Evidence-based librarianship offers a decision-making framework, which integrates the best available research evidence. By employing this framework and the higher levels of research evidence it promotes, health sciences librarians can lay the foundation for more collaborative and scientific endeavors. PMID:11055296

Development of Methodologies for IV and V of Neural Networks

NASA Technical Reports Server (NTRS)

Taylor, Brian; Darrah, Marjorie

2003-01-01

Non-deterministic systems often rely upon neural network (NN) technology to "lean" to manage flight systems under controlled conditions using carefully chosen training sets. How can these adaptive systems be certified to ensure that they will become increasingly efficient and behave appropriately in real-time situations? The bulk of Independent Verification and Validation (IV&V) research of non-deterministic software control systems such as Adaptive Flight Controllers (AFC's) addresses NNs in well-behaved and constrained environments such as simulations and strict process control. However, neither substantive research, nor effective IV&V techniques have been found to address AFC's learning in real-time and adapting to live flight conditions. Adaptive flight control systems offer good extensibility into commercial aviation as well as military aviation and transportation. Consequently, this area of IV&V represents an area of growing interest and urgency. ISR proposes to further the current body of knowledge to meet two objectives: Research the current IV&V methods and assess where these methods may be applied toward a methodology for the V&V of Neural Network; and identify effective methods for IV&V of NNs that learn in real-time, including developing a prototype test bed for IV&V of AFC's. Currently. no practical method exists. lSR will meet these objectives through the tasks identified and described below. First, ISR will conduct a literature review of current IV&V technology. TO do this, ISR will collect the existing body of research on IV&V of non-deterministic systems and neural network. ISR will also develop the framework for disseminating this information through specialized training. This effort will focus on developing NASA's capability to conduct IV&V of neural network systems and to provide training to meet the increasing need for IV&V expertise in such systems.

Ground-based adaptive optics coronagraphic performance under closed-loop predictive control

NASA Astrophysics Data System (ADS)

Males, Jared R.; Guyon, Olivier

2018-01-01

The discovery of the exoplanet Proxima b highlights the potential for the coming generation of giant segmented mirror telescopes (GSMTs) to characterize terrestrial-potentially habitable-planets orbiting nearby stars with direct imaging. This will require continued development and implementation of optimized adaptive optics systems feeding coronagraphs on the GSMTs. Such development should proceed with an understanding of the fundamental limits imposed by atmospheric turbulence. Here, we seek to address this question with a semianalytic framework for calculating the postcoronagraph contrast in a closed-loop adaptive optics system. We do this starting with the temporal power spectra of the Fourier basis calculated assuming frozen flow turbulence, and then apply closed-loop transfer functions. We include the benefits of a simple predictive controller, which we show could provide over a factor of 1400 gain in raw point spread function contrast at 1 λ/D on bright stars, and more than a factor of 30 gain on an I=7.5 mag star such as Proxima. More sophisticated predictive control can be expected to improve this even further. Assuming a photon-noise limited observing technique such as high-dispersion coronagraphy, these gains in raw contrast will decrease integration times by the same large factors. Predictive control of atmospheric turbulence should therefore be seen as one of the key technologies that will enable ground-based telescopes to characterize terrestrial planets.

Cultural adaptation of evidence-based practice utilizing an iterative stakeholder process and theoretical framework: problem solving therapy for Chinese older adults

PubMed Central

Chu, Joyce P.; Huynh, Loanie; Areán, Patricia

2011-01-01

Objectives Main objectives were to familiarize the reader with a theoretical framework for modifying evidence-based interventions for cultural groups, and to provide an example of one method, Formative Method for Adapting Psychotherapies (FMAP), in the adaptation of an evidence-based intervention for a cultural group notorious for refusing mental health treatment. Methods Provider and client stakeholder input combined with an iterative testing process within the FMAP framework was utilized to create the Problem Solving Therapy—Chinese Older Adult (PST-COA) manual for depression. Data from pilot-testing the intervention with a clinically depressed Chinese elderly woman are reported. Results PST-COA is categorized as a ‘culturally-adapted’ treatment, where core mediating mechanisms of PST were preserved, but cultural themes of measurement methodology, stigma, hierarchical provider-client relationship expectations, and acculturation enhanced core components to make PST more understandable and relevant for Chinese elderly. Modifications also encompassed therapeutic framework and peripheral elements affecting engagement and retention. PST-COA applied with a depressed Chinese older adult indicated remission of clinical depression and improvement in mood. Fidelity with and acceptability of the treatment was sufficient as the client completed and reported high satisfaction with PST-COA. Conclusions PST, as a non-emotion-focused, evidence-based intervention, is a good fit for depressed Chinese elderly. Through an iterative stakeholder process of cultural adaptation, several culturally-specific modifications were applied to PST to create the PST-COA manual. PST-COA preserves core therapeutic PST elements but includes cultural adaptations in therapeutic framework and key administration and content areas that ensure greater applicability and effectiveness for the Chinese elderly community. PMID:21500283

Using planned adaptation to implement evidence-based programs with new populations.

PubMed

Lee, Shawna J; Altschul, Inna; Mowbray, Carol T

2008-06-01

The Interactive Systems Framework (ISF) for Dissemination and Implementation (Wandersman et al. 2008) elaborates the functions and structures that move evidence-based programs (EBPs) from research to practice. Inherent in that process is the tension between implementing programs with fidelity and the need to tailor programs to fit the target population. We propose Planned Adaptation as one approach to resolve this tension, with the goal of guiding practitioners in adapting EBPs so that they maintain core components of program theory while taking into account the needs of particular populations. Planned Adaptation is a form of capacity building within the Prevention Support System that provides a framework to guide practitioners in adapting programs while encouraging researchers to provide information relevant to adaptation as a critical aspect of dissemination research, with the goal of promoting wider dissemination and better implementation of EBPs. We illustrate Planned Adaptation using the JOBS Program (Caplan et al. 1989), which was developed for recently laid-off, working- and middle-class workers and subsequently implemented with welfare recipients.

Qualitative analysis of a discrete thermostatted kinetic framework modeling complex adaptive systems

NASA Astrophysics Data System (ADS)

Bianca, Carlo; Mogno, Caterina

2018-01-01

This paper deals with the derivation of a new discrete thermostatted kinetic framework for the modeling of complex adaptive systems subjected to external force fields (nonequilibrium system). Specifically, in order to model nonequilibrium stationary states of the system, the external force field is coupled to a dissipative term (thermostat). The well-posedness of the related Cauchy problem is investigated thus allowing the new discrete thermostatted framework to be suitable for the derivation of specific models and the related computational analysis. Applications to crowd dynamics and future research directions are also discussed within the paper.

Development and Flight Testing of an Adaptive Vehicle Health-Monitoring Architecture

NASA Technical Reports Server (NTRS)

Woodard, Stanley E.; Coffey, Neil C.; Gonzalez, Guillermo A.; Taylor, B. Douglas; Brett, Rube R.; Woodman, Keith L.; Weathered, Brenton W.; Rollins, Courtney H.

2002-01-01

On going development and testing of an adaptable vehicle health-monitoring architecture is presented. The architecture is being developed for a fleet of vehicles. It has three operational levels: one or more remote data acquisition units located throughout the vehicle; a command and control unit located within the vehicle, and, a terminal collection unit to collect analysis results from all vehicles. Each level is capable of performing autonomous analysis with a trained expert system. The expert system is parameterized, which makes it adaptable to be trained to both a user's subject reasoning and existing quantitative analytic tools. Communication between all levels is done with wireless radio frequency interfaces. The remote data acquisition unit has an eight channel programmable digital interface that allows the user discretion for choosing type of sensors; number of sensors, sensor sampling rate and sampling duration for each sensor. The architecture provides framework for a tributary analysis. All measurements at the lowest operational level are reduced to provide analysis results necessary to gauge changes from established baselines. These are then collected at the next level to identify any global trends or common features from the prior level. This process is repeated until the results are reduced at the highest operational level. In the framework, only analysis results are forwarded to the next level to reduce telemetry congestion. The system's remote data acquisition hardware and non-analysis software have been flight tested on the NASA Langley B757's main landing gear. The flight tests were performed to validate the following: the wireless radio frequency communication capabilities of the system, the hardware design, command and control; software operation and, data acquisition, storage and retrieval.

A Bayesian Uncertainty Framework for Conceptual Snowmelt and Hydrologic Models Applied to the Tenderfoot Creek Experimental Forest

NASA Astrophysics Data System (ADS)

Smith, T.; Marshall, L.

2007-12-01

In many mountainous regions, the single most important parameter in forecasting the controls on regional water resources is snowpack (Williams et al., 1999). In an effort to bridge the gap between theoretical understanding and functional modeling of snow-driven watersheds, a flexible hydrologic modeling framework is being developed. The aim is to create a suite of models that move from parsimonious structures, concentrated on aggregated watershed response, to those focused on representing finer scale processes and distributed response. This framework will operate as a tool to investigate the link between hydrologic model predictive performance, uncertainty, model complexity, and observable hydrologic processes. Bayesian methods, and particularly Markov chain Monte Carlo (MCMC) techniques, are extremely useful in uncertainty assessment and parameter estimation of hydrologic models. However, these methods have some difficulties in implementation. In a traditional Bayesian setting, it can be difficult to reconcile multiple data types, particularly those offering different spatial and temporal coverage, depending on the model type. These difficulties are also exacerbated by sensitivity of MCMC algorithms to model initialization and complex parameter interdependencies. As a way of circumnavigating some of the computational complications, adaptive MCMC algorithms have been developed to take advantage of the information gained from each successive iteration. Two adaptive algorithms are compared is this study, the Adaptive Metropolis (AM) algorithm, developed by Haario et al (2001), and the Delayed Rejection Adaptive Metropolis (DRAM) algorithm, developed by Haario et al (2006). While neither algorithm is truly Markovian, it has been proven that each satisfies the desired ergodicity and stationarity properties of Markov chains. Both algorithms were implemented as the uncertainty and parameter estimation framework for a conceptual rainfall-runoff model based on the Probability Distributed Model (PDM), developed by Moore (1985). We implement the modeling framework in Stringer Creek watershed in the Tenderfoot Creek Experimental Forest (TCEF), Montana. The snowmelt-driven watershed offers that additional challenge of modeling snow accumulation and melt and current efforts are aimed at developing a temperature- and radiation-index snowmelt model. Auxiliary data available from within TCEF's watersheds are used to support in the understanding of information value as it relates to predictive performance. Because the model is based on lumped parameters, auxiliary data are hard to incorporate directly. However, these additional data offer benefits through the ability to inform prior distributions of the lumped, model parameters. By incorporating data offering different information into the uncertainty assessment process, a cross-validation technique is engaged to better ensure that modeled results reflect real process complexity.

Adjusted Framework of M-Learning in Blended Learning System for Mathematics Study Field of Junior High School Level VII

NASA Astrophysics Data System (ADS)

Sugiyanta, Lipur; Sukardjo, Moch.

2018-04-01

The 2013 curriculum requires teachers to be more productive, creative, and innovative in encouraging students to be more independent by strengthening attitudes, skills and knowledge. Teachers are given the options to create lesson plan according to the environment and conditions of their students. At the junior level, Core Competence (KI) and Basic Competence (KD) have been completely designed. In addition, there had already guidebooks, both for teacher manuals (Master’s Books) and for learners (Student Books). The lesson plan and guidebooks which already exist are intended only for learning in the classroom/in-school. Many alternative classrooms and alternatives learning models opened up using educational technology. The advance of educational technology opened opportunity for combination of class interaction using mobile learning applications. Mobile learning has rapidly evolved in education for the last ten years and many initiatives have been conducted worldwide. However, few of these efforts have produced any lasting outcomes. It is evident that mobile education applications are complex and hence, will not become sustainable. Long-term sustainability remains a risk. Long-term sustainability usually was resulted from continuous adaptation to changing conditions [4]. Frameworks are therefore required to avoid sustainability pitfalls. The implementation should start from simple environment then gradually become complex through adaptation steps. Therefore, our paper developed the framework of mobile learning (m-learning) adaptation for grade 7th (junior high school). The environment setup was blended mobile learning (not full mobile learning) and emphasize on Algebra. The research is done by R&D method (research and development). Results of the framework includes requirements and adaptation steps. The adjusted m-learning framework is designed to be a guidance for teachers to adopt m-learning to support blended learning environments. During mock-up prototype, the adjusted framework demonstrates how to make successful implementation of early blended mobile learning through framework. The Social area is in focus of adaptation because participation is important to improve the sustainability. From the short practice of mock-up prototype, blended mobile learning can be an effective pedagogical model in supporting students in inquiry-based learning.

Exploring Discretization Error in Simulation-Based Aerodynamic Databases

NASA Technical Reports Server (NTRS)

Aftosmis, Michael J.; Nemec, Marian

2010-01-01

This work examines the level of discretization error in simulation-based aerodynamic databases and introduces strategies for error control. Simulations are performed using a parallel, multi-level Euler solver on embedded-boundary Cartesian meshes. Discretization errors in user-selected outputs are estimated using the method of adjoint-weighted residuals and we use adaptive mesh refinement to reduce these errors to specified tolerances. Using this framework, we examine the behavior of discretization error throughout a token database computed for a NACA 0012 airfoil consisting of 120 cases. We compare the cost and accuracy of two approaches for aerodynamic database generation. In the first approach, mesh adaptation is used to compute all cases in the database to a prescribed level of accuracy. The second approach conducts all simulations using the same computational mesh without adaptation. We quantitatively assess the error landscape and computational costs in both databases. This investigation highlights sensitivities of the database under a variety of conditions. The presence of transonic shocks or the stiffness in the governing equations near the incompressible limit are shown to dramatically increase discretization error requiring additional mesh resolution to control. Results show that such pathologies lead to error levels that vary by over factor of 40 when using a fixed mesh throughout the database. Alternatively, controlling this sensitivity through mesh adaptation leads to mesh sizes which span two orders of magnitude. We propose strategies to minimize simulation cost in sensitive regions and discuss the role of error-estimation in database quality.

An Integrated Framework for Model-Based Distributed Diagnosis and Prognosis

NASA Technical Reports Server (NTRS)

Bregon, Anibal; Daigle, Matthew J.; Roychoudhury, Indranil

2012-01-01

Diagnosis and prognosis are necessary tasks for system reconfiguration and fault-adaptive control in complex systems. Diagnosis consists of detection, isolation and identification of faults, while prognosis consists of prediction of the remaining useful life of systems. This paper presents a novel integrated framework for model-based distributed diagnosis and prognosis, where system decomposition is used to enable the diagnosis and prognosis tasks to be performed in a distributed way. We show how different submodels can be automatically constructed to solve the local diagnosis and prognosis problems. We illustrate our approach using a simulated four-wheeled rover for different fault scenarios. Our experiments show that our approach correctly performs distributed fault diagnosis and prognosis in an efficient and robust manner.

Teaching Equivalent Fractions to Secondary Students with Disabilities via the Virtual-Representational-Abstract Instructional Sequence

ERIC Educational Resources Information Center

Bouck, Emily C.; Bassette, Laura; Shurr, Jordan; Park, Jiyoon; Kerr, Jackie; Whorley, Abbie

2017-01-01

Fractions are an important mathematical concept; however, fractions are also a struggle for many students with disabilities. This study explored a new framework adapted from the evidence-based concrete-representational-abstract framework: the virtual-representational-abstract (VRA) framework. The VRA framework involves teaching students to solve…

Decision support frameworks and tools for conservation

USGS Publications Warehouse

Schwartz, Mark W.; Cook, Carly N.; Pressey, Robert L.; Pullin, Andrew S.; Runge, Michael C.; Salafsky, Nick; Sutherland, William J.; Williamson, Matthew A.

2018-01-01

The practice of conservation occurs within complex socioecological systems fraught with challenges that require transparent, defensible, and often socially engaged project planning and management. Planning and decision support frameworks are designed to help conservation practitioners increase planning rigor, project accountability, stakeholder participation, transparency in decisions, and learning. We describe and contrast five common frameworks within the context of six fundamental questions (why, who, what, where, when, how) at each of three planning stages of adaptive management (project scoping, operational planning, learning). We demonstrate that decision support frameworks provide varied and extensive tools for conservation planning and management. However, using any framework in isolation risks diminishing potential benefits since no one framework covers the full spectrum of potential conservation planning and decision challenges. We describe two case studies that have effectively deployed tools from across conservation frameworks to improve conservation actions and outcomes. Attention to the critical questions for conservation project planning should allow practitioners to operate within any framework and adapt tools to suit their specific management context. We call on conservation researchers and practitioners to regularly use decision support tools as standard practice for framing both practice and research.

A framework for exploring integrated learning systems for the governance and management of public protected areas.

PubMed

Nkhata, Bimo Abraham; Breen, Charles

2010-02-01

This article discusses how the concept of integrated learning systems provides a useful means of exploring the functional linkages between the governance and management of public protected areas. It presents a conceptual framework of an integrated learning system that explicitly incorporates learning processes in governance and management subsystems. The framework is premised on the assumption that an understanding of an integrated learning system is essential if we are to successfully promote learning across multiple scales as a fundamental component of adaptability in the governance and management of protected areas. The framework is used to illustrate real-world situations that reflect the nature and substance of the linkages between governance and management. Drawing on lessons from North America and Africa, the article demonstrates that the establishment and maintenance of an integrated learning system take place in a complex context which links elements of governance learning and management learning subsystems. The degree to which the two subsystems are coupled influences the performance of an integrated learning system and ultimately adaptability. Such performance is largely determined by how integrated learning processes allow for the systematic testing of societal assumptions (beliefs, values, and public interest) to enable society and protected area agencies to adapt and learn in the face of social and ecological change. It is argued that an integrated perspective provides a potentially useful framework for explaining and improving shared understanding around which the concept of adaptability is structured and implemented.

A new method for fusion, denoising and enhancement of x-ray images retrieved from Talbot-Lau grating interferometry.

PubMed

Scholkmann, Felix; Revol, Vincent; Kaufmann, Rolf; Baronowski, Heidrun; Kottler, Christian

2014-03-21

This paper introduces a new image denoising, fusion and enhancement framework for combining and optimal visualization of x-ray attenuation contrast (AC), differential phase contrast (DPC) and dark-field contrast (DFC) images retrieved from x-ray Talbot-Lau grating interferometry. The new image fusion framework comprises three steps: (i) denoising each input image (AC, DPC and DFC) through adaptive Wiener filtering, (ii) performing a two-step image fusion process based on the shift-invariant wavelet transform, i.e. first fusing the AC with the DPC image and then fusing the resulting image with the DFC image, and finally (iii) enhancing the fused image to obtain a final image using adaptive histogram equalization, adaptive sharpening and contrast optimization. Application examples are presented for two biological objects (a human tooth and a cherry) and the proposed method is compared to two recently published AC/DPC/DFC image processing techniques. In conclusion, the new framework for the processing of AC, DPC and DFC allows the most relevant features of all three images to be combined in one image while reducing the noise and enhancing adaptively the relevant image features. The newly developed framework may be used in technical and medical applications.

Exploring the genetic counselor's role in facilitating meaning-making: rare disease diagnoses.

PubMed

Helm, Benjamin M

2015-04-01

The main goal of the constructivist meaning-making framework is to encourage grief adaptation through the search for meaning in loss. Strategies to help patients construct meaning from their experiences may lead to positive adaptation. This strategy has been used in contemporary grief counseling, but it may also be beneficial in the genetic counseling scenario. The diagnosis of a rare genetic disorder often has considerable psychosocial impact as patients and families describe feelings of isolation and hopelessness. Negative experiences with healthcare providers often reinforce these feelings. Genetic counselors continue to provide education and psychosocial support to patients and families with rare genetic disorders, and meaning-making strategies may provide a framework for which to help patients and families adapt to these challenging diagnoses. In this paper I explore the background of meaning-making counseling strategy and describe an experience in which it was used for counseling a family with a child with Mowat-Wilson syndrome. I show how a meaning-making framework can help families explore and construct meaning from their experiences and encourage positive adaptation. I also address the possible limitations of this strategy and the need to share additional experiences with this counseling framework. Meaning-making can be another tool for genetic counselors to help guide families in their grief and adaptation to rare disease diagnoses. I also describe qualities and aspects of counseling through the lens of meaning-making and stress the importance of addressing psychosocial dimensions of rare disease diagnoses.

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

NASA Technical Reports Server (NTRS)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter; Brenner, Martin J.

2017-01-01

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Turning risk assessment and adaptation policy priorities into meaningful interventions and governance processes.

PubMed

Brown, Kathryn; DiMauro, Manuela; Johns, Daniel; Holmes, Gemma; Thompson, David; Russell, Andrew; Style, David

2018-06-13

The UK is one of the first countries in the world to have set up a statutory system of national climate risk assessments followed by a national adaptation programme. Having this legal framework has been essential for enabling adaptation at the government level in a challenging political environment. However, using this framework to create an improvement in resilience to climate change across the country requires more than publishing a set of documents; it requires careful thought about what interventions work, how they can be enabled and what level of risk acceptability individuals, organizations and the country should be aiming for.This article is part of the theme issue 'Advances in risk assessment for climate change adaptation policy'. © 2018 The Author(s).

Turning risk assessment and adaptation policy priorities into meaningful interventions and governance processes

NASA Astrophysics Data System (ADS)

Brown, Kathryn; DiMauro, Manuela; Johns, Daniel; Holmes, Gemma; Thompson, David; Russell, Andrew; Style, David

2018-06-01

The UK is one of the first countries in the world to have set up a statutory system of national climate risk assessments followed by a national adaptation programme. Having this legal framework has been essential for enabling adaptation at the government level in a challenging political environment. However, using this framework to create an improvement in resilience to climate change across the country requires more than publishing a set of documents; it requires careful thought about what interventions work, how they can be enabled and what level of risk acceptability individuals, organizations and the country should be aiming for. This article is part of the theme issue `Advances in risk assessment for climate change adaptation policy'.

Adapting Certified Safe Farm to North Carolina Agriculture: An Implementation Study.

PubMed

Storm, Julia F; LePrevost, Catherine E; Tutor-Marcom, Robin; Cope, W Gregory

2016-01-01

Certified Safe Farm (CSF) is a multimodal safety and health program developed and assessed through multiple controlled intervention studies in Iowa. Although developed with the intent to be broadly applicable to agriculture, CSF has not been widely implemented outside the midwestern United States. This article describes the CSF implementation process in North Carolina (NC), as piloted on a large-scale in three agriculturally diverse and productive counties of NC, and reports its effectiveness using the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework. Implementation involved (1) capacity building through safety and health training, (2) adaptation of components of Iowa's CSF model to NC agriculture, (3) marketing and recruitment, and (4) formative evaluation, including an online survey and focus group discussion. From 2009 to 2012, 113 farms participated in at least one component of the CSF intervention, representing a NC farm participation rate of 3.1% in the study area. A major adaptation of NC implementation was the utilization of NC Cooperative Extension as the local driver of implementation in contrast to local AgriSafe clinics in Iowa. The most innovative adaptation to CSF components was the development of a defined economic incentive in the form of a cost-share program. The RE-AIM framework was found to be useful and relevant to the field of agricultural health and safety translational research. This study provides effectiveness measures and implementation alternatives useful for those considering implementing CSF. It informs current efforts to move CSF from research to practice through the National Sustainable Model CSF Program initiative.

An Adaptive Scaffolding E-Learning System for Middle School Students' Physics Learning

ERIC Educational Resources Information Center

Chen, Ching-Huei

2014-01-01

This study presents a framework that utilizes cognitive and motivational aspects of learning to design an adaptive scaffolding e-learning system. It addresses scaffolding processes and conditions for designing adaptive scaffolds. The features and effectiveness of this adaptive scaffolding e-learning system are discussed and evaluated. An…

Cerebellarlike corrective model inference engine for manipulation tasks.

PubMed

Luque, Niceto Rafael; Garrido, Jesús Alberto; Carrillo, Richard Rafael; Coenen, Olivier J-M D; Ros, Eduardo

2011-10-01

This paper presents how a simple cerebellumlike architecture can infer corrective models in the framework of a control task when manipulating objects that significantly affect the dynamics model of the system. The main motivation of this paper is to evaluate a simplified bio-mimetic approach in the framework of a manipulation task. More concretely, the paper focuses on how the model inference process takes place within a feedforward control loop based on the cerebellar structure and on how these internal models are built up by means of biologically plausible synaptic adaptation mechanisms. This kind of investigation may provide clues on how biology achieves accurate control of non-stiff-joint robot with low-power actuators which involve controlling systems with high inertial components. This paper studies how a basic temporal-correlation kernel including long-term depression (LTD) and a constant long-term potentiation (LTP) at parallel fiber-Purkinje cell synapses can effectively infer corrective models. We evaluate how this spike-timing-dependent plasticity correlates sensorimotor activity arriving through the parallel fibers with teaching signals (dependent on error estimates) arriving through the climbing fibers from the inferior olive. This paper addresses the study of how these LTD and LTP components need to be well balanced with each other to achieve accurate learning. This is of interest to evaluate the relevant role of homeostatic mechanisms in biological systems where adaptation occurs in a distributed manner. Furthermore, we illustrate how the temporal-correlation kernel can also work in the presence of transmission delays in sensorimotor pathways. We use a cerebellumlike spiking neural network which stores the corrective models as well-structured weight patterns distributed among the parallel fibers to Purkinje cell connections.

Improved fuzzy PID controller design using predictive functional control structure.

PubMed

Wang, Yuzhong; Jin, Qibing; Zhang, Ridong

2017-11-01

In conventional PID scheme, the ensemble control performance may be unsatisfactory due to limited degrees of freedom under various kinds of uncertainty. To overcome this disadvantage, a novel PID control method that inherits the advantages of fuzzy PID control and the predictive functional control (PFC) is presented and further verified on the temperature model of a coke furnace. Based on the framework of PFC, the prediction of the future process behavior is first obtained using the current process input signal. Then, the fuzzy PID control based on the multi-step prediction is introduced to acquire the optimal control law. Finally, the case study on a temperature model of a coke furnace shows the effectiveness of the fuzzy PID control scheme when compared with conventional PID control and fuzzy self-adaptive PID control. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Quantifying the adaptive cycle

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Garmestani, Ahjond S.; Gunderson, Lance H.; Hjerne, Olle; Winder, Monika

2015-01-01

The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994–2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

Quantifying the Adaptive Cycle.

PubMed

Angeler, David G; Allen, Craig R; Garmestani, Ahjond S; Gunderson, Lance H; Hjerne, Olle; Winder, Monika

2015-01-01

The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994-2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

Climate adaptation wedges: a case study of premium wine in the western United States

NASA Astrophysics Data System (ADS)

Diffenbaugh, Noah S.; White, Michael A.; Jones, Gregory V.; Ashfaq, Moetasim

2011-04-01

Design and implementation of effective climate change adaptation activities requires quantitative assessment of the impacts that are likely to occur without adaptation, as well as the fraction of impact that can be avoided through each activity. Here we present a quantitative framework inspired by the greenhouse gas stabilization wedges of Pacala and Socolow. In our proposed framework, the damage avoided by each adaptation activity creates an 'adaptation wedge' relative to the loss that would occur without that adaptation activity. We use premium winegrape suitability in the western United States as an illustrative case study, focusing on the near-term period that covers the years 2000-39. We find that the projected warming over this period results in the loss of suitable winegrape area throughout much of California, including most counties in the high-value North Coast and Central Coast regions. However, in quantifying adaptation wedges for individual high-value counties, we find that a large adaptation wedge can be captured by increasing the severe heat tolerance, including elimination of the 50% loss projected by the end of the 2030-9 period in the North Coast region, and reduction of the projected loss in the Central Coast region from 30% to less than 15%. Increased severe heat tolerance can capture an even larger adaptation wedge in the Pacific Northwest, including conversion of a projected loss of more than 30% in the Columbia Valley region of Washington to a projected gain of more than 150%. We also find that warming projected over the near-term decades has the potential to alter the quality of winegrapes produced in the western US, and we discuss potential actions that could create adaptation wedges given these potential changes in quality. While the present effort represents an initial exploration of one aspect of one industry, the climate adaptation wedge framework could be used to quantitatively evaluate the opportunities and limits of climate adaptation within and across a broad range of natural and human systems.

Experiences with HPTN 067/ADAPT Study-Provided Open-Label PrEP Among Women in Cape Town: Facilitators and Barriers Within a Mutuality Framework.

PubMed

Amico, K Rivet; Wallace, Melissa; Bekker, Linda-Gail; Roux, Surita; Atujuna, Millicent; Sebastian, Elaine; Dye, Bonnie J; Elharrar, Vanessa; Grant, Robert M

2017-05-01

Placebo-controlled trials of pre-exposure prophylaxis (PrEP) have reported challenges with study-product uptake and use, with the greatest challenges reported in studies with young women in sub-Saharan Africa. We conducted a qualitative sub-study to explore experiences with open-label PrEP among young women in Cape Town, South Africa participating in HTPN 067/Alternative Dosing to Augment Pre-Exposure Prophylaxis Pill Taking (ADAPT). HPTN 067/ADAPT provided open label oral FTC/TDF PrEP to young women in Cape Town, South Africa who were randomized to daily and non-daily PrEP regimens. Following completion of study participation, women were invited into a qualitative sub-study including focus groups and in-depth interviews. Interviews and groups followed a semi-structured guide, were recorded, transcribed, and translated to English from isiXhosa, and coded using framework analysis. Sixty of the 179 women enrolled in HPTN 067/ADAPT participated in either a focus group (six groups for a total of 42 participants) or an in-depth interview (n = 18). This sample of mostly young, unmarried women identified facilitators of and barriers to PrEP use, as well as factors influencing study participation. Cross-cutting themes characterizing discourse suggested that women placed high value on contributing to the well-being of one's community (Ubuntu), experienced a degree of skepticism towards PrEP and the study more generally, and reported a wide range of approaches towards PrEP (ranging from active avoidance to high levels of persistence and adherence). A Mutuality Framework is proposed that identifies four dynamics (distrust, uncertainty, alignment, and mutuality) that represent distinct interactions between self, community and study and serve to contextualize women's experiences. Implications for better understanding PrEP use, and non-use, and intervention opportunities are discussed. In this sample of women, PrEP use in the context of an open-label research trial was heavily influenced by underlying beliefs about safety, reciprocity of contributions to community, and trust in transparency and integrity of the research. Greater attention to factors positioning women in the different dynamics of the proposed Mutuality Framework could direct intervention approaches in clinical trials, as well as open-label PrEP scale-up.

Feedback and feedforward locomotor adaptations to ankle-foot load in people with incomplete spinal cord injury.

PubMed

Gordon, Keith E; Wu, Ming; Kahn, Jennifer H; Schmit, Brian D

2010-09-01

Humans with spinal cord injury (SCI) modulate locomotor output in response to limb load. Understanding the neural control mechanisms responsible for locomotor adaptation could provide a framework for selecting effective interventions. We quantified feedback and feedforward locomotor adaptations to limb load modulations in people with incomplete SCI. While subjects airstepped (stepping performed with kinematic assistance and 100% bodyweight support), a powered-orthosis created a dorisflexor torque during the "stance phase" of select steps producing highly controlled ankle-load perturbations. When given repetitive, stance phase ankle-load, the increase in hip extension work, 0.27 J/kg above baseline (no ankle-load airstepping), was greater than the response to ankle-load applied during a single step, 0.14 J/kg (P = 0.029). This finding suggests that, at the hip, subjects produced both feedforward and feedback locomotor modulations. We estimate that, at the hip, the locomotor response to repetitive ankle-load was modulated almost equally by ongoing feedback and feedforward adaptations. The majority of subjects also showed after-effects in hip kinetic patterns that lasted 3 min in response to repetitive loading, providing additional evidence of feedforward locomotor adaptations. The magnitude of the after-effect was proportional to the response to repetitive ankle-foot load (R(2) = 0.92). In contrast, increases in soleus EMG amplitude were not different during repetitive and single-step ankle-load exposure, suggesting that ankle locomotor modulations were predominately feedback-based. Although subjects made both feedback and feedforward locomotor adaptations to changes in ankle-load, between-subject variations suggest that walking function may be related to the ability to make feedforward adaptations.

Probabilistic co-adaptive brain-computer interfacing

NASA Astrophysics Data System (ADS)

Bryan, Matthew J.; Martin, Stefan A.; Cheung, Willy; Rao, Rajesh P. N.

2013-12-01

Objective. Brain-computer interfaces (BCIs) are confronted with two fundamental challenges: (a) the uncertainty associated with decoding noisy brain signals, and (b) the need for co-adaptation between the brain and the interface so as to cooperatively achieve a common goal in a task. We seek to mitigate these challenges. Approach. We introduce a new approach to brain-computer interfacing based on partially observable Markov decision processes (POMDPs). POMDPs provide a principled approach to handling uncertainty and achieving co-adaptation in the following manner: (1) Bayesian inference is used to compute posterior probability distributions (‘beliefs’) over brain and environment state, and (2) actions are selected based on entire belief distributions in order to maximize total expected reward; by employing methods from reinforcement learning, the POMDP’s reward function can be updated over time to allow for co-adaptive behaviour. Main results. We illustrate our approach using a simple non-invasive BCI which optimizes the speed-accuracy trade-off for individual subjects based on the signal-to-noise characteristics of their brain signals. We additionally demonstrate that the POMDP BCI can automatically detect changes in the user’s control strategy and can co-adaptively switch control strategies on-the-fly to maximize expected reward. Significance. Our results suggest that the framework of POMDPs offers a promising approach for designing BCIs that can handle uncertainty in neural signals and co-adapt with the user on an ongoing basis. The fact that the POMDP BCI maintains a probability distribution over the user’s brain state allows a much more powerful form of decision making than traditional BCI approaches, which have typically been based on the output of classifiers or regression techniques. Furthermore, the co-adaptation of the system allows the BCI to make online improvements to its behaviour, adjusting itself automatically to the user’s changing circumstances.

Prototype of an auto-calibrating, context-aware, hybrid brain-computer interface.

PubMed

Faller, J; Torrellas, S; Miralles, F; Holzner, C; Kapeller, C; Guger, C; Bund, J; Müller-Putz, G R; Scherer, R

2012-01-01

We present the prototype of a context-aware framework that allows users to control smart home devices and to access internet services via a Hybrid BCI system of an auto-calibrating sensorimotor rhythm (SMR) based BCI and another assistive device (Integra Mouse mouth joystick). While there is extensive literature that describes the merit of Hybrid BCIs, auto-calibrating and co-adaptive ERD BCI training paradigms, specialized BCI user interfaces, context-awareness and smart home control, there is up to now, no system that includes all these concepts in one integrated easy-to-use framework that can truly benefit individuals with severe functional disabilities by increasing independence and social inclusion. Here we integrate all these technologies in a prototype framework that does not require expert knowledge or excess time for calibration. In a first pilot-study, 3 healthy volunteers successfully operated the system using input signals from an ERD BCI and an Integra Mouse and reached average positive predictive values (PPV) of 72 and 98% respectively. Based on what we learned here we are planning to improve the system for a test with a larger number of healthy volunteers so we can soon bring the system to benefit individuals with severe functional disability.

CAreDroid: Adaptation Framework for Android Context-Aware Applications

PubMed Central

Elmalaki, Salma; Wanner, Lucas; Srivastava, Mani

2015-01-01

Context-awareness is the ability of software systems to sense and adapt to their physical environment. Many contemporary mobile applications adapt to changing locations, connectivity states, available computational and energy resources, and proximity to other users and devices. Nevertheless, there is little systematic support for context-awareness in contemporary mobile operating systems. Because of this, application developers must build their own context-awareness adaptation engines, dealing directly with sensors and polluting application code with complex adaptation decisions. In this paper, we introduce CAreDroid, which is a framework that is designed to decouple the application logic from the complex adaptation decisions in Android context-aware applications. In this framework, developers are required— only—to focus on the application logic by providing a list of methods that are sensitive to certain contexts along with the permissible operating ranges under those contexts. At run time, CAreDroid monitors the context of the physical environment and intercepts calls to sensitive methods, activating only the blocks of code that best fit the current physical context. CAreDroid is implemented as part of the Android runtime system. By pushing context monitoring and adaptation into the runtime system, CAreDroid eases the development of context-aware applications and increases their efficiency. In particular, case study applications implemented using CAre-Droid are shown to have: (1) at least half lines of code fewer and (2) at least 10× more efficient in execution time compared to equivalent context-aware applications that use only standard Android APIs. PMID:26834512

CAreDroid: Adaptation Framework for Android Context-Aware Applications.

PubMed

Elmalaki, Salma; Wanner, Lucas; Srivastava, Mani

2015-09-01

Context-awareness is the ability of software systems to sense and adapt to their physical environment. Many contemporary mobile applications adapt to changing locations, connectivity states, available computational and energy resources, and proximity to other users and devices. Nevertheless, there is little systematic support for context-awareness in contemporary mobile operating systems. Because of this, application developers must build their own context-awareness adaptation engines, dealing directly with sensors and polluting application code with complex adaptation decisions. In this paper, we introduce CAreDroid, which is a framework that is designed to decouple the application logic from the complex adaptation decisions in Android context-aware applications. In this framework, developers are required- only-to focus on the application logic by providing a list of methods that are sensitive to certain contexts along with the permissible operating ranges under those contexts. At run time, CAreDroid monitors the context of the physical environment and intercepts calls to sensitive methods, activating only the blocks of code that best fit the current physical context. CAreDroid is implemented as part of the Android runtime system. By pushing context monitoring and adaptation into the runtime system, CAreDroid eases the development of context-aware applications and increases their efficiency. In particular, case study applications implemented using CAre-Droid are shown to have: (1) at least half lines of code fewer and (2) at least 10× more efficient in execution time compared to equivalent context-aware applications that use only standard Android APIs.

A trait-based framework for predicting when and where microbial adaptation to climate change will affect ecosystem functioning

USGS Publications Warehouse

Wallenstein, Matthew D.; Hall, Edward K.

2012-01-01

As the earth system changes in response to human activities, a critical objective is to predict how biogeochemical process rates (e.g. nitrification, decomposition) and ecosystem function (e.g. net ecosystem productivity) will change under future conditions. A particular challenge is that the microbial communities that drive many of these processes are capable of adapting to environmental change in ways that alter ecosystem functioning. Despite evidence that microbes can adapt to temperature, precipitation regimes, and redox fluctuations, microbial communities are typically not optimally adapted to their local environment. For example, temperature optima for growth and enzyme activity are often greater than in situ temperatures in their environment. Here we discuss fundamental constraints on microbial adaptation and suggest specific environments where microbial adaptation to climate change (or lack thereof) is most likely to alter ecosystem functioning. Our framework is based on two principal assumptions. First, there are fundamental ecological trade-offs in microbial community traits that occur across environmental gradients (in time and space). These trade-offs result in shifting of microbial function (e.g. ability to take up resources at low temperature) in response to adaptation of another trait (e.g. limiting maintenance respiration at high temperature). Second, the mechanism and level of microbial community adaptation to changing environmental parameters is a function of the potential rate of change in community composition relative to the rate of environmental change. Together, this framework provides a basis for developing testable predictions about how the rate and degree of microbial adaptation to climate change will alter biogeochemical processes in aquatic and terrestrial ecosystems across the planet.

Human Guidance Behavior Decomposition and Modeling

NASA Astrophysics Data System (ADS)

Feit, Andrew James

Trained humans are capable of high performance, adaptable, and robust first-person dynamic motion guidance behavior. This behavior is exhibited in a wide variety of activities such as driving, piloting aircraft, skiing, biking, and many others. Human performance in such activities far exceeds the current capability of autonomous systems in terms of adaptability to new tasks, real-time motion planning, robustness, and trading safety for performance. The present work investigates the structure of human dynamic motion guidance that enables these performance qualities. This work uses a first-person experimental framework that presents a driving task to the subject, measuring control inputs, vehicle motion, and operator visual gaze movement. The resulting data is decomposed into subspace segment clusters that form primitive elements of action-perception interactive behavior. Subspace clusters are defined by both agent-environment system dynamic constraints and operator control strategies. A key contribution of this work is to define transitions between subspace cluster segments, or subgoals, as points where the set of active constraints, either system or operator defined, changes. This definition provides necessary conditions to determine transition points for a given task-environment scenario that allow a solution trajectory to be planned from known behavior elements. In addition, human gaze behavior during this task contains predictive behavior elements, indicating that the identified control modes are internally modeled. Based on these ideas, a generative, autonomous guidance framework is introduced that efficiently generates optimal dynamic motion behavior in new tasks. The new subgoal planning algorithm is shown to generate solutions to certain tasks more quickly than existing approaches currently used in robotics.

Adapting Maslow's Hierarchy of Needs as a Framework for Resident Wellness.

PubMed

Hale, Andrew J; Ricotta, Daniel N; Freed, Jason; Smith, C Christopher; Huang, Grace C

2018-04-30

Burnout in graduate medical education is pervasive and has a deleterious impact on career satisfaction, personal well-being, and patient outcomes. Interventions in residency programs have often addressed isolated contributors to burnout; however, a more comprehensive framework for conceptualizing wellness is needed. In this article the authors propose Maslow's hierarchy of human needs (physiologic, safety, love/belonging, esteem, and self-actualization) as a potential framework for addressing wellness initiatives. There are numerous contributors to burnout among physician-trainees, and programs to combat burnout must be equally multifaceted. A holistic approach, considering both the trainees personal and professional needs, is recommended. Maslow's Needs can be adapted to create such a framework in graduate medical education. The authors review current evidence to support this model. This work surveys current interventions to mitigate burnout and organizes them into a scaffold that can be used by residency programs interested in a complete framework to supporting wellness.

Adaptive silviculture for climate change: a national experiment in manager-scientist partnerships to apply an adaptation framework

Treesearch

Linda M. ​Nagel; Brian J. Palik; Michael A. Battaglia; Anthony W. D' Amato; James M. Guldin; Chris Swanston; Maria K. Janowiak; Matthew P. Powers; Linda A. Joyce; Constance I. Millar; David L. Peterson; Lisa M. Ganio; Chad Kirschbaum; Molly R. Roske

2017-01-01

Forest managers in the United States must respond to the need for climate-adaptive strategies in the face of observed and projected climatic changes. However, there is a lack of on-the-ground forest adaptation research to indicate what adaptation measures or tactics might be effective in preparing forest ecosystems to deal with climate change. Natural resource managers...

CLAss-Specific Subspace Kernel Representations and Adaptive Margin Slack Minimization for Large Scale Classification.

PubMed

Yu, Yinan; Diamantaras, Konstantinos I; McKelvey, Tomas; Kung, Sun-Yuan

2018-02-01

In kernel-based classification models, given limited computational power and storage capacity, operations over the full kernel matrix becomes prohibitive. In this paper, we propose a new supervised learning framework using kernel models for sequential data processing. The framework is based on two components that both aim at enhancing the classification capability with a subset selection scheme. The first part is a subspace projection technique in the reproducing kernel Hilbert space using a CLAss-specific Subspace Kernel representation for kernel approximation. In the second part, we propose a novel structural risk minimization algorithm called the adaptive margin slack minimization to iteratively improve the classification accuracy by an adaptive data selection. We motivate each part separately, and then integrate them into learning frameworks for large scale data. We propose two such frameworks: the memory efficient sequential processing for sequential data processing and the parallelized sequential processing for distributed computing with sequential data acquisition. We test our methods on several benchmark data sets and compared with the state-of-the-art techniques to verify the validity of the proposed techniques.

Commonalities between Disaster and Climate Change Risks for Health: A Theoretical Framework.

PubMed

Banwell, Nicola; Rutherford, Shannon; Mackey, Brendan; Street, Roger; Chu, Cordia

2018-03-16

Disasters and climate change have significant implications for human health worldwide. Both climate change and the climate-sensitive hazards that result in disasters, are discussed in terms of direct and indirect impacts on health. A growing body of literature has argued for the need to link disaster risk reduction and climate change adaptation. However, there is limited articulation of the commonalities between these health impacts. Understanding the shared risk pathways is an important starting point for developing joint strategies for adapting to, and reducing, health risks. Therefore, this article discusses the common aspects of direct and indirect health risks of climate change and climate-sensitive disasters. Based on this discussion a theoretical framework is presented for understanding these commonalities. As such, this article hopes to extend the current health impact frameworks and provide a platform for further research exploring opportunities for linked adaptation and risk reduction strategies.

Commonalities between Disaster and Climate Change Risks for Health: A Theoretical Framework

PubMed Central

Banwell, Nicola; Rutherford, Shannon; Mackey, Brendan; Street, Roger; Chu, Cordia

2018-01-01

Disasters and climate change have significant implications for human health worldwide. Both climate change and the climate-sensitive hazards that result in disasters, are discussed in terms of direct and indirect impacts on health. A growing body of literature has argued for the need to link disaster risk reduction and climate change adaptation. However, there is limited articulation of the commonalities between these health impacts. Understanding the shared risk pathways is an important starting point for developing joint strategies for adapting to, and reducing, health risks. Therefore, this article discusses the common aspects of direct and indirect health risks of climate change and climate-sensitive disasters. Based on this discussion a theoretical framework is presented for understanding these commonalities. As such, this article hopes to extend the current health impact frameworks and provide a platform for further research exploring opportunities for linked adaptation and risk reduction strategies. PMID:29547592

Livelihoods, power, and food insecurity: adaptation of social capital portfolios in protracted crises--case study Burundi.

PubMed

Vervisch, Thomas G A; Vlassenroot, Koen; Braeckman, Johan

2013-04-01

The failure of food security and livelihood interventions to adapt to conflict settings remains a key challenge in humanitarian responses to protracted crises. This paper proposes a social capital analysis to address this policy gap, adding a political economy dimension on food security and conflict to the actor-based livelihood framework. A case study of three hillsides in north Burundi provides an ethnographic basis for this hypothesis. While relying on a theoretical framework in which different combinations of social capital (bonding, bridging, and linking) account for a diverse range of outcomes, the findings offer empirical insights into how social capital portfolios adapt to a protracted crisis. It is argued that these social capital adaptations have the effect of changing livelihood policies, institutions, and processes (PIPs), and clarify the impact of the distribution of power and powerlessness on food security issues. In addition, they represent a solid way of integrating political economy concerns into the livelihood framework. © 2013 The Author(s). Journal compilation © Overseas Development Institute, 2013.

The General Adaptation Syndrome: A Foundation for the Concept of Periodization.

PubMed

Cunanan, Aaron J; DeWeese, Brad H; Wagle, John P; Carroll, Kevin M; Sausaman, Robert; Hornsby, W Guy; Haff, G Gregory; Triplett, N Travis; Pierce, Kyle C; Stone, Michael H

2018-04-01

Recent reviews have attempted to refute the efficacy of applying Selye's general adaptation syndrome (GAS) as a conceptual framework for the training process. Furthermore, the criticisms involved are regularly used as the basis for arguments against the periodization of training. However, these perspectives fail to consider the entirety of Selye's work, the evolution of his model, and the broad applications he proposed. While it is reasonable to critically evaluate any paradigm, critics of the GAS have yet to dismantle the link between stress and adaptation. Disturbance to the state of an organism is the driving force for biological adaptation, which is the central thesis of the GAS model and the primary basis for its application to the athlete's training process. Despite its imprecisions, the GAS has proven to be an instructive framework for understanding the mechanistic process of providing a training stimulus to induce specific adaptations that result in functional enhancements. Pioneers of modern periodization have used the GAS as a framework for the management of stress and fatigue to direct adaptation during sports training. Updates to the periodization concept have retained its founding constructs while explicitly calling for scientifically based, evidence-driven practice suited to the individual. Thus, the purpose of this review is to provide greater clarity on how the GAS serves as an appropriate mechanistic model to conceptualize the periodization of training.

Homeostasis, inflammation, and disease susceptibility.

PubMed

Kotas, Maya E; Medzhitov, Ruslan

2015-02-26

While modernization has dramatically increased lifespan, it has also witnessed the increasing prevalence of diseases such as obesity, hypertension, and type 2 diabetes. Such chronic, acquired diseases result when normal physiologic control goes awry and may thus be viewed as failures of homeostasis. However, while nearly every process in human physiology relies on homeostatic mechanisms for stability, only some have demonstrated vulnerability to dysregulation. Additionally, chronic inflammation is a common accomplice of the diseases of homeostasis, yet the basis for this connection is not fully understood. Here we review the design of homeostatic systems and discuss universal features of control circuits that operate at the cellular, tissue, and organismal levels. We suggest a framework for classification of homeostatic signals that is based on different classes of homeostatic variables they report on. Finally, we discuss how adaptability of homeostatic systems with adjustable set points creates vulnerability to dysregulation and disease. This framework highlights the fundamental parallels between homeostatic and inflammatory control mechanisms and provides a new perspective on the physiological origin of inflammation. Copyright © 2015 Elsevier Inc. All rights reserved.

A survey on adaptive engine technology for serious games

NASA Astrophysics Data System (ADS)

Rasim, Langi, Armein Z. R.; Munir, Rosmansyah, Yusep

2016-02-01

Serious Games has become a priceless tool in learning because it can simulate abstract concept to appear more realistic. The problem faced is that the players have different ability in playing the games. This causes the players to become frustrated if the game is too difficult or to get bored if it is too easy. Serious games have non-player character (NPC) in it. The NPC should be able to adapt to the players in such a way so that the players can feel comfortable in playing the games. Because of that, serious games development must involve an adaptive engine, which is by applying a learning machine that can adapt to different players. The development of adaptive engine can be viewed in terms of the frameworks and the algorithms. Frameworks include rules based, plan based, organization description based, proficiency of player based, and learning style and cognitive state based. Algorithms include agents based and non-agent based

Consolidating tactical planning and implementation frameworks for integrated vector management in Uganda.

PubMed

Okia, Michael; Okui, Peter; Lugemwa, Myers; Govere, John M; Katamba, Vincent; Rwakimari, John B; Mpeka, Betty; Chanda, Emmanuel

2016-04-14

Integrated vector management (IVM) is the recommended approach for controlling some vector-borne diseases (VBD). In the face of current challenges to disease vector control, IVM is vital to achieve national targets set for VBD control. Though global efforts, especially for combating malaria, now focus on elimination and eradication, IVM remains useful for Uganda which is principally still in the control phase of the malaria continuum. This paper outlines the processes undertaken to consolidate tactical planning and implementation frameworks for IVM in Uganda. The Uganda National Malaria Control Programme with its efforts to implement an IVM approach to vector control was the 'case' for this study. Integrated management of malaria vectors in Uganda remained an underdeveloped component of malaria control policy. In 2012, knowledge and perceptions of malaria vector control policy and IVM were assessed, and recommendations for a specific IVM policy were made. In 2014, a thorough vector control needs assessment (VCNA) was conducted according to WHO recommendations. The findings of the VCNA informed the development of the national IVM strategic guidelines. Information sources for this study included all available data and accessible archived documentary records on VBD control in Uganda. The literature was reviewed and adapted to the local context and translated into the consolidated tactical framework. WHO recommends implementation of IVM as the main strategy to vector control and has encouraged member states to adopt the approach. However, many VBD-endemic countries lack IVM policy frameworks to guide implementation of the approach. In Uganda most VBD coexists and could be managed more effectively if done in tandem. In order to successfully control malaria and other VBD and move towards their elimination, the country needs to scale up proven and effective vector control interventions and also learn from the experience of other countries. The IVM strategy is important in consolidating inter-sectoral collaboration and coordination and providing the tactical direction for effective deployment of vector control interventions along the five key elements of the approach and to align them with contemporary epidemiology of VBD in the country. Uganda has successfully established an evidence-based IVM approach and consolidated strategic planning and operational frameworks for VBD control. However, operating implementation arrangements as outlined in the national strategic guidelines for IVM and managing insecticide resistance, as well as improving vector surveillance, are imperative. In addition, strengthened information, education and communication/behaviour change and communication, collaboration and coordination will be crucial in scaling up and using vector control interventions.

An Adaptive Course Generation Framework

ERIC Educational Resources Information Center

Li, Frederick W. B.; Lau, Rynson W. H.; Dharmendran, Parthiban

2010-01-01

Existing adaptive e-learning methods are supported by student (user) profiling for capturing student characteristics, and course structuring for organizing learning materials according to topics and levels of difficulties. Adaptive courses are then generated by extracting materials from the course structure to match the criteria specified in the…

Water System Adaptation To Hydrological Changes: Module 8, Regulatory Framework Intersections: Past, Present, and Future

EPA Science Inventory

This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

A Meta-Analysis of Urban Climate Change Adaptation Planning in the U.S.

EPA Science Inventory

The concentration of people, infrastructure, and ecosystem services in urban areas make them prime sites for climate change adaptation. While advances have been made in developing frameworks for adaptation planning and identifying both real and potential barriers to action, empir...

What is adaptive about adaptive decision making? A parallel constraint satisfaction account.

PubMed

Glöckner, Andreas; Hilbig, Benjamin E; Jekel, Marc

2014-12-01

There is broad consensus that human cognition is adaptive. However, the vital question of how exactly this adaptivity is achieved has remained largely open. Herein, we contrast two frameworks which account for adaptive decision making, namely broad and general single-mechanism accounts vs. multi-strategy accounts. We propose and fully specify a single-mechanism model for decision making based on parallel constraint satisfaction processes (PCS-DM) and contrast it theoretically and empirically against a multi-strategy account. To achieve sufficiently sensitive tests, we rely on a multiple-measure methodology including choice, reaction time, and confidence data as well as eye-tracking. Results show that manipulating the environmental structure produces clear adaptive shifts in choice patterns - as both frameworks would predict. However, results on the process level (reaction time, confidence), in information acquisition (eye-tracking), and from cross-predicting choice consistently corroborate single-mechanisms accounts in general, and the proposed parallel constraint satisfaction model for decision making in particular. Copyright © 2014 Elsevier B.V. All rights reserved.

Adaptive effort investment in cognitive and physical tasks: a neurocomputational model

PubMed Central

Verguts, Tom; Vassena, Eliana; Silvetti, Massimo

2015-01-01

Despite its importance in everyday life, the computational nature of effort investment remains poorly understood. We propose an effort model obtained from optimality considerations, and a neurocomputational approximation to the optimal model. Both are couched in the framework of reinforcement learning. It is shown that choosing when or when not to exert effort can be adaptively learned, depending on rewards, costs, and task difficulty. In the neurocomputational model, the limbic loop comprising anterior cingulate cortex (ACC) and ventral striatum in the basal ganglia allocates effort to cortical stimulus-action pathways whenever this is valuable. We demonstrate that the model approximates optimality. Next, we consider two hallmark effects from the cognitive control literature, namely proportion congruency and sequential congruency effects. It is shown that the model exerts both proactive and reactive cognitive control. Then, we simulate two physical effort tasks. In line with empirical work, impairing the model's dopaminergic pathway leads to apathetic behavior. Thus, we conceptually unify the exertion of cognitive and physical effort, studied across a variety of literatures (e.g., motivation and cognitive control) and animal species. PMID:25805978

Developing an Addictions Nursing Competency Framework Within a Canadian Context.

PubMed

Ling, Sara; Watson, Alison; Gehrs, Margaret

Clients with substance use disorders access care in all areas of the health care system, yet the Canadian nursing literature lacks content on the knowledge, skills, and judgment needed by nurses who work with this population. To address this literature gap, two Advanced Practice Nurses adapted the Canadian Centre on Substance Abuse's Technical Competencies for Canada's Substance Abuse Workforce to include nursing content and theory. This article describes the adaptation process and validation method used by the Advanced Practice Nurses at a large, Canadian urban teaching hospital and includes discussion about actual and potential opportunities for practical application of the adapted framework.

Integrating adaptive management and ecosystem services concepts to improve natural resource management: Challenges and opportunities

USGS Publications Warehouse

Epanchin-Niell, Rebecca S.; Boyd, James W.; Macauley, Molly K.; Scarlett, Lynn; Shapiro, Carl D.; Williams, Byron K.

2018-05-07

Executive Summary—OverviewNatural resource managers must make decisions that affect broad-scale ecosystem processes involving large spatial areas, complex biophysical interactions, numerous competing stakeholder interests, and highly uncertain outcomes. Natural and social science information and analyses are widely recognized as important for informing effective management. Chief among the systematic approaches for improving the integration of science into natural resource management are two emergent science concepts, adaptive management and ecosystem services. Adaptive management (also referred to as “adaptive decision making”) is a deliberate process of learning by doing that focuses on reducing uncertainties about management outcomes and system responses to improve management over time. Ecosystem services is a conceptual framework that refers to the attributes and outputs of ecosystems (and their components and functions) that have value for humans.This report explores how ecosystem services can be moved from concept into practice through connection to a decision framework—adaptive management—that accounts for inherent uncertainties. Simultaneously, the report examines the value of incorporating ecosystem services framing and concepts into adaptive management efforts.Adaptive management and ecosystem services analyses have not typically been used jointly in decision making. However, as frameworks, they have a natural—but to date underexplored—affinity. Both are policy and decision oriented in that they attempt to represent the consequences of resource management choices on outcomes of interest to stakeholders. Both adaptive management and ecosystem services analysis take an empirical approach to the analysis of ecological systems. This systems orientation is a byproduct of the fact that natural resource actions affect ecosystems—and corresponding societal outcomes—often across large geographic scales. Moreover, because both frameworks focus on resource systems, both must confront the analytical challenges of systems modeling—in terms of complexity, dynamics, and uncertainty.Given this affinity, the integration of ecosystem services analysis and adaptive management poses few conceptual hurdles. In this report, we synthesize discussions from two workshops that considered ways in which adaptive management approaches and ecosystem service concepts may be complementary, such that integrating them into a common framework may lead to improved natural resource management outcomes. Although the literature on adaptive management and ecosystem services is vast and growing, the report focuses specifically on the integration of these two concepts rather than aiming to provide new definitions or an indepth review or primer of the concepts individually.Key issues considered include the bidirectional links between adaptive decision making and ecosystem services, as well as the potential benefits and inevitable challenges arising in the development and use of an integrated framework. Specifically, the workshops addressed the following questions:How can application of ecosystem service analysis within an adaptive decision process improve the outcomes of management and advance understanding of ecosystem service identification, production, and valuation?How can these concepts be integrated in concept and practice?What are the constraints and challenges to integrating adaptive management and ecosystem services?And, should the integration of these concepts be moved forward to wider application—and if so, how?

Assessing the effects of adaptation measures on optimal water resources allocation under varied water availability conditions

NASA Astrophysics Data System (ADS)

Liu, Dedi; Guo, Shenglian; Shao, Quanxi; Liu, Pan; Xiong, Lihua; Wang, Le; Hong, Xingjun; Xu, Yao; Wang, Zhaoli

2018-01-01

Human activities and climate change have altered the spatial and temporal distribution of water availability which is a principal prerequisite for allocation of different water resources. In order to quantify the impacts of climate change and human activities on water availability and optimal allocation of water resources, hydrological models and optimal water resource allocation models should be integrated. Given that increasing human water demand and varying water availability conditions necessitate adaptation measures, we propose a framework to assess the effects of these measures on optimal allocation of water resources. The proposed model and framework were applied to a case study of the middle and lower reaches of the Hanjiang River Basin in China. Two representative concentration pathway (RCP) scenarios (RCP2.6 and RCP4.5) were employed to project future climate, and the Variable Infiltration Capacity (VIC) hydrological model was used to simulate the variability of flows under historical (1956-2011) and future (2012-2099) conditions. The water availability determined by simulating flow with the VIC hydrological model was used to establish the optimal water resources allocation model. The allocation results were derived under an extremely dry year (with an annual average water flow frequency of 95%), a very dry year (with an annual average water flow frequency of 90%), a dry year (with an annual average water flow frequency of 75%), and a normal year (with an annual average water flow frequency of 50%) during historical and future periods. The results show that the total available water resources in the study area and the inflow of the Danjiangkou Reservoir will increase in the future. However, the uneven distribution of water availability will cause water shortage problems, especially in the boundary areas. The effects of adaptation measures, including water saving, and dynamic control of flood limiting water levels (FLWLs) for reservoir operation, were assessed and implemented to alleviate water shortages. The negative impacts from the South-to-North Water Transfer Project (Middle Route) in the mid-lower reaches of the Hanjiang River Basin can be avoided through the dynamic control of FLWLs in Danjiangkou Reservoir, under the historical and future RCP2.6 and RCP4.5 scenarios. However, the effects of adaptation measures are limited due to their own constraints, such as the characteristics of the reservoirs influencing the FLWLs. The utilization of storm water appears necessary to meet future water demand. Overall, the results indicate that the framework for assessing the effects of adaptation measures on water resources allocation might aid water resources management, not only in the study area but also in other places where water availability conditions vary due to climate change and human activities.

A framework for quantification of groundwater dynamics - concepts and hydro(geo-)logical metrics

NASA Astrophysics Data System (ADS)

Haaf, Ezra; Heudorfer, Benedikt; Stahl, Kerstin; Barthel, Roland

2017-04-01

Fluctuation patterns in groundwater hydrographs are generally assumed to contain information on aquifer characteristics, climate and environmental controls. However, attempts to disentangle this information and map the dominant controls have been few. This is due to the substantial heterogeneity and complexity of groundwater systems, which is reflected in the abundance of morphologies of groundwater time series. To describe the structure and shape of hydrographs, descriptive terms like "slow"/ "fast" or "flashy"/ "inert" are frequently used, which are subjective, irreproducible and limited. This lack of objective and refined concepts limit approaches for regionalization of hydrogeological characteristics as well as our understanding of dominant processes controlling groundwater dynamics. Therefore, we propose a novel framework for groundwater hydrograph characterization in an attempt to categorize morphologies explicitly and quantitatively based on perceptual concepts of aspects of the dynamics. This quantitative framework is inspired by the existing and operational eco-hydrological classification frameworks for streamflow. The need for a new framework for groundwater systems is justified by the fundamental differences between the state variable groundwater head and the flow variable streamflow. Conceptually, we extracted exemplars of specific dynamic patterns, attributing descriptive terms for means of systematisation. Metrics, primarily taken from streamflow literature, were subsequently adapted to groundwater and assigned to the described patterns for means of quantification. In this study, we focused on the particularities of groundwater as a state variable. Furthermore, we investigated the descriptive skill of individual metrics as well as their usefulness for groundwater hydrographs. The ensemble of categorized metrics result in a framework, which can be used to describe and quantify groundwater dynamics. It is a promising tool for the setup of a successful similarity classification framework for groundwater hydrographs. However, the overabundance of metrics available calls for a systematic redundancy analysis of the metrics, which we describe in a second study (Heudorfer et al., 2017). Heudorfer, B., Haaf, E., Barthel, R., Stahl, K., 2017. A framework for quantification of groundwater dynamics - redundancy and transferability of hydro(geo-)logical metrics. EGU General Assembly 2017, Vienna, Austria.

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

NASA Astrophysics Data System (ADS)

Turner, D.

2014-12-01

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

A family beliefs framework for socially and culturally specific preventive interventions with refugee youths and families.

PubMed

Weine, Stevan; Feetham, Suzanne; Kulauzovic, Yasmina; Knafl, Kathleen; Besic, Sanela; Klebic, Alma; Mujagic, Aida; Muzurovic, Jasmina; Spahovic, Dzemila; Pavkovic, Ivan

2006-01-01

To assist in designing socially and culturally specific preventive interventions for refugee youths and families, this study identified the processes by which refugee families adapt and apply family beliefs concerning youths. A grounded-theory model constructed with ATLAS/ti for Windows and named the family beliefs framework describes (a) family beliefs concerning refugee youths, (b) contextual factors interacting with these family beliefs, (c) adaptation of family beliefs concerning refugee youths, and (d) the interplay of adapting family beliefs and behaviors concerning refugee youths. Preventive interventions for refugee youths and families would be more socially and culturally specific if they addressed the specific processes of adapting family beliefs experienced by refugee youths and their families amid transitions and traumas. 2006 APA, all rights reserved

Efficient Load Balancing and Data Remapping for Adaptive Grid Calculations

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak

1997-01-01

Mesh adaption is a powerful tool for efficient unstructured- grid computations but causes load imbalance among processors on a parallel machine. We present a novel method to dynamically balance the processor workloads with a global view. This paper presents, for the first time, the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. Previous results indicated that mesh repartitioning and data remapping are potential bottlenecks for performing large-scale scientific calculations. We resolve these issues and demonstrate that our framework remains viable on a large number of processors.

(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis

PubMed Central

2013-01-01

Background Metabolic control analysis (MCA) and supply–demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply–demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. Results This study integrates control engineering and classical MCA augmented with supply–demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the ‘integral control’ (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of ‘integral control’ should rarely be expected to lead to the ‘perfect adaptation’: although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. Conclusions A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems biology, correspond to the ‘perfect’ regulatory structures designed by control engineering vis-à-vis optimal functions such as robustness. To the extent that they are not, the analyses suggest how they may become so and this in turn should facilitate synthetic biology and metabolic engineering. PMID:24261908

Real-Time Local Volt/VAR Control Under External Disturbances with High PV Penetration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singhal, A.; Ajjarapu, V.; Fuller, Jason C.

Volt/var control (VVC) of smart PV inverter is becoming one of the most popular solutions to address the voltage challenges associated with high PV penetration. This work focuses on the local droop VVC recommended by the grid integration standards IEEE1547, rule21 and addresses their major challenges i.e. appropriate parameters selection under changing conditions, and the control being vulnerable to instability (or voltage oscillations) and significant steady state error (SSE). This is achieved by proposing a two-layer local real-time adaptive VVC that has two major features i.e. a) it is able to ensure both low SSE and control stability simultaneously withoutmore » compromising either; and b) it dynamically adapts its parameters to ensure good performance in a wide range of external disturbances such as sudden cloud cover, cloud intermittency, and substation voltage changes. A theoretical analysis and convergence proof of the proposed control is also discussed. The proposed control is implementation friendly as it fits well within the integration standard framework and depends only on the local bus information. Furthermore, the performance is compared with the existing droop VVC methods in several scenarios on a large unbalanced 3-phase feeder with detailed secondary side modeling.« less

Real-Time Local Volt/VAR Control Under External Disturbances with High PV Penetration

DOE PAGES

Singhal, A.; Ajjarapu, V.; Fuller, Jason C.; ...

2018-05-28

Volt/var control (VVC) of smart PV inverter is becoming one of the most popular solutions to address the voltage challenges associated with high PV penetration. This work focuses on the local droop VVC recommended by the grid integration standards IEEE1547, rule21 and addresses their major challenges i.e. appropriate parameters selection under changing conditions, and the control being vulnerable to instability (or voltage oscillations) and significant steady state error (SSE). This is achieved by proposing a two-layer local real-time adaptive VVC that has two major features i.e. a) it is able to ensure both low SSE and control stability simultaneously withoutmore » compromising either; and b) it dynamically adapts its parameters to ensure good performance in a wide range of external disturbances such as sudden cloud cover, cloud intermittency, and substation voltage changes. A theoretical analysis and convergence proof of the proposed control is also discussed. The proposed control is implementation friendly as it fits well within the integration standard framework and depends only on the local bus information. Furthermore, the performance is compared with the existing droop VVC methods in several scenarios on a large unbalanced 3-phase feeder with detailed secondary side modeling.« less

A Learning Framework for Control-Oriented Modeling of Buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rubio-Herrero, Javier; Chandan, Vikas; Siegel, Charles M.

Buildings consume a significant amount of energy worldwide. Several building optimization and control use cases require models of energy consumption which are control oriented, have high predictive capability, imposes minimal data pre-processing requirements, and have the ability to be adapted continuously to account for changing conditions as new data becomes available. Data driven modeling techniques, that have been investigated so far, while promising in the context of buildings, have been unable to simultaneously satisfy all the requirements mentioned above. In this context, deep learning techniques such as Recurrent Neural Networks (RNNs) hold promise, empowered by advanced computational capabilities and bigmore » data opportunities. In this paper, we propose a deep learning based methodology for the development of control oriented models for building energy management and test in on data from a real building. Results show that the proposed methodology outperforms other data driven modeling techniques significantly. We perform a detailed analysis of the proposed methodology along dimensions such as topology, sensitivity, and downsampling. Lastly, we conclude by envisioning a building analytics suite empowered by the proposed deep framework, that can drive several use cases related to building energy management.« less

REDD+ and climate smart agriculture in landscapes: A case study in Vietnam using companion modelling.

PubMed

Salvini, G; Ligtenberg, A; van Paassen, A; Bregt, A K; Avitabile, V; Herold, M

2016-05-01

Finding land use strategies that merge land-based climate change mitigation measures and adaptation strategies is still an open issue in climate discourse. This article explores synergies and trade-offs between REDD+, a scheme that focuses mainly on mitigation through forest conservation, with "Climate Smart Agriculture", an approach that emphasizes adaptive agriculture. We introduce a framework for ex-ante assessment of the impact of land management policies and interventions and for quantifying their impacts on land-based mitigation and adaptation goals. The framework includes a companion modelling (ComMod) process informed by interviews with policymakers, local experts and local farmers. The ComMod process consists of a Role-Playing Game with local farmers and an Agent Based Model. The game provided a participatory means to develop policy and climate change scenarios. These scenarios were then used as inputs to the Agent Based Model, a spatially explicit model to simulate landscape dynamics and the associated carbon emissions over decades. We applied the framework using as case study a community in central Vietnam, characterized by deforestation for subsistence agriculture and cultivation of acacias as a cash crop. The main findings show that the framework is useful in guiding consideration of local stakeholders' goals, needs and constraints. Additionally the framework provided beneficial information to policymakers, pointing to ways that policies might be re-designed to make them better tailored to local circumstances and therefore more effective in addressing synergistically climate change mitigation and adaptation objectives. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Attention-Information-Based Spatial Adaptation Framework for Browsing Videos via Mobile Devices

NASA Astrophysics Data System (ADS)

Li, Houqiang; Wang, Yi; Chen, Chang Wen

2007-12-01

With the growing popularity of personal digital assistant devices and smart phones, more and more consumers are becoming quite enthusiastic to appreciate videos via mobile devices. However, limited display size of the mobile devices has been imposing significant barriers for users to enjoy browsing high-resolution videos. In this paper, we present an attention-information-based spatial adaptation framework to address this problem. The whole framework includes two major parts: video content generation and video adaptation system. During video compression, the attention information in video sequences will be detected using an attention model and embedded into bitstreams with proposed supplement-enhanced information (SEI) structure. Furthermore, we also develop an innovative scheme to adaptively adjust quantization parameters in order to simultaneously improve the quality of overall encoding and the quality of transcoding the attention areas. When the high-resolution bitstream is transmitted to mobile users, a fast transcoding algorithm we developed earlier will be applied to generate a new bitstream for attention areas in frames. The new low-resolution bitstream containing mostly attention information, instead of the high-resolution one, will be sent to users for display on the mobile devices. Experimental results show that the proposed spatial adaptation scheme is able to improve both subjective and objective video qualities.

A Framework for Integration of IVHM Technologies for Intelligent Integration for Vehicle Management

NASA Technical Reports Server (NTRS)

Paris, Deidre E.; Trevino, Luis; Watson, Mike

2005-01-01

As a part of the overall goal of developing Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of IIVM. These real-time responses allow the IIVM to modify the effected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for IIVH includes: 1) robust controllers for use in re-usable launch vehicles, 2) scaleable/flexible computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project. The integration of these IVHM technologies forms the framework for IIVM.

PScan 1.0: flexible software framework for polygon based multiphoton microscopy

NASA Astrophysics Data System (ADS)

Li, Yongxiao; Lee, Woei Ming

2016-12-01

Multiphoton laser scanning microscopes exhibit highly localized nonlinear optical excitation and are powerful instruments for in-vivo deep tissue imaging. Customized multiphoton microscopy has a significantly superior performance for in-vivo imaging because of precise control over the scanning and detection system. To date, there have been several flexible software platforms catered to custom built microscopy systems i.e. ScanImage, HelioScan, MicroManager, that perform at imaging speeds of 30-100fps. In this paper, we describe a flexible software framework for high speed imaging systems capable of operating from 5 fps to 1600 fps. The software is based on the MATLAB image processing toolbox. It has the capability to communicate directly with a high performing imaging card (Matrox Solios eA/XA), thus retaining high speed acquisition. The program is also designed to communicate with LabVIEW and Fiji for instrument control and image processing. Pscan 1.0 can handle high imaging rates and contains sufficient flexibility for users to adapt to their high speed imaging systems.

The dynamics of perception and action.

PubMed

Warren, William H

2006-04-01

How might one account for the organization in behavior without attributing it to an internal control structure? The present article develops a theoretical framework called behavioral dynamics that integrates an information-based approach to perception with a dynamical systems approach to action. For a given task, the agent and its environment are treated as a pair of dynamical systems that are coupled mechanically and informationally. Their interactions give rise to the behavioral dynamics, a vector field with attractors that correspond to stable task solutions, repellers that correspond to avoided states, and bifurcations that correspond to behavioral transitions. The framework is used to develop theories of several tasks in which a human agent interacts with the physical environment, including bouncing a ball on a racquet, balancing an object, braking a vehicle, and guiding locomotion. Stable, adaptive behavior emerges from the dynamics of the interaction between a structured environment and an agent with simple control laws, under physical and informational constraints. ((c) 2006 APA, all rights reserved).

Organizational strategy, structure, and process.

PubMed

Miles, R E; Snow, C C; Meyer, A D; Coleman, H J

1978-07-01

Organizational adaptation is a topic that has received only limited and fragmented theoretical treatment. Any attempt to examine organizational adaptation is difficult, since the process is highly complex and changeable. The proposed theoretical framework deals with alternative ways in which organizations define their product-market domains (strategy) and construct mechanisms (structures and processes) to pursue these strategies. The framework is based on interpretation of existing literature and continuing studies in four industries (college textbook publishing, electronics, food processing, and health care).

Adaptive invasive species distribution models: A framework for modeling incipient invasions

USGS Publications Warehouse

Uden, Daniel R.; Allen, Craig R.; Angeler, David G.; Corral, Lucia; Fricke, Kent A.

2015-01-01

The utilization of species distribution model(s) (SDM) for approximating, explaining, and predicting changes in species’ geographic locations is increasingly promoted for proactive ecological management. Although frameworks for modeling non-invasive species distributions are relatively well developed, their counterparts for invasive species—which may not be at equilibrium within recipient environments and often exhibit rapid transformations—are lacking. Additionally, adaptive ecological management strategies address the causes and effects of biological invasions and other complex issues in social-ecological systems. We conducted a review of biological invasions, species distribution models, and adaptive practices in ecological management, and developed a framework for adaptive, niche-based, invasive species distribution model (iSDM) development and utilization. This iterative, 10-step framework promotes consistency and transparency in iSDM development, allows for changes in invasive drivers and filters, integrates mechanistic and correlative modeling techniques, balances the avoidance of type 1 and type 2 errors in predictions, encourages the linking of monitoring and management actions, and facilitates incremental improvements in models and management across space, time, and institutional boundaries. These improvements are useful for advancing coordinated invasive species modeling, management and monitoring from local scales to the regional, continental and global scales at which biological invasions occur and harm native ecosystems and economies, as well as for anticipating and responding to biological invasions under continuing global change.

Repeated-Slip Training: An Emerging Paradigm for Prevention of Slip-Related Falls Among Older Adults

PubMed Central

Pai, YC; Bhatt, TS

2009-01-01

Falls frequently cause injury-related hospitalization or death among older adults. This article reviews a new conceptual framework on dynamic stability and weight support in reducing the risk for falls resulting from a forward slip, based on the principles of motor control and learning, in the context of adaptation and longer-term retention induced by repeated-slip training. Although an unexpected slip is severely destabilizing, a recovery step often is adequate for regaining stability, regardless of age. Consequently, poor weight support (quantified by reduction in hip height), rather than instability, is the major determinant of slip-related fall risk. Promisingly, a single session of repeated-slip training can enhance neuromechanical control of dynamic stability and weight support to prevent falls, which can be retained for several months or longer. These principles provide the theoretical basis for establishing task-specific adaptive training that facilitates the development of protective strategies to reduce falls among older adults. PMID:17712033

Ventral Striatum and the Evaluation of Memory Retrieval Strategies

PubMed Central

Badre, David; Lebrecht, Sophie; Pagliaccio, David; Long, Nicole M.; Scimeca, Jason M.

2015-01-01

Adaptive memory retrieval requires mechanisms of cognitive control that facilitate the recovery of goal-relevant information. Frontoparietal systems are known to support control of memory retrieval. However, the mechanisms by which the brain acquires, evaluates, and adapts retrieval strategies remain unknown. Here, we provide evidence that ventral striatal activation tracks the success of a retrieval strategy and correlates with subsequent reliance on that strategy. Human participants were scanned with fMRI while performing a lexical decision task. A rule was provided that indicated the likely semantic category of a target word given the category of a preceding prime. Reliance on the rule improved decision-making, as estimated within a drift diffusion framework. Ventral striatal activation tracked the benefit that relying on the rule had on decision-making. Moreover, activation in ventral striatum correlated with a participant’s subsequent reliance on the rule. Taken together, these results support a role for ventral striatum in learning and evaluating declarative retrieval strategies. PMID:24564466

Automated Kinematics Equations Generation and Constrained Motion Planning Resolution for Modular and Reconfigurable Robots

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pin, Francois G.; Love, Lonnie L.; Jung, David L.

2004-03-29

Contrary to the repetitive tasks performed by industrial robots, the tasks in most DOE missions such as environmental restoration or Decontamination and Decommissioning (D&D) can be characterized as ''batches-of-one'', in which robots must be capable of adapting to changes in constraints, tools, environment, criteria and configuration. No commercially available robot control code is suitable for use with such widely varying conditions. In this talk we present our development of a ''generic code'' to allow real time (at loop rate) robot behavior adaptation to changes in task objectives, tools, number and type of constraints, modes of controls or kinematics configuration. Wemore » present the analytical framework underlying our approach and detail the design of its two major modules for the automatic generation of the kinematics equations when the robot configuration or tools change and for the motion planning under time-varying constraints. Sample problems illustrating the capabilities of the developed system are presented.« less

KSC-98pc644

NASA Image and Video Library

1998-05-22

KENNEDY SPACE CENTER, FLA. -- The International Space Station's (ISS) Unity node, with Pressurized Mating Adapter (PMA)-2 attached, awaits further processing in the Space Station Processing Facility (SSPF). The Unity node is the first element of the ISS to be manufactured in the United States and is currently scheduled to lift off aboard the Space Shuttle Endeavour on STS-88 later this year. Unity has two PMAs attached to it now that this mate is completed. PMAs are conical docking adapters which will allow the docking systems used by the Space Shuttle and by Russian modules to attach to the node's hatches and berthing mechanisms. Once in orbit, Unity, which has six hatches, will be mated with the already orbiting Control Module and will eventually provide attachment points for the U.S. laboratory module; Node 3; an early exterior framework or truss for the station; an airlock; and a multi-windowed cupola. The Control Module, or Functional Cargo Block, is a U.S.-funded and Russian-built component that will be launched aboard a Russian rocket from Kazakstan

KSC-98pc645

NASA Image and Video Library

1998-05-22

KENNEDY SPACE CENTER, FLA. -- The International Space Station's (ISS) Unity node, with Pressurized Mating Adapter (PMA)-2 attached, awaits further processing in the Space Station Processing Facility (SSPF). The Unity node is the first element of the ISS to be manufactured in the United States and is currently scheduled to lift off aboard the Space Shuttle Endeavour on STS-88 later this year. Unity has two PMAs attached to it now that this mate is completed. PMAs are conical docking adapters which will allow the docking systems used by the Space Shuttle and by Russian modules to attach to the node's hatches and berthing mechanisms. Once in orbit, Unity, which has six hatches, will be mated with the already orbiting Control Module and will eventually provide attachment points for the U.S. laboratory module; Node 3; an early exterior framework or truss for the station; an airlock; and a multi-windowed cupola. The Control Module, or Functional Cargo Block, is a U.S.-funded and Russian-built component that will be launched aboard a Russian rocket from Kazakstan

Neurocognitive therapeutics: from concept to application in the treatment of negative attention bias.

PubMed

Schnyer, David M; Beevers, Christopher G; deBettencourt, Megan T; Sherman, Stephanie M; Cohen, Jonathan D; Norman, Kenneth A; Turk-Browne, Nicholas B

2015-01-01

There is growing interest in the use of neuroimaging for the direct treatment of mental illness. Here, we present a new framework for such treatment, neurocognitive therapeutics. What distinguishes neurocognitive therapeutics from prior approaches is the use of precise brain-decoding techniques within a real-time feedback system, in order to adapt treatment online and tailor feedback to individuals' needs. We report an initial feasibility study that uses this framework to alter negative attention bias in a small number of patients experiencing significant mood symptoms. The results are consistent with the promise of neurocognitive therapeutics to improve mood symptoms and alter brain networks mediating attentional control. Future work should focus on optimizing the approach, validating its effectiveness, and expanding the scope of targeted disorders.

Interaction Pattern Analysis in cMOOCs Based on the Connectivist Interaction and Engagement Framework

ERIC Educational Resources Information Center

Wang, Zhijun; Anderson, Terry; Chen, Li; Barbera, Elena

2017-01-01

Connectivist learning is interaction-centered learning. A framework describing interaction and cognitive engagement in connectivist learning was constructed using logical reasoning techniques. The framework and analysis was designed to help researchers and learning designers understand and adapt the characteristics and principles of interaction in…

An Automated, Adaptive Framework for Optimizing Preprocessing Pipelines in Task-Based Functional MRI

PubMed Central

Churchill, Nathan W.; Spring, Robyn; Afshin-Pour, Babak; Dong, Fan; Strother, Stephen C.

2015-01-01

BOLD fMRI is sensitive to blood-oxygenation changes correlated with brain function; however, it is limited by relatively weak signal and significant noise confounds. Many preprocessing algorithms have been developed to control noise and improve signal detection in fMRI. Although the chosen set of preprocessing and analysis steps (the “pipeline”) significantly affects signal detection, pipelines are rarely quantitatively validated in the neuroimaging literature, due to complex preprocessing interactions. This paper outlines and validates an adaptive resampling framework for evaluating and optimizing preprocessing choices by optimizing data-driven metrics of task prediction and spatial reproducibility. Compared to standard “fixed” preprocessing pipelines, this optimization approach significantly improves independent validation measures of within-subject test-retest, and between-subject activation overlap, and behavioural prediction accuracy. We demonstrate that preprocessing choices function as implicit model regularizers, and that improvements due to pipeline optimization generalize across a range of simple to complex experimental tasks and analysis models. Results are shown for brief scanning sessions (<3 minutes each), demonstrating that with pipeline optimization, it is possible to obtain reliable results and brain-behaviour correlations in relatively small datasets. PMID:26161667

Autonomous Propulsion System Technology Being Developed to Optimize Engine Performance Throughout the Lifecycle

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

2004-01-01

The goal of the Autonomous Propulsion System Technology (APST) project is to reduce pilot workload under both normal and anomalous conditions. Ongoing work under APST develops and leverages technologies that provide autonomous engine monitoring, diagnosing, and controller adaptation functions, resulting in an integrated suite of algorithms that maintain the propulsion system's performance and safety throughout its life. Engine-to-engine performance variation occurs among new engines because of manufacturing tolerances and assembly practices. As an engine wears, the performance changes as operability limits are reached. In addition to these normal phenomena, other unanticipated events such as sensor failures, bird ingestion, or component faults may occur, affecting pilot workload as well as compromising safety. APST will adapt the controller as necessary to achieve optimal performance for a normal aging engine, and the safety net of APST algorithms will examine and interpret data from a variety of onboard sources to detect, isolate, and if possible, accommodate faults. Situations that cannot be accommodated within the faulted engine itself will be referred to a higher level vehicle management system. This system will have the authority to redistribute the faulted engine's functionality among other engines, or to replan the mission based on this new engine health information. Work is currently underway in the areas of adaptive control to compensate for engine degradation due to aging, data fusion for diagnostics and prognostics of specific sensor and component faults, and foreign object ingestion detection. In addition, a framework is being defined for integrating all the components of APST into a unified system. A multivariable, adaptive, multimode control algorithm has been developed that accommodates degradation-induced thrust disturbances during throttle transients. The baseline controller of the engine model currently being investigated has multiple control modes that are selected according to some performance or operational criteria. As the engine degrades, parameters shift from their nominal values. Thus, when a new control mode is swapped in, a variable that is being brought under control might have an excessive initial error. The new adaptive algorithm adjusts the controller gains on the basis of the level of degradation to minimize the disruptive influence of the large error on other variables and to recover the desired thrust response.

Framework for mapping the drivers of coastal vulnerability and spatial decision making for climate-change adaptation: A case study from Maharashtra, India.

PubMed

Krishnan, Pandian; Ananthan, Pachampalayam Shanmugam; Purvaja, Ramachandran; Joyson Joe Jeevamani, Jeyapaul; Amali Infantina, John; Srinivasa Rao, Cherukumalli; Anand, Arur; Mahendra, Ranganalli Somashekharappa; Sekar, Iyyapa; Kareemulla, Kalakada; Biswas, Amit; Kalpana Sastry, Regulagedda; Ramesh, Ramachandran

2018-05-31

The impacts of climate change are of particular concern to the coastal region of tropical countries like India, which are exposed to cyclones, floods, tsunami, seawater intrusion, etc. Climate-change adaptation presupposes comprehensive assessment of vulnerability status. Studies so far relied either on remote sensing-based spatial mapping of physical vulnerability or on certain socio-economic aspects with limited scope for upscaling or replication. The current study is an attempt to develop a holistic and robust framework to assess the vulnerability of coastal India at different levels. We propose and estimate cumulative vulnerability index (CVI) as a function of exposure, sensitivity and adaptive capacity, at the village level, using nationally comparable and credible datasets. The exposure index (EI) was determined at the village level by decomposing the spatial multi-hazard maps, while sensitivity (SI) and adaptive capacity indices (ACI) were estimated using 23 indicators, covering social and economic aspects. The indicators were identified through the literature review, expert consultations, opinion survey, and were further validated through statistical tests. The socio-economic vulnerability index (SEVI) was constructed as a function of sensitivity and adaptive capacity for planning grassroot-level interventions and adaptation strategies. The framework was piloted in Sindhudurg, a coastal district in Maharashtra, India. It comprises 317 villages, spread across three taluks viz., Devgad, Malvan and Vengurla. The villages in Sindhudurg were ranked based on this multi-criteria approach. Based on CVI values, 92 villages (30%) in Sindhudurg were identified as highly vulnerable. We propose a decision tool for identifying villages vulnerable to changing climate, based on their level of sensitivity and adaptive capacity in a two-dimensional matrix, thus aiding in planning location-specific interventions. Here, vulnerability indicators are classified and designated as 'drivers' (indicators with significantly high values and intervention priority) and 'buffers' (indicators with low-to-moderate values) at the village level. The framework provides for aggregation or decomposition of CVI and other sub-indices, in order to plan spatial contingency plans and enable swift action for climate adaptation.

Deep reinforcement learning for automated radiation adaptation in lung cancer.

PubMed

Tseng, Huan-Hsin; Luo, Yi; Cui, Sunan; Chien, Jen-Tzung; Ten Haken, Randall K; Naqa, Issam El

2017-12-01

To investigate deep reinforcement learning (DRL) based on historical treatment plans for developing automated radiation adaptation protocols for nonsmall cell lung cancer (NSCLC) patients that aim to maximize tumor local control at reduced rates of radiation pneumonitis grade 2 (RP2). In a retrospective population of 114 NSCLC patients who received radiotherapy, a three-component neural networks framework was developed for deep reinforcement learning (DRL) of dose fractionation adaptation. Large-scale patient characteristics included clinical, genetic, and imaging radiomics features in addition to tumor and lung dosimetric variables. First, a generative adversarial network (GAN) was employed to learn patient population characteristics necessary for DRL training from a relatively limited sample size. Second, a radiotherapy artificial environment (RAE) was reconstructed by a deep neural network (DNN) utilizing both original and synthetic data (by GAN) to estimate the transition probabilities for adaptation of personalized radiotherapy patients' treatment courses. Third, a deep Q-network (DQN) was applied to the RAE for choosing the optimal dose in a response-adapted treatment setting. This multicomponent reinforcement learning approach was benchmarked against real clinical decisions that were applied in an adaptive dose escalation clinical protocol. In which, 34 patients were treated based on avid PET signal in the tumor and constrained by a 17.2% normal tissue complication probability (NTCP) limit for RP2. The uncomplicated cure probability (P+) was used as a baseline reward function in the DRL. Taking our adaptive dose escalation protocol as a blueprint for the proposed DRL (GAN + RAE + DQN) architecture, we obtained an automated dose adaptation estimate for use at ∼2/3 of the way into the radiotherapy treatment course. By letting the DQN component freely control the estimated adaptive dose per fraction (ranging from 1-5 Gy), the DRL automatically favored dose escalation/de-escalation between 1.5 and 3.8 Gy, a range similar to that used in the clinical protocol. The same DQN yielded two patterns of dose escalation for the 34 test patients, but with different reward variants. First, using the baseline P+ reward function, individual adaptive fraction doses of the DQN had similar tendencies to the clinical data with an RMSE = 0.76 Gy; but adaptations suggested by the DQN were generally lower in magnitude (less aggressive). Second, by adjusting the P+ reward function with higher emphasis on mitigating local failure, better matching of doses between the DQN and the clinical protocol was achieved with an RMSE = 0.5 Gy. Moreover, the decisions selected by the DQN seemed to have better concordance with patients eventual outcomes. In comparison, the traditional temporal difference (TD) algorithm for reinforcement learning yielded an RMSE = 3.3 Gy due to numerical instabilities and lack of sufficient learning. We demonstrated that automated dose adaptation by DRL is a feasible and a promising approach for achieving similar results to those chosen by clinicians. The process may require customization of the reward function if individual cases were to be considered. However, development of this framework into a fully credible autonomous system for clinical decision support would require further validation on larger multi-institutional datasets. © 2017 American Association of Physicists in Medicine.

Adaptive Numerical Algorithms in Space Weather Modeling

NASA Technical Reports Server (NTRS)

Toth, Gabor; vanderHolst, Bart; Sokolov, Igor V.; DeZeeuw, Darren; Gombosi, Tamas I.; Fang, Fang; Manchester, Ward B.; Meng, Xing; Nakib, Dalal; Powell, Kenneth G.;

Investigating Work and Learning through Complex Adaptive Organisations

ERIC Educational Resources Information Center

Lizier, Amanda Louise

2017-01-01

Purpose: The purpose of this paper is to outline an empirical study of how professionals experience work and learning in complex adaptive organisations. The study uses a complex adaptive systems approach, which forms the basis of a specifically developed conceptual framework for explaining professionals' experiences of work and learning.…

Guiding Preservice Teachers to Adapt Mathematics Word Problems through Interactions with ELLs

ERIC Educational Resources Information Center

Kurz, Terri L.; Gómez, Conrado; Jimenez-Silva, Margarita

2017-01-01

In this article, the authors present a framework for guiding elementary preservice teachers in adapting mathematics word problems to better meet English language learners' (ELLs) needs. They analyze preservice teachers' ELL adaptations implemented in a one-on-one setting. Through qualitative methods, four themes regarding implemented adaptations…

Management for adaptation

Treesearch

John Innes; Linda A. Joyce; Seppo Kellomaki; Bastiaan Louman; Aynslie Ogden; Ian Thompson; Matthew Ayres; Chin Ong; Heru Santoso; Brent Sohngen; Anita Wreford

2009-01-01

This chapter develops a framework to explore examples of adaptation options that could be used to ensure that the ecosystem services provided by forests are maintained under future climates. The services are divided into broad areas within which managers can identify specific management goals for individual forests or landscapes. Adaptation options exist for the major...

Langley Wind Tunnel Data Quality Assurance-Check Standard Results

NASA Technical Reports Server (NTRS)

Hemsch, Michael J.; Grubb, John P.; Krieger, William B.; Cler, Daniel L.

2000-01-01

A framework for statistical evaluation, control and improvement of wind funnel measurement processes is presented The methodology is adapted from elements of the Measurement Assurance Plans developed by the National Bureau of Standards (now the National Institute of Standards and Technology) for standards and calibration laboratories. The present methodology is based on the notions of statistical quality control (SQC) together with check standard testing and a small number of customer repeat-run sets. The results of check standard and customer repeat-run -sets are analyzed using the statistical control chart-methods of Walter A. Shewhart long familiar to the SQC community. Control chart results are presented for. various measurement processes in five facilities at Langley Research Center. The processes include test section calibration, force and moment measurements with a balance, and instrument calibration.

A unified perspective on robot control - The energy Lyapunov function approach

NASA Technical Reports Server (NTRS)

Wen, John T.

1990-01-01

A unified framework for the stability analysis of robot tracking control is presented. By using an energy-motivated Lyapunov function candidate, the closed-loop stability is shown for a large family of control laws sharing a common structure of proportional and derivative feedback and a model-based feedforward. The feedforward can be zero, partial or complete linearized dynamics, partial or complete nonlinear dynamics, or linearized or nonlinear dynamics with parameter adaptation. As result, the dichotomous approaches to the robot control problem based on the open-loop linearization and nonlinear Lyapunov analysis are both included in this treatment. Furthermore, quantitative estimates of the trade-offs between different schemes in terms of the tracking performance, steady state error, domain of convergence, realtime computation load and required a prior model information are derived.

Competitive strategy in the hospital industry.

PubMed

Autrey, P; Thomas, D

1986-01-01

Porter recently developed a framework for applying effective strategies in an increasingly competitive business environment. His framework can be adapted to the health care industry and can serve as a tool for success.

Spatial-temporal-covariance-based modeling, analysis, and simulation of aero-optics wavefront aberrations.

PubMed

Vogel, Curtis R; Tyler, Glenn A; Wittich, Donald J

2014-07-01

We introduce a framework for modeling, analysis, and simulation of aero-optics wavefront aberrations that is based on spatial-temporal covariance matrices extracted from wavefront sensor measurements. Within this framework, we present a quasi-homogeneous structure function to analyze nonhomogeneous, mildly anisotropic spatial random processes, and we use this structure function to show that phase aberrations arising in aero-optics are, for an important range of operating parameters, locally Kolmogorov. This strongly suggests that the d5/3 power law for adaptive optics (AO) deformable mirror fitting error, where d denotes actuator separation, holds for certain important aero-optics scenarios. This framework also allows us to compute bounds on AO servo lag error and predictive control error. In addition, it provides us with the means to accurately simulate AO systems for the mitigation of aero-effects, and it may provide insight into underlying physical processes associated with turbulent flow. The techniques introduced here are demonstrated using data obtained from the Airborne Aero-Optics Laboratory.

Detection and attribution of climate change at regional scale: case study of Karkheh river basin in the west of Iran

NASA Astrophysics Data System (ADS)

Zohrabi, Narges; Goodarzi, Elahe; Massah Bavani, Alireza; Najafi, Husain

2017-11-01

This research aims at providing a statistical framework for detection and attribution of climate variability and change at regional scale when at least 30 years of observation data are available. While extensive research has been done on detecting significant observed trends in hydroclimate variables and attribution to anthropogenic greenhouse gas emissions in large continents, less attention has been paid for regional scale analysis. The latter is mainly important for adaptation to climate change in different sectors including but not limited to energy, agriculture, and water resources planning and management, and it is still an open discussion in many countries including the West Asian ones. In the absence of regional climate models, an informative framework is suggested providing useful insights for policymakers. It benefits from general flexibility, not being computationally expensive, and applying several trend tests to analyze temporal variations in temperature and precipitation (gradual and step changes). The framework is implemented for a very important river basin in the west of Iran. In general, some increasing and decreasing trends of the interannual precipitation and temperature have been detected. For precipitation annual time series, a reducing step was seen around 1996 compared with the gradual change in most of the stations, which have not experience a dramatical change. The range of natural forcing is found to be ±76 % for precipitation and ±1.4 °C for temperature considering a two-dimensional diagram of precipitation and temperature anomalies from 1000-year control run of global climate model (GCM). Findings out of applying the proposed framework may provide useful insights into how to approach structural and non-structural climate change adaptation strategies from central governments.

Safe-trajectory optimization and tracking control in ultra-close proximity to a failed satellite

NASA Astrophysics Data System (ADS)

Zhang, Jingrui; Chu, Xiaoyu; Zhang, Yao; Hu, Quan; Zhai, Guang; Li, Yanyan

2018-03-01

This paper presents a trajectory-optimization method for a chaser spacecraft operating in ultra-close proximity to a failed satellite. Based on the combination of active and passive trajectory protection, the constraints in the optimization framework are formulated for collision avoidance and successful docking in the presence of any thruster failure. The constraints are then handled by an adaptive Gauss pseudospectral method, in which the dynamic residuals are used as the metric to determine the distribution of collocation points. A finite-time feedback control is further employed in tracking the optimized trajectory. In particular, the stability and convergence of the controller are proved. Numerical results are given to demonstrate the effectiveness of the proposed methods.

Nonlinear model predictive control applied to the separation of praziquantel in simulated moving bed chromatography.

PubMed

Andrade Neto, A S; Secchi, A R; Souza, M B; Barreto, A G

2016-10-28

An adaptive nonlinear model predictive control of a simulated moving bed unit for the enantioseparation of praziquantel is presented. A first principle model was applied at the proposed purity control scheme. The main concern about this kind of model in a control framework is in regard to the computational effort to solve it; however, a fast enough solution was achieved. In order to evaluate the controller's performance, several cases were simulated, including external pumps and switching valve malfunctions. The problem of plant-model mismatch was also investigated, and for that reason a parameter estimation step was introduced in the control strategy. In every studied scenario, the controller was able to maintain the purity levels at their set points, which were set to 99% and 98.6% for extract and raffinate, respectively. Additionally, fast responses and smooth actuation were achieved. Copyright © 2016 Elsevier B.V. All rights reserved.

Joint Cross-Layer Design for Wireless QoS Content Delivery

NASA Astrophysics Data System (ADS)

Chen, Jie; Lv, Tiejun; Zheng, Haitao

2005-12-01

In this paper, we propose a joint cross-layer design for wireless quality-of-service (QoS) content delivery. Central to our proposed cross-layer design is the concept of adaptation. Adaptation represents the ability to adjust protocol stacks and applications to respond to channel variations. We focus our cross-layer design especially on the application, media access control (MAC), and physical layers. The network is designed based on our proposed fast frequency-hopping orthogonal frequency division multiplex (OFDM) technique. We also propose a QoS-awareness scheduler and a power adaptation transmission scheme operating at both the base station and mobile sides. The proposed MAC scheduler coordinates the transmissions of an IP base station and mobile nodes. The scheduler also selects appropriate transmission formats and packet priorities for individual users based on current channel conditions and the users' QoS requirements. The test results show that our cross-layer design provides an excellent framework for wireless QoS content delivery.

The new VLT-DSM M2 unit: construction and electromechanical testing

NASA Astrophysics Data System (ADS)

Gallieni, Daniele; Biasi, Roberto

2013-12-01

We present the design, construction and validation of the new M2 unit of the VLT Deformable Secondary Mirror. In the framework of the Adaptive Optics Facility program, ADS and Microgate designed a new secondary unit which replaces the current Dornier one. The M2 is composed by the mechanical structure, a new hexapod positioner and the Deformable Secondary Mirror unit.The DSM is based on the well proven contactless, voice coil motor technology that has been already successfully implemented in the MMT, LBT and Magellan adaptive secondaries, and is considered a promising technical choice for the E-ELT M4 and the GMT ASM. The VLT adaptive unit has been fully integrated and, before starting the optical calibration, has completed the electromechanical characterization, focused on the dynamic performance. With respect to the previous units we introduced several improvements, both in hardware and control architecture that allowed achieving a significant enhancement of the system dynamics and reduction of power consumption.

Extending the Shared Socioeconomic Pathways for sub-national impacts, adaptation, and vulnerability studies

DOE PAGES

Absar, Syeda Mariya; Preston, Benjamin L.

2015-05-25

The exploration of alternative socioeconomic futures is an important aspect of understanding the potential consequences of climate change. While socioeconomic scenarios are common and, at times essential, tools for the impact, adaptation and vulnerability and integrated assessment modeling research communities, their approaches to scenario development have historically been quite distinct. However, increasing convergence of impact, adaptation and vulnerability and integrated assessment modeling research in terms of scales of analysis suggests there may be value in the development of a common framework for socioeconomic scenarios. The Shared Socioeconomic Pathways represents an opportunity for the development of such a common framework. However,more » the scales at which these global storylines have been developed are largely incommensurate with the sub-national scales at which impact, adaptation and vulnerability, and increasingly integrated assessment modeling, studies are conducted. Our objective for this study was to develop sub-national and sectoral extensions of the global SSP storylines in order to identify future socioeconomic challenges for adaptation for the U.S. Southeast. A set of nested qualitative socioeconomic storyline elements, integrated storylines, and accompanying quantitative indicators were developed through an application of the Factor-Actor-Sector framework. Finally, in addition to revealing challenges and opportunities associated with the use of the SSPs as a basis for more refined scenario development, this study generated sub-national storyline elements and storylines that can subsequently be used to explore the implications of alternative subnational socioeconomic futures for the assessment of climate change impacts and adaptation.« less

GMDPtoolbox: A Matlab library for designing spatial management policies. Application to the long-term collective management of an airborne disease

PubMed Central

Aubertot, Jean-Noël; Peyrard, Nathalie; Sabbadin, Régis

2017-01-01

Designing management policies in ecology and agroecology is complex. Several components must be managed together while they strongly interact spatially. Decision choices must be made under uncertainty on the results of the actions and on the system dynamics. Furthermore, the objectives pursued when managing ecological systems or agroecosystems are usually long term objectives, such as biodiversity conservation or sustainable crop production. The framework of Graph-Based Markov Decision Processes (GMDP) is well adapted to the qualitative modeling of such problems of sequential decision under uncertainty. Spatial interactions are easily modeled and integrated control policies (combining several action levers) can be designed through optimization. The provided policies are adaptive, meaning that management actions are decided at each time step (for instance yearly) and the chosen actions depend on the current system state. This framework has already been successfully applied to forest management and invasive species management. However, up to now, no “easy-to-use” implementation of this framework was available. We present GMDPtoolbox, a Matlab toolbox which can be used both for the design of new management policies and for comparing policies by simulation. We provide an illustration of the use of the toolbox on a realistic crop disease management problem: the design of long term management policy of blackleg of canola using an optimal combination of three possible cultural levers. This example shows how GMDPtoolbox can be used as a tool to support expert thinking. PMID:28982151

GMDPtoolbox: A Matlab library for designing spatial management policies. Application to the long-term collective management of an airborne disease.

PubMed

Cros, Marie-Josée; Aubertot, Jean-Noël; Peyrard, Nathalie; Sabbadin, Régis

2017-01-01

Designing management policies in ecology and agroecology is complex. Several components must be managed together while they strongly interact spatially. Decision choices must be made under uncertainty on the results of the actions and on the system dynamics. Furthermore, the objectives pursued when managing ecological systems or agroecosystems are usually long term objectives, such as biodiversity conservation or sustainable crop production. The framework of Graph-Based Markov Decision Processes (GMDP) is well adapted to the qualitative modeling of such problems of sequential decision under uncertainty. Spatial interactions are easily modeled and integrated control policies (combining several action levers) can be designed through optimization. The provided policies are adaptive, meaning that management actions are decided at each time step (for instance yearly) and the chosen actions depend on the current system state. This framework has already been successfully applied to forest management and invasive species management. However, up to now, no "easy-to-use" implementation of this framework was available. We present GMDPtoolbox, a Matlab toolbox which can be used both for the design of new management policies and for comparing policies by simulation. We provide an illustration of the use of the toolbox on a realistic crop disease management problem: the design of long term management policy of blackleg of canola using an optimal combination of three possible cultural levers. This example shows how GMDPtoolbox can be used as a tool to support expert thinking.

Preclinical Feasibility of a Technology Framework for MRI-guided Iliac Angioplasty

PubMed Central

Rube, Martin A.; Fernandez-Gutierrez, Fabiola; Cox, Benjamin F.; Holbrook, Andrew B.; Houston, J. Graeme; White, Richard D.; McLeod, Helen; Fatahi, Mahsa; Melzer, Andreas

2015-01-01

Purpose Interventional MRI has significant potential for image guidance of iliac angioplasty and related vascular procedures. A technology framework with in-room image display, control, communication and MRI-guided intervention techniques was designed and tested for its potential to provide safe, fast and efficient MRI-guided angioplasty of the iliac arteries. Methods A 1.5T MRI scanner was adapted for interactive imaging during endovascular procedures using new or modified interventional devices such as guidewires and catheters. A perfused vascular phantom was used for testing. Pre-, intra- and post-procedural visualization and measurement of vascular morphology and flow was implemented. A detailed analysis of X-Ray fluoroscopic angiography workflow was conducted and applied. Two interventional radiologists and one physician in training performed 39 procedures. All procedures were timed and analyzed. Results MRI-guided iliac angioplasty procedures were successfully performed with progressive adaptation of techniques and workflow. The workflow, setup and protocol enabled a reduction in table time for a dedicated MRI-guided procedure to 6 min 33 s with a mean procedure time of 9 min 2 s, comparable to the mean procedure time of 8 min 42 s for the standard X-Ray guided procedure. Conclusions MRI-guided iliac vascular interventions were found to be feasible and practical using this framework and optimized workflow. In particular the real-time flow analysis was found to be helpful for pre- and post-interventional assessments. Design optimization of the catheters and in vivo experiments are required before clinical evaluation. PMID:25102933

Hearing Impairment and Cognitive Energy: The Framework for Understanding Effortful Listening (FUEL).

PubMed

Pichora-Fuller, M Kathleen; Kramer, Sophia E; Eckert, Mark A; Edwards, Brent; Hornsby, Benjamin W Y; Humes, Larry E; Lemke, Ulrike; Lunner, Thomas; Matthen, Mohan; Mackersie, Carol L; Naylor, Graham; Phillips, Natalie A; Richter, Michael; Rudner, Mary; Sommers, Mitchell S; Tremblay, Kelly L; Wingfield, Arthur

2016-01-01

The Fifth Eriksholm Workshop on "Hearing Impairment and Cognitive Energy" was convened to develop a consensus among interdisciplinary experts about what is known on the topic, gaps in knowledge, the use of terminology, priorities for future research, and implications for practice. The general term cognitive energy was chosen to facilitate the broadest possible discussion of the topic. It goes back to who described the effects of attention on perception; he used the term psychic energy for the notion that limited mental resources can be flexibly allocated among perceptual and mental activities. The workshop focused on three main areas: (1) theories, models, concepts, definitions, and frameworks; (2) methods and measures; and (3) knowledge translation. We defined effort as the deliberate allocation of mental resources to overcome obstacles in goal pursuit when carrying out a task, with listening effort applying more specifically when tasks involve listening. We adapted Kahneman's seminal (1973) Capacity Model of Attention to listening and proposed a heuristically useful Framework for Understanding Effortful Listening (FUEL). Our FUEL incorporates the well-known relationship between cognitive demand and the supply of cognitive capacity that is the foundation of cognitive theories of attention. Our FUEL also incorporates a motivation dimension based on complementary theories of motivational intensity, adaptive gain control, and optimal performance, fatigue, and pleasure. Using a three-dimensional illustration, we highlight how listening effort depends not only on hearing difficulties and task demands but also on the listener's motivation to expend mental effort in the challenging situations of everyday life.

Development as adaptation: a paradigm for gravitational and space biology

NASA Technical Reports Server (NTRS)

Alberts, Jeffrey R.; Ronca, April E.

2005-01-01

Adaptation is a central precept of biology; it provides a framework for identifying functional significance. We equate mammalian development with adaptation, by viewing the developmental sequence as a series of adaptations to a stereotyped sequence of habitats. In this way development is adaptation. The Norway rat is used as a mammalian model, and the sequence of habitats that is used to define its adaptive-developmental sequence is (a) the uterus, (b) the mother's body, (c) the huddle, and (d) the coterie of pups as they gain independence. Then, within this framework and in relation to each of the habitats, we consider problems of organismal responses to altered gravitational forces (micro-g to hyper-g), especially those encountered during space flight and centrifugation. This approach enables a clearer identification of simple "effects" and active "responses" with respect to gravity. It focuses our attention on functional systems and brings to the fore the manner in which experience shapes somatic adaptation. We argue that this basic developmental approach is not only central to basic issues in gravitational biology, but that it provides a natural tool for understanding the underlying processes that are vital to astronaut health and well-being during long duration flights that will involve adaptation to space flight conditions and eventual re-adaptation to Earth's gravity.

A framework of psychological compensation in attention deficit hyperactivity disorder.

PubMed

Merkt, Julia; Reinelt, Tilman; Petermann, Franz

2015-01-01

The term compensation is widely used in the context of attention deficit hyperactivity disorder (ADHD), yet, it is neither defined nor theory driven. Adapting a model of psychological compensation (Bäckman and Dixon, 1992) to fit ADHD research is the aim of this review: we will (1) introduce the existing theoretical framework of psychological compensation, (2) discuss its applicability to ADHD and adapt the model to fit ADHD research, and (3) set up requirements for research on psychological compensation in ADHD. According to the framework psychological compensation can be inferred if a deficit (i.e., a mismatch between skill and environmental demand) is counterbalanced by the investment of more effort, the utilization of latent skills, or the acquisition of new skills. The framework has to be adapted because ADHD deficits are developmental and in individuals with ADHD compensation can appear independent of awareness of the deficit. A better understanding of psychological compensation in ADHD could foster diagnosis and interventions. Therefore, we suggest that future studies should follow a research design incorporating independent measures of deficit, compensation, and outcome as well as include individuals who compensate for their ADHD related deficits.

Functional neuroimaging of normal aging: Declining brain, adapting brain.

PubMed

Sugiura, Motoaki

2016-09-01

Early functional neuroimaging research on normal aging brain has been dominated by the interest in cognitive decline. In this framework the age-related compensatory recruitment of prefrontal cortex, in terms of executive system or reduced lateralization, has been established. Further details on these compensatory mechanisms and the findings reflecting cognitive decline, however, remain the matter of intensive investigations. Studies in another framework where age-related neural alteration is considered adaptation to the environmental change are recently burgeoning and appear largely categorized into three domains. The age-related increase in activation of the sensorimotor network may reflect the alteration of the peripheral sensorimotor systems. The increased susceptibility of the network for the mental-state inference to the socioemotional significance may be explained by the age-related motivational shift due to the altered social perception. The age-related change in activation of the self-referential network may be relevant to the focused positive self-concept of elderly driven by a similar motivational shift. Across the domains, the concept of the self and internal model may provide the theoretical bases of this adaptation framework. These two frameworks complement each other to provide a comprehensive view of the normal aging brain. Copyright © 2016 Elsevier B.V. All rights reserved.

Climate adaptation wedges: a case study of premium wine in the western United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Diffenbaugh, Noah; White, Michael A; Jones, Gregory V

2011-01-01

Design and implementation of effective climate change adaptation activities requires quantitative assessment of the impacts that are likely to occur without adaptation, as well as the fraction of impact that can be avoided through each activity. Here we present a quantitative framework inspired by the greenhouse gas stabilization wedges of Pacala and Socolow. In our proposed framework, the damage avoided by each adaptation activity creates an 'adaptation wedge' relative to the loss that would occur without that adaptation activity. We use premium winegrape suitability in the western United States as an illustrative case study, focusing on the near-term period thatmore » covers the years 2000 39. We find that the projected warming over this period results in the loss of suitable winegrape area throughout much of California, including most counties in the high-value North Coast and Central Coast regions. However, in quantifying adaptation wedges for individual high-value counties, we find that a large adaptation wedge can be captured by increasing the severe heat tolerance, including elimination of the 50% loss projected by the end of the 2030 9 period in the North Coast region, and reduction of the projected loss in the Central Coast region from 30% to less than 15%. Increased severe heat tolerance can capture an even larger adaptation wedge in the Pacific Northwest, including conversion of a projected loss of more than 30% in the Columbia Valley region of Washington to a projected gain of more than 150%. We also find that warming projected over the near-term decades has the potential to alter the quality of winegrapes produced in the western US, and we discuss potential actions that could create adaptation wedges given these potential changes in quality. While the present effort represents an initial exploration of one aspect of one industry, the climate adaptation wedge framework could be used to quantitatively evaluate the opportunities and limits of climate adaptation within and across a broad range of natural and human systems.« less

A framework for identifying water management typologies for agent based modeling of water resources and its application in the Boise River Basin, USA.

NASA Astrophysics Data System (ADS)

Kaiser, K. E.; Flores, A. N.; Hillis, V.; Moroney, J.; Schneider, J.

2017-12-01

Modeling the management of water resources necessitates incorporation of complex social and hydrologic dynamics. Simulation of these socio-ecological systems requires characterization of the decision-making process of relevant actors, the mechanisms through which they exert control on the biophysical system, their ability to react and adapt to regional environmental conditions, and the plausible behaviors in response to changes in those conditions. Agent based models (ABMs) are a useful tool in simulating these complex adaptive systems because they can dynamically couple hydrological models and the behavior of decision making actors. ABMs can provide a flexible, integrated framework that can represent multi-scale interactions, and the heterogeneity of information networks and sources. However, the variability in behavior of water management actors across systems makes characterizing agent behaviors and relationships challenging. Agent typologies, or agent functional types (AFTs), group together individuals and/or agencies with similar functional roles, management objectives, and decision-making strategies. AFTs have been used to represent archetypal land managers in the agricultural and forestry sectors in large-scale socio-economic system models. A similar typology of water actors could simplify the representation of water management across river basins, and increase transferability and scaling of resulting ABMs. Here, we present a framework for identifying and classifying major water actors and show how we will link an ABM of water management to a regional hydrologic model in a western river basin. The Boise River Basin in southwest Idaho is an interesting setting to apply our AFT framework because of the diverse stakeholders and associated management objectives which include managing urban growth pressures and water supply in the face of climate change. Precipitation in the upper basin supplies 90% of the surface water used in the basin, thus managers of the reservoir system (located in the upper basin) must balance flood control for the metropolitan area with water supply for downstream agricultural and hydropower use. Identifying dominant water management typologies that include state and federal agencies will increase the transferability of water management ABMs in the western US.

All New and All Outcome-Based? The German Qualifications Framework and the Persistence of National Governance Approaches

ERIC Educational Resources Information Center

Gössling, Bernd

2016-01-01

This article analyses the development of the first national qualifications framework in Germany ("Deutscher Qualifikationsrahmen" or "DQR"). In this case, a qualifications framework, which is supposedly outcome-based, had to be adapted to a highly input-oriented qualification system. This raises the question, how clashing…

Representations of control and psychological symptoms in couples dealing with cancer: a dyadic-regulation approach.

PubMed

Karademas, Evangelos C; Giannousi, Zoe

2013-01-01

The aim of this study was to examine the relation between illness representations of personal and treatment control and psychological symptoms (i.e. symptoms of anxiety and depression) in 72 married couples dealing with a recently diagnosed cancer. Patients were first-diagnosed with early stage (45.83%) or metastatic cancer (54.17%). Dyadic responses were examined with the actor-partner interdependence model. Also, in order to examine whether patients and spouses' representations of control moderate the relation of their partners' corresponding representations to psychological symptoms, we used the relevant bootstrapping framework developed by Hayes and Matthes [(2009). Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations. Behavior Research Methods, 41, 924-936]. Patients' symptoms of anxiety and depression were associated with both partners' representations of control. Chi-square difference tests indicated that actor and partner effects were equal. Spouses' symptoms of anxiety and depression were related only to their own representations. Moreover, spouses' representations of personal control moderated the relation of patients' corresponding representations to depressive symptoms, whereas patients' representations of treatment control moderated the relation of their spouses' corresponding representations to both anxiety and depression. Findings suggest that both partners' representations of control are important for adaptation to illness. Moreover, they indicate that dyadic regulation may be equally important to self-regulation as far as adaptation to illness is concerned.

Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

NASA Astrophysics Data System (ADS)

Hadjidoukas, P. E.; Angelikopoulos, P.; Papadimitriou, C.; Koumoutsakos, P.

2015-03-01

We present Π4U, an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

Computerized Adaptive Test (CAT) Applications and Item Response Theory Models for Polytomous Items

ERIC Educational Resources Information Center

Aybek, Eren Can; Demirtasli, R. Nukhet

2017-01-01

This article aims to provide a theoretical framework for computerized adaptive tests (CAT) and item response theory models for polytomous items. Besides that, it aims to introduce the simulation and live CAT software to the related researchers. Computerized adaptive test algorithm, assumptions of item response theory models, nominal response…

Adaptation Guidance for Evidence-Based Teen Pregnancy and STI/HIV Prevention Curricula: From Development to Practice

ERIC Educational Resources Information Center

Rolleri, Lori A.; Fuller, Taleria R.; Firpo-Triplett, Regina; Lesesne, Catherine A.; Moore, Claire; Leeks, Kimberly D.

2014-01-01

Evidence-based interventions (EBIs) are effective in preventing adolescent pregnancy and sexually transmitted infections; however, prevention practitioners are challenged when selecting and adapting the most appropriate programs. While there are existing adaptation frameworks, there is little practical guidance in applying research in the field.…

Complex Adaptive Schools: Educational Leadership and School Change

ERIC Educational Resources Information Center

Kershner, Brad; McQuillan, Patrick

2016-01-01

This paper utilizes the theoretical framework of complexity theory to compare and contrast leadership and educational change in two urban schools. Drawing on the notion of a complex adaptive system--an interdependent network of interacting elements that learns and evolves in adapting to an ever-shifting context--our case studies seek to reveal the…

Understanding the Leaky Engineering Pipeline: Motivation and Job Adaptability of Female Engineers

ERIC Educational Resources Information Center

Saraswathiamma, Manjusha Thekkedathu

2010-01-01

This dissertation is a mixed-method study conducted using qualitative grounded theory and quantitative survey and correlation approaches. This study aims to explore the motivation and adaptability of females in the engineering profession and to develop a theoretical framework for both motivation and adaptability issues. As a result, this study…

Adaption to Extreme Rainfall with Open Urban Drainage System: An Integrated Hydrological Cost-Benefit Analysis

NASA Astrophysics Data System (ADS)

Zhou, Qianqian; Panduro, Toke Emil; Thorsen, Bo Jellesmark; Arnbjerg-Nielsen, Karsten

2013-03-01

This paper presents a cross-disciplinary framework for assessment of climate change adaptation to increased precipitation extremes considering pluvial flood risk as well as additional environmental services provided by some of the adaptation options. The ability of adaptation alternatives to cope with extreme rainfalls is evaluated using a quantitative flood risk approach based on urban inundation modeling and socio-economic analysis of corresponding costs and benefits. A hedonic valuation model is applied to capture the local economic gains or losses from more water bodies in green areas. The framework was applied to the northern part of the city of Aarhus, Denmark. We investigated four adaptation strategies that encompassed laissez-faire, larger sewer pipes, local infiltration units, and open drainage system in the urban green structure. We found that when taking into account environmental amenity effects, an integration of open drainage basins in urban recreational areas is likely the best adaptation strategy, followed by pipe enlargement and local infiltration strategies. All three were improvements compared to the fourth strategy of no measures taken.

Adaption to extreme rainfall with open urban drainage system: an integrated hydrological cost-benefit analysis.

PubMed

Zhou, Qianqian; Panduro, Toke Emil; Thorsen, Bo Jellesmark; Arnbjerg-Nielsen, Karsten

2013-03-01

This paper presents a cross-disciplinary framework for assessment of climate change adaptation to increased precipitation extremes considering pluvial flood risk as well as additional environmental services provided by some of the adaptation options. The ability of adaptation alternatives to cope with extreme rainfalls is evaluated using a quantitative flood risk approach based on urban inundation modeling and socio-economic analysis of corresponding costs and benefits. A hedonic valuation model is applied to capture the local economic gains or losses from more water bodies in green areas. The framework was applied to the northern part of the city of Aarhus, Denmark. We investigated four adaptation strategies that encompassed laissez-faire, larger sewer pipes, local infiltration units, and open drainage system in the urban green structure. We found that when taking into account environmental amenity effects, an integration of open drainage basins in urban recreational areas is likely the best adaptation strategy, followed by pipe enlargement and local infiltration strategies. All three were improvements compared to the fourth strategy of no measures taken.

[Strategic framework for cholera prevention and control in Chengdu: construction and effectiveness evaluation].

PubMed

Liang, Xian; Du, Chang-hui; Yang, Lan; Ma, Lin; Huang, Zhong-hang; Tuo, Xiao-Li; Yin, Zhong-liang

2011-02-01

To construct an operable strategic framework for cholera prevention and control which mobilized the advantages of local resources and adapted to social developments in Chengdu, and to evaluate its application effects. (1) After analyzing the local epidemic data of cholera in Chengdu from 1994 to 2004, we determined the main problems of cholera prevention and control works as well as the efficiency and deficiency of employed measures, and then formed a basic strategic framework. (2) After 55 invited experts preliminarily scored the strategic framework, we selected 72 specific measures to establish a measure entry database, and then the importance and operability of each measure were scored by 17 core experts. (3) Finally, the effectiveness of this strategic framework was evaluated according to the analyzing results of infection control, health education and etiological monitoring. (1) The framework took government leadership as main scenario and the informatization as subordination scenario. Meanwhile, it focused on three points: the improvement of social environment, the completion of system and mechanisms for monitoring and early warning, and the enhancement of CDC response to public health emergencies. Total importance score and operability score of 35 specific measures included in this framework was 4.20 ± 0.86 and 4.09 ± 0.87, respectively. (2) Chengdu had maintained zero cholera incidence for five consecutive years from 2005 to 2009 since it gradually began to implement the strategic framework in 2002. There were 19 positive cholera cases detected by etiological monitoring and all of them were seafood or fishery products including soft-shelled turtles, silver carps and bullfrogs. The coverage rate and qualification rate of the training for grassroots cadres, grassroots medical workers, mobile cooks and their assistants was 98.14% (198 452/202 220) and 98.17% (194 820/198 452) in average, respectively. The qualification rate of the training for employees in food industry was over 96.00% (912 470/950 489). The average awareness rate of cholera prevention and cure knowledge in rural residents, grassroots cadres, grassroots medical workers, mobile cooks and their assistants was 93.87% (1653/1761) and the average formation rate of good hygiene habits was 70.58% (1243/1761). A strategic framework suitable for cholera prevention and control in Chengdu has been successfully established in this study. The incidence rate of cholera has maintained zero in Chengdu for five consecutive years under incessant threatening conditions such as the occurrence of cholera cases from time to time in its surrounding areas and the continuous existence of Bacillus comma in seafood or fishery products that entered local markets. Therefore, it demonstrated a good application effects.

A New Framework and Practice Center for Adapting, Translating, and Scaling Evidence-Based Health/Wellness Programs for People With Disabilities.

PubMed

Rimmer, James H; Vanderbom, Kerri A; Graham, Ian D

2016-04-01

Supporting the transition of people with newly acquired and existing disability from rehabilitation into community-based health/wellness programs, services, and venues requires rehabilitation professionals to build evidence by capturing successful strategies at the local level, finding innovative ways to translate successful practices to other communities, and ultimately to upgrade and maintain their applicability and currency for future scale-up. This article describes a knowledge-to-practice framework housed in a national resource and practice center that will support therapists and other rehabilitation professionals in building and maintaining a database of successful health/wellness guidelines, recommendations, and adaptations to promote community health inclusion for people with disabilities. A framework was developed in the National Center on Health, Physical Activity and Disability (NCHPAD) to systematically build and advance the evidence base of health/wellness programs, practices, and services applicable to people with disabilities. N-KATS (NCHPAD Knowledge Adaptation, Translation, and Scale-up) has 4 sequencing strategies: strategy 1-new evidence- and practice-based knowledge is collected and adapted for the local context (ie, community); strategy 2-customized resources are effectively disseminated to key stakeholders including rehabilitation professionals with appropriate training tools; strategy 3-NCHPAD staff serve as facilitators assisting key stakeholders in implementing recommendations; strategy 4-successful elements of practice (eg, guideline, recommendation, adaptation) are archived and scaled to other rehabilitation providers. The N-KATS framework supports the role of rehabilitation professionals as knowledge brokers, facilitators, and users in a collaborative, dynamic structure that will grow and be sustained over time through the NCHPAD.Video abstract available for additional insights from the authors (see Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A130).

DyNAvectors: dynamic constitutional vectors for adaptive DNA transfection.

PubMed

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.

A reinforcement learning model of joy, distress, hope and fear

NASA Astrophysics Data System (ADS)

Broekens, Joost; Jacobs, Elmer; Jonker, Catholijn M.

2015-07-01

In this paper we computationally study the relation between adaptive behaviour and emotion. Using the reinforcement learning framework, we propose that learned state utility, ?, models fear (negative) and hope (positive) based on the fact that both signals are about anticipation of loss or gain. Further, we propose that joy/distress is a signal similar to the error signal. We present agent-based simulation experiments that show that this model replicates psychological and behavioural dynamics of emotion. This work distinguishes itself by assessing the dynamics of emotion in an adaptive agent framework - coupling it to the literature on habituation, development, extinction and hope theory. Our results support the idea that the function of emotion is to provide a complex feedback signal for an organism to adapt its behaviour. Our work is relevant for understanding the relation between emotion and adaptation in animals, as well as for human-robot interaction, in particular how emotional signals can be used to communicate between adaptive agents and humans.

Adaptive Management: From More Talk to Real Action

NASA Astrophysics Data System (ADS)

Williams, Byron K.; Brown, Eleanor D.

2014-02-01

The challenges currently facing resource managers are large-scale and complex, and demand new approaches to balance development and conservation goals. One approach that shows considerable promise for addressing these challenges is adaptive management, which by now is broadly seen as a natural, intuitive, and potentially effective way to address decision-making in the face of uncertainties. Yet the concept of adaptive management continues to evolve, and its record of success remains limited. In this article, we present an operational framework for adaptive decision-making, and describe the challenges and opportunities in applying it to real-world problems. We discuss the key elements required for adaptive decision-making, and their integration into an iterative process that highlights and distinguishes technical and social learning. We illustrate the elements and processes of the framework with some successful on-the-ground examples of natural resource management. Finally, we address some of the difficulties in applying learning-based management, and finish with a discussion of future directions and strategic challenges.

Understanding adolescent type 1 diabetes self-management as an adaptive process: A grounded theory approach.

PubMed

Chilton, Roy; Pires-Yfantouda, Renata

2015-01-01

To develop a conceptual understanding of the process of adapting to the self-management of type 1 diabetes during adolescence. Participants were recruited from a National Health Service paediatric diabetes service within the south-west of England which runs six countywide diabetes clinics. Thirteen interviews were conducted using a social constructivist grounded theory approach. The findings illustrate how self-management can be understood in terms of a continuum-based framework, ranging from difficulties with, to successful self-management. Adaptation within the continuum can further be understood by specific transitional phases and process mechanisms, providing further depth to individuals' experiences of adaptation. This investigation provides a conceptual understanding of the complex issues adolescents encounter while adapting to and integrating a diabetes self-management regime into their lives. It provides an invaluable framework for exploring psychological mechanisms and contextualising them within a self-management continuum. Implications for healthcare professionals are discussed and further research proposes whether the model could be applicable to other chronic illnesses.

The power of simplicity: a fast-and-frugal heuristics approach to performance science.

PubMed

Raab, Markus; Gigerenzer, Gerd

2015-01-01

Performance science is a fairly new multidisciplinary field that integrates performance domains such as sports, medicine, business, and the arts. To give its many branches a structure and its research a direction, it requires a theoretical framework. We demonstrate the applications of this framework with examples from sport and medicine. Because performance science deals mainly with situations of uncertainty rather than known risks, the needed framework can be provided by the fast-and-frugal heuristics approach. According to this approach, experts learn to rely on heuristics in an adaptive way in order to make accurate decisions. We investigate the adaptive use of heuristics in three ways: the descriptive study of the heuristics in the cognitive "adaptive toolbox;" the prescriptive study of their "ecological rationality," that is, the characterization of the situations in which a given heuristic works; and the engineering study of "intuitive design," that is, the design of transparent aids for making better decisions.

The power of simplicity: a fast-and-frugal heuristics approach to performance science

PubMed Central

Raab, Markus; Gigerenzer, Gerd

2015-01-01

Performance science is a fairly new multidisciplinary field that integrates performance domains such as sports, medicine, business, and the arts. To give its many branches a structure and its research a direction, it requires a theoretical framework. We demonstrate the applications of this framework with examples from sport and medicine. Because performance science deals mainly with situations of uncertainty rather than known risks, the needed framework can be provided by the fast-and-frugal heuristics approach. According to this approach, experts learn to rely on heuristics in an adaptive way in order to make accurate decisions. We investigate the adaptive use of heuristics in three ways: the descriptive study of the heuristics in the cognitive “adaptive toolbox;” the prescriptive study of their “ecological rationality,” that is, the characterization of the situations in which a given heuristic works; and the engineering study of “intuitive design,” that is, the design of transparent aids for making better decisions. PMID:26579051

Filtering Based Adaptive Visual Odometry Sensor Framework Robust to Blurred Images

PubMed Central

Zhao, Haiying; Liu, Yong; Xie, Xiaojia; Liao, Yiyi; Liu, Xixi

2016-01-01

Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and present an adaptive visual odometry estimation framework robust to blurred images. Our approach employs an objective measure of images, named small image gradient distribution (SIGD), to evaluate the blurring degree of the image, then an adaptive blurred image classification algorithm is proposed to recognize the blurred images, finally we propose an anti-blurred key-frame selection algorithm to enable the VO robust to blurred images. We also carried out varied comparable experiments to evaluate the performance of the VO algorithms with our anti-blur framework under varied blurred images, and the experimental results show that our approach can achieve superior performance comparing to the state-of-the-art methods under the condition with blurred images while not increasing too much computation cost to the original VO algorithms. PMID:27399704

A model predictive speed tracking control approach for autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Zhu, Min; Chen, Huiyan; Xiong, Guangming

2017-03-01

This paper presents a novel speed tracking control approach based on a model predictive control (MPC) framework for autonomous ground vehicles. A switching algorithm without calibration is proposed to determine the drive or brake control. Combined with a simple inverse longitudinal vehicle model and adaptive regulation of MPC, this algorithm can make use of the engine brake torque for various driving conditions and avoid high frequency oscillations automatically. A simplified quadratic program (QP) solving algorithm is used to reduce the computational time, and the approach has been applied in a 16-bit microcontroller. The performance of the proposed approach is evaluated via simulations and vehicle tests, which were carried out in a range of speed-profile tracking tasks. With a well-designed system structure, high-precision speed control is achieved. The system can robustly model uncertainty and external disturbances, and yields a faster response with less overshoot than a PI controller.

A transactional framework for pediatric rehabilitation: shifting the focus to situated contexts, transactional processes, and adaptive developmental outcomes.

PubMed

King, Gillian; Imms, Christine; Stewart, Debra; Freeman, Matt; Nguyen, Tram

2018-07-01

A paradigm shift is taking place in pediatric rehabilitation research, practice, and policy - a shift towards the real-life contexts of clients rather than requiring clients to navigate the world of pediatric rehabilitation. This article proposes a conceptual framework to bring about a broader awareness of clients' lives and transactional processes of change over the life course. The framework draws attention to transactional processes by which individuals, situated in life contexts, change and adapt over the life course and, in turn, influence their contextual settings and broader environments. This framework is based on (a) basic tenets derived from foundational theories taking a life course perspective to change, and (b) transactional processes identified from relevant pediatric rehabilitation models that bring these foundational theories into the pediatric rehabilitation sphere. The framework identifies three types of transactional processes relevant to pediatric rehabilitation: facilitative, resiliency, and socialization processes. These processes describe how contexts and people mutually influence each other via opportunities and situated experiences, thus facilitating capacity, adaptation to adversity, and socialization to new roles and life transitions. The utility of the framework is considered for research, practice, service organizations, and policy. Implications for Rehabilitation The framework supports practitioners going beyond person and environment as separate entities, to provide services to the "situated person" in real-life contexts The framework shifts the focus from "body structures/functions" and "person in activity" to "person in changing and challenging life contexts" Working from a transactional perspective, practitioner-client conversations will change; practitioners will view client situations through a lens of opportunities and experiences, assess client experiences in real-life contexts, and strive to create context-based therapy opportunities The framework suggests the benefit of greater focus on resiliency processes to support client self-efficacy, self-determination, and autonomy, and socialization processes to enhance ability to enact new life roles at times of transition.

Molecular Retrofitting Adapts a Metal–Organic Framework to Extreme Pressure

DOE PAGES

Kapustin, Eugene A.; Lee, Seungkyu; Alshammari, Ahmad S.; ...

2017-06-07

Despite numerous studies on chemical and thermal stability of metal-organic frameworks (MOFs), mechanical stability remains largely undeveloped. No strategy exists to control the mechanical deformation of MOFs under ultrahigh pressure, to date. We show that the mechanically unstable MOF-520 can be retrofitted by precise placement of a rigid 4,4'-biphenyldicarboxylate (BPDC) linker as a "girder" to afford a mechanically robust framework: MOF-520-BPDC. This retrofitting alters how the structure deforms under ultrahigh pressure and thus leads to a drastic enhancement of its mechanical robustness. While in the parent MOF-520 the pressure transmitting medium molecules diffuse into the pore and expand the structuremore » from the inside upon compression, the girder in the new retrofitted MOF-520-BPDC prevents the framework from expansion by linking two adjacent secondary building units together. As a result, the modified MOF is stable under hydrostatic compression in a diamond-anvil cell up to 5.5 gigapascal. The increased mechanical stability of MOF-520-BPDC prohibits the typical amorphization observed for MOFs in this pressure range. Direct correlation between the orientation of these girders within the framework and its linear strain was estimated, providing new insights for the design of MOFs with optimized mechanical properties.« less

Adaptation strategies for health impacts of climate change in Western Australia: Application of a Health Impact Assessment framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spickett, Jeffery T., E-mail: J.Spickett@curtin.edu.a; Brown, Helen L., E-mail: h.brown@curtin.edu.a; Katscherian, Dianne, E-mail: Dianne.Katscherian@health.wa.gov.a

2011-04-15

Climate change is one of the greatest challenges facing the globe and there is substantial evidence that this will result in a number of health impacts, regardless of the level of greenhouse gas mitigation. It is therefore apparent that a combined approach of mitigation and adaptation will be required to protect public health. While the importance of mitigation is recognised, this project focused on the role of adaptation strategies in addressing the potential health impacts of climate change. The nature and magnitude of these health impacts will be determined by a number of parameters that are dependent upon the location.more » Firstly, climate change will vary between regions. Secondly, the characteristics of each region in terms of population and the ability to adapt to changes will greatly influence the extent of the health impacts that are experienced now and into the future. Effective adaptation measures therefore need to be developed with these differences in mind. A Health Impact Assessment (HIA) framework was used to consider the implications of climate change on the health of the population of Western Australia (WA) and to develop a range of adaptive responses suited to WA. A broad range of stakeholders participated in the HIA process, providing informed input into developing an understanding of the potential health impacts and potential adaptation strategies from a diverse sector perspective. Potential health impacts were identified in relation to climate change predictions in WA in the year 2030. The risk associated with each of these impacts was assessed using a qualitative process that considered the consequences and the likelihood of the health impact occurring. Adaptations were then developed which could be used to mitigate the identified health impacts and provide responses which could be used by Government for future decision making. The periodic application of a HIA framework is seen as an ideal tool to develop appropriate adaptation strategies to address the potential health impacts of climate change.« less

GRADE Evidence to Decision (EtD) frameworks for adoption, adaptation, and de novo development of trustworthy recommendations: GRADE-ADOLOPMENT.

PubMed

Schünemann, Holger J; Wiercioch, Wojtek; Brozek, Jan; Etxeandia-Ikobaltzeta, Itziar; Mustafa, Reem A; Manja, Veena; Brignardello-Petersen, Romina; Neumann, Ignacio; Falavigna, Maicon; Alhazzani, Waleed; Santesso, Nancy; Zhang, Yuan; Meerpohl, Jörg J; Morgan, Rebecca L; Rochwerg, Bram; Darzi, Andrea; Rojas, Maria Ximenas; Carrasco-Labra, Alonso; Adi, Yaser; AlRayees, Zulfa; Riva, John; Bollig, Claudia; Moore, Ainsley; Yepes-Nuñez, Juan José; Cuello, Carlos; Waziry, Reem; Akl, Elie A

2017-01-01

Guideline developers can: (1) adopt existing recommendations from others; (2) adapt existing recommendations to their own context; or (3) create recommendations de novo. Monetary and nonmonetary resources, credibility, maximization of uptake, as well as logical arguments should guide the choice of the approach and processes. To describe a potentially efficient model for guideline production based on adoption, adaptation, and/or de novo development of recommendations utilizing the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Evidence to Decision (EtD) frameworks. We applied the model in a new national guideline program producing 22 practice guidelines. We searched for relevant evidence that informs the direction and strength of a recommendation. We then produced GRADE EtDs for guideline panels to develop recommendations. We produced a total of 80 EtD frameworks in approximately 4 months and 146 EtDs in approximately 6 months in two waves. Use of the EtD frameworks allowed panel members understand judgments of others about the criteria that bear on guideline recommendations and then make their own judgments about those criteria in a systematic approach. The "GRADE-ADOLOPMENT" approach to guideline production combines adoption, adaptation, and, as needed, de novo development of recommendations. If developers of guidelines follow EtD criteria more widely and make their work publically available, this approach should prove even more useful. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

An Advanced Pharmacy Practice Framework for Australia

PubMed Central

Jackson, Shane; Martin, Grant; Bergin, Jennifer; Clark, Bronwyn; Stupans, Ieva; Yeates, Gilbert; Nissen, Lisa; Marty, Stephen; Gysslink, Paul; Matthews, Andrew; Kirsa, Sue; Deans, Kerry; Sorimachi, Kay

2015-01-01

The need to develop An Advanced Pharmacy Practice Framework for Australia (the “APPF”) was identified during the 2010 review of the competency standards for Australian pharmacists. The Advanced Pharmacy Practice Framework Steering Committee, a collaborative profession-wide committee comprised of representatives of ten pharmacy organisations, examined and adapted existing advanced practice frameworks, all of which were found to have been based on the Competency Development and Evaluation Group (CoDEG) Advanced and Consultant Level Framework (the “CoDEG Framework”) from the United Kingdom. Its competency standards were also found to align well with the Domains of the National Competency Standards Framework for Pharmacists in Australia (the “National Framework”). Adaptation of the CoDEG Framework created an APPF that is complementary to the National Framework, sufficiently flexible to customise for recognising advanced practice in any area of professional practice and has been approved by the boards/councils of all participating organisations. The primary purpose of the APPF is to assist the development of the profession to meet the changing health care needs of the community. However, it is also a valuable tool for assuring members of the public of the competence of an advanced practice pharmacist and the quality and safety of the services they deliver. PMID:28975900

DRUG EVALUATION AND DECISION MAKING IN CATALONIA: DEVELOPMENT AND VALIDATION OF A METHODOLOGICAL FRAMEWORK BASED ON MULTI-CRITERIA DECISION ANALYSIS (MCDA) FOR ORPHAN DRUGS.

PubMed

Gilabert-Perramon, Antoni; Torrent-Farnell, Josep; Catalan, Arancha; Prat, Alba; Fontanet, Manel; Puig-Peiró, Ruth; Merino-Montero, Sandra; Khoury, Hanane; Goetghebeur, Mireille M; Badia, Xavier

2017-01-01

The aim of this study was to adapt and assess the value of a Multi-Criteria Decision Analysis (MCDA) framework (EVIDEM) for the evaluation of Orphan drugs in Catalonia (Catalan Health Service). The standard evaluation and decision-making procedures of CatSalut were compared with the EVIDEM methodology and contents. The EVIDEM framework was adapted to the Catalan context, focusing on the evaluation of Orphan drugs (PASFTAC program), during a Workshop with sixteen PASFTAC members. The criteria weighting was done using two different techniques (nonhierarchical and hierarchical). Reliability was assessed by re-test. The EVIDEM framework and methodology was found useful and feasible for Orphan drugs evaluation and decision making in Catalonia. All the criteria considered for the development of the CatSalut Technical Reports and decision making were considered in the framework. Nevertheless, the framework could improve the reporting of some of these criteria (i.e., "unmet needs" or "nonmedical costs"). Some Contextual criteria were removed (i.e., "Mandate and scope of healthcare system", "Environmental impact") or adapted ("population priorities and access") for CatSalut purposes. Independently of the weighting technique considered, the most important evaluation criteria identified for orphan drugs were: "disease severity", "unmet needs" and "comparative effectiveness", while the "size of the population" had the lowest relevance for decision making. Test-retest analysis showed weight consistency among techniques, supporting reliability overtime. MCDA (EVIDEM framework) could be a useful tool to complement the current evaluation methods of CatSalut, contributing to standardization and pragmatism, providing a method to tackle ethical dilemmas and facilitating discussions related to decision making.

Dual-phase evolution in complex adaptive systems

PubMed Central

Paperin, Greg; Green, David G.; Sadedin, Suzanne

2011-01-01

Understanding the origins of complexity is a key challenge in many sciences. Although networks are known to underlie most systems, showing how they contribute to well-known phenomena remains an issue. Here, we show that recurrent phase transitions in network connectivity underlie emergent phenomena in many systems. We identify properties that are typical of systems in different connectivity phases, as well as characteristics commonly associated with the phase transitions. We synthesize these common features into a common framework, which we term dual-phase evolution (DPE). Using this framework, we review the literature from several disciplines to show that recurrent connectivity phase transitions underlie the complex properties of many biological, physical and human systems. We argue that the DPE framework helps to explain many complex phenomena, including perpetual novelty, modularity, scale-free networks and criticality. Our review concludes with a discussion of the way DPE relates to other frameworks, in particular, self-organized criticality and the adaptive cycle. PMID:21247947

Dual-phase evolution in complex adaptive systems.

PubMed

Paperin, Greg; Green, David G; Sadedin, Suzanne

2011-05-06

Understanding the origins of complexity is a key challenge in many sciences. Although networks are known to underlie most systems, showing how they contribute to well-known phenomena remains an issue. Here, we show that recurrent phase transitions in network connectivity underlie emergent phenomena in many systems. We identify properties that are typical of systems in different connectivity phases, as well as characteristics commonly associated with the phase transitions. We synthesize these common features into a common framework, which we term dual-phase evolution (DPE). Using this framework, we review the literature from several disciplines to show that recurrent connectivity phase transitions underlie the complex properties of many biological, physical and human systems. We argue that the DPE framework helps to explain many complex phenomena, including perpetual novelty, modularity, scale-free networks and criticality. Our review concludes with a discussion of the way DPE relates to other frameworks, in particular, self-organized criticality and the adaptive cycle.

KRISTINA: Kinematic rib-based structural system for innovative adaptive trailing edge

NASA Astrophysics Data System (ADS)

Pecora, R.; Amoroso, F.; Magnifico, M.; Dimino, I.; Concilio, A.

2016-04-01

Nature teaches that the flight of the birds succeeds perfectly since they are able to change the shape of their wings in a continuous manner. The careful observation of this phenomenon has re-introduced in the recent research topics the study of "metamorphic" wing structures; these innovative architectures allow for the controlled wing shape adaptation to different flight conditions with the ultimate goal of getting desirable improvements such as the increase of aerodynamic efficiency or load control effectiveness. In this framework, the European research project SARISTU aimed at combining morphing and smart ideas to the leading edge, the trailing edge and the winglet of a large commercial airplane (EASA CS25 category) while assessing integrated technologies validation through high-speed wind tunnel test on a true scale outer wing segment. The design process of the adaptive trailing edge (ATED) addressed by SARISTU is here outlined, from the conceptual definition of the camber-morphing architecture up to the assessment of the device executive layout. Rational design criteria were implemented in order to preliminarily define ATED structural layout and the general configuration of the embedded mechanisms enabling morphing under the action of aerodynamic loads. Advanced FE analyses were then carried out and the robustness of adopted structural arrangements was proven in compliance with applicable airworthiness requirements.

Instrument Remote Control via the Astronomical Instrument Markup Language

NASA Technical Reports Server (NTRS)

Sall, Ken; Ames, Troy; Warsaw, Craig; Koons, Lisa; Shafer, Richard

1998-01-01

The Instrument Remote Control (IRC) project ongoing at NASA's Goddard Space Flight Center's (GSFC) Information Systems Center (ISC) supports NASA's mission by defining an adaptive intranet-based framework that provides robust interactive and distributed control and monitoring of remote instruments. An astronomical IRC architecture that combines the platform-independent processing capabilities of Java with the power of Extensible Markup Language (XML) to express hierarchical data in an equally platform-independent, as well as human readable manner, has been developed. This architecture is implemented using a variety of XML support tools and Application Programming Interfaces (API) written in Java. IRC will enable trusted astronomers from around the world to easily access infrared instruments (e.g., telescopes, cameras, and spectrometers) located in remote, inhospitable environments, such as the South Pole, a high Chilean mountaintop, or an airborne observatory aboard a Boeing 747. Using IRC's frameworks, an astronomer or other scientist can easily define the type of onboard instrument, control the instrument remotely, and return monitoring data all through the intranet. The Astronomical Instrument Markup Language (AIML) is the first implementation of the more general Instrument Markup Language (IML). The key aspects of our approach to instrument description and control applies to many domains, from medical instruments to machine assembly lines. The concepts behind AIML apply equally well to the description and control of instruments in general. IRC enables us to apply our techniques to several instruments, preferably from different observatories.

Application and Adaptation of an Institutional Learning Framework

ERIC Educational Resources Information Center

Foutz, Susan; Emmons, Claire Thoma

2017-01-01

The Children's Museum of Indianapolis has used a mission-aligned learning framework for more than a decade. Designed to foster and support adult-child interaction in exhibitions and programs, the central tool of the family learning framework is the Assessment of Learning Families in Exhibits (ALFIE) Inventory. ALFIE is used as a tool to plan for…

A Conceptual Framework for Exploring the Role of Studies Abroad in Nurturing Global Citizenship

ERIC Educational Resources Information Center

Tarrant, Michael Andrew

2010-01-01

A conceptual framework, adapted from the Value-Belief-Norm theory, is proposed for understanding the role of studying abroad in nurturing global citizenship. The framework is oriented in concepts of justice, the environment, and civic obligations as key issues in the predictive validity of values, beliefs, and norms. The VBN approach is then…

PELEC

DOE Office of Scientific and Technical Information (OSTI.GOV)

2017-05-17

PeleC is an adaptive-mesh compressible hydrodynamics code for reacting flows. It solves the compressible Navier-Stokes with multispecies transport in a block structured framework. The resulting algorithm is well suited for flows with localized resolution requirements and robust to discontinuities. User controllable refinement crieteria has the potential to result in extremely small numerical dissipation and dispersion, making this code appropriate for both research and applied usage. The code is built on the AMReX library which facilitates hierarchical parallelism and manages distributed memory parallism. PeleC algorithms are implemented to express shared memory parallelism.

4-D COMMON OPERATIONAL PICTURE (COP) FOR MISSION ASSURANCE (4D COP) Task Order 0001: Air Force Research Laboratory (AFRL) Autonomy Collaboration in Intelligence, Surveillance, and Reconnaissance (ISR), Electronic Warfare (EW)/Cyber and Combat Identification (CID)

DTIC Science & Technology

2016-10-27

Domain C2, Adaptive Domain Control, Global Integrated ISR, Rapid Global Mobility , and Global Precision Strike, orgnanized within a framework of...mission needs. (Among the dozen implications) A more transparent, networked infrastructure that integrates ubiquitous sensors, automated systems...Conclusion 5.1 Common Technical Trajectory One of the most significant opportunities for AFRL is to develop and mobilize the qualitative roadmap

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

NASA Technical Reports Server (NTRS)

Jedlovec, Gary; Srikishen, Jayanthi; Edwards, Rita; Cross, David; Welch, Jon; Smith, Matt

2013-01-01

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of "big data" available from new high resolution remote sensing satellite sensors or four-dimensional numerical model simulations is propelling the wider adoption of ultra-resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well-integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Shortterm Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display-to-dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data-intensive information. This information can be digital-cinema animations, high-resolution images, high-definition video-teleconferences, presentation slides, documents, spreadsheets or laptop screens. SAGE is cross-platform, community-driven, open-source visualization and collaboration middleware that utilizes shared national and international cyberinfrastructure for the advancement of scientific research and education.

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

NASA Astrophysics Data System (ADS)

Jedlovec, G.; Srikishen, J.; Edwards, R.; Cross, D.; Welch, J. D.; Smith, M. R.

2013-12-01

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of 'big data' available from new high resolution remote sensing satellite sensors or four-dimensional numerical model simulations is propelling the wider adoption of ultra-resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well-integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Short-term Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display-to-dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data-intensive information. This information can be digital-cinema animations, high-resolution images, high-definition video-teleconferences, presentation slides, documents, spreadsheets or laptop screens. SAGE is cross-platform, community-driven, open-source visualization and collaboration middleware that utilizes shared national and international cyberinfrastructure for the advancement of scientific research and education.

Adaptive management of watersheds and related resources

USGS Publications Warehouse

Williams, Byron K.

2009-01-01

The concept of learning about natural resources through the practice of management has been around for several decades and by now is associated with the term adaptive management. The objectives of this paper are to offer a framework for adaptive management that includes an operational definition, a description of conditions in which it can be usefully applied, and a systematic approach to its application. Adaptive decisionmaking is described as iterative, learning-based management in two phases, each with its own mechanisms for feedback and adaptation. The linkages between traditional experimental science and adaptive management are discussed.

Wavelet domain image restoration with adaptive edge-preserving regularization.

PubMed

Belge, M; Kilmer, M E; Miller, E L

2000-01-01

In this paper, we consider a wavelet based edge-preserving regularization scheme for use in linear image restoration problems. Our efforts build on a collection of mathematical results indicating that wavelets are especially useful for representing functions that contain discontinuities (i.e., edges in two dimensions or jumps in one dimension). We interpret the resulting theory in a statistical signal processing framework and obtain a highly flexible framework for adapting the degree of regularization to the local structure of the underlying image. In particular, we are able to adapt quite easily to scale-varying and orientation-varying features in the image while simultaneously retaining the edge preservation properties of the regularizer. We demonstrate a half-quadratic algorithm for obtaining the restorations from observed data.

Reinforcement learning for a biped robot based on a CPG-actor-critic method.

PubMed

Nakamura, Yutaka; Mori, Takeshi; Sato, Masa-aki; Ishii, Shin

2007-08-01

Animals' rhythmic movements, such as locomotion, are considered to be controlled by neural circuits called central pattern generators (CPGs), which generate oscillatory signals. Motivated by this biological mechanism, studies have been conducted on the rhythmic movements controlled by CPG. As an autonomous learning framework for a CPG controller, we propose in this article a reinforcement learning method we call the "CPG-actor-critic" method. This method introduces a new architecture to the actor, and its training is roughly based on a stochastic policy gradient algorithm presented recently. We apply this method to an automatic acquisition problem of control for a biped robot. Computer simulations show that training of the CPG can be successfully performed by our method, thus allowing the biped robot to not only walk stably but also adapt to environmental changes.

Control of Next Generation Aircraft and Wind Turbines

NASA Technical Reports Server (NTRS)

Frost, Susan

2010-01-01

The first part of this talk will describe some of the exciting new next generation aircraft that NASA is proposing for the future. These aircraft are being designed to reduce aircraft fuel consumption and environmental impact. Reducing the aircraft weight is one approach that will be used to achieve these goals. A new control framework will be presented that enables lighter, more flexible aircraft to maintain aircraft handling qualities, while preventing the aircraft from exceeding structural load limits. The second part of the talk will give an overview of utility-scale wind turbines and their control. Results of collaboration with Dr. Balas will be presented, including new theory to adaptively control the turbine in the presence of structural modes, with the focus on the application of this theory to a high-fidelity simulation of a wind turbine.