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Sample records for adaptive decision feedback

  1. Oscillatory profiles of positive, negative and neutral feedback stimuli during adaptive decision making.

    PubMed

    Li, Peng; Baker, Travis E; Warren, Chris; Li, Hong

    2016-09-01

    The electrophysiological response to positive and negative feedback during reinforcement learning has been well documented over the past two decades, yet, little is known about the neural response to uninformative events that often follow our actions. To address this issue, we recorded the electroencephalograph (EEG) during a time-estimation task using both informative (positive and negative) and uninformative (neutral) feedback. In the time-frequency domain, uninformative feedback elicited significantly less induced beta-gamma activity than informative feedback. This result suggests that beta-gamma activity is particularly sensitive to feedback that can guide behavioral adjustments, consistent with other work. In contrast, neither theta nor delta activity were sensitive to the difference between negative and neutral feedback, though both frequencies discriminated between positive, and non-positive (neutral or negative) feedback. Interestingly, in the time domain, we observed a linear relationship in the amplitude of the feedback-related negativity (neutral>negative>positive), a component of the event-related brain potential thought to index a specific kind of reinforcement learning signal called a reward prediction error. Taken together, these results suggest that the reinforcement learning system treats neutral feedback as a special case, providing valuable information about the electrophysiological measures used to index the cognitive function of frontal midline cortex. PMID:27378537

  2. Oscillatory profiles of positive, negative and neutral feedback stimuli during adaptive decision making.

    PubMed

    Li, Peng; Baker, Travis E; Warren, Chris; Li, Hong

    2016-09-01

    The electrophysiological response to positive and negative feedback during reinforcement learning has been well documented over the past two decades, yet, little is known about the neural response to uninformative events that often follow our actions. To address this issue, we recorded the electroencephalograph (EEG) during a time-estimation task using both informative (positive and negative) and uninformative (neutral) feedback. In the time-frequency domain, uninformative feedback elicited significantly less induced beta-gamma activity than informative feedback. This result suggests that beta-gamma activity is particularly sensitive to feedback that can guide behavioral adjustments, consistent with other work. In contrast, neither theta nor delta activity were sensitive to the difference between negative and neutral feedback, though both frequencies discriminated between positive, and non-positive (neutral or negative) feedback. Interestingly, in the time domain, we observed a linear relationship in the amplitude of the feedback-related negativity (neutral>negative>positive), a component of the event-related brain potential thought to index a specific kind of reinforcement learning signal called a reward prediction error. Taken together, these results suggest that the reinforcement learning system treats neutral feedback as a special case, providing valuable information about the electrophysiological measures used to index the cognitive function of frontal midline cortex.

  3. Effects of invalid feedback on learning and feedback-related brain activity in decision-making.

    PubMed

    Ernst, Benjamin; Steinhauser, Marco

    2015-10-01

    For adaptive decision-making it is important to utilize only relevant, valid and to ignore irrelevant feedback. The present study investigated how feedback processing in decision-making is impaired when relevant feedback is combined with irrelevant and potentially invalid feedback. We analyzed two electrophysiological markers of feedback processing, the feedback-related negativity (FRN) and the P300, in a simple decision-making task, in which participants processed feedback stimuli consisting of relevant and irrelevant feedback provided by the color and meaning of a Stroop stimulus. We found that invalid, irrelevant feedback not only impaired learning, it also altered the amplitude of the P300 to relevant feedback, suggesting an interfering effect of irrelevant feedback on the processing of relevant feedback. In contrast, no such effect on the FRN was obtained. These results indicate that detrimental effects of invalid, irrelevant feedback result from failures of controlled feedback processing. PMID:26263382

  4. Adaptation to delayed auditory feedback

    NASA Technical Reports Server (NTRS)

    Katz, D. I.; Lackner, J. R.

    1977-01-01

    Delayed auditory feedback disrupts the production of speech, causing an increase in speech duration as well as many articulatory errors. To determine whether prolonged exposure to delayed auditory feedback (DAF) leads to adaptive compensations in speech production, 10 subjects were exposed in separate experimental sessions to both incremental and constant-delay exposure conditions. Significant adaptation occurred for syntactically structured stimuli in the form of increased speaking rates. After DAF was removed, aftereffects were apparent for all stimulus types in terms of increased speech rates. A carry-over effect from the first to the second experimental session was evident as long as 29 days after the first session. The use of strategies to overcome DAF and the differences between adaptation to DAF and adaptation to visual rearrangement are discussed.

  5. Feedback Blunting: Total Sleep Deprivation Impairs Decision Making that Requires Updating Based on Feedback

    PubMed Central

    Whitney, Paul; Hinson, John M.; Jackson, Melinda L.; Van Dongen, Hans P.A.

    2015-01-01

    Study Objectives: To better understand the sometimes catastrophic effects of sleep loss on naturalistic decision making, we investigated effects of sleep deprivation on decision making in a reversal learning paradigm requiring acquisition and updating of information based on outcome feedback. Design: Subjects were randomized to a sleep deprivation or control condition, with performance testing at baseline, after 2 nights of total sleep deprivation (or rested control), and following 2 nights of recovery sleep. Subjects performed a decision task involving initial learning of go and no go response sets followed by unannounced reversal of contingencies, requiring use of outcome feedback for decisions. A working memory scanning task and psychomotor vigilance test were also administered. Setting: Six consecutive days and nights in a controlled laboratory environment with continuous behavioral monitoring. Subjects: Twenty-six subjects (22–40 y of age; 10 women). Interventions: Thirteen subjects were randomized to a 62-h total sleep deprivation condition; the others were controls. Results: Unlike controls, sleep deprived subjects had difficulty with initial learning of go and no go stimuli sets and had profound impairment adapting to reversal. Skin conductance responses to outcome feedback were diminished, indicating blunted affective reactions to feedback accompanying sleep deprivation. Working memory scanning performance was not significantly affected by sleep deprivation. And although sleep deprived subjects showed expected attentional lapses, these could not account for impairments in reversal learning decision making. Conclusions: Sleep deprivation is particularly problematic for decision making involving uncertainty and unexpected change. Blunted reactions to feedback while sleep deprived underlie failures to adapt to uncertainty and changing contingencies. Thus, an error may register, but with diminished effect because of reduced affective valence of the feedback

  6. Factors Influencing Spanish Instructors' In-Class Feedback Decisions

    ERIC Educational Resources Information Center

    Gurzynski-Weiss, Laura

    2016-01-01

    While oral corrective feedback is a principal focus in second language acquisition research, most studies examine feedback once it has been provided. Investigating how instructors make in-class feedback decisions has not been thoroughly explored, despite the fact that classroom feedback occurs at the discretion of the individual language…

  7. Adaptive output feedback control of flexible systems

    NASA Astrophysics Data System (ADS)

    Yang, Bong-Jun

    Neural network-based adaptive output feedback approaches that augment a linear control design are described in this thesis, and emphasis is placed on their real-time implementation with flexible systems. Two different control architectures that are robust to parametric uncertainties and unmodelled dynamics are presented. The unmodelled effects can consist of minimum phase internal dynamics of the system together with external disturbance process. Within this context, adaptive compensation for external disturbances is addressed. In the first approach, internal model-following control, adaptive elements are designed using feedback inversion. The effect of an actuator limit is treated using control hedging, and the effect of other actuation nonlinearities, such as dead zone and backlash, is mitigated by a disturbance observer-based control design. The effectiveness of the approach is illustrated through simulation and experimental testing with a three-disk torsional system, which is subjected to control voltage limit and stiction. While the internal model-following control is limited to minimum phase systems, the second approach, external model-following control, does not involve feedback linearization and can be applied to non-minimum phase systems. The unstable zero dynamics are assumed to have been modelled in the design of the existing linear controller. The laboratory tests for this method include a three-disk torsional pendulum, an inverted pendulum, and a flexible-base robot manipulator. The external model-following control architecture is further extended in three ways. The first extension is an approach for control of multivariable nonlinear systems. The second extension is a decentralized adaptive control approach for large-scale interconnected systems. The third extension is to make use of an adaptive observer to augment a linear observer-based controller. In this extension, augmenting terms for the adaptive observer can be used to achieve adaptation in

  8. Feedback May Harm: Role of Feedback in Probabilistic Decision Making of Adolescents with ADHD.

    PubMed

    Pollak, Yehuda; Shoham, Rachel

    2015-10-01

    Inept probabilistic decision making is commonly associated with ADHD. In experimental designs aimed to model probabilistic decision making in ADHD, feedback following each choice was, in the majority of studies, part of the paradigm. This study examined whether feedback processing plays a role in the maladaptive choice behavior of subjects with ADHD by comparing feedback and no-feedback conditions. Sixty adolescents (49 males), ages 13-18, with and without ADHD, performed a descriptive probabilistic choice task in which outcomes and probabilities were explicitly provided. Subjects performed the task either with or without feedback. Under the no-feedback condition, adolescents with ADHD and controls performed similarly, whereas under the feedback condition, subjects with ADHD chose the unfavorable outcomes more frequently and risked smaller sums than controls. These finding demonstrate the crucial role of feedback in the decision making of adolescents with ADHD.

  9. Decision-making triggers in adaptive management.

    PubMed

    Nie, Martin A; Schultz, Courtney A

    2012-12-01

    We analyzed whether decision-making triggers increase accountability of adaptive-management plans. Triggers are prenegotiated commitments in an adaptive-management plan that specify what actions are to be taken and when on the basis of information obtained from monitoring. Triggers improve certainty that particular actions will be taken by agencies in the future. We conducted an in-depth, qualitative review of the political and legal contexts of adaptive management and its application by U.S. federal agencies. Agencies must satisfy the judiciary that adaptive-management plans meet substantive legal standards and comply with the U.S. National Environmental Policy Act. We examined 3 cases in which triggers were used in adaptive-management plans: salmon (Oncorhynchus spp.) in the Columbia River, oil and gas development by the Bureau of Land Management, and a habitat conservation plan under the U.S. Endangered Species Act. In all the cases, key aspects of adaptive management, including controls and preidentified feedback loops, were not incorporated in the plans. Monitoring and triggered mitigation actions were limited in their enforceability, which was contingent on several factors, including which laws applied in each case and the degree of specificity in how triggers were written into plans. Other controversial aspects of these plans revolved around who designed, conducted, interpreted, and funded monitoring programs. Additional contentious issues were the level of precaution associated with trigger mechanisms and the definition of ecological baselines used as points of comparison. Despite these challenges, triggers can be used to increase accountability, by predefining points at which an adaptive management plan will be revisited and reevaluated, and thus improve the application of adaptive management in its complicated political and legal context. PMID:22891956

  10. Adapting Progress Feedback and Emotional Support to Learner Personality

    ERIC Educational Resources Information Center

    Dennis, Matt; Masthoff, Judith; Mellish, Chris

    2016-01-01

    As feedback is an important part of learning and motivation, we investigate how to adapt the feedback of a conversational agent to learner personality (as well as to learner performance, as we expect an interaction effect between personality and performance on feedback). We investigate two aspects of feedback. Firstly, we investigate whether the…

  11. Adaptive method with intercessory feedback control for an intelligent agent

    DOEpatents

    Goldsmith, Steven Y.

    2004-06-22

    An adaptive architecture method with feedback control for an intelligent agent provides for adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. An adaptive architecture method with feedback control for multiple intelligent agents provides for coordinating and adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. Re-programming of the adaptive architecture is through a nexus which coordinates reflexive and deliberator components.

  12. Constrained adaptation for feedback cancellation in hearing aids.

    PubMed

    Kates, J M

    1999-08-01

    In feedback cancellation in hearing aids, an adaptive filter is used to model the feedback path. The output of the adaptive filter is subtracted from the microphone signal to cancel the acoustic and mechanical feedback picked up by the microphone, thus allowing more gain in the hearing aid. In general, the feedback-cancellation filter adapts on the hearing-aid input signal, and signal cancellation and coloration artifacts can occur for a narrow-band input. In this paper, two procedures for LMS adaptation with a constraint on the magnitude of the adaptive weight vector are derived. The constraints greatly reduce the probability that the adaptive filter will cancel a narrow-band input. Simulation results are used to demonstrate the efficacy of the constrained adaptation. PMID:10462806

  13. Engaging Students with Feedback through Adaptive Release

    ERIC Educational Resources Information Center

    Irwin, Brian; Hepplestone, Stuart; Holden, Graham; Parkin, Helen J.; Thorpe, Louise

    2013-01-01

    Feedback to students has been highlighted in the literature as an area where improvements are needed. Students need high quality, prompt feedback, but they also need guidance and tools to help them engage with and learn from that feedback. This case study explores staff and student perceptions of a tool at Sheffield Hallam University which…

  14. Adaptive feedback cancellation in hearing aids with clipping in the feedback path.

    PubMed

    Freed, Daniel J

    2008-03-01

    Adaptive linear filtering algorithms are commonly used to cancel feedback in hearing aids. The use of these algorithms is based on the assumption that the feedback path is linear, so nonlinearities in the feedback path may affect performance. This study investigated the effect on feedback canceller performance of clipping of the feedback signal arriving at the microphone, as well as the benefit of applying identical clipping to the cancellation signal so that the cancellation path modeled the nonlinearity of the feedback path. Feedback signal clipping limited the amount of added stable gain that the feedback canceller could provide, and caused misadjustment in response to high-level inputs, by biasing adaptive filter coefficients toward lower magnitudes. Cancellation signal clipping mitigated these negative effects, permitting higher amounts of added stable gain and less misadjustment in response to high-level inputs, but the benefit was reduced in the presence of the highest-level inputs. PMID:18345849

  15. Physical modeling of the feedback path in hearing aids with application to adaptive feedback cancellation

    NASA Astrophysics Data System (ADS)

    Hayes, Joanna L.; Rafaely, Boaz

    2002-05-01

    Hearing aid system modeling based on two-port network theory has been used previously to study the forward gain and the feedback path in hearing aids. The two-port modeling approach is employed in this work to develop an analytic model of the feedback path by reducing the model matrices to simplified analytic expressions. Such an analytic model can simulate the frequency response of the feedback path given the values of relatively few physical parameters such as vent dimensions. The model was extended to include variability in the feedback path due to slit leaks, for example. The analytic model was then incorporated in an adaptive feedback cancellation system, where the physical parameters of the model were adapted to match the actual feedback path and cancel the feedback signal. In the initial stage of this study, the ability of the model to match the frequency response of various measured feedback paths was studied using numerical optimization. Then, an adaptive filtering configuration based on the physical model was developed and studied using computer simulations. Results show that this new approach to adaptive feedback cancellation has the potential to improve both adaptation speed and performance robustness.

  16. Offset quadrature communications with decision-feedback carrier synchronization

    NASA Technical Reports Server (NTRS)

    Simon, M. K.; Smith, J. G.

    1974-01-01

    In order to accommodate a quadrature amplitude-shift-keyed (QASK) signal, Simon and Smith (1974) have modified the decision-feedback loop which tracks a quadrature phase-shift-keyed (QPSK). In the investigation reported approaches are considered to modify the loops in such a way that offset QASK signals can be tracked, giving attention to the special case of an offset QPSK. The development of the stochastic integro-differential equation of operation for a decision-feedback offset QASK loop is discussed along with the probability density function of the phase error process.

  17. An adaptive phase alignment algorithm for cartesian feedback loops

    NASA Astrophysics Data System (ADS)

    Gimeno-Martin, A.; Pardo-Martin, J.; Ortega-Gonzalez, F.

    2010-01-01

    An adaptive algorithm to correct phase misalignments in Cartesian feedback linearization loops for power amplifiers has been presented. It yields an error smaller than 0.035 rad between forward and feedback loop signals once convergence is reached. Because this algorithm enables a feedback system to process forward and feedback samples belonging to almost the same algorithm iteration, it is suitable to improve the performance not only of power amplifiers but also any other digital feedback system for communications systems and circuits such as all digital phase locked loops. Synchronizing forward and feedback paths of Cartesian feedback loops takes a small period of time after the system starts up. The phase alignment algorithm needs to converge before the feedback Cartesian loop can start its ideal behavior. However, once the steady state is reached, both paths can be considered synchronized, and the Cartesian feedback loop will only depend on the loop parameters (open-loop gain, loop bandwidth, etc.). It means that the linearization process will also depend only on these parameters since the misalignment effect disappears. Therefore, this algorithm relieves the power amplifier linearizer circuit design of any task required for solving phase misalignment effects inherent to Cartesian feedback systems. Furthermore, when a feedback Cartesian loop has to be designed, the designer can consider that forward and feedback paths are synchronized, since the phase alignment algorithm will do this task. This will reduce the simulation complexity. Then, all efforts are applied to determining the suitable loop parameters that will make the linearization process more efficient.

  18. Feedback in Videogame-Based Adaptive Training

    ERIC Educational Resources Information Center

    Rivera, Iris Daliz

    2010-01-01

    The field of training has been changing rapidly due to advances in technology such as videogame-based adaptive training. Videogame-based adaptive training has provided flexibility and adaptability for training in cost-effective ways. Although this method of training may have many benefits for the trainee, current research has not kept up to pace…

  19. Training Adaptive Decision-Making.

    SciTech Connect

    Abbott, Robert G.; Forsythe, James C.

    2014-10-01

    Adaptive Thinking has been defined here as the capacity to recognize when a course of action that may have previously been effective is no longer effective and there is need to adjust strategy. Research was undertaken with human test subjects to identify the factors that contribute to adaptive thinking. It was discovered that those most effective in settings that call for adaptive thinking tend to possess a superior capacity to quickly and effectively generate possible courses of action, as measured using the Category Generation test. Software developed for this research has been applied to develop capabilities enabling analysts to identify crucial factors that are predictive of outcomes in fore-on-force simulation exercises.

  20. Decision-level adaptation in motion perception

    PubMed Central

    2015-01-01

    Prolonged exposure to visual stimuli causes a bias in observers' responses to subsequent stimuli. Such adaptation-induced biases are usually explained in terms of changes in the relative activity of sensory neurons in the visual system which respond selectively to the properties of visual stimuli. However, the bias could also be due to a shift in the observer's criterion for selecting one response rather than the alternative; adaptation at the decision level of processing rather than the sensory level. We investigated whether adaptation to implied motion is best attributed to sensory-level or decision-level bias. Three experiments sought to isolate decision factors by changing the nature of the participants' task while keeping the sensory stimulus unchanged. Results showed that adaptation-induced bias in reported stimulus direction only occurred when the participants' task involved a directional judgement, and disappeared when adaptation was measured using a non-directional task (reporting where motion was present in the display, regardless of its direction). We conclude that adaptation to implied motion is due to decision-level bias, and that a propensity towards such biases may be widespread in sensory decision-making. PMID:27019726

  1. Differential representation of feedback and decision in adolescents and adults

    PubMed Central

    Javadi, Amir Homayoun; Schmidt, Dirk H.K.; Smolka, Michael N.

    2014-01-01

    It is widely accepted that brain maturation from adolescence to adulthood contributes to substantial behavioural changes. Despite this, however, knowledge of the precise mechanisms is still sparse. We used fMRI to investigate developmental differences between healthy adolescents (age range 14–15) and adults (age range 20–39) in feedback-related decision making using a probabilistic reversal learning task. Conventionally groups are compared based on continuous values of blood oxygen level dependent (BOLD) percentage signal change. In contrast, we transformed these values into discrete states and used the pattern of these states to compare groups. We focused our analysis on anterior cingulate cortex (ACC), ventral striatum (VS) and ventromedial prefrontal cortex (vmPFC) as their functions have been shown to be critical in feedback related decision making. Discretisation of continuous BOLD values revealed differential patterns of activity as compared to conventional statistical methods. Results showed differential representation of feedback and decision in ACC and vmPFC between adolescents and adults but no difference in VS. We argue that the pattern of activity of ACC, vmPFC and VS in adolescents resulted in several drawbacks in decision making such as redundant and imprecise representation of decision and subsequently poorer performance in terms of the number of system changes (change of contingencies). This method can be effectively used to infer group differences from within-group analysis rather than studying the differences by direct between-group comparisons. PMID:24513024

  2. Bayesian Decision Support for Adaptive Lung Treatments

    NASA Astrophysics Data System (ADS)

    McShan, Daniel; Luo, Yi; Schipper, Matt; TenHaken, Randall

    2014-03-01

    Purpose: A Bayesian Decision Network will be demonstrated to provide clinical decision support for adaptive lung response-driven treatment management based on evidence that physiologic metrics may correlate better with individual patient response than traditional (population-based) dose and volume-based metrics. Further, there is evidence that information obtained during the course of radiation therapy may further improve response predictions. Methods: Clinical factors were gathered for 58 patients including planned mean lung dose, and the bio-markers IL-8 and TGF-β1 obtained prior to treatment and two weeks into treatment along with complication outcomes for these patients. A Bayesian Decision Network was constructed using Netica 5.0.2 from Norsys linking these clinical factors to obtain a prediction of radiation induced lung disese (RILD) complication. A decision node was added to the network to provide a plan adaption recommendation based on the trade-off between the RILD prediction and complexity of replanning. A utility node provides the weighting cost between the competing factors. Results: The decision node predictions were optimized against the data for the 58 cases. With this decision network solution, one can consider the decision result for a new patient with specific findings to obtain a recommendation to adaptively modify the originally planned treatment course. Conclusions: A Bayesian approach allows handling and propagating probabilistic data in a logical and principled manner. Decision networks provide the further ability to provide utility-based trade-offs, reflecting non-medical but practical cost/benefit analysis. The network demonstrated illustrates the basic concept, but many other factors may affect these decisions and work on building better models are being designed and tested. Acknowledgement: Supported by NIH-P01-CA59827

  3. Adaptive Feedback Improving Learningful Conversations at Workplace

    ERIC Educational Resources Information Center

    Gaeta, Matteo; Mangione, Giuseppina Rita; Miranda, Sergio; Orciuoli, Francesco

    2013-01-01

    This work proposes the definition of an Adaptive Conversation-based Learning System (ACLS) able to foster computer-mediated tutorial dialogues at the workplace in order to increase the probability to generate meaningful learning during conversations. ACLS provides a virtual assistant selecting the best partner to involve in the conversation and…

  4. Synthesis of oscillating adaptive feedback systems

    NASA Technical Reports Server (NTRS)

    Smay, J. W.

    1973-01-01

    A synthesis theory is developed which allows system design to proceed from practical specifications on system command and/or disturbance response to a design which is very nearly optimal in terms of feedback sensor noise effects. The approach taken is to replace the nonlinear element by a mean square error minimizing approximation (dual-input describing function), and then use linear frequency domain synthesis techniques subject to additional constraints imposed by the limit cycle and the approximator. Synthesis techniques are also developed for a similar system using an externally excited oscillating signal with the above approach. The results remove the design of the systems considered from the realm of simulation and experimentation, permitting true synthesis and the optimization that accompanies it.

  5. Farmer Decision-Making for Climate Adaptation

    NASA Astrophysics Data System (ADS)

    Lubell, M.; Niles, M.; Salerno, J.

    2015-12-01

    This talk will provide an overview of several studies of how farmers make decisions about climate change adaptation and mitigation. A particular focus will be the "limiting factors hypothesis", which argues that farmers will respond to the climate variables that usually have the largest impact on their crop productivity. For example, the most limiting factor in California is usually water so how climate change affects water will be the largest drive of climate adaptation decisions. This basic idea is drawn from the broader theory of "psychological distance", which argue that human decisions are more attuned to ideas that are psychologically closer in space, time, or other factors. Empirical examples come from California, New Zealand, and Africa.

  6. Adaptive disengagement buffers self-esteem from negative social feedback.

    PubMed

    Leitner, Jordan B; Hehman, Eric; Deegan, Matthew P; Jones, James M

    2014-11-01

    The degree to which self-esteem hinges on feedback in a domain is known as a contingency of self-worth, or engagement. Although previous research has conceptualized engagement as stable, it would be advantageous for individuals to dynamically regulate engagement. The current research examined whether the tendency to disengage from negative feedback accounts for variability in self-esteem. We created the Adaptive Disengagement Scale (ADS) to capture individual differences in the tendency to disengage self-esteem from negative outcomes. Results demonstrated that the ADS is reliable and valid (Studies 1 and 2). Furthermore, in response to negative social feedback, higher scores on the ADS predicted greater state self-esteem (Study 3), and this relationship was mediated by disengagement (Study 4). These findings demonstrate that adaptive disengagement protects self-esteem from negative outcomes and that the ADS is a valid measure of individual differences in the implementation of this process.

  7. Adaptive disengagement buffers self-esteem from negative social feedback.

    PubMed

    Leitner, Jordan B; Hehman, Eric; Deegan, Matthew P; Jones, James M

    2014-11-01

    The degree to which self-esteem hinges on feedback in a domain is known as a contingency of self-worth, or engagement. Although previous research has conceptualized engagement as stable, it would be advantageous for individuals to dynamically regulate engagement. The current research examined whether the tendency to disengage from negative feedback accounts for variability in self-esteem. We created the Adaptive Disengagement Scale (ADS) to capture individual differences in the tendency to disengage self-esteem from negative outcomes. Results demonstrated that the ADS is reliable and valid (Studies 1 and 2). Furthermore, in response to negative social feedback, higher scores on the ADS predicted greater state self-esteem (Study 3), and this relationship was mediated by disengagement (Study 4). These findings demonstrate that adaptive disengagement protects self-esteem from negative outcomes and that the ADS is a valid measure of individual differences in the implementation of this process. PMID:25189323

  8. Iterative Frequency Domain Decision Feedback Equalization and Decoding for Underwater Acoustic Communications

    NASA Astrophysics Data System (ADS)

    Zhao, Liang; Ge, Jian-Hua

    2012-12-01

    Single-carrier (SC) transmission with frequency-domain equalization (FDE) is today recognized as an attractive alternative to orthogonal frequency-division multiplexing (OFDM) for communication application with the inter-symbol interference (ISI) caused by multi-path propagation, especially in shallow water channel. In this paper, we investigate an iterative receiver based on minimum mean square error (MMSE) decision feedback equalizer (DFE) with symbol rate and fractional rate samplings in the frequency domain (FD) and serially concatenated trellis coded modulation (SCTCM) decoder. Based on sound speed profiles (SSP) measured in the lake and finite-element ray tracking (Bellhop) method, the shallow water channel is constructed to evaluate the performance of the proposed iterative receiver. Performance results show that the proposed iterative receiver can significantly improve the performance and obtain better data transmission than FD linear and adaptive decision feedback equalizers, especially in adopting fractional rate sampling.

  9. Adaptive Inferential Feedback Partner Training for Depression: A Pilot Study

    ERIC Educational Resources Information Center

    Dobkin, Roseanne DeFronzo; Allen, Lesley A.; Alloy, Lauren B.; Menza, Matthew; Gara, Michael A.; Panzarella, Catherine

    2007-01-01

    Adaptive inferential feedback (AIF) partner training is a cognitive technique that teaches the friends and family members of depressed patients to respond to the patients' dysfunctional thoughts in a targeted manner. These dysfunctional attributions, which AIF addresses, are a common residual feature of depression amongst remitted patients, and…

  10. Semantic richness effects in lexical decision: The role of feedback.

    PubMed

    Yap, Melvin J; Lim, Gail Y; Pexman, Penny M

    2015-11-01

    Across lexical processing tasks, it is well established that words with richer semantic representations are recognized faster. This suggests that the lexical system has access to meaning before a word is fully identified, and is consistent with a theoretical framework based on interactive and cascaded processing. Specifically, semantic richness effects are argued to be produced by feedback from semantic representations to lower-level representations. The present study explores the extent to which richness effects are mediated by feedback from lexical- to letter-level representations. In two lexical decision experiments, we examined the joint effects of stimulus quality and four semantic richness dimensions (imageability, number of features, semantic neighborhood density, semantic diversity). With the exception of semantic diversity, robust additive effects of stimulus quality and richness were observed for the targeted dimensions. Our results suggest that semantic feedback does not typically reach earlier levels of representation in lexical decision, and further reinforces the idea that task context modulates the processing dynamics of early word recognition processes. PMID:26155967

  11. L1 adaptive output-feedback control architectures

    NASA Astrophysics Data System (ADS)

    Kharisov, Evgeny

    This research focuses on development of L 1 adaptive output-feedback control. The objective is to extend the L1 adaptive control framework to a wider class of systems, as well as obtain architectures that afford more straightforward tuning. We start by considering an existing L1 adaptive output-feedback controller for non-strictly positive real systems based on piecewise constant adaptation law. It is shown that L 1 adaptive control architectures achieve decoupling of adaptation from control, which leads to bounded away from zero time-delay and gain margins in the presence of arbitrarily fast adaptation. Computed performance bounds provide quantifiable performance guarantees both for system output and control signal in transient and steady state. A noticeable feature of the L1 adaptive controller is that its output behavior can be made close to the behavior of a linear time-invariant system. In particular, proper design of the lowpass filter can achieve output response, which almost scales for different step reference commands. This property is relevant to applications with human operator in the loop (for example: control augmentation systems of piloted aircraft), since predictability of the system response is necessary for adequate performance of the operator. Next we present applications of the L1 adaptive output-feedback controller in two different fields of engineering: feedback control of human anesthesia, and ascent control of a NASA crew launch vehicle (CLV). The purpose of the feedback controller for anesthesia is to ensure that the patient's level of sedation during surgery follows a prespecified profile. The L1 controller is enabled by anesthesiologist after he/she achieves sufficient patient sedation level by introducing sedatives manually. This problem formulation requires safe switching mechanism, which avoids controller initialization transients. For this purpose, we used an L1 adaptive controller with special output predictor initialization routine

  12. Multichannel decision feedback equalization in underwater acoustic communication

    NASA Astrophysics Data System (ADS)

    Yang, Xiaoxia; Wang, Haibin; Wang, Jun

    2012-11-01

    This paper studies an underwater acoustic communication system and its performance in shallow water. A channel encoder and a quadrature phase shift keying (QPSK) modulation scheme have been adopted at the transmitter, and a multichannel decision feedback equalizer (DFE) with a soft decision device has been used at the receiver. This system has been tested in a Yellow Sea experiment for transmitting an image at a range of 18.5km. A space diversity procedure is used to mitigate the performance degradation of the multichannel DFE caused by occasional impulsive noise in the receiver. In the case of two receivers, the equalizer exhibits good performance with bit error number of 319 out of 239946. After channel decoding, an image is obtained without any errant bits.

  13. Age Differences in Adaptive Decision Making: The Role of Numeracy

    ERIC Educational Resources Information Center

    Chen, Yiwei; Wang, Jiaxi; Kirk, Robert M.; Pethtel, Olivia L.; Kiefner, Allison E.

    2014-01-01

    The primary purposes of the present study were to examine age differences in adaptive decision making and to evaluate the role of numeracy in mediating the relationship between age and adaptive decision making. Adaptive decision making was assessed by the Cups task (Levin, Weller, Pederson, & Harshman, 2007). Forty-six younger (18 to 24 years…

  14. Toward an Expanded Definition of Adaptive Decision Making.

    ERIC Educational Resources Information Center

    Phillips, Susan D.

    1997-01-01

    Uses the lifespan, life-space model to examine the definition of adaptive decision making. Reviews the existing definition of adaptive decision making as "rational" decision making and offers alternate perspectives on decision making with an emphasis on the implications of using the model. Makes suggestions for future theory, research, and…

  15. Combination of Adaptive Feedback Cancellation and Binaural Adaptive Filtering in Hearing Aids

    NASA Astrophysics Data System (ADS)

    Lombard, Anthony; Reindl, Klaus; Kellermann, Walter

    2009-12-01

    We study a system combining adaptive feedback cancellation and adaptive filtering connecting inputs from both ears for signal enhancement in hearing aids. For the first time, such a binaural system is analyzed in terms of system stability, convergence of the algorithms, and possible interaction effects. As major outcomes of this study, a new stability condition adapted to the considered binaural scenario is presented, some already existing and commonly used feedback cancellation performance measures for the unilateral case are adapted to the binaural case, and possible interaction effects between the algorithms are identified. For illustration purposes, a blind source separation algorithm has been chosen as an example for adaptive binaural spatial filtering. Experimental results for binaural hearing aids confirm the theoretical findings and the validity of the new measures.

  16. Decision Making Under Objective Risk Conditions-a Review of Cognitive and Emotional Correlates, Strategies, Feedback Processing, and External Influences.

    PubMed

    Schiebener, Johannes; Brand, Matthias

    2015-06-01

    While making decisions under objective risk conditions, the probabilities of the consequences of the available options are either provided or calculable. Brand et al. (Neural Networks 19:1266-1276, 2006) introduced a model describing the neuro-cognitive processes involved in such decisions. In this model, executive functions associated with activity in the fronto-striatal loop are important for developing and applying decision-making strategies, and for verifying, adapting, or revising strategies according to feedback. Emotional rewards and punishments learned from such feedback accompany these processes. In this literature review, we found support for the role of executive functions, but also found evidence for the importance of further cognitive abilities in decision making. Moreover, in addition to reflective processing (driven by cognition), decisions can be guided by impulsive processing (driven by anticipation of emotional reward and punishment). Reflective and impulsive processing may interact during decision making, affecting the evaluation of available options, as both processes are affected by feedback. Decision-making processes are furthermore modulated by individual attributes (e.g., age), and external influences (e.g., stressors). Accordingly, we suggest a revised model of decision making under objective risk conditions.

  17. Mechanisms in Adaptive Feedback Control: Photoisomerization in a Liquid

    SciTech Connect

    Hoki, Kunihito; Brumer, Paul

    2005-10-14

    The underlying mechanism for Adaptive Feedback Control in the experimental photoisomerization of 3,3'-diethyl-2,2'-thiacyanine iodide (NK88) in methanol is exposed theoretically. With given laboratory limitations on laser output, the complicated electric fields are shown to achieve their targets in qualitatively simple ways. Further, control over the cis population without laser limitations reveals an incoherent pump-dump scenario as the optimal isomerization strategy. In neither case are there substantial contributions from quantum multiple-path interference or from nuclear wave packet coherence. Environmentally induced decoherence is shown to justify the use of a simplified theoretical model.

  18. Adaptive feedback cancellation with frequency compression for hearing aids.

    PubMed

    Joson, H A; Asano, F; Suzuki, Y; Sone, T

    1993-12-01

    The use of an adaptive feedback canceler (AFC) for howling suppression in hearing aids seems very attractive since it is not only unaffected by the changes in the operating environment, but it also limits signal degradation due to the feedback signal. This, however, requires a reference signal which is correlated with the feedback signal but not with the input signal. In hearing aids, such a signal is hard to obtain. The output signal could be used as reference if its correlation with the input signal could sufficiently be removed. If the reference signal is correlated with the input signal, the input signal will also be canceled by the AFC. Here, the use of a frequency compressor as a decorrelator is proposed. The performance of this system is then investigated via digital simulation. Results indicated that with the use of the proposed system and the proper choice of system parameters, an increase of about 18 dB in the howling margin could be achieved with minimal deterioration in output signal quality. PMID:8300960

  19. Characterizing Uncertainty for Regional Climate Change Mitigation and Adaptation Decisions

    SciTech Connect

    Unwin, Stephen D.; Moss, Richard H.; Rice, Jennie S.; Scott, Michael J.

    2011-09-30

    This white paper describes the results of new research to develop an uncertainty characterization process to help address the challenges of regional climate change mitigation and adaptation decisions.

  20. An Adapting Auditory-motor Feedback Loop Can Contribute to Generating Vocal Repetition

    PubMed Central

    Brainard, Michael S.; Jin, Dezhe Z.

    2015-01-01

    Consecutive repetition of actions is common in behavioral sequences. Although integration of sensory feedback with internal motor programs is important for sequence generation, if and how feedback contributes to repetitive actions is poorly understood. Here we study how auditory feedback contributes to generating repetitive syllable sequences in songbirds. We propose that auditory signals provide positive feedback to ongoing motor commands, but this influence decays as feedback weakens from response adaptation during syllable repetitions. Computational models show that this mechanism explains repeat distributions observed in Bengalese finch song. We experimentally confirmed two predictions of this mechanism in Bengalese finches: removal of auditory feedback by deafening reduces syllable repetitions; and neural responses to auditory playback of repeated syllable sequences gradually adapt in sensory-motor nucleus HVC. Together, our results implicate a positive auditory-feedback loop with adaptation in generating repetitive vocalizations, and suggest sensory adaptation is important for feedback control of motor sequences. PMID:26448054

  1. Auditory categories with separable decision boundaries are learned faster with full feedback than with minimal feedback.

    PubMed

    Yi, Han Gyol; Chandrasekaran, Bharath

    2016-08-01

    During visual category learning, full feedback (e.g., "Wrong, that was a category 4."), relative to minimal feedback (e.g., "Wrong."), enhances performance when the relevant dimensions are separable. This pattern is reversed with inseparable dimensions. Here, the interaction between trial-by-trial feedback and separability of dimensions in the auditory domain is examined. Participants were trained to categorize auditory stimuli along separable or inseparable dimensions. One group received full feedback, while the other group received minimal feedback. In the separable-dimensions condition, the full-feedback group achieved higher accuracy than did the minimal-feedback group. In the inseparable-dimensions condition, performance was equivalent across the feedback groups. These results altogether suggest that trial-by-trial feedback affects auditory category learning performance differentially for separable and inseparable categories. PMID:27586759

  2. Observations to support adaptation: Principles, scales and decision-making

    NASA Astrophysics Data System (ADS)

    Pulwarty, R. S.

    2012-12-01

    As has been long noted, a comprehensive, coordinated observing system is the backbone of any Earth information system. Demands are increasingly placed on earth observation and prediction systems and attendant services to address the needs of economically and environmentally vulnerable sectors and investments, including energy, water, human health, transportation, agriculture, fisheries, tourism, biodiversity, and national security. Climate services include building capacity to interpret information and recognize standards and limitations of data in the promotion of social and economic development in a changing climate. This includes improving the understanding of climate in the context of a variety of temporal and spatial scales (including the influence of decadal scale forcings and land surface feedbacks on seasonal forecast reliability). Climate data and information are central for developing decision options that are sensitive to climate-related uncertainties and the design of flexible adaptation pathways. Ideally monitoring should be action oriented to support climate risk assessment and adaptation including informing robust decision making to multiple risks over the long term. Based on the experience of global observations programs and empirical research we outline- Challenges in developing effective monitoring and climate information systems to support adaptation. The types of observations of critical importance needed for sector planning to enhance food, water and energy security, and to improve early warning for disaster risk reduction Observations needed for ecosystem-based adaptation including the identification of thresholds, maintenance of biological diversity and land degradation The benefits and limits of linking regional model output to local observations including analogs and verification for adaptation planning To support these goals a robust systems of integrated observations are needed to characterize the uncertainty surrounding emergent risks

  3. Neural-Based Adaptive Output-Feedback Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Systems.

    PubMed

    Wang, Huanqing; Liu, Kefu; Liu, Xiaoping; Chen, Bing; Lin, Chong

    2015-09-01

    In this paper, we consider the problem of observer-based adaptive neural output-feedback control for a class of stochastic nonlinear systems with nonstrict-feedback structure. To overcome the design difficulty from the nonstrict-feedback structure, a variable separation approach is introduced by using the monotonically increasing property of system bounding functions. On the basis of the state observer, and by combining the adaptive backstepping technique with radial basis function neural networks' universal approximation capability, an adaptive neural output feedback control algorithm is presented. It is shown that the proposed controller can guarantee that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded in the sense of mean quartic value. Simulation results are provided to show the effectiveness of the proposed control scheme.

  4. An Examination of Students' Adaptation, Aggression, and Apprehension Traits with Their Instructional Feedback Orientations

    ERIC Educational Resources Information Center

    Malachowski, Colleen C.; Martin, Matthew M.; Vallade, Jessalyn I.

    2013-01-01

    Feedback orientations refer to students' perceptions of instructional feedback utility, retention, sensitivity, and confidentiality. In this paper, we report three studies that investigated the relationships among feedback orientations and communication traits. Specifically, we examined the associations among communication adaptation traits (Study…

  5. An Adaptive Feedback and Review Paradigm for Computer-Based Drills.

    ERIC Educational Resources Information Center

    Siegel, Martin A.; Misselt, A. Lynn

    The Corrective Feedback Paradigm (CFP), which has been refined and expanded through use on the PLATO IV Computer-Based Education System, is based on instructional design strategies implied by stimulus-locus analyses, direct instruction, and instructional feedback methods. Features of the paradigm include adaptive feedback techniques with…

  6. Decision criteria of potential solar IPH adapters

    NASA Astrophysics Data System (ADS)

    Perwin, E.; Levine, A.; Mikasa, G.; Noun, R. J.; Schaller, D.

    1981-12-01

    If national programs are to be effective in the research and development of viable renewable resource technologies for the industrial sector, understanding industry's decision criteria will be important. The results of a preliminary investigation of the decision criteria of potential and actual users of solar industrial process heat systems are presented. Detailed interviews were completed with decision-makers from ten manufacturing firms. Based on economic theory, it was assumed that corporate decision-makers assess the expected cost, revenue, and uncertainty of competing investment opportunities. These decision criteria are composed of factors that are financial, technical, and institutional. Clearly, the firms interviewed were more concerned with costs than any other category of decision criteria. Most of the firms also believed that there was less uncertainty with competing investments than with current solar technology. Based on this preliminary investigation, a more extensive survey of industrial firms is suggested to determine a more comprehensive list of significant decision criteria.

  7. Walking Flexibility after Hemispherectomy: Split-Belt Treadmill Adaptation and Feedback Control

    ERIC Educational Resources Information Center

    Choi, Julia T.; Vining, Eileen P. G.; Reisman, Darcy S.; Bastian, Amy J.

    2009-01-01

    Walking flexibility depends on use of feedback or reactive control to respond to unexpected changes in the environment, and the ability to adapt feedforward or predictive control for sustained alterations. Recent work has demonstrated that cerebellar damage impairs feedforward adaptation, but not feedback control, during human split-belt treadmill…

  8. Interior Noise Reduction by Adaptive Feedback Vibration Control

    NASA Technical Reports Server (NTRS)

    Lim, Tae W.

    1998-01-01

    The objective of this project is to investigate the possible use of adaptive digital filtering techniques in simultaneous, multiple-mode identification of the modal parameters of a vibrating structure in real-time. It is intended that the results obtained from this project will be used for state estimation needed in adaptive structural acoustics control. The work done in this project is basically an extension of the work on real-time single mode identification, which was performed successfully using a digital signal processor (DSP) at NASA, Langley. Initially, in this investigation the single mode identification work was duplicated on a different processor, namely the Texas Instruments TMS32OC40 DSP. The system identification results for the single mode case were very good. Then an algorithm for simultaneous two mode identification was developed and tested using analytical simulation. When it successfully performed the expected tasks, it was implemented in real-time on the DSP system to identify the first two modes of vibration of a cantilever aluminum beam. The results of the simultaneous two mode case were good but some problems were identified related to frequency warping and spurious mode identification. The frequency warping problem was found to be due to the bilinear transformation used in the algorithm to convert the system transfer function from the continuous-time domain to the discrete-time domain. An alternative approach was developed to rectify the problem. The spurious mode identification problem was found to be associated with high sampling rates. Noise in the signal is suspected to be the cause of this problem but further investigation will be needed to clarify the cause. For simultaneous identification of more than two modes, it was found that theoretically an adaptive digital filter can be designed to identify the required number of modes, but the algebra became very complex which made it impossible to implement in the DSP system used in this study

  9. Failure to utilize feedback causes decision-making deficits among excessive Internet gamers.

    PubMed

    Yao, Yuan-Wei; Chen, Pin-Ru; Chen, Chang; Wang, Ling-Jiao; Zhang, Jin-Tao; Xue, Gui; Deng, Lin-Yuan; Liu, Qin-Xue; Yip, Sarah W; Fang, Xiao-Yi

    2014-11-30

    Internet gaming addiction (IGA) is an increasing mental health issue worldwide. Previous studies have revealed decision-making impairments in excessive Internet gamers (EIGs) with high symptoms of IGA. However, the role of feedback processing in decision-making deficits among EIGs remains unknown. The present study aimed to investigate the effect of feedback processing on decision-making deficits under risk among EIGs, using the Game of Dice Task (GDT) and a modified version of the GDT in which no feedback was provided. Twenty-six EIGs and 26 matched occasional Internet gamers (OIGs) were recruited. The results showed: (a) OIGs performed better on the original GDT than on the modified GDT (no feedback condition); however, EIGs performed similarly on both tasks; (b) EIGs and OIGs performed equally on the modified GDT; however, EIGs chose more disadvantageous options than OIGs on the original GDT; (c) EIGs utilized feedback less frequently on the original GDT relative to OIGs. These results suggest that EIGs are not able to utilize feedback to optimize their decisions, which could underlie their poor decision-making under risk.

  10. Augmented multisensory feedback enhances locomotor adaptation in humans with incomplete spinal cord injury.

    PubMed

    Yen, Sheng-Che; Landry, Jill M; Wu, Ming

    2014-06-01

    Different forms of augmented feedback may engage different motor learning pathways, but it is unclear how these pathways interact with each other, especially in patients with incomplete spinal cord injury (SCI). The purpose of this study was to test whether augmented multisensory feedback could enhance aftereffects following short term locomotor training (i.e., adaptation) in patients with incomplete SCI. A total of 10 subjects with incomplete SCI were recruited to perform locomotor adaptation. Three types of augmented feedback were provided during the adaptation: (a) computerized visual cues showing the actual and target stride length (augmented visual feedback); (b) a swing resistance applied to the leg (augmented proprioceptive feedback); (c) a combination of the visual cues and resistance (augmented multisensory feedback). The results showed that subjects' stride length increased in all conditions following the adaptation, but the increase was greater and retained longer in the multisensory feedback condition. The multisensory feedback provided in this study may engage both explicit and implicit learning pathways during the adaptation and in turn enhance the aftereffect. The results implied that multisensory feedback may be used as an adjunctive approach to enhance gait recovery in humans with SCI. PMID:24746604

  11. The adaptability of career decision-making profiles.

    PubMed

    Gadassi, Reuma; Gati, Itamar; Dayan, Amira

    2012-10-01

    The Career Decision-Making Profiles questionnaire (CDMP; Gati, Landman, Davidovitch, Asulin-Peretz, & Gadassi, 2010) uses a new model for characterizing the way individuals make decisions based on the simultaneous use of 11 dimensions. The present study investigated which pole of each dimension is more adaptive. Using the data of 383 young adults who were about to make a career choice, we assessed the individuals' decision status and the associations of the dimensions Emotional and Personality-related Career decision-making Difficulties (EPCD; Saka, Gati, & Kelly, 2008) and personality factors (NEO Personality Inventory-Revised; Costa & McCrae, 1992). The results suggest that, as hypothesized, comprehensive Information gathering, analytic Information processing, a more internal Locus of control, more Effort invested, less Procrastination, greater Speed of making the final decision, less Dependence on others, and less Desire to please others were more adaptive in making career decisions. However, contrary to our hypotheses, high Aspiration for an ideal occupation was more adaptive for the decision-making process, Willingness to compromise was not associated with more adaptive decision making, and the results regarding Consulting with others were mixed. Gender differences in the CDMP dimensions and counseling implications are discussed. PMID:22746185

  12. The Adaptability of Career Decision-Making Profiles

    ERIC Educational Resources Information Center

    Gadassi, Reuma; Gati, Itamar; Dayan, Amira

    2012-01-01

    The Career Decision-Making Profiles questionnaire (CDMP; Gati, Landman, Davidovitch, Asulin-Peretz, & Gadassi, 2010) uses a new model for characterizing the way individuals make decisions based on the simultaneous use of 11 dimensions. The present study investigated which pole of each dimension is more adaptive. Using the data of 383 young adults…

  13. Decision-making in healthcare as a complex adaptive system.

    PubMed

    Kuziemsky, Craig

    2016-01-01

    Healthcare transformation requires a change in how the business of healthcare is done. Traditional decision-making approaches based on stable and predictable systems are inappropriate in healthcare because of the complex nature of healthcare delivery. This article reviews challenges to using traditional decision-making approaches in healthcare and how insight from Complex Adaptive Systems (CAS) could support healthcare management. The article also provides a system model to guide decision-making in healthcare as a CAS.

  14. An Efficient Adaptive Feedback cancellation using by Independent component analysis for hearing aids.

    PubMed

    Ji, Y S; Jung, S Y; Kwon, S Y; Kim, I Y; Kim, Sun; Lee, S M

    2005-01-01

    In this paper, we proposed a feedback cancellation algorithm based on independent component analysis (ICA) for digital hearing aids. In conventional adaptive feedback cancelling systems, the normalized least mean squares (NLMS) algorithm used to reduce acoustic feedback in which hearing aids occurs, generally at high gains. But primary input signal depend on the acoustic feedback signal in higher-order statistics, proposed algorithm was better acoustic feedback cancelling performance than the conventional NLMS algorithm when the input signal has a Laplacian distribution with high-order processing in real-time simulation of TMS320C 6711 DSK. PMID:17282799

  15. Adaptive Decision Aiding in Computer-Assisted Instruction: Adaptive Computerized Training System (ACTS).

    ERIC Educational Resources Information Center

    Hopf-Weichel, Rosemarie; And Others

    This report describes results of the first year of a three-year program to develop and evaluate a new Adaptive Computerized Training System (ACTS) for electronics maintenance training. (ACTS incorporates an adaptive computer program that learns the student's diagnostic and decision value structure, compares it to that of an expert, and adapts the…

  16. How Useful Are Climate Projections for Adaptation Decision Making?

    NASA Astrophysics Data System (ADS)

    Smith, J. B.; Vogel, J. M.

    2011-12-01

    Decision making is often portrayed as a linear process that assumes scientific knowledge is a necessary precursor to effective policy and is used directly in policy making. Yet, in practice, the use of scientific information in decision making is more complex than the linear model implies. The use of climate projections in adaptation decision making is a case in point. This paper briefly reviews efforts by some decision makers to understand climate change risks and to apply this knowledge when making decisions on management of climate sensitive resources and infrastructure . In general, and in spite of extensive efforts to study climate change at the regional and local scale to support decision making, few decisions outside of adapting to sea level rise appear to directly apply to climate change projections. A number of U.S. municipalities and states, including Seattle, New York City, Phoenix, and the States of California and Washington, have used climate change projections to assess their vulnerability to various climate change impacts. Some adaptation decisions have been made based on projections of sea level rise, such as change in location of infrastructure. This may be because a future rise is sea level is virtually certain. In contrast, decision making on precipitation has been more limited, even where there is consensus on likely changes in sign of the variable. Nonetheless, decision makers are adopting strategies that can be justified based on current climate and climate variability and that also reduce risks to climate change. A key question for the scientific community is whether improved projections will add value to decision making. For example, it remains unclear how higher-resolution projections can change decision making as long as the sign and magnitude of projections across climate models and downscaling techniques retains a wide range of uncertainty. It is also unclear whether even better information on the sign and magnitude of change would

  17. Delayed feedback during sensorimotor learning selectively disrupts adaptation but not strategy use.

    PubMed

    Brudner, Samuel N; Kethidi, Nikhit; Graeupner, Damaris; Ivry, Richard B; Taylor, Jordan A

    2016-03-01

    In sensorimotor adaptation tasks, feedback delays can cause significant reductions in the rate of learning. This constraint is puzzling given that many skilled behaviors have inherently long delays (e.g., hitting a golf ball). One difference in these task domains is that adaptation is primarily driven by error-based feedback, whereas skilled performance may also rely to a large extent on outcome-based feedback. This difference suggests that error- and outcome-based feedback may engage different learning processes, and these processes may be associated with different temporal constraints. We tested this hypothesis in a visuomotor adaptation task. Error feedback was indicated by the terminal position of a cursor, while outcome feedback was indicated by points. In separate groups of participants, the two feedback signals were presented immediately at the end of the movement, after a delay, or with just the error feedback delayed. Participants learned to counter the rotation in a similar manner regardless of feedback delay. However, the aftereffect, an indicator of implicit motor adaptation, was attenuated with delayed error feedback, consistent with the hypothesis that a different learning process supports performance under delay. We tested this by employing a task that dissociates the contribution of explicit strategies and implicit adaptation. We find that explicit aiming strategies contribute to the majority of the learning curve, regardless of delay; however, implicit learning, measured over the course of learning and by aftereffects, was significantly attenuated with delayed error-based feedback. These experiments offer new insight into the temporal constraints associated with different motor learning processes. PMID:26792878

  18. Composite Adaptive Fuzzy Output Feedback Control Design for Uncertain Nonlinear Strict-Feedback Systems With Input Saturation.

    PubMed

    Li, Yongming; Tong, Shaocheng; Li, Tieshan

    2015-10-01

    In this paper, a composite adaptive fuzzy output-feedback control approach is proposed for a class of single-input and single-output strict-feedback nonlinear systems with unmeasured states and input saturation. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and a fuzzy state observer is designed to estimate the unmeasured states. By utilizing the designed fuzzy state observer, a serial-parallel estimation model is established. Based on adaptive backstepping dynamic surface control technique and utilizing the prediction error between the system states observer model and the serial-parallel estimation model, a new fuzzy controller with the composite parameters adaptive laws are developed. It is proved that all the signals of the closed-loop system are bounded and the system output can follow the given bounded reference signal. A numerical example and simulation comparisons with previous control methods are provided to show the effectiveness of the proposed approach.

  19. Sex-ratio control erodes sexual selection, revealing evolutionary feedback from adaptive plasticity.

    PubMed

    Fawcett, Tim W; Kuijper, Bram; Weissing, Franz J; Pen, Ido

    2011-09-20

    Female choice is a powerful selective force, driving the elaboration of conspicuous male ornaments. This process of sexual selection has profound implications for many life-history decisions, including sex allocation. For example, females with attractive partners should produce more sons, because these sons will inherit their father's attractiveness and enjoy high mating success, thereby yielding greater fitness returns than daughters. However, previous research has overlooked the fact that there is a reciprocal feedback from life-history strategies to sexual selection. Here, using a simple mathematical model, we show that if mothers adaptively control offspring sex in relation to their partner's attractiveness, sexual selection is weakened and male ornamentation declines. This weakening occurs because the ability to determine offspring sex reduces the fitness difference between females with attractive and unattractive partners. We use individual-based, evolutionary simulations to show that this result holds under more biologically realistic conditions. Sexual selection and sex allocation thus interact in a dynamic fashion: The evolution of conspicuous male ornaments favors sex-ratio adjustment, but this conditional strategy then undermines the very same process that generated it, eroding sexual selection. We predict that, all else being equal, the most elaborate sexual displays should be seen in species with little or no control over offspring sex. The feedback process we have described points to a more general evolutionary principle, in which a conditional strategy weakens directional selection on another trait by reducing fitness differences.

  20. At the Intersection of Health Information Technology and Decision Support: Measurement Feedback Systems... and Beyond.

    PubMed

    Chorpita, Bruce F; Daleiden, Eric L; Bernstein, Adam D

    2016-05-01

    We select and comment on concepts and examples from the target articles in this special issue on measurement feedback systems, placing them in the context of some of our own insights and ideas about measurement feedback systems, and where those systems lie at the intersection of technology and decision making. We contend that, connected to the many implementation challenges relevant to many new technologies, there are fundamental design challenges that await a more elaborate specification of the clinical information and decision models that underlie these systems. Candidate features of such models are discussed, which include referencing multiple evidence bases, facilitating observed and expected value comparisons, fostering collaboration, and allowing translation across multiple ontological systems. We call for a new metaphor for these technologies that goes beyond measurement feedback and encourages a deeper consideration of the increasingly complex clinical decision models needed to manage the uncertainty of delivering clinical care. PMID:26604202

  1. Striatum in stimulus-response learning via feedback and in decision making.

    PubMed

    Hiebert, Nole M; Vo, Andrew; Hampshire, Adam; Owen, Adrian M; Seergobin, Ken N; MacDonald, Penny A

    2014-11-01

    Cognitive deficits are recognized in Parkinson's disease. Understanding cognitive functions mediated by the striatum can clarify some of these impairments and inform treatment strategies. The dorsal striatum, a region impaired in Parkinson's disease, has been implicated in stimulus-response learning. However, most investigations combine acquisition of associations between stimuli, responses, or outcomes (i.e., learning) and expression of learning through response selection and decision enactment, confounding these separate processes. Using neuroimaging, we provide evidence that dorsal striatum does not mediate stimulus-response learning from feedback but rather underlies decision making once associations between stimuli and responses are learned. In the experiment, 11 males and 5 females (mean age 22) learned to associate abstract images to specific button-press responses through feedback in Session 1. In Session 2, they were asked to provide responses learned in Session 1. Feedback was omitted, precluding further feedback-based learning in this session. Using functional magnetic resonance imaging, dorsal striatum activation in healthy young participants was observed at the time of response selection and not during feedback, when greatest learning presumably occurs. Moreover, dorsal striatum activity increased across the duration of Session 1, peaking after most associations were well learned, and was significant during Session 2 where no feedback was provided, and therefore no feedback-based learning occurred. Preferential ventral striatum activity occurred during feedback and was maximal early in Session 1. Taken together, the results suggest that the ventral striatum underlies learning associations between stimuli and responses via feedback whereas the dorsal striatum mediates enacting decisions. PMID:25038436

  2. Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach.

    PubMed

    Cavagnaro, Daniel R; Gonzalez, Richard; Myung, Jay I; Pitt, Mark A

    2013-02-01

    Collecting data to discriminate between models of risky choice requires careful selection of decision stimuli. Models of decision making aim to predict decisions across a wide range of possible stimuli, but practical limitations force experimenters to select only a handful of them for actual testing. Some stimuli are more diagnostic between models than others, so the choice of stimuli is critical. This paper provides the theoretical background and a methodological framework for adaptive selection of optimal stimuli for discriminating among models of risky choice. The approach, called Adaptive Design Optimization (ADO), adapts the stimulus in each experimental trial based on the results of the preceding trials. We demonstrate the validity of the approach with simulation studies aiming to discriminate Expected Utility, Weighted Expected Utility, Original Prospect Theory, and Cumulative Prospect Theory models. PMID:24532856

  3. Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach

    PubMed Central

    Cavagnaro, Daniel R.; Gonzalez, Richard; Myung, Jay I.; Pitt, Mark A.

    2014-01-01

    Collecting data to discriminate between models of risky choice requires careful selection of decision stimuli. Models of decision making aim to predict decisions across a wide range of possible stimuli, but practical limitations force experimenters to select only a handful of them for actual testing. Some stimuli are more diagnostic between models than others, so the choice of stimuli is critical. This paper provides the theoretical background and a methodological framework for adaptive selection of optimal stimuli for discriminating among models of risky choice. The approach, called Adaptive Design Optimization (ADO), adapts the stimulus in each experimental trial based on the results of the preceding trials. We demonstrate the validity of the approach with simulation studies aiming to discriminate Expected Utility, Weighted Expected Utility, Original Prospect Theory, and Cumulative Prospect Theory models. PMID:24532856

  4. Adaptive Peircean decision aid project summary assessments.

    SciTech Connect

    Senglaub, Michael E.

    2007-01-01

    This efforts objective was to identify and hybridize a suite of technologies enabling the development of predictive decision aids for use principally in combat environments but also in any complex information terrain. The technologies required included formal concept analysis for knowledge representation and information operations, Peircean reasoning to support hypothesis generation, Mill's's canons to begin defining information operators that support the first two technologies and co-evolutionary game theory to provide the environment/domain to assess predictions from the reasoning engines. The intended application domain is the IED problem because of its inherent evolutionary nature. While a fully functioning integrated algorithm was not achieved the hybridization and demonstration of the technologies was accomplished and demonstration of utility provided for a number of ancillary queries.

  5. 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.

  6. 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. PMID:26585836

  7. Episodic memories predict adaptive value-based decision-making.

    PubMed

    Murty, Vishnu P; FeldmanHall, Oriel; Hunter, Lindsay E; Phelps, Elizabeth A; Davachi, Lila

    2016-05-01

    Prior research illustrates that memory can guide value-based decision-making. For example, previous work has implicated both working memory and procedural memory (i.e., reinforcement learning) in guiding choice. However, other types of memories, such as episodic memory, may also influence decision-making. Here we test the role for episodic memory-specifically item versus associative memory-in supporting value-based choice. Participants completed a task where they first learned the value associated with trial unique lotteries. After a short delay, they completed a decision-making task where they could choose to reengage with previously encountered lotteries, or new never before seen lotteries. Finally, participants completed a surprise memory test for the lotteries and their associated values. Results indicate that participants chose to reengage more often with lotteries that resulted in high versus low rewards. Critically, participants not only formed detailed, associative memories for the reward values coupled with individual lotteries, but also exhibited adaptive decision-making only when they had intact associative memory. We further found that the relationship between adaptive choice and associative memory generalized to more complex, ecologically valid choice behavior, such as social decision-making. However, individuals more strongly encode experiences of social violations-such as being treated unfairly, suggesting a bias for how individuals form associative memories within social contexts. Together, these findings provide an important integration of episodic memory and decision-making literatures to better understand key mechanisms supporting adaptive behavior. PMID:26999046

  8. Adaptive criterion setting in perceptual decision making.

    PubMed

    Stüttgen, Maik C; Yildiz, Ali; Güntürkün, Onur

    2011-09-01

    Pigeons responded in a perceptual categorization task with six different stimuli (shades of gray), three of which were to be classified as "light" or "dark", respectively. Reinforcement probability for correct responses was varied from 0.2 to 0.6 across blocks of sessions and was unequal for correct light and dark responses. Introduction of a new reinforcement contingency resulted in a biphasic process of adjustment: First, choices were strongly biased towards the favored alternative, which was followed by a shift of preference back towards unbiased choice allocation. The data are well described by a signal detection model in which adjustment to a change in reinforcement contingency is modeled as the change of a criterion along a decision axis with fixed stimulus distributions. Moreover, the model shows that pigeons, after an initial overadjustment, distribute their responses almost optimally, although the overall benefit from doing so is extremely small. The strong and swift effect of minute changes in overall reinforcement probability precludes a choice strategy directly maximizing expected value, contrary to the assumption of signal detection theory. Instead, the rapid adjustments observed can be explained by a model in which reinforcement probabilities for each action, contingent on perceived stimulus intensity, determine choice allocation.

  9. Adaptive neural coding: from biological to behavioral decision-making

    PubMed Central

    Louie, Kenway; Glimcher, Paul W.; Webb, Ryan

    2015-01-01

    Empirical decision-making in diverse species deviates from the predictions of normative choice theory, but why such suboptimal behavior occurs is unknown. Here, we propose that deviations from optimality arise from biological decision mechanisms that have evolved to maximize choice performance within intrinsic biophysical constraints. Sensory processing utilizes specific computations such as divisive normalization to maximize information coding in constrained neural circuits, and recent evidence suggests that analogous computations operate in decision-related brain areas. These adaptive computations implement a relative value code that may explain the characteristic context-dependent nature of behavioral violations of classical normative theory. Examining decision-making at the computational level thus provides a crucial link between the architecture of biological decision circuits and the form of empirical choice behavior. PMID:26722666

  10. A Feedback Learning and Mental Models Perspective on Strategic Decision Making

    ERIC Educational Resources Information Center

    Capelo, Carlos; Dias, Joao Ferreira

    2009-01-01

    This study aims to be a contribution to a theoretical model that explains the effectiveness of the learning and decision-making processes by means of a feedback and mental models perspective. With appropriate mental models, managers should be able to improve their capacity to deal with dynamically complex contexts, in order to achieve long-term…

  11. Chaotic Feedback Loops within Decision Making Groups: Towards an Integration of Chaos Theory and Cybernetics.

    ERIC Educational Resources Information Center

    Keaten, James A.

    This paper offers a model that integrates chaos theory and cybernetics, which can be used to describe the structure of decision making within small groups. The paper begins with an overview of cybernetics and chaos. Definitional characteristics of cybernetics are reviewed along with salient constructs, such as goal-seeking, feedback, feedback…

  12. Information-reduced Carrier Synchronization of Iterative Decoded BPSK and QPSK using Soft Decision (Extrinsic) Feedback

    NASA Technical Reports Server (NTRS)

    Simon, Marvin; Valles, Esteban; Jones, Christopher

    2008-01-01

    This paper addresses the carrier-phase estimation problem under low SNR conditions as are typical of turbo- and LDPC-coded applications. In previous publications by the first author, closed-loop carrier synchronization schemes for error-correction coded BPSK and QPSK modulation were proposed that were based on feeding back hard data decisions at the input of the loop, the purpose being to remove the modulation prior to attempting to track the carrier phase as opposed to the more conventional decision-feedback schemes that incorporate such feedback inside the loop. In this paper, we consider an alternative approach wherein the extrinsic soft information from the iterative decoder of turbo or LDPC codes is instead used as the feedback.

  13. Multivariable output feedback robust adaptive tracking control design for a class of delayed systems

    NASA Astrophysics Data System (ADS)

    Mirkin, Boris; Gutman, Per-Olof

    2015-02-01

    In this paper, we develop a model reference adaptive control scheme for a class of multi-input multi-output nonlinearly perturbed dynamic systems with unknown time-varying state delays which is also robust with respect to an external disturbance with unknown bounds. The output feedback adaptive control scheme uses feedback actions only, and thus does not require a direct measurement of the command or disturbance signals. A suitable Lyapunov-Krasovskii type functional is introduced to design the adaptation algorithms and to prove stability.

  14. Do Amnesic Patients with Korsakoff's Syndrome Use Feedback when Making Decisions under Risky Conditions? An Experimental Investigation with the Game of Dice Task with and without Feedback

    ERIC Educational Resources Information Center

    Brand, Matthias; Pawlikowski, Mirko; Labudda, Kirsten; Laier, Christian; von Rothkirch, Nadine; Markowitsch, Hans J.

    2009-01-01

    We investigated the role of feedback processing in decision making under risk conditions in 50 patients with amnesia in the course of alcoholic Korsakoff's syndrome (KS). Half of the patients were administered the Game of Dice Task (GDT) and the remaining 25 patients were examined with a modified version of the GDT in which no feedback was…

  15. Adaptive all the way down: building responsive materials from hierarchies of chemomechanical feedback.

    PubMed

    Grinthal, Alison; Aizenberg, Joanna

    2013-09-01

    A living organism is a bundle of dynamic, integrated adaptive processes: not only does it continuously respond to constant changes in temperature, sunlight, nutrients, and other features of its environment, but it does so by coordinating hierarchies of feedback among cells, tissues, organs, and networks all continuously adapting to each other. At the root of it all is one of the most fundamental adaptive processes: the constant tug of war between chemistry and mechanics that interweaves chemical signals with endless reconfigurations of macromolecules, fibers, meshworks, and membranes. In this tutorial we explore how such chemomechanical feedback - as an inherently dynamic, iterative process connecting size and time scales - can and has been similarly evoked in synthetic materials to produce a fascinating diversity of complex multiscale responsive behaviors. We discuss how chemical kinetics and architecture can be designed to generate stimulus-induced 3D spatiotemporal waves and topographic patterns within a single bulk material, and how feedback between interior dynamics and surface-wide instabilities can further generate higher order buckling and wrinkling patterns. Building on these phenomena, we show how yet higher levels of feedback and spatiotemporal complexity can be programmed into hybrid materials, and how these mechanisms allow hybrid materials to be further integrated into multicompartmental systems capable of hierarchical chemo-mechano-chemical feedback responses. These responses no doubt represent only a small sample of the chemomechanical feedback behaviors waiting to be discovered in synthetic materials, and enable us to envision nearly limitless possibilities for designing multiresponsive, multifunctional, self-adapting materials and systems.

  16. Sequential decision making in computational sustainability via adaptive submodularity

    USGS Publications Warehouse

    Andreas Krause,; Daniel Golovin,; Converse, Sarah J.

    2015-01-01

    Many problems in computational sustainability require making a sequence of decisions in complex, uncertain environments. Such problems are generally notoriously difficult. In this article, we review the recently discovered notion of adaptive submodularity, an intuitive diminishing returns condition that generalizes the classical notion of submodular set functions to sequential decision problems. Problems exhibiting the adaptive submodularity property can be efficiently and provably near-optimally solved using simple myopic policies. We illustrate this concept in several case studies of interest in computational sustainability: First, we demonstrate how it can be used to efficiently plan for resolving uncertainty in adaptive management scenarios. Secondly, we show how it applies to dynamic conservation planning for protecting endangered species, a case study carried out in collaboration with the US Geological Survey and the US Fish and Wildlife Service.

  17. Adaptive cancellation of variable feedback path for hearing aid using misalignment-dependent step size values.

    PubMed

    Khoubrouy, Soudeh A; Panahi, Issa M S

    2011-01-01

    Various methods have been proposed to overcome the problem of compensating the acoustic feedback path that negatively impacts the performance of hearing aid devices. However, in most of them feedback path model is assumed to be fixed which is not quite realistic. In this paper, we consider fixed and variable feedback paths and analyze for each case the performance of one of the robust Adaptive Feedback Cancellation (AFC) schemes, i.e. the Prediction Error Method AFC which uses Partitioned Block Frequency-Domain Normalized Least Mean Square (PBFD-NLMS) algorithm. Based on the analysis results we propose varying the step size values for the same adaptive algorithm on the fly by monitoring the misalignment criteria. The experimental results using the proposed method show improvement made on the system performance. PMID:22256175

  18. Engaging stakeholders for adaptive management using structured decision analysis

    USGS Publications Warehouse

    Irwin, Elise R.; Kathryn, D.; Kennedy, Mickett

    2009-01-01

    Adaptive management is different from other types of management in that it includes all stakeholders (versus only policy makers) in the process, uses resource optimization techniques to evaluate competing objectives, and recognizes and attempts to reduce uncertainty inherent in natural resource systems. Management actions are negotiated by stakeholders, monitored results are compared to predictions of how the system should respond, and management strategies are adjusted in a “monitor-compare-adjust” iterative routine. Many adaptive management projects fail because of the lack of stakeholder identification, engagement, and continued involvement. Primary reasons for this vary but are usually related to either stakeholders not having ownership (or representation) in decision processes or disenfranchisement of stakeholders after adaptive management begins. We present an example in which stakeholders participated fully in adaptive management of a southeastern regulated river. Structured decision analysis was used to define management objectives and stakeholder values and to determine initial flow prescriptions. The process was transparent, and the visual nature of the modeling software allowed stakeholders to see how their interests and values were represented in the decision process. The development of a stakeholder governance structure and communication mechanism has been critical to the success of the project.

  19. Feedback Delays: How Can Decision Makers Learn Not to Buy a New Car Every Time the Garage Is Empty?

    PubMed

    Gibson

    2000-09-01

    Decision makers in dynamic environments (e.g., stock trading, inventory control, and firefighting) learn poorly in experiments where feedback about the outcomes of their actions is delayed. In searching for ways to mitigate these effects, this paper presents two computational models of learning with feedback delays and contrasts them against human decision-makers' performance. The no-memory model hypothesizes that decision makers always perceive feedback as immediate. The with-memory model hypothesizes that, over time, decision makers are able to develop internal representations of the task that help them to perform with delayed feedback. As borne out by human subjects, both models predict that a display of past history improves learning with delay and that increasing delay increasingly degrades performance. Even though the length of training in this task exceeds that used in many laboratory-based dynamic tasks, neither the two models nor the subjects are able to effectively learn without decision aids when faced with feedback delays. When given an amount of training that more closely approximates that provided in functioning dynamic environments, the with-memory model predicts that human decision makers may learn without decision aids over the long term if feedback delays are simple. These results raise several issues for continued theoretical investigation as well as potential suggestions for training and supporting decision makers in dynamic environments with feedback delays. Copyright 2000 Academic Press.

  20. Risky decision making from childhood through adulthood: Contributions of learning and sensitivity to negative feedback.

    PubMed

    Humphreys, Kathryn L; Telzer, Eva H; Flannery, Jessica; Goff, Bonnie; Gabard-Durnam, Laurel; Gee, Dylan G; Lee, Steve S; Tottenham, Nim

    2016-02-01

    Decision making in the context of risk is a complex and dynamic process that changes across development. Here, we assessed the influence of sensitivity to negative feedback (e.g., loss) and learning on age-related changes in risky decision making, both of which show unique developmental trajectories. In the present study, we examined risky decision making in 216 individuals, ranging in age from 3-26 years, using the balloon emotional learning task (BELT), a computerized task in which participants pump up a series of virtual balloons to earn points, but risk balloon explosion on each trial, which results in no points. It is important to note that there were 3 balloon conditions, signified by different balloon colors, ranging from quick- to slow-to-explode, and participants could learn the color-condition pairings through task experience. Overall, we found age-related increases in pumps made and points earned. However, in the quick-to-explode condition, there was a nonlinear adolescent peak for points earned. Follow-up analyses indicated that this adolescent phenotype occurred at the developmental intersection of linear age-related increases in learning and decreases in sensitivity to negative feedback. Adolescence was marked by intermediate values on both these processes. These findings show that a combination of linearly changing processes can result in nonlinear changes in risky decision making, the adolescent-specific nature of which is associated with developmental improvements in learning and reduced sensitivity to negative feedback. PMID:26389647

  1. Adaptive NN backstepping output-feedback control for stochastic nonlinear strict-feedback systems with time-varying delays.

    PubMed

    Chen, Weisheng; Jiao, Licheng; Li, Jing; Li, Ruihong

    2010-06-01

    For the first time, this paper addresses the problem of adaptive output-feedback control for a class of uncertain stochastic nonlinear strict-feedback systems with time-varying delays using neural networks (NNs). The circle criterion is applied to designing a nonlinear observer, and no linear growth condition is imposed on nonlinear functions depending on system states. Under the assumption that time-varying delays exist in the system output, only an NN is employed to compensate for all unknown nonlinear terms depending on the delayed output, and thus, the proposed control algorithm is more simple even than the existing NN backstepping control schemes for uncertain systems described by ordinary differential equations. Three examples are given to demonstrate the effectiveness of the control scheme proposed in this paper.

  2. A Decision Analysis Tool for Climate Impacts, Adaptations, and Vulnerabilities

    SciTech Connect

    Omitaomu, Olufemi A; Parish, Esther S; Nugent, Philip J

    2016-01-01

    Climate change related extreme events (such as flooding, storms, and drought) are already impacting millions of people globally at a cost of billions of dollars annually. Hence, there are urgent needs for urban areas to develop adaptation strategies that will alleviate the impacts of these extreme events. However, lack of appropriate decision support tools that match local applications is limiting local planning efforts. In this paper, we present a quantitative analysis and optimization system with customized decision support modules built on geographic information system (GIS) platform to bridge this gap. This platform is called Urban Climate Adaptation Tool (Urban-CAT). For all Urban-CAT models, we divide a city into a grid with tens of thousands of cells; then compute a list of metrics for each cell from the GIS data. These metrics are used as independent variables to predict climate impacts, compute vulnerability score, and evaluate adaptation options. Overall, the Urban-CAT system has three layers: data layer (that contains spatial data, socio-economic and environmental data, and analytic data), middle layer (that handles data processing, model management, and GIS operation), and application layer (that provides climate impacts forecast, adaptation optimization, and site evaluation). The Urban-CAT platform can guide city and county governments in identifying and planning for effective climate change adaptation strategies.

  3. Optimal classifier feedback improves cost-benefit but not base-rate decision criterion learning in perceptual categorization.

    PubMed

    Maddox, W Todd; Bohil, Corey J

    2005-03-01

    Unequal payoffs engender separate reward- and accuracy-maximizing decision criteria; unequal base rates do not. When payoffs are unequal, observers place greater emphasis on accuracy than is optimal. This study compares objective classifier (the objectively correct response) with optimal classifier feedback (the optimal classifier's response) when payoffs or base rates are unequal. It provides a critical test of Maddox and Bohil's (1998) competition between reward and accuracy maximization (COBRA) hypothesis, comparing it with a competition between reward and probability matching (COBRM) and a competition between reward and equal response frequencies (COBRE) hypothesis. The COBRA prediction that optimal classifier feedback leads to better decision criterion leaning relative to objective classifier feedback when payoffs are unequal, but not when base rates are unequal, was supported. Model-based analyses suggested that the weight placed on accuracy was reduced for optimal classifier feedback relative to objective classifier feedback. In addition, delayed feedback affected learning of the reward-maximizing decision criterion.

  4. Adaptive output feedback control of a class of uncertain nonlinear systems with unknown time delays

    NASA Astrophysics Data System (ADS)

    Guan, Wei

    2012-04-01

    This article studies the adaptive output feedback control problem of a class of uncertain nonlinear systems with unknown time delays. The systems considered are dominated by a triangular system without zero dynamics satisfying linear growth in the unmeasurable states. The novelty of this article is that a universal-type adaptive output feedback controller is presented to time-delay systems, which can globally regulate all the states of the uncertain systems without knowing the growth rate. An illustrative example is provided to show the applicability of the developed control strategy.

  5. Robust adaptive dynamic programming and feedback stabilization of nonlinear systems.

    PubMed

    Jiang, Yu; Jiang, Zhong-Ping

    2014-05-01

    This paper studies the robust optimal control design for a class of uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (RADP). The objective is to fill up a gap in the past literature of adaptive dynamic programming (ADP) where dynamic uncertainties or unmodeled dynamics are not addressed. A key strategy is to integrate tools from modern nonlinear control theory, such as the robust redesign and the backstepping techniques as well as the nonlinear small-gain theorem, with the theory of ADP. The proposed RADP methodology can be viewed as an extension of ADP to uncertain nonlinear systems. Practical learning algorithms are developed in this paper, and have been applied to the controller design problems for a jet engine and a one-machine power system. PMID:24808035

  6. Social-ecological feedbacks between climate, reindeer and people - contributions to climate change adaptation?

    NASA Astrophysics Data System (ADS)

    Käyhkö, Jukka; Horstkotte, Tim; Kivinen, Sonja; Johansen, Bernt

    2015-04-01

    The circumpolar tundra is experiencing significant transformations as a consequence of climate change. The anticipated changes include greening of the tundra due to a latitudinal and altitudinal progression of the tree line and range expansion of shrubs. In Northern Fennoscandia, reindeer husbandry by the indigenous Sámi people depends on large, seasonally variable grazing grounds, including the tundra. We demonstrate relationships between different vegetation types and climate conditions in Northern Fennoscandia. A generalized, seamless vegetation type map with 100 m grid, based on Landsat TM/ETM+ satellite images and various ancillary data, allows examination of vegetation types in relation to current climate conditions (1950-2000). Downscaled GCMs with different RCPs for 2050 and 2070 allow estimating future vegetation changes. Recently, the potential of herbivores has been recognized in slowing down this regime shift of vegetation composition with its feedbacks e.g. on the atmospheric energy balance, biodiversity and local livelihoods that depend on the tundra ecosystem. However, ecology alone is not the answer. We need comprehensive scenarios for adaptive ecosystem management for this social-ecological system to slow down the unfavourable impacts of climate change and excessive grazing pressure by reindeer in space and time, as well as across country borders. Possible adaptations could encourage the design of new institutional structures, and thus contest the legal background governing reindeer husbandry in the Nordic countries today. Designing such policy options for socially desirable and ecologically reasonable decision making, as well as navigating trade-offs inherent in flexible grazing patterns, require careful scenario analysis and acceptance by a variety of land users. A clear understanding of which values should be prioritized in relation to what ecosystem dynamics over what time scales is essential.

  7. High trait anxiety is associated with attenuated feedback-related negativity in risky decision making.

    PubMed

    Takács, Ádám; Kóbor, Andrea; Janacsek, Karolina; Honbolygó, Ferenc; Csépe, Valéria; Németh, Dezső

    2015-07-23

    Expectation biases could affect decision making in trait anxiety. Studying the alterations of feedback processing in real-life risk-taking tasks could reveal the presence of expectation biases at the neural level. A functional relevance of the feedback-related negativity (FRN) is the expression of outcome expectation errors. The aim of the study was to investigate whether nonclinical adults with high trait anxiety show smaller FRN for negative feedback than those with low trait anxiety. Participants (N=26) were assigned to low and high trait anxiety groups by a median split on the state-trait anxiety inventory trait score. They performed a balloon analogue risk task (BART) where they pumped a balloon on a screen. Each pump yielded either a reward or a balloon pop. If the balloon popped, the accumulated reward was lost. Participants were matched on their behavioral performance. We measured event-related brain potentials time-locked to the presentation of the feedback (balloon increase or pop). Our results showed that the FRN for balloon pops was decreased in the high anxiety group compared to the low anxiety group. We propose that pessimistic expectations triggered by the ambiguity in the BART decreased outcome expectation errors in the high anxiety group indicated by the smaller FRN. Our results highlight the importance of expectation biases at the neural level of decision making in anxiety. PMID:26093064

  8. Adaptive shape coding for perceptual decisions in the human brain.

    PubMed

    Kourtzi, Zoe; Welchman, Andrew E

    2015-01-01

    In its search for neural codes, the field of visual neuroscience has uncovered neural representations that reflect the structure of stimuli of variable complexity from simple features to object categories. However, accumulating evidence suggests an adaptive neural code that is dynamically shaped by experience to support flexible and efficient perceptual decisions. Here, we review work showing that experience plays a critical role in molding midlevel visual representations for perceptual decisions. Combining behavioral and brain imaging measurements, we demonstrate that learning optimizes feature binding for object recognition in cluttered scenes, and tunes the neural representations of informative image parts to support efficient categorical judgements. Our findings indicate that similar learning mechanisms may mediate long-term optimization through development, tune the visual system to fundamental principles of feature binding, and optimize feature templates for perceptual decisions. PMID:26024511

  9. Adaptive shape coding for perceptual decisions in the human brain

    PubMed Central

    Kourtzi, Zoe; Welchman, Andrew E.

    2015-01-01

    In its search for neural codes, the field of visual neuroscience has uncovered neural representations that reflect the structure of stimuli of variable complexity from simple features to object categories. However, accumulating evidence suggests an adaptive neural code that is dynamically shaped by experience to support flexible and efficient perceptual decisions. Here, we review work showing that experience plays a critical role in molding midlevel visual representations for perceptual decisions. Combining behavioral and brain imaging measurements, we demonstrate that learning optimizes feature binding for object recognition in cluttered scenes, and tunes the neural representations of informative image parts to support efficient categorical judgements. Our findings indicate that similar learning mechanisms may mediate long-term optimization through development, tune the visual system to fundamental principles of feature binding, and optimize feature templates for perceptual decisions. PMID:26024511

  10. Social provocation modulates decision making and feedback processing: Examining the trajectory of development in adolescent participants.

    PubMed

    Pincham, Hannah L; Wu, Claire; Killikelly, Clare; Vuillier, Laura; Fearon, R M Pasco

    2015-10-01

    Increasingly, research is turning to the ways in which social context impacts decision making and feedback processing in adolescents. The current study recorded electroencephalography to examine the trajectory of development across adolescence, with a focus on how social context impacts cognition and behaviour. To that end, younger (10-12 years) and older (14-16 years) adolescents played a modified Taylor Aggression Paradigm against two virtual opponents: a low-provoker and a high-provoker. During the task's decision phase (where participants select punishment for their opponent), we examined two event-related potentials: the N2 and the late positive potential (LPP). During the outcome phase (where participants experience win or loss feedback), we measured the feedback related negativity (FRN). Although N2 amplitudes did not vary with provocation, LPP amplitudes were enhanced under high provocation for the younger group, suggesting that emotional reactivity during the decision phase was heightened for early adolescents. During the outcome phase, the FRN was reduced following win outcomes under high provocation for both groups, suggesting that a highly provocative social opponent may influence the reward response. Collectively, the data argue that social context is an important factor modulating neural responses in adolescent behavioural and brain development.

  11. Decision Feedback Partial Response Maximum Likelihood for Super-Resolution Media

    NASA Astrophysics Data System (ADS)

    Kasahara, Ryosuke; Ogata, Tetsuya; Kawasaki, Toshiyuki; Miura, Hiroshi; Yokoi, Kenya

    2007-06-01

    A decision feedback partial response maximum likelihood (PRML) for super-resolution media was developed. Decision feedback is used to compensate for nonlinear distortion in the readout signals of super-resolution media, making it possible to compensate for long-bit nonlinear distortion in small circuits. An field programmable gate array (FPGA) was fabricated with a decision feedback PRML, and a real-time bit error rate (bER) measuring system was developed. As a result, a bER of 4× 10-5 was achieved with an actual readout signal at the double density of a Blu-ray disc converted to the optical properties of the experimental setup using a red-laser system. Also, a bER of 1.5× 10-5 was achieved at double the density of an a high definition digital versatile disc read-only memory (HD DVD-ROM), and the radial and tangential tilt margins were measured in a blue-laser system.

  12. Online adaptive decision fusion framework based on projections onto convex sets with application to wildfire detection in video

    NASA Astrophysics Data System (ADS)

    Günay, Osman; Töreyin, Behcet Uǧur; Çetin, Ahmet Enis

    2011-07-01

    In this paper, an online adaptive decision fusion framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several sub-algorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular sub-algorithm. Decision values are linearly combined with weights that are updated online according to an active fusion method based on performing orthogonal projections onto convex sets describing sub-algorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video-based wildfire detection system is developed to evaluate the performance of the algorithm in handling the problems where data arrives sequentially. In this case, the oracle is the security guard of the forest lookout tower verifying the decision of the combined algorithm. Simulation results are presented.

  13. Antithetic Integral Feedback Ensures Robust Perfect Adaptation in Noisy Biomolecular Networks.

    PubMed

    Briat, Corentin; Gupta, Ankit; Khammash, Mustafa

    2016-01-27

    The ability to adapt to stimuli is a defining feature of many biological systems and critical to maintaining homeostasis. While it is well appreciated that negative feedback can be used to achieve homeostasis when networks behave deterministically, the effect of noise on their regulatory function is not understood. Here, we combine probability and control theory to develop a theory of biological regulation that explicitly takes into account the noisy nature of biochemical reactions. We introduce tools for the analysis and design of robust homeostatic circuits and propose a new regulation motif, which we call antithetic integral feedback. This motif exploits stochastic noise, allowing it to achieve precise regulation in scenarios where similar deterministic regulation fails. Specifically, antithetic integral feedback preserves the stability of the overall network, steers the population of any regulated species to a desired set point, and adapts perfectly. We suggest that this motif may be prevalent in endogenous biological circuits and useful when creating synthetic circuits. PMID:27136686

  14. Adaptive optimal stochastic state feedback control of resistive wall modes in tokamaks

    SciTech Connect

    Sun, Z.; Sen, A.K.; Longman, R.W.

    2006-01-15

    An adaptive optimal stochastic state feedback control is developed to stabilize the resistive wall mode (RWM) instability in tokamaks. The extended least-square method with exponential forgetting factor and covariance resetting is used to identify (experimentally determine) the time-varying stochastic system model. A Kalman filter is used to estimate the system states. The estimated system states are passed on to an optimal state feedback controller to construct control inputs. The Kalman filter and the optimal state feedback controller are periodically redesigned online based on the identified system model. This adaptive controller can stabilize the time-dependent RWM in a slowly evolving tokamak discharge. This is accomplished within a time delay of roughly four times the inverse of the growth rate for the time-invariant model used.

  15. Feedback.

    ERIC Educational Resources Information Center

    Stenstrom, Anna-Brita

    A study of feedback in conversational question-response exchanges focused on the questioner's feedback to the respondent. It examined three types of "followup" moves: the ordinary type revealing the questioner's attitude to the response and closing the exchange; the type signaling the questioner's reaction to the response and inviting further…

  16. How Does the Brain Implement Adaptive Decision Making to Eat?

    PubMed Central

    Walsh, B. Timothy; Kaye, Walter; Geliebter, Allan

    2015-01-01

    Adaptive decision making to eat is crucial for survival, but in anorexia nervosa, the brain persistently supports reduced food intake despite a growing need for energy. How the brain persists in reducing food intake, sometimes even to the point of death and despite the evolution of multiple mechanisms to ensure survival by governing adaptive eating behaviors, remains mysterious. Neural substrates belong to the reward-habit system, which could differ among the eating disorders. The present review provides an overview of neural circuitry of restrictive food choice, binge eating, and the contribution of specific serotonin receptors. One possibility is that restrictive food intake critically engages goal-directed (decision making) systems and “habit,” supporting the view that persistent caloric restriction mimics some aspects of addiction to drugs of abuse. SIGNIFICANCE STATEMENT An improved understanding of the neural basis of eating disorders is a timely challenge because these disorders can be deadly. Up to 70 million of people in the world suffer from eating disorders. Anorexia nervosa affects 1–4% of women in United States and is the first cause of death among adolescents in Europe. Studies relying on animal models suggest that decision making to eat (or not) can prevail over actual energy requirements due to emotional disturbances resulting in abnormal habitual behavior, mimicking dependence. These recent studies provide a foundation for developing more specific and effective interventions for these disorders. PMID:26468187

  17. New synchronization criteria for memristor-based networks: adaptive control and feedback control schemes.

    PubMed

    Li, Ning; Cao, Jinde

    2015-01-01

    In this paper, we investigate synchronization for memristor-based neural networks with time-varying delay via an adaptive and feedback controller. Under the framework of Filippov's solution and differential inclusion theory, and by using the adaptive control technique and structuring a novel Lyapunov functional, an adaptive updated law was designed, and two synchronization criteria were derived for memristor-based neural networks with time-varying delay. By removing some of the basic literature assumptions, the derived synchronization criteria were found to be more general than those in existing literature. Finally, two simulation examples are provided to illustrate the effectiveness of the theoretical results.

  18. New synchronization criteria for memristor-based networks: adaptive control and feedback control schemes.

    PubMed

    Li, Ning; Cao, Jinde

    2015-01-01

    In this paper, we investigate synchronization for memristor-based neural networks with time-varying delay via an adaptive and feedback controller. Under the framework of Filippov's solution and differential inclusion theory, and by using the adaptive control technique and structuring a novel Lyapunov functional, an adaptive updated law was designed, and two synchronization criteria were derived for memristor-based neural networks with time-varying delay. By removing some of the basic literature assumptions, the derived synchronization criteria were found to be more general than those in existing literature. Finally, two simulation examples are provided to illustrate the effectiveness of the theoretical results. PMID:25299765

  19. Learning from adaptive neural network output feedback control of a unicycle-type mobile robot.

    PubMed

    Zeng, Wei; Wang, Qinghui; Liu, Fenglin; Wang, Ying

    2016-03-01

    This paper studies learning from adaptive neural network (NN) output feedback control of nonholonomic unicycle-type mobile robots. The major difficulties are caused by the unknown robot system dynamics and the unmeasurable states. To overcome these difficulties, a new adaptive control scheme is proposed including designing a new adaptive NN output feedback controller and two high-gain observers. It is shown that the stability of the closed-loop robot system and the convergence of tracking errors are guaranteed. The unknown robot system dynamics can be approximated by radial basis function NNs. When repeating same or similar control tasks, the learned knowledge can be recalled and reused to achieve guaranteed stability and better control performance, thereby avoiding the tremendous repeated training process of NNs. PMID:26830003

  20. Learning from adaptive neural network output feedback control of a unicycle-type mobile robot.

    PubMed

    Zeng, Wei; Wang, Qinghui; Liu, Fenglin; Wang, Ying

    2016-03-01

    This paper studies learning from adaptive neural network (NN) output feedback control of nonholonomic unicycle-type mobile robots. The major difficulties are caused by the unknown robot system dynamics and the unmeasurable states. To overcome these difficulties, a new adaptive control scheme is proposed including designing a new adaptive NN output feedback controller and two high-gain observers. It is shown that the stability of the closed-loop robot system and the convergence of tracking errors are guaranteed. The unknown robot system dynamics can be approximated by radial basis function NNs. When repeating same or similar control tasks, the learned knowledge can be recalled and reused to achieve guaranteed stability and better control performance, thereby avoiding the tremendous repeated training process of NNs.

  1. Effects of Strong Interest Inventory Feedback on Career Decision-Making Self-Efficacy and Social Cognitive Career Beliefs.

    ERIC Educational Resources Information Center

    Luzzo, Darrell Anthony; Day, Michael Andrew

    1999-01-01

    College students were assigned to three groups: Strong Interest Inventory (SII) plus social cognitive group feedback (n=52), SII only (n=22), and controls (n=25). The feedback group had higher career decision-making self-efficacy and more differentiated career beliefs than the SII-only group. Both SII groups were more likely to see the…

  2. Adaptive feedback potential in dynamic stability during disturbed walking in the elderly.

    PubMed

    Bierbaum, Stefanie; Peper, Andreas; Karamanidis, Kiros; Arampatzis, Adamantios

    2011-07-01

    After perturbation of the gait, feedback information may help regaining balance adequately, but it remains unknown whether adaptive feedback responses are possible after repetitive and unexpected perturbations during gait and if there are age-related differences. Prior experience may contribute to improved reactive behavior. Fourteen old (59-73 yrs) and fourteen young (22-31 yrs) males walked on a walkway which included one covered element. By exchanging this element participants either stepped on hard surface or unexpectedly on soft surface which caused a perturbation in gait. The gait protocol contained 5 unexpected soft trials to quantify the reactive adaptation. Each soft trial was followed by 4-8 hard trials to generate a wash-out effect. The dynamic stability was investigated by using the margin of stability (MoS), which was calculated as the difference between the anterior boundary of the base of support and the extrapolated position of the center of mass in the anterior-posterior direction. MoS at recovery leg touchdown were significantly lower in the unexpected soft trials compared to the baseline, indicating a less stable posture. However, MoS increased (p<0.05) in both groups within the disturbed trials, indicating feedback adaptive improvements. Young and old participants showed differences in the handling of the perturbation in the course of several trials. The magnitude of the reactive adaptation after the fifth unexpected perturbation was significantly different compared to the first unexpected perturbation (old: 49±30%; young: 77±40%), showing a tendency (p=0.065) for higher values in the young participants. Old individuals maintain the ability to adapt to feedback controlled perturbations. However, the locomotor behavior is more conservative compared to the young ones, leading to disadvantages in the reactive adaptation during disturbed walking.

  3. Integrated Decision Support for Global Environmental Change Adaptation

    NASA Astrophysics Data System (ADS)

    Kumar, S.; Cantrell, S.; Higgins, G. J.; Marshall, J.; VanWijngaarden, F.

    2011-12-01

    Environmental changes are happening now that has caused concern in many parts of the world; particularly vulnerable are the countries and communities with limited resources and with natural environments that are more susceptible to climate change impacts. Global leaders are concerned about the observed phenomena and events such as Amazon deforestation, shifting monsoon patterns affecting agriculture in the mountain slopes of Peru, floods in Pakistan, water shortages in Middle East, droughts impacting water supplies and wildlife migration in Africa, and sea level rise impacts on low lying coastal communities in Bangladesh. These environmental changes are likely to get exacerbated as the temperatures rise, the weather and climate patterns change, and sea level rise continues. Large populations and billions of dollars of infrastructure could be affected. At Northrop Grumman, we have developed an integrated decision support framework for providing necessary information to stakeholders and planners to adapt to the impacts of climate variability and change at the regional and local levels. This integrated approach takes into account assimilation and exploitation of large and disparate weather and climate data sets, regional downscaling (dynamic and statistical), uncertainty quantification and reduction, and a synthesis of scientific data with demographic and economic data to generate actionable information for the stakeholders and decision makers. Utilizing a flexible service oriented architecture and state-of-the-art visualization techniques, this information can be delivered via tailored GIS portals to meet diverse set of user needs and expectations. This integrated approach can be applied to regional and local risk assessments, predictions and decadal projections, and proactive adaptation planning for vulnerable communities. In this paper we will describe this comprehensive decision support approach with selected applications and case studies to illustrate how this

  4. Fuzzy Multicriteria Decision Analysis for Adaptive Watershed Management

    NASA Astrophysics Data System (ADS)

    Chang, N.

    2006-12-01

    The dramatic changes of societal complexity due to intensive interactions among agricultural, industrial, and municipal sectors have resulted in acute issues of water resources redistribution and water quality management in many river basins. Given the fact that integrated watershed management is more a political and societal than a technical challenge, there is a need for developing a compelling method leading to justify a water-based land use program in some critical regions. Adaptive watershed management is viewed as an indispensable tool nowadays for providing step-wise constructive decision support that is concerned with all related aspects of the water consumption cycle and those facilities affecting water quality and quantity temporally and spatially. Yet the greatest challenge that decision makers face today is to consider how to leverage ambiguity, paradox, and uncertainty to their competitive advantage of management policy quantitatively. This paper explores a fuzzy multicriteria evaluation method for water resources redistribution and subsequent water quality management with respect to a multipurpose channel-reservoir system--the Tseng- Wen River Basin, South Taiwan. Four fuzzy operators tailored for this fuzzy multicriteria decision analysis depict greater flexibility in representing the complexity of various possible trade-offs among management alternatives constrained by physical, economic, and technical factors essential for adaptive watershed management. The management strategies derived may enable decision makers to integrate a vast number of internal weirs, water intakes, reservoirs, drainage ditches, transfer pipelines, and wastewater treatment facilities within the basin and bring up the permitting issue for transboundary diversion from a neighboring river basin. Experience gained indicates that the use of different types of fuzzy operators is highly instructive, which also provide unique guidance collectively for achieving the overarching goals

  5. Combination of spatial diversity and parallel decision feedback equalizer in a Single Input Multiple Output underwater acoustic communication system operating at very high frequencies

    NASA Astrophysics Data System (ADS)

    Skoro Kaskarovska, Violeta; Beaujean, Pierre-Philippe

    2013-05-01

    Single Input Multiple Output (SIMO) acoustic communication system using an adaptive spatial diversity combined with parallel Decision Feedback Equalizer (DFE) is presented in this document. The SIMO system operates at high frequencies with high data rate over a limited range (less than 200 m) in very shallow waters. The SIMO system consists of a single source transmitting Phase Shift Keying (PSK) messages modulated at 300 kHz and received by multiple receivers. In a first configuration, the symbols collected at each receiver are equalized using a decision feedback equalizer and combined using Maximum Ratio Combining (MRC). In a second configuration, the MRC outputs are used as decision symbols in the DFE. This second configuration is a form of turbo equalization: the process can be repeated over and over, leading to a better estimate of the received message as the number of iterations increases. The adaptive process of diversity is repeated until the best possible result is achieved or a predefined error criterion is met. Bit Error Rate (BER) and Signal-to-Noise-and-Interference Ratio (SNIR) are used as performance metrics of the acoustic channel. Experimental results using SIMO system with three, four or five receivers and pre-processed real recorded data demonstrate ability to improve the performance of the acoustic channel in challenging environments. Using received messages with non-zero BER, adaptive spatial diversity can achieve BER of 0% and increased SNIR of 3 dB with number of iterations depending on the number of receivers used.

  6. An epidemic spreading model on adaptive scale-free networks with feedback mechanism

    NASA Astrophysics Data System (ADS)

    Li, Tao; Liu, Xiongding; Wu, Jie; Wan, Chen; Guan, Zhi-Hong; Wang, Yuanmei

    2016-05-01

    A SIRS epidemic model with feedback mechanism on adaptive scale-free networks is presented. Using the mean field theory the spreading dynamics of the epidemic is studied in detail. The basic reproductive number and equilibriums are derived. Theoretical results indicate that the basic reproductive number is significantly dependent on the topology of the underlying networks. The existence of equilibriums is determined by the basic reproductive number. The global stability of disease-free equilibrium and the epidemic permanence are proved in detail. The feedback mechanism cannot change the basic reproductive number, but it can reduce the endemic level and weaken the epidemic spreading. Numerical simulations confirmed the analytical results.

  7. Global adaptive output feedback control for a class of nonlinear time-delay systems.

    PubMed

    Zhai, Jun-yong; Zha, Wen-ting

    2014-01-01

    This paper addresses the problem of global output feedback control for a class of nonlinear time-delay systems. The nonlinearities are dominated by a triangular form satisfying linear growth condition in the unmeasurable states with an unknown growth rate. With a change of coordinates, a linear-like controller is constructed, which avoids the repeated derivatives of the nonlinearities depending on the observer states and the dynamic gain in backstepping approach and therefore, simplifies the design procedure. Using the idea of universal control, we explicitly construct a universal-type adaptive output feedback controller which globally regulates all the states of the nonlinear time-delay systems.

  8. 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.

  9. The role of time delay in adaptive cellular negative feedback systems.

    PubMed

    Lapytsko, Anastasiya; Schaber, Jörg

    2016-06-01

    Adaptation in cellular systems is often mediated by negative feedbacks, which usually come with certain time delays causing several characteristic response patterns including an overdamped response, damped or sustained oscillations. Here, we analyse generic two-dimensional delay differential equations with delayed negative feedback describing the dynamics of biochemical adaptive signal-response networks. We derive explicit thresholds and boundaries showing how time delay determines characteristic response patterns of these networks. Applying our theoretical analyses to concrete data we show that adaptation to osmotic stress in yeast is optimal in the sense of minimizing adaptation time without causing oscillatory behaviour, i.e., a critically damped response. In addition, our framework demonstrates that a slight increase of time delay in the NF-κB system might induce a switch from damped to sustained oscillatory behaviour. Thus, we demonstrate how delay differential equations can be used to explicitly study the delay in biochemical negative feedback systems. Our analysis also provides insight into how time delay may tune biological signal-response patterns and control the systems behaviour.

  10. Improved methods in neural network-based adaptive output feedback control, with applications to flight control

    NASA Astrophysics Data System (ADS)

    Kim, Nakwan

    Utilizing the universal approximation property of neural networks, we develop several novel approaches to neural network-based adaptive output feedback control of nonlinear systems, and illustrate these approaches for several flight control applications. In particular, we address the problem of non-affine systems and eliminate the fixed point assumption present in earlier work. All of the stability proofs are carried out in a form that eliminates an algebraic loop in the neural network implementation. An approximate input/output feedback linearizing controller is augmented with a neural network using input/output sequences of the uncertain system. These approaches permit adaptation to both parametric uncertainty and unmodeled dynamics. All physical systems also have control position and rate limits, which may either deteriorate performance or cause instability for a sufficiently high control bandwidth. Here we apply a method for protecting an adaptive process from the effects of input saturation and time delays, known as "pseudo control hedging". This method was originally developed for the state feedback case, and we provide a stability analysis that extends its domain of applicability to the case of output feedback. The approach is illustrated by the design of a pitch-attitude flight control system for a linearized model of an R-50 experimental helicopter, and by the design of a pitch-rate control system for a 58-state model of a flexible aircraft consisting of rigid body dynamics coupled with actuator and flexible modes. A new approach to augmentation of an existing linear controller is introduced. It is especially useful when there is limited information concerning the plant model, and the existing controller. The approach is applied to the design of an adaptive autopilot for a guided munition. Design of a neural network adaptive control that ensures asymptotically stable tracking performance is also addressed.

  11. A decision analysis approach to climate adaptation: comparing multiple pathways for multi-decadal decision making

    NASA Astrophysics Data System (ADS)

    Lin, B. B.; Little, L.

    2013-12-01

    Policy planners around the world are required to consider the implications of adapting to climatic change across spatial contexts and decadal timeframes. However, local level information for planning is often poorly defined, even though climate adaptation decision-making is made at this scale. This is especially true when considering sea level rise and coastal impacts of climate change. We present a simple approach using sea level rise simulations paired with adaptation scenarios to assess a range of adaptation options available to local councils dealing with issues of beach recession under present and future sea level rise and storm surge. Erosion and beach recession pose a large socioeconomic risk to coastal communities because of the loss of key coastal infrastructure. We examine the well-known adaptation technique of beach nourishment and assess various timings and amounts of beach nourishment at decadal time spans in relation to beach recession impacts. The objective was to identify an adaptation strategy that would allow for a low frequency of management interventions, the maintenance of beach width, and the ability to minimize variation in beach width over the 2010 to 2100 simulation period. 1000 replications of each adaptation option were produced against the 90 year simulation in order to model the ability each adaptation option to achieve the three key objectives. Three sets of adaptation scenarios were identified. Within each scenario, a number of adaptation options were tested. The three scenarios were: 1) Fixed periodic beach replenishment of specific amounts at 20 and 50 year intervals, 2) Beach replenishment to the initial beach width based on trigger levels of recession (5m, 10m, 20m), and 3) Fixed period beach replenishment of a variable amount at decadal intervals (every 10, 20, 30, 40, 50 years). For each adaptation option, we show the effectiveness of each beach replenishment scenario to maintain beach width and consider the implications of more

  12. Blunted feedback processing during risky decision making in adolescents with a parental history of substance use disorders.

    PubMed

    Euser, Anja S; Greaves-Lord, Kirstin; Crowley, Michael J; Evans, Brittany E; Huizink, Anja C; Franken, Ingmar H A

    2013-11-01

    Risky decision making, a hallmark phenotype of substance use disorders (SUD), is thought to be associated with deficient feedback processing. Whether these aberrations are present prior to SUD onset or reflect merely a consequence of chronic substance use on the brain remains unclear. The present study investigated whether blunted feedback processing during risky decision making reflects a biological predisposition to SUD. We assessed event-related potentials elicited by positive and negative feedback during performance of a modified version of the Balloon Analogue Risk Task (BART) among high-risk adolescents with a parental history of SUD (HR; n = 61) and normal-risk controls (NR; n = 91). HR males made significantly more risky and faster decisions during the BART than did NR controls. Moreover, HR adolescents showed significantly reduced P300 amplitudes in response to both positive and negative feedback as compared to NR controls. These differences were not secondary to prolonged substance use exposure. Results are discussed in terms of feedback-specific processes. Reduced P300 amplitudes in the BART may reflect poor processing of feedback at the level of overall salience, which may keep people from effectively predicting the probability of future gains and losses. Though conclusions are tentative, blunted feedback processing during risky decision making may represent a promising endophenotypic vulnerability marker for SUD. PMID:24229553

  13. Vibration suppression for large scale adaptive truss structures using direct output feedback control

    NASA Technical Reports Server (NTRS)

    Lu, Lyan-Ywan; Utku, Senol; Wada, Ben K.

    1993-01-01

    In this article, the vibration control of adaptive truss structures, where the control actuation is provided by length adjustable active members, is formulated as a direct output feedback control problem. A control method named Model Truncated Output Feedback (MTOF) is presented. The method allows the control feedback gain to be determined in a decoupled and truncated modal space in which only the critical vibration modes are retained. The on-board computation required by MTOF is minimal; thus, the method is favorable for the applications of vibration control of large scale structures. The truncation of the modal space inevitably introduces spillover effect during the control process. In this article, the effect is quantified in terms of active member locations, and it is shown that the optimal placement of active members, which minimizes the spillover effect (and thus, maximizes the control performance) can be sought. The problem of optimally selecting the locations of active members is also treated.

  14. Homeostatic Regulation of Memory Systems and Adaptive Decisions

    PubMed Central

    Mizumori, Sheri JY; Jo, Yong Sang

    2013-01-01

    While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The “multiple memory systems of the brain” have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result

  15. Adaptive awareness for personal and small group decision making.

    SciTech Connect

    Perano, Kenneth J.; Tucker, Steve; Pancerella, Carmen M.; Doser, Adele Beatrice; Berry, Nina M.; Kyker, Ronald D.

    2003-12-01

    Many situations call for the use of sensors monitoring physiological and environmental data. In order to use the large amounts of sensor data to affect decision making, we are coupling heterogeneous sensors with small, light-weight processors, other powerful computers, wireless communications, and embedded intelligent software. The result is an adaptive awareness and warning tool, which provides both situation awareness and personal awareness to individuals and teams. Central to this tool is a sensor-independent architecture, which combines both software agents and a reusable core software framework that manages the available hardware resources and provides services to the agents. Agents can recognize cues from the data, warn humans about situations, and act as decision-making aids. Within the agents, self-organizing maps (SOMs) are used to process physiological data in order to provide personal awareness. We have employed a novel clustering algorithm to train the SOM to discern individual body states and activities. This awareness tool has broad applicability to emergency teams, military squads, military medics, individual exercise and fitness monitoring, health monitoring for sick and elderly persons, and environmental monitoring in public places. This report discusses our hardware decisions, software framework, and a pilot awareness tool, which has been developed at Sandia National Laboratories.

  16. Impact of Web Searching and Social Feedback on Consumer Decision Making: A Prospective Online Experiment

    PubMed Central

    Lau, Annie YS

    2008-01-01

    Background The World Wide Web has increasingly become an important source of information in health care consumer decision making. However, little is known about whether searching online resources actually improves consumers’ understanding of health issues. Objectives The aim was to study whether searching on the World Wide Web improves consumers’ accuracy in answering health questions and whether consumers’ understanding of health issues is subject to further change under social feedback. Methods This was a pre/post prospective online study. A convenience sample of 227 undergraduate students was recruited from the population of the University of New South Wales. Subjects used a search engine that retrieved online documents from PubMed, MedlinePlus, and HealthInsite and answered a set of six questions (before and after use of the search engine) designed for health care consumers. They were then presented with feedback consisting of a summary of the post-search answers provided by previous subjects for the same questions and were asked to answer the questions again. Results There was an improvement in the percentage of correct answers after searching (pre-search 61.2% vs post-search 82.0%, P <.001) and after feedback with other subjects’ answers (pre-feedback 82.0% vs post-feedback 85.3%, P =.051).The proportion of subjects with highly confident correct answers (ie, confident or very confident) and the proportion with highly confident incorrect answers significantly increased after searching (correct pre-search 61.6% vs correct post-search 95.5%, P <.001; incorrect pre-search 55.3% vs incorrect post-search 82.0%, P <.001). Subjects who were not as confident in their post-search answers were 28.5% more likely than those who were confident or very confident to change their answer after feedback with other subjects’ post-search answers (χ 2 1= 66.65, P <.001). Conclusions Searching across quality health information sources on the Web can improve consumers

  17. The Effects of Feedback in Computerized Adaptive and Self-Adapted Tests.

    ERIC Educational Resources Information Center

    Roos, Linda L.; And Others

    Computerized adaptive (CA) testing uses an algorithm to match examinee ability to item difficulty, while self-adapted (SA) testing allows the examinee to choose the difficulty of his or her items. Research comparing SA and CA testing has shown that examinees experience lower anxiety and improved performance with SA testing. All previous research…

  18. CSI feedback-based CS for underwater acoustic adaptive modulation OFDM system with channel prediction

    NASA Astrophysics Data System (ADS)

    Kuai, Xiao-yan; Sun, Hai-xin; Qi, Jie; Cheng, En; Xu, Xiao-ka; Guo, Yu-hui; Chen, You-gan

    2014-06-01

    In this paper, we investigate the performance of adaptive modulation (AM) orthogonal frequency division multiplexing (OFDM) system in underwater acoustic (UWA) communications. The aim is to solve the problem of large feedback overhead for channel state information (CSI) in every subcarrier. A novel CSI feedback scheme is proposed based on the theory of compressed sensing (CS). We propose a feedback from the receiver that only feedback the sparse channel parameters. Additionally, prediction of the channel state is proposed every several symbols to realize the AM in practice. We describe a linear channel prediction algorithm which is used in adaptive transmission. This system has been tested in the real underwater acoustic channel. The linear channel prediction makes the AM transmission techniques more feasible for acoustic channel communications. The simulation and experiment show that significant improvements can be obtained both in bit error rate (BER) and throughput in the AM scheme compared with the fixed Quadrature Phase Shift Keying (QPSK) modulation scheme. Moreover, the performance with standard CS outperforms the Discrete Cosine Transform (DCT) method.

  19. Adaptive femtosecond control using feedback from three-dimensional momentum images

    NASA Astrophysics Data System (ADS)

    Wells, E.

    2011-05-01

    Shaping ultrafast laser pulses using adaptive feedback is a proven technique for manipulating dynamics in molecular systems with no readily apparent control mechanism. Commonly employed feedback signals include fluorescence or ion yield, which may not uniquely identify the final state. Raw velocity map images, which contain a two-dimensional representation of the full three-dimensional photofragment momentum vector, are a more specific feedback source. The raw images, however, are limited by an azimuthal ambiguity which is usually removed in offline processing. By implementing a rapid inversion procedure based upon the onion-peeling technique, we are able to incorporate three-dimensional momentum information directly into the adaptive control loop. This method enables more targeted control experiments. Two examples are used to demonstrate the utility of this feedback. First, double ionization of CO produces C+ and O+ fragments ejected both perpendicular and parallel to the laser polarization with kinetic energy release of ~6 eV. Both suppression and enhancement of the perpendicular transitions relative to the parallel transitions are demonstrated. Second, double ionization of acetylene can lead to both HCCH2+ and HHCC2+ isomers. We select between these outcomes using the angular information contained in the CH+ and CH2+images. Supported by National Science Foundation award PHY-0969687 and the Chemical Sciences, Geosciences, and Biosciences Division, Office of Basic Energy Science, Office of Science, US Department of Energy.

  20. Adaptive neural control for a class of perturbed strict-feedback nonlinear time-delay systems.

    PubMed

    Wang, Min; Chen, Bing; Shi, Peng

    2008-06-01

    This paper proposes a novel adaptive neural control scheme for a class of perturbed strict-feedback nonlinear time-delay systems with unknown virtual control coefficients. Based on the radial basis function neural network online approximation capability, an adaptive neural controller is presented by combining the backstepping approach and Lyapunov-Krasovskii functionals. The proposed controller guarantees the semiglobal boundedness of all the signals in the closed-loop system and contains minimal learning parameters. Finally, three simulation examples are given to demonstrate the effectiveness and applicability of the proposed scheme.

  1. Toolbox or Adjustable Spanner? A Critical Comparison of Two Metaphors for Adaptive Decision Making

    ERIC Educational Resources Information Center

    Söllner, Anke; Bröder, Arndt

    2016-01-01

    For multiattribute decision tasks, different metaphors exist that describe the process of decision making and its adaptation to diverse problems and situations. Multiple strategy models (MSMs) assume that decision makers choose adaptively from a set of different strategies (toolbox metaphor), whereas evidence accumulation models (EAMs) hold that a…

  2. Sensory and decision-related activity propagate in a cortical feedback loop during touch perception.

    PubMed

    Kwon, Sung Eun; Yang, Hongdian; Minamisawa, Genki; O'Connor, Daniel H

    2016-09-01

    The brain transforms physical sensory stimuli into meaningful perceptions. In animals making choices about sensory stimuli, neuronal activity in successive cortical stages reflects a progression from sensation to decision. Feedforward and feedback pathways connecting cortical areas are critical for this transformation. However, the computational functions of these pathways are poorly understood because pathway-specific activity has rarely been monitored during a perceptual task. Using cellular-resolution, pathway-specific imaging, we measured neuronal activity across primary (S1) and secondary (S2) somatosensory cortices of mice performing a tactile detection task. S1 encoded the stimulus better than S2, while S2 activity more strongly reflected perceptual choice. S1 neurons projecting to S2 fed forward activity that predicted choice. Activity encoding touch and choice propagated in an S1-S2 loop along feedforward and feedback axons. Our results suggest that sensory inputs converge into a perceptual outcome as feedforward computations are reinforced in a feedback loop. PMID:27437910

  3. Peaking-Free Output-Feedback Adaptive Neural Control Under a Nonseparation Principle.

    PubMed

    Pan, Yongping; Sun, Tairen; Yu, Haoyong

    2015-12-01

    High-gain observers have been extensively applied to construct output-feedback adaptive neural control (ANC) for a class of feedback linearizable uncertain nonlinear systems under a nonlinear separation principle. Yet due to static-gain and linear properties, high-gain observers are usually subject to peaking responses and noise sensitivity. Existing adaptive neural network (NN) observers cannot effectively relax the limitations of high-gain observers. This paper presents an output-feedback indirect ANC strategy under a nonseparation principle, where a hybrid estimation scheme that integrates an adaptive NN observer with state variable filters is proposed to estimate plant states. By applying a single Lyapunov function candidate to the entire system, it is proved that the closed-loop system achieves practical asymptotic stability under a relatively low observer gain dominated by controller parameters. Our approach can completely avoid peaking responses without control saturation while keeping favourable noise rejection ability. Simulation results have shown effectiveness and superiority of this approach.

  4. Monitoring in the context of structured decision-making and adaptive management

    USGS Publications Warehouse

    Lyons, J.E.; Runge, M.C.; Laskowski, H.P.; Kendall, W.L.

    2008-01-01

    In a natural resource management setting, monitoring is a crucial component of an informed process for making decisions, and monitoring design should be driven by the decision context and associated uncertainties. Monitoring itself can play >3 roles. First, it is important for state-dependent decision-making, as when managers need to know the system state before deciding on the appropriate course of action during the ensuing management cycle. Second, monitoring is critical for evaluating the effectiveness of management actions relative to objectives. Third, in an adaptive management setting, monitoring provides the feedback loop for learning about the system; learning is sought not for its own sake but primarily to better achieve management objectives. In this case, monitoring should be designed to reduce the critical uncertainties in models of the managed system. The United States Geological Survey and United States Fish and Wildlife Service are conducting a large-scale management experiment on 23 National Wildlife Refuges across the Northeast and Midwest Regions. The primary management objective is to provide habitat for migratory waterbirds, particularly during migration, using water-level manipulations in managed wetlands. Key uncertainties are related to the potential trade-offs created by management for a specific waterbird guild (e.g., migratory shorebirds) and the response of waterbirds, plant communities, and invertebrates to specific experimental hydroperiods. We reviewed the monitoring program associated with this study, and the ways that specific observations fill >1 of the roles identified above. We used observations from our monitoring to improve state-dependent decisions to control undesired plants, to evaluate management performance relative to shallow-water habitat objectives, and to evaluate potential trade-offs between waterfowl and shorebird habitat management. With limited staff and budgets, management agencies need efficient monitoring

  5. Implementation of an Automated Grading System with an Adaptive Learning Component to Affect Student Feedback and Response Time

    ERIC Educational Resources Information Center

    Matthews, Kevin; Janicki, Thomas; He, Ling; Patterson, Laurie

    2012-01-01

    This research focuses on the development and implementation of an adaptive learning and grading system with a goal to increase the effectiveness and quality of feedback to students. By utilizing various concepts from established learning theories, the goal of this research is to improve the quantity, quality, and speed of feedback as it pertains…

  6. Adaptive Fuzzy Control of Strict-Feedback Nonlinear Time-Delay Systems With Unmodeled Dynamics.

    PubMed

    Yin, Shen; Shi, Peng; Yang, Hongyan

    2016-08-01

    In this paper, an approximated-based adaptive fuzzy control approach with only one adaptive parameter is presented for a class of single input single output strict-feedback nonlinear systems in order to deal with phenomena like nonlinear uncertainties, unmodeled dynamics, dynamic disturbances, and unknown time delays. Lyapunov-Krasovskii function approach is employed to compensate the unknown time delays in the design procedure. By combining the advances of the hyperbolic tangent function with adaptive fuzzy backstepping technique, the proposed controller guarantees the semi-globally uniformly ultimately boundedness of all the signals in the closed-loop system from the mean square point of view. Two simulation examples are finally provided to show the superior effectiveness of the proposed scheme.

  7. Spatially Common Sparsity Based Adaptive Channel Estimation and Feedback for FDD Massive MIMO

    NASA Astrophysics Data System (ADS)

    Gao, Zhen; Dai, Linglong; Wang, Zhaocheng; Chen, Sheng

    2015-12-01

    This paper proposes a spatially common sparsity based adaptive channel estimation and feedback scheme for frequency division duplex based massive multi-input multi-output (MIMO) systems, which adapts training overhead and pilot design to reliably estimate and feed back the downlink channel state information (CSI) with significantly reduced overhead. Specifically, a non-orthogonal downlink pilot design is first proposed, which is very different from standard orthogonal pilots. By exploiting the spatially common sparsity of massive MIMO channels, a compressive sensing (CS) based adaptive CSI acquisition scheme is proposed, where the consumed time slot overhead only adaptively depends on the sparsity level of the channels. Additionally, a distributed sparsity adaptive matching pursuit algorithm is proposed to jointly estimate the channels of multiple subcarriers. Furthermore, by exploiting the temporal channel correlation, a closed-loop channel tracking scheme is provided, which adaptively designs the non-orthogonal pilot according to the previous channel estimation to achieve an enhanced CSI acquisition. Finally, we generalize the results of the multiple-measurement-vectors case in CS and derive the Cramer-Rao lower bound of the proposed scheme, which enlightens us to design the non-orthogonal pilot signals for the improved performance. Simulation results demonstrate that the proposed scheme outperforms its counterparts, and it is capable of approaching the performance bound.

  8. A simplified adaptive neural network prescribed performance controller for uncertain MIMO feedback linearizable systems.

    PubMed

    Theodorakopoulos, Achilles; Rovithakis, George A

    2015-03-01

    In this paper, the problem of deriving a continuous, state-feedback controller for a class of multiinput multioutput feedback linearizable systems is considered with special emphasis on controller simplification and reduction of the overall design complexity with respect to the current state of the art. The proposed scheme achieves prescribed bounds on the transient and steady-state performance of the output tracking errors despite the uncertainty in system nonlinearities. Contrary to the current state of the art, however, only a single neural network is utilized to approximate a scalar function that partly incorporates the system nonlinearities. Furthermore, the loss of model controllability problem, typically introduced owing to approximation model singularities, is avoided without attaching additional complexity to the control or adaptive law. Simulations are performed to verify and clarify the theoretical findings.

  9. Adaptation to Coriolis force perturbation of movement trajectory; role of proprioceptive and cutaneous somatosensory feedback.

    PubMed

    Lackner, James R; DiZio, Paul

    2002-01-01

    Subjects exposed to constant velocity rotation in a large fully-enclosed room that rotates initially make large reaching errors in pointing to targets. The paths and endpoints of their reaches are deviated in the direction of the transient lateral Coriolis forces generated by the forward velocity of their reaches. With additional reaches, subjects soon reach in straighter paths and become more accurate at landing on target even in the absence of visual feedback about their movements. Two factors contribute to this adaptation: first, muscle spindle and golgi tendon organ feedback interpreted in relation to efferent commands provide information about movement trajectory, and second, somatosensory stimulation of the fingertip at the completion of a reach provides information about the location of the fingertip relative to the torso.

  10. Adaptation to Coriolis force perturbation of movement trajectory; role of proprioceptive and cutaneous somatosensory feedback

    NASA Technical Reports Server (NTRS)

    Lackner, James R.; DiZio, Paul

    2002-01-01

    Subjects exposed to constant velocity rotation in a large fully-enclosed room that rotates initially make large reaching errors in pointing to targets. The paths and endpoints of their reaches are deviated in the direction of the transient lateral Coriolis forces generated by the forward velocity of their reaches. With additional reaches, subjects soon reach in straighter paths and become more accurate at landing on target even in the absence of visual feedback about their movements. Two factors contribute to this adaptation: first, muscle spindle and golgi tendon organ feedback interpreted in relation to efferent commands provide information about movement trajectory, and second, somatosensory stimulation of the fingertip at the completion of a reach provides information about the location of the fingertip relative to the torso.

  11. Performance of a modified feedback loop adaptive array with TVRO satellite signals

    NASA Technical Reports Server (NTRS)

    Steadman, K.; Gupta, I. J.; Walton, E. K.

    1990-01-01

    The performance of an experimental adaptive antenna array system is evaluated using television-receive-only (TVRO) satellite signals. The experimental system is a sidelobe canceler with two auxiliary channels. Modified feedback loops are used to enhance the suppression of weak interfering signals. The modified feedback loops use two spatially separate antennas, each with an individual amplifier for each auxiliary channel. Thus, the experimental system uses five antenna elements. Instead of using five separate antennas, a reflector antenna with multiple feeds is used to receive signals from various TVRO satellites. The details of the earth station are given. It is shown that the experimental system can null up to two signals originating from interfering TVRO satellites while receiving the signals from a desired TVRO satellite.

  12. Proof of quasi-adaptivity for the m-measurement feedback class of stochastic control policies

    NASA Technical Reports Server (NTRS)

    Bayard, David S.

    1987-01-01

    Bounds on expected performance are established which show that the m-measurement feedback (mM) policy for nonlinear stochastic control performs as well or better than the open-loop optimal control policy, and thus is quasi-adaptive in the sense of Witenhausen (1966). The chain of performance inequalities indicate a tendency for the mM policy performance to improve with increasing m. It is suggested that the present analytical method, based on the construction of artificial control sequences denoted as utility controls, can be used to establish performance bounds on other well-known policies, avoiding the extensive Monte Carlo simulations necessary in comparing stochastic control policies.

  13. A digital feedback controller application for studying photoreceptor adaptation by 'voltage clamp by light'.

    PubMed

    Djupsund, K; Kouvalainen, E; Järvilehto, M; Weckström, M

    1995-11-01

    We present a new digital feedback application for the study of the sensitivity characteristics of photoreceptors. The amplitude of the recorded membrane voltage of a cell is steered by changing the incoming light intensity with a motor-driven circular, linear neutral-density wedge (CFW). The voltage response is sampled and fed to a software position controller of the CFW. The controller determines the position of the wedge according to the desired (command) value of the response. The light intensity changes during steady-state represent the sensitivity change, the time-course of adaptation.

  14. Parallel Multistage Decision Feedback Equalizer for Single-Carrier Layered Space-Time Systems in Frequency-Selective Channels

    NASA Astrophysics Data System (ADS)

    Xu, Jing; Wang, Haifeng; Cheng, Shixin; Chen, Ming

    2004-12-01

    Space-time transmission techniques can greatly increase the spectral efficiency. In this paper, a parallel multistage decision feedback equalizer (PMDFE) is proposed for single-carrier layered space-time systems with a fixed cyclic prefix over frequency-selective channels. It is composed of a parallel interference canceller, a multiple-input single-output decision feedback equalizer (MISO-DFE), and a linear combiner. The soft output of the MISO-DFE is linearly combined with the previous tentative soft decision. In addition, an algorithm is proposed to obtain tentative soft and hard decisions for initializing the equalizer. The initializing complexity of the PMDFE is lower than that of MIMO-OFDM. Simulation results show that the PMDFE outperforms MIMO-OFDM and previously existing equalizers for single-carrier layered space-time systems.

  15. Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation.

    PubMed

    Peternel, Luka; Noda, Tomoyuki; Petrič, Tadej; Ude, Aleš; Morimoto, Jun; Babič, Jan

    2016-01-01

    In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs) as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG) signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion.

  16. Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation.

    PubMed

    Peternel, Luka; Noda, Tomoyuki; Petrič, Tadej; Ude, Aleš; Morimoto, Jun; Babič, Jan

    2016-01-01

    In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs) as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG) signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion. PMID:26881743

  17. Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation

    PubMed Central

    Peternel, Luka; Noda, Tomoyuki; Petrič, Tadej; Ude, Aleš; Morimoto, Jun; Babič, Jan

    2016-01-01

    In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs) as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG) signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion. PMID:26881743

  18. MAPK feedback encodes a switch and timer for tunable stress adaptation in yeast

    PubMed Central

    English, Justin G.; Shellhammer, James P.; Malahe, Michael; McCarter, Patrick C.; Elston, Timothy C.; Dohlman, Henrik G.

    2015-01-01

    Signaling pathways can behave as switches or rheostats, generating binary or graded responses to a given cell stimulus. We evaluated whether a single signaling pathway can simultaneously encode a switch and a rheostat. We found that the kinase Hog1 mediated a bifurcated cellular response: Activation and commitment to adaptation to osmotic stress are switch-like, whereas protein induction and the resolution of this commitment are graded. Through experimentation, bioinformatics analysis, and computational modeling, we determined that graded recovery is encoded through feedback phosphorylation and a gene induction program that is both temporally staggered and variable across the population. This switch-to-rheostat signaling mechanism represents a versatile stress adaptation system, wherein a broad range of inputs generate an “all-in” response that is later tuned to allow graded recovery of individual cells over time. PMID:25587192

  19. Output feedback adaptive fuzzy control of uncertain MIMO nonlinear systems with unknown input nonlinearities.

    PubMed

    Shahnazi, Reza

    2015-01-01

    An adaptive fuzzy output feedback controller is proposed for a class of uncertain MIMO nonlinear systems with unknown input nonlinearities. The input nonlinearities can be backlash-like hysteresis or dead-zone. Besides, the gains of unknown input nonlinearities are unknown nonlinear functions. Based on universal approximation theorem, the unknown nonlinear functions are approximated by fuzzy systems. The proposed method does not need the availability of the states and an observer based on strictly positive real (SPR) theory is designed to estimate the states. An adaptive robust structure is used to cope with fuzzy approximation error and external disturbances. The semi-global asymptotic stability of the closed-loop system is guaranteed via Lyapunov approach. The applicability of the proposed method is also shown via simulations.

  20. Output feedback adaptive fuzzy control of uncertain MIMO nonlinear systems with unknown input nonlinearities.

    PubMed

    Shahnazi, Reza

    2015-01-01

    An adaptive fuzzy output feedback controller is proposed for a class of uncertain MIMO nonlinear systems with unknown input nonlinearities. The input nonlinearities can be backlash-like hysteresis or dead-zone. Besides, the gains of unknown input nonlinearities are unknown nonlinear functions. Based on universal approximation theorem, the unknown nonlinear functions are approximated by fuzzy systems. The proposed method does not need the availability of the states and an observer based on strictly positive real (SPR) theory is designed to estimate the states. An adaptive robust structure is used to cope with fuzzy approximation error and external disturbances. The semi-global asymptotic stability of the closed-loop system is guaranteed via Lyapunov approach. The applicability of the proposed method is also shown via simulations. PMID:25104646

  1. Parental Rearing Behavior Prospectively Predicts Adolescents' Risky Decision-Making and Feedback-Related Electrical Brain Activity

    ERIC Educational Resources Information Center

    Euser, Anja S.; Evans, Brittany E.; Greaves-Lord, Kirstin; Huizink, Anja C.; Franken, Ingmar H. A.

    2013-01-01

    The present study examined the role of parental rearing behavior in adolescents' risky decision-making and the brain's feedback processing mechanisms. Healthy adolescent participants ("n" = 110) completed the EMBU-C, a self-report questionnaire on perceived parental rearing behaviors between 2006 and 2008 (T1). Subsequently, after an average of…

  2. Indirect adaptive output feedback control of a biorobotic AUV using pectoral-like mechanical fins.

    PubMed

    Naik, Mugdha S; Singh, Sahjendra N; Mittal, Rajat

    2009-06-01

    This paper treats the question of servoregulation of autonomous underwater vehicles (AUVs) in the yaw plane using pectoral-like mechanical fins. The fins attached to the vehicle have oscillatory swaying and yawing motion. The bias angle of the angular motion of the fin is used for the purpose of control. Of course, the design approach considered here is applicable to AUVs for other choices of oscillation patterns of the fins, which produce periodic forces and moments. It is assumed that the vehicle parameters, hydrodynamic coefficients, as well the fin forces and moments are unknown. For the trajectory control of the yaw angle, a sampled-data indirect adaptive control system using output (yaw angle) feedback is derived. The control system has a modular structure, which includes a parameter identifier and a stabilizer. For the control law derivation, an internal model of the exosignals (reference signal (constant or ramp) and constant disturbance) is included. Unlike the direct adaptive control scheme, the derived control law is applicable to minimum as well as nonminimum phase biorobotic AUVs (BAUVs). This is important, because for most of the fin locations on the vehicle, the model is a nonminimum phase. In the closed-loop system, the yaw angle trajectory tracking error converges to zero and the remaining state variables remain bounded. Simulation results are presented which show that the derived modular control system accomplishes precise set point yaw angle control and turning maneuvers in spite of the uncertainties in the system parameters using only yaw angle feedback.

  3. Adaptive Neural Control of Pure-Feedback Nonlinear Time-Delay Systems via Dynamic Surface Technique.

    PubMed

    Min Wang; Xiaoping Liu; Peng Shi

    2011-12-01

    This paper is concerned with robust stabilization problem for a class of nonaffine pure-feedback systems with unknown time-delay functions and perturbed uncertainties. Novel continuous packaged functions are introduced in advance to remove unknown nonlinear terms deduced from perturbed uncertainties and unknown time-delay functions, which avoids the functions with control law to be approximated by radial basis function (RBF) neural networks. This technique combining implicit function and mean value theorems overcomes the difficulty in controlling the nonaffine pure-feedback systems. Dynamic surface control (DSC) is used to avoid "the explosion of complexity" in the backstepping design. Design difficulties from unknown time-delay functions are overcome using the function separation technique, the Lyapunov-Krasovskii functionals, and the desirable property of hyperbolic tangent functions. RBF neural networks are employed to approximate desired virtual controls and desired practical control. Under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced significantly, and semiglobal uniform ultimate boundedness of all of the signals in the closed-loop system is guaranteed. Simulation studies are given to demonstrate the effectiveness of the proposed design scheme.

  4. Formation tracker design of multiple mobile robots with wheel perturbations: adaptive output-feedback approach

    NASA Astrophysics Data System (ADS)

    Yoo, Sung Jin

    2016-11-01

    This paper presents a theoretical design approach for output-feedback formation tracking of multiple mobile robots under wheel perturbations. It is assumed that these perturbations are unknown and the linear and angular velocities of the robots are unmeasurable. First, adaptive state observers for estimating unmeasurable velocities of the robots are developed under the robots' kinematics and dynamics including wheel perturbation effects. Then, we derive a virtual-structure-based formation tracker scheme according to the observer dynamic surface design procedure. The main difficulty of the output-feedback control design is to manage the coupling problems between unmeasurable velocities and unknown wheel perturbation effects. These problems are avoided by using the adaptive technique and the function approximation property based on fuzzy logic systems. From the Lyapunov stability analysis, it is shown that point tracking errors of each robot and synchronisation errors for the desired formation converge to an adjustable neighbourhood of the origin, while all signals in the controlled closed-loop system are semiglobally uniformly ultimately bounded.

  5. A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines

    PubMed Central

    Mikut, Ralf; Reischl, Markus

    2016-01-01

    The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts. PMID:27764213

  6. The Selection of Test Items for Decision Making with a Computer Adaptive Test.

    ERIC Educational Resources Information Center

    Spray, Judith A.; Reckase, Mark D.

    The issue of test-item selection in support of decision making in adaptive testing is considered. The number of items needed to make a decision is compared for two approaches: selecting items from an item pool that are most informative at the decision point or selecting items that are most informative at the examinee's ability level. The first…

  7. Feedbacks, Bifurcations, and Cell Fate Decision-Making in the p53 System

    PubMed Central

    Bogdał, Marta N.; Lipniacki, Tomasz

    2016-01-01

    The p53 transcription factor is a regulator of key cellular processes including DNA repair, cell cycle arrest, and apoptosis. In this theoretical study, we investigate how the complex circuitry of the p53 network allows for stochastic yet unambiguous cell fate decision-making. The proposed Markov chain model consists of the regulatory core and two subordinated bistable modules responsible for cell cycle arrest and apoptosis. The regulatory core is controlled by two negative feedback loops (regulated by Mdm2 and Wip1) responsible for oscillations, and two antagonistic positive feedback loops (regulated by phosphatases Wip1 and PTEN) responsible for bistability. By means of bifurcation analysis of the deterministic approximation we capture the recurrent solutions (i.e., steady states and limit cycles) that delineate temporal responses of the stochastic system. Direct switching from the limit-cycle oscillations to the “apoptotic” steady state is enabled by the existence of a subcritical Neimark—Sacker bifurcation in which the limit cycle loses its stability by merging with an unstable invariant torus. Our analysis provides an explanation why cancer cell lines known to have vastly diverse expression levels of Wip1 and PTEN exhibit a broad spectrum of responses to DNA damage: from a fast transition to a high level of p53 killer (a p53 phosphoform which promotes commitment to apoptosis) in cells characterized by high PTEN and low Wip1 levels to long-lasting p53 level oscillations in cells having PTEN promoter methylated (as in, e.g., MCF-7 cell line). PMID:26928575

  8. Parental rearing behavior prospectively predicts adolescents' risky decision-making and feedback-related electrical brain activity.

    PubMed

    Euser, Anja S; Evans, Brittany E; Greaves-Lord, Kirstin; Huizink, Anja C; Franken, Ingmar H A

    2013-05-01

    The present study examined the role of parental rearing behavior in adolescents' risky decision-making and the brain's feedback processing mechanisms. Healthy adolescent participants (n = 110) completed the EMBU-C, a self-report questionnaire on perceived parental rearing behaviors between 2006 and 2008 (T1). Subsequently, after an average of 3.5 years, we assessed (a) risky decision-making during performance of the Balloon Analogue Risk Task (BART); (b) event-related brain potentials (ERPs) elicited by positive (gain) and negative feedback (loss) during the BART; and (c) self-reported substance use behavior (T2). Age-corrected regression analyses showed that parental rejection at T1 accounted for a unique and significant proportion of the variance in risk-taking during the BART; the more adolescents perceived their parents as rejecting, the more risky decisions were made. Higher levels of perceived emotional warmth predicted increased P300 amplitudes in response to positive feedback at T2. Moreover, these larger P300 amplitudes (gain) significantly predicted risky decision-making during the BART. Parental rearing behaviors during childhood thus seem to be significant predictors of both behavioral and electrophysiological indices of risky decision-making in adolescence several years later. This is in keeping with the notion that environmental factors such as parental rearing are important in explaining adolescents' risk-taking propensities. PMID:23587039

  9. Iterative Information-Reduced Carrier Synchronization Using Decision Feedback for Low SNR Applications

    NASA Astrophysics Data System (ADS)

    Simon, M. K.; Vilnrotter, V. A.

    1997-04-01

    Traditional methods for carrier synchronization of uncoded binary phase-shiftkeyed (BPSK) signals, e.g, conventional and polarity-type Costas loops, data-aided loops, demodulation{remodulation loops, etc., are obtained from approximations made to a closed-loop structure motivated by the maximum a posteriori (MAP) estimation of carrier phase. Inherent in all of these loops is the fact that their input data are assumed to be equiprobable (balanced) independent identically distributed (i.i.d.) binary sequences, and the MAP estimation loop from which these various structures are derived is predicated on this fact. The tracking performance limitation of such loops is the so-called squaring loss associated with the mean-squared phase error, which is the result of signal and noise products created by the necessity to remove the data modulation from the loop error signal. By reducing the amount of randomness (information) in the data that are input to the carrier synchronizer (hence the term information-reduced carrier synchronization), yet maintaining their i.i.d (but not necessarily balanced) property and also their independence of the additive noise, and then suitably modifying the synchronizer structure in accordance with this data reduction, one can obtain a significant squaring-loss improvement relative to what is achievable with the above-mentioned structures. One method for accomplishing this reduction in data randomness is through the use of decision feedback at the input of the loop structure, which should be contrasted with conventional structures such as the data-aided or polarity-type Costas loops that use decision feedback within the loop structure itself, and hence do not modify the structure based on the amount of information reduction achieved. While applying such a method to uncoded modulations will not satisfy the noise independence constraint on the modified data sequence (for reasons explained in the article), for coded modulations, we show that it is

  10. 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

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

    PubMed

    Shanechi, Maryam M; Orsborn, Amy L; Carmena, Jose M

    2016-04-01

    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

  12. A Model for Making Decisions about Text Adaptations.

    ERIC Educational Resources Information Center

    Dyck, Norma; Pemberton, Jane B.

    2002-01-01

    This article examines a process for teachers to use when deciding whether to adapt a text for a student. The following five options for text adaptations are described: bypass reading, decrease reading, support reading, organize reading, and guide reading. Adaptations for student work products and for tests are also addressed. (Contains…

  13. Visual feedback of the moving arm allows complete adaptation of pointing movements to centrifugal and Coriolis forces in human subjects.

    PubMed

    Bourdin, C; Gauthier, G; Blouin, J; Vercher, J L

    2001-03-23

    A classical visuo-manual adaptation protocol carried out on a rotating platform was used to test the ability of subjects to adapt to centrifugal and Coriolis forces when visual feedback of the arm is manipulated. Three main results emerge: (a) an early modification of the initial trajectory of the movements takes place even without visual feedback of the arm; (b) despite the change in the initial trajectory, the new external force decreases the accuracy of the pointing movements when vision is precluded; (c) a visual adaptive phase allows complete adaptation of the pointing movements performed in a modified gravitoinertial field. Therefore vision would be essential for subjects to completely adapt to centrifugal and Coriolis forces. However, other sensory signals (i.e. vestibular and proprioceptive) may constitute the basis for early but partial correction of the pointing movements.

  14. Modeling Feedbacks Between Individual Human Decisions and Hydrology Using Interconnected Physical and Social Models

    NASA Astrophysics Data System (ADS)

    Murphy, J.; Lammers, R. B.; Proussevitch, A. A.; Ozik, J.; Altaweel, M.; Collier, N. T.; Alessa, L.; Kliskey, A. D.

    2014-12-01

    The global hydrological cycle intersects with human decision making at multiple scales, from dams and irrigation works to the taps in individuals' homes. Residential water consumers are commonly encouraged to conserve; these messages are heard against a background of individual values and conceptions about water quality, uses, and availability. The degree to which these values impact the larger-hydrological dynamics, the way that changes in those values have impacts on the hydrological cycle through time, and the feedbacks by which water availability and quality in turn shape those values, are not well explored. To investigate this domain we employ a global-scale water balance model (WBM) coupled with a social-science-grounded agent-based model (ABM). The integration of a hydrological model with an agent-based model allows us to explore driving factors in the dynamics in coupled human-natural systems. From the perspective of the physical hydrologist, the ABM offers a richer means of incorporating the human decisions that drive the hydrological system; from the view of the social scientist, a physically-based hydrological model allows the decisions of the agents to play out against constraints faithful to the real world. We apply the interconnected models to a study of Tucson, Arizona, USA, and its role in the larger Colorado River system. Our core concept is Technology-Induced Environmental Distancing (TIED), which posits that layers of technology can insulate consumers from direct knowledge of a resource. In Tucson, multiple infrastructure and institutional layers have arguably increased the conceptual distance between individuals and their water supply, offering a test case of the TIED framework. Our coupled simulation allows us to show how the larger system transforms a resource with high temporal and spatial variability into a consumer constant, and the effects of this transformation on the regional system. We use this to explore how pricing, messaging, and

  15. Hybrid feedback feedforward: An efficient design of adaptive neural network control.

    PubMed

    Pan, Yongping; Liu, Yiqi; Xu, Bin; Yu, Haoyong

    2016-04-01

    This paper presents an efficient hybrid feedback feedforward (HFF) adaptive approximation-based control (AAC) strategy for a class of uncertain Euler-Lagrange systems. The control structure includes a proportional-derivative (PD) control term in the feedback loop and a radial-basis-function (RBF) neural network (NN) in the feedforward loop, which mimics the human motor learning control mechanism. At the presence of discontinuous friction, a sigmoid-jump-function NN is incorporated to improve control performance. The major difference of the proposed HFF-AAC design from the traditional feedback AAC (FB-AAC) design is that only desired outputs, rather than both tracking errors and desired outputs, are applied as RBF-NN inputs. Yet, such a slight modification leads to several attractive properties of HFF-AAC, including the convenient choice of an approximation domain, the decrease of the number of RBF-NN inputs, and semiglobal practical asymptotic stability dominated by control gains. Compared with previous HFF-AAC approaches, the proposed approach possesses the following two distinctive features: (i) all above attractive properties are achieved by a much simpler control scheme; (ii) the bounds of plant uncertainties are not required to be known. Consequently, the proposed approach guarantees a minimum configuration of the control structure and a minimum requirement of plant knowledge for the AAC design, which leads to a sharp decrease of implementation cost in terms of hardware selection, algorithm realization and system debugging. Simulation results have demonstrated that the proposed HFF-AAC can perform as good as or even better than the traditional FB-AAC under much simpler control synthesis and much lower computational cost. PMID:26890657

  16. Adaptive feedback synchronisation of complex dynamical network with discrete-time communications and delayed nodes

    NASA Astrophysics Data System (ADS)

    Wang, Tong; Ding, Yongsheng; Zhang, Lei; Hao, Kuangrong

    2016-08-01

    This paper considered the synchronisation of continuous complex dynamical networks with discrete-time communications and delayed nodes. The nodes in the dynamical networks act in the continuous manner, while the communications between nodes are discrete-time; that is, they communicate with others only at discrete time instants. The communication intervals in communication period can be uncertain and variable. By using a piecewise Lyapunov-Krasovskii function to govern the characteristics of the discrete communication instants, we investigate the adaptive feedback synchronisation and a criterion is derived to guarantee the existence of the desired controllers. The globally exponential synchronisation can be achieved by the controllers under the updating laws. Finally, two numerical examples including globally coupled network and nearest-neighbour coupled networks are presented to demonstrate the validity and effectiveness of the proposed control scheme.

  17. An Adaptive Learning Rate for RBFNN Using Time-Domain Feedback Analysis

    PubMed Central

    Ali, Syed Saad Azhar; Moinuddin, Muhammad; Raza, Kamran

    2014-01-01

    Radial basis function neural networks are used in a variety of applications such as pattern recognition, nonlinear identification, control and time series prediction. In this paper, the learning algorithm of radial basis function neural networks is analyzed in a feedback structure. The robustness of the learning algorithm is discussed in the presence of uncertainties that might be due to noisy perturbations at the input or to modeling mismatch. An intelligent adaptation rule is developed for the learning rate of RBFNN which gives faster convergence via an estimate of error energy while giving guarantee to the l 2 stability governed by the upper bounding via small gain theorem. Simulation results are presented to support our theoretical development. PMID:24987745

  18. An adaptive learning rate for RBFNN using time-domain feedback analysis.

    PubMed

    Ali, Syed Saad Azhar; Moinuddin, Muhammad; Raza, Kamran; Adil, Syed Hasan

    2014-01-01

    Radial basis function neural networks are used in a variety of applications such as pattern recognition, nonlinear identification, control and time series prediction. In this paper, the learning algorithm of radial basis function neural networks is analyzed in a feedback structure. The robustness of the learning algorithm is discussed in the presence of uncertainties that might be due to noisy perturbations at the input or to modeling mismatch. An intelligent adaptation rule is developed for the learning rate of RBFNN which gives faster convergence via an estimate of error energy while giving guarantee to the l 2 stability governed by the upper bounding via small gain theorem. Simulation results are presented to support our theoretical development.

  19. Adaptive output feedback consensus tracking for linear multi-agent systems with unknown dynamics

    NASA Astrophysics Data System (ADS)

    Sun, Junyong; Geng, Zhiyong

    2015-09-01

    In this paper, the consensus tracking problem with unknown dynamics in the leader for the linear multi-agent systems is addressed. Based on the relative output information among the agents, decentralised adaptive consensus protocols with static coupling gains are designed to guarantee that the consensus tracking errors converge to a small neighbourhood around the origin and all the signals in the closed-loop dynamics are uniformly ultimately bounded. Moreover, the result is extended to the case with dynamic coupling gains which are independent of the eigenvalues of the Laplacian matrix. Both of the protocols with static and dynamic coupling gains are designed by using the relative outputs, which are more practical than the state-feedback ones. Finally, the theoretical results are verified through an example.

  20. Learning from ISS-modular adaptive NN control of nonlinear strict-feedback systems.

    PubMed

    Wang, Cong; Wang, Min; Liu, Tengfei; Hill, David J

    2012-10-01

    This paper studies learning from adaptive neural control (ANC) for a class of nonlinear strict-feedback systems with unknown affine terms. To achieve the purpose of learning, a simple input-to-state stability (ISS) modular ANC method is first presented to ensure the boundedness of all the signals in the closed-loop system and the convergence of tracking errors in finite time. Subsequently, it is proven that learning with the proposed stable ISS-modular ANC can be achieved. The cascade structure and unknown affine terms of the considered systems make it very difficult to achieve learning using existing methods. To overcome these difficulties, the stable closed-loop system in the control process is decomposed into a series of linear time-varying (LTV) perturbed subsystems with the appropriate state transformation. Using a recursive design, the partial persistent excitation condition for the radial basis function neural network (NN) is established, which guarantees exponential stability of LTV perturbed subsystems. Consequently, accurate approximation of the closed-loop system dynamics is achieved in a local region along recurrent orbits of closed-loop signals, and learning is implemented during a closed-loop feedback control process. The learned knowledge is reused to achieve stability and an improved performance, thereby avoiding the tremendous repeated training process of NNs. Simulation studies are given to demonstrate the effectiveness of the proposed method.

  1. Adaptive Control Model Reveals Systematic Feedback and Key Molecules in Metabolic Pathway Regulation

    PubMed Central

    Moffitt, Richard A.; Merrill, Alfred H.; Wang, May D.

    2011-01-01

    Abstract Robust behavior in metabolic pathways resembles stabilized performance in systems under autonomous control. This suggests we can apply control theory to study existing regulation in these cellular networks. Here, we use model-reference adaptive control (MRAC) to investigate the dynamics of de novo sphingolipid synthesis regulation in a combined theoretical and experimental case study. The effects of serine palmitoyltransferase over-expression on this pathway are studied in vitro using human embryonic kidney cells. We report two key results from comparing numerical simulations with observed data. First, MRAC simulations of pathway dynamics are comparable to simulations from a standard model using mass action kinetics. The root-sum-square (RSS) between data and simulations in both cases differ by less than 5%. Second, MRAC simulations suggest systematic pathway regulation in terms of adaptive feedback from individual molecules. In response to increased metabolite levels available for de novo sphingolipid synthesis, feedback from molecules along the main artery of the pathway is regulated more frequently and with greater amplitude than from other molecules along the branches. These biological insights are consistent with current knowledge while being new that they may guide future research in sphingolipid biology. In summary, we report a novel approach to study regulation in cellular networks by applying control theory in the context of robust metabolic pathways. We do this to uncover potential insight into the dynamics of regulation and the reverse engineering of cellular networks for systems biology. This new modeling approach and the implementation routines designed for this case study may be extended to other systems. Supplementary Material is available at www.liebertonline.com/cmb. PMID:21314456

  2. Modeling Adaptation as a Flow and Stock Decision with Mitigation

    EPA Science Inventory

    Mitigation and adaptation are the two key responses available to policymakers to reduce the risks of climate change. We model these two policies together in a new DICE-based integrated assessment model that characterizes adaptation as either short-lived flow spending or long-liv...

  3. An adaptive source-channel coding with feedback for progressive transmission of medical images.

    PubMed

    Lo, Jen-Lung; Sanei, Saeid; Nazarpour, Kianoush

    2009-01-01

    A novel adaptive source-channel coding with feedback for progressive transmission of medical images is proposed here. In the source coding part, the transmission starts from the region of interest (RoI). The parity length in the channel code varies with respect to both the proximity of the image subblock to the RoI and the channel noise, which is iteratively estimated in the receiver. The overall transmitted data can be controlled by the user (clinician). In the case of medical data transmission, it is vital to keep the distortion level under control as in most of the cases certain clinically important regions have to be transmitted without any visible error. The proposed system significantly reduces the transmission time and error. Moreover, the system is very user friendly since the selection of the RoI, its size, overall code rate, and a number of test features such as noise level can be set by the users in both ends. A MATLAB-based TCP/IP connection has been established to demonstrate the proposed interactive and adaptive progressive transmission system. The proposed system is simulated for both binary symmetric channel (BSC) and Rayleigh channel. The experimental results verify the effectiveness of the design.

  4. Experimental Evidence of an Eco-evolutionary Feedback during Adaptive Divergence.

    PubMed

    Matthews, Blake; Aebischer, Thierry; Sullam, Karen E; Lundsgaard-Hansen, Bänz; Seehausen, Ole

    2016-02-22

    Differences in how organisms modify their environment can evolve rapidly and might influence adaptive population divergence. In a common garden experiment in aquatic mesocosms, we found that adult stickleback from a recently diverged pair of lake and stream populations had contrasting effects on ecosystem metrics. These modifications were caused by both genetic and plastic differences between populations and were sometimes comparable in magnitude to those caused by the presence/absence of stickleback. Lake and stream fish differentially affected the biomass of zooplankton and phytoplankton, the concentration of phosphorus, and the abundance of several prey (e.g., copepods) and non-prey (e.g., cyanobacteria) species. The adult-mediated effects on mesocosm ecosystems influenced the survival and growth of a subsequent generation of juvenile stickleback reared in the same mesocosms. The prior presence of adults decreased the overall growth rate of juveniles, and the prior presence of stream adults lowered overall juvenile survival. Among the survivors, lake juveniles grew faster than co-occurring stream juveniles, except in mesocosm ecosystems previously modified by adult lake fish that were reared on plankton. Overall, our results provide evidence for reciprocal interactions between ecosystem dynamics and evolutionary change (i.e., eco-evolutionary feedbacks) in the early stages of adaptive population divergence. PMID:26804555

  5. Adaptation of cardiac structure by mechanical feedback in the environment of the cell: a model study.

    PubMed Central

    Arts, T; Prinzen, F W; Snoeckx, L H; Rijcken, J M; Reneman, R S

    1994-01-01

    In the cardiac left ventricle during systole mechanical load of the myocardial fibers is distributed uniformly. A mechanism is proposed by which control of mechanical load is distributed over many individual control units acting in the environment of the cell. The mechanics of the equatorial region of the left ventricle was modeled by a thick-walled cylinder composed of 6-1500 shells of myocardial fiber material. In each shell a separate control unit was simulated. The direction of the cells was varied so that systolic fiber shortening approached a given optimum of 15%. End-diastolic sarcomere length was maintained at 2.1 microns. Regional early-systolic stretch and global contractility stimulated growth of cellular mass. If systolic shortening was more than normal the passive extracellular matrix stretched. The design of the load-controlling mechanism was derived from biological experiments showing that cellular processes are sensitive to mechanical deformation. After simulating a few hundred adaptation cycles, the macroscopic anatomical arrangement of helical pathways of the myocardial fibers formed automatically. If pump load of the ventricle was changed, wall thickness and cavity volume adapted physiologically. We propose that the cardiac anatomy may be defined and maintained by a multitude of control units for mechanical load, each acting in the cellular environment. Interestingly, feedback through fiber stress is not a compelling condition for such control. PMID:8038399

  6. An Adaptive Source-Channel Coding with Feedback for Progressive Transmission of Medical Images

    PubMed Central

    Lo, Jen-Lung; Sanei, Saeid; Nazarpour, Kianoush

    2009-01-01

    A novel adaptive source-channel coding with feedback for progressive transmission of medical images is proposed here. In the source coding part, the transmission starts from the region of interest (RoI). The parity length in the channel code varies with respect to both the proximity of the image subblock to the RoI and the channel noise, which is iteratively estimated in the receiver. The overall transmitted data can be controlled by the user (clinician). In the case of medical data transmission, it is vital to keep the distortion level under control as in most of the cases certain clinically important regions have to be transmitted without any visible error. The proposed system significantly reduces the transmission time and error. Moreover, the system is very user friendly since the selection of the RoI, its size, overall code rate, and a number of test features such as noise level can be set by the users in both ends. A MATLAB-based TCP/IP connection has been established to demonstrate the proposed interactive and adaptive progressive transmission system. The proposed system is simulated for both binary symmetric channel (BSC) and Rayleigh channel. The experimental results verify the effectiveness of the design. PMID:19190770

  7. Study of a co-designed decision feedback equalizer, deinterleaver, and decoder

    NASA Technical Reports Server (NTRS)

    Peile, Robert E.; Welch, Loyd

    1990-01-01

    A technique that promises better quality data from band limited channels at lower received power in digital transmission systems is presented. Data transmission, in such systems often suffers from intersymbol interference (ISI) and noise. Two separate techniques, channel coding and equalization, have caused considerable advances in the state of communication systems and both concern themselves with removing the undesired effects of a communication channel. Equalizers mitigate the ISI whereas coding schemes are used to incorporate error-correction. In the past, most of the research in these two areas has been carried out separately. However, the individual techniques have strengths and weaknesses that are complementary in many applications: an integrated approach realizes gains in excess to that of a simple juxtaposition. Coding schemes have been successfully used in cascade with linear equalizers which in the absence of ISI provide excellent performance. However, when both ISI and the noise level are relatively high, nonlinear receivers like the decision feedback equalizer (DFE) perform better. The DFE has its drawbacks: it suffers from error propagation. The technique presented here takes advantage of interleaving to integrate the two approaches so that the error propagation in DFE can be reduced with the help of error correction provided by the decoder. The results of simulations carried out for both, binary, and non-binary, channels confirm that significant gain can be obtained by codesigning equalizer and decoder. Although, systems with time-invariant channels and simple DFE having linear filters were looked into, the technique is fairly general and can easily be modified for more sophisticated equalizers to obtain even larger gains.

  8. Characterizing Decision-Analysis Performances of Risk Prediction Models Using ADAPT Curves

    PubMed Central

    Lee, Wen-Chung; Wu, Yun-Chun

    2016-01-01

    Abstract The area under the receiver operating characteristic curve is a widely used index to characterize the performance of diagnostic tests and prediction models. However, the index does not explicitly acknowledge the utilities of risk predictions. Moreover, for most clinical settings, what counts is whether a prediction model can guide therapeutic decisions in a way that improves patient outcomes, rather than to simply update probabilities. Based on decision theory, the authors propose an alternative index, the “average deviation about the probability threshold” (ADAPT). An ADAPT curve (a plot of ADAPT value against the probability threshold) neatly characterizes the decision-analysis performances of a risk prediction model. Several prediction models can be compared for their ADAPT values at a chosen probability threshold, for a range of plausible threshold values, or for the whole ADAPT curves. This should greatly facilitate the selection of diagnostic tests and prediction models. PMID:26765451

  9. Adaptive fuzzy output-feedback controller design for nonlinear time-delay systems with unknown control direction.

    PubMed

    Hua, Chang-Chun; Wang, Qing-Guo; Guan, Xin-Ping

    2009-04-01

    In this paper, the robust-control problem is investigated for a class of uncertain nonlinear time-delay systems via dynamic output-feedback approach. The considered system is in the strict-feedback form with unknown control direction. A full-order observer is constructed with the gains computed via linear matrix inequality at first. Then, with the bounds of uncertain functions known, we design the dynamic output-feedback controller such that the closed-loop system is asymptotically stable. Furthermore, when the bound functions of uncertainties are not available, the adaptive fuzzy-logic system is employed to approximate the uncertain function, and the corresponding output-feedback controller is designed. It is shown that the resulting closed-loop system is stable in the sense of semiglobal uniform ultimate boundedness. Finally, simulations are done to verify the feasibility and effectiveness of the obtained theoretical results.

  10. Learning from adaptive neural dynamic surface control of strict-feedback systems.

    PubMed

    Wang, Min; Wang, Cong

    2015-06-01

    Learning plays an essential role in autonomous control systems. However, how to achieve learning in the nonstationary environment for nonlinear systems is a challenging problem. In this paper, we present learning method for a class of n th-order strict-feedback systems by adaptive dynamic surface control (DSC) technology, which achieves the human-like ability of learning by doing and doing with learned knowledge. To achieve the learning, this paper first proposes stable adaptive DSC with auxiliary first-order filters, which ensures the boundedness of all the signals in the closed-loop system and the convergence of tracking errors in a finite time. With the help of DSC, the derivative of the filter output variable is used as the neural network (NN) input instead of traditional intermediate variables. As a result, the proposed adaptive DSC method reduces greatly the dimension of NN inputs, especially for high-order systems. After the stable DSC design, we decompose the stable closed-loop system into a series of linear time-varying perturbed subsystems. Using a recursive design, the recurrent property of NN input variables is easily verified since the complexity is overcome using DSC. Subsequently, the partial persistent excitation condition of the radial basis function NN is satisfied. By combining a state transformation, accurate approximations of the closed-loop system dynamics are recursively achieved in a local region along recurrent orbits. Then, the learning control method using the learned knowledge is proposed to achieve the closed-loop stability and the improved control performance. Simulation studies are performed to demonstrate the proposed scheme can not only reuse the learned knowledge to achieve the better control performance with the faster tracking convergence rate and the smaller tracking error but also greatly alleviate the computational burden because of reducing the number and complexity of NN input variables.

  11. Integrated Flight/Structural Mode Control for Very Flexible Aircraft Using L1 Adaptive Output Feedback Controller

    NASA Technical Reports Server (NTRS)

    Che, Jiaxing; Cao, Chengyu; Gregory, Irene M.

    2012-01-01

    This paper explores application of adaptive control architecture to a light, high-aspect ratio, flexible aircraft configuration that exhibits strong rigid body/flexible mode coupling. Specifically, an L(sub 1) adaptive output feedback controller is developed for a semi-span wind tunnel model capable of motion. The wind tunnel mount allows the semi-span model to translate vertically and pitch at the wing root, resulting in better simulation of an aircraft s rigid body motion. The control objective is to design a pitch control with altitude hold while suppressing body freedom flutter. The controller is an output feedback nominal controller (LQG) augmented by an L(sub 1) adaptive loop. A modification to the L(sub 1) output feedback is proposed to make it more suitable for flexible structures. The new control law relaxes the required bounds on the unmatched uncertainty and allows dependence on the state as well as time, i.e. a more general unmatched nonlinearity. The paper presents controller development and simulated performance responses. Simulation is conducted by using full state flexible wing models derived from test data at 10 different dynamic pressure conditions. An L(sub 1) adaptive output feedback controller is designed for a single test point and is then applied to all the test cases. The simulation results show that the L(sub 1) augmented controller can stabilize and meet the performance requirements for all 10 test conditions ranging from 30 psf to 130 psf dynamic pressure.

  12. Video-Feedback Intervention to Promote Positive Parenting Adapted to Autism (VIPP-AUTI): A Randomized Controlled Trial

    ERIC Educational Resources Information Center

    Poslawsky, Irina E; Naber, Fabiënne BA; Bakermans-Kranenburg, Marian J; van Daalen, Emma; van Engeland, Herman; van IJzendoorn, Marinus H

    2015-01-01

    In a randomized controlled trial, we evaluated the early intervention program Video-feedback Intervention to promote Positive Parenting adapted to Autism (VIPP-AUTI) with 78 primary caregivers and their child (16-61 months) with Autism Spectrum Disorder. VIPP-AUTI is a brief attachment-based intervention program, focusing on improving parent-child…

  13. Usability Testing and Adaptation of the Pediatric Cardiovascular Risk Reduction Clinical Decision Support Tool

    PubMed Central

    Furberg, Robert D; Bagwell, Jacqueline E; LaBresh, Kenneth A

    2016-01-01

    Background Cardiovascular disease (CVD) is 1 of the leading causes of death, years of life lost, and disability-adjusted years of life lost worldwide. CVD prevention for children and teens is needed, as CVD risk factors and behaviors beginning in youth contribute to CVD development. In 2012, the National Heart, Lung, and Blood Institute released their “Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents” for clinicians, describing CVD risk factors they should address with patients at primary care preventative visits. However, uptake of new guidelines is slow. Clinical decision support (CDS) tools can improve guideline uptake. In this paper, we describe our process of testing and adapting a CDS tool to help clinicians evaluate patient risk, recommend behaviors to prevent development of risk, and complete complex calculations to determine appropriate interventions as recommended by the guidelines, using a user-centered design approach. Objective The objective of the study was to assess the usability of a pediatric CVD risk factor tool by clinicians. Methods The tool was tested using one-on-one in-person testing and a “think aloud” approach with 5 clinicians and by using the tool in clinical practice along with formal usability metrics with 14 pediatricians. Thematic analysis of the data from the in-person testing and clinical practice testing identified suggestions for change in 3 major areas: user experience, content refinement, and technical deployment. Descriptive statistical techniques were employed to summarize users’ overall experience with the tool. Results Data from testers showed that general reactions toward the CDS tool were positive. Clinical practice testers suggested revisions to make the application more user-friendly, especially for clinicians using the application on the iPhone, and called for refining recommendations to be more succinct and better tailored to the patient. Tester feedback was

  14. Adaptive network models of collective decision making in swarming systems.

    PubMed

    Chen, Li; Huepe, Cristián; Gross, Thilo

    2016-08-01

    We consider a class of adaptive network models where links can only be created or deleted between nodes in different states. These models provide an approximate description of a set of systems where nodes represent agents moving in physical or abstract space, the state of each node represents the agent's heading direction, and links indicate mutual awareness. We show analytically that the adaptive network description captures a phase transition to collective motion in some swarming systems, such as the Vicsek model, and that the properties of this transition are determined by the number of states (discrete heading directions) that can be accessed by each agent.

  15. Adaptive network models of collective decision making in swarming systems

    NASA Astrophysics Data System (ADS)

    Chen, Li; Huepe, Cristián; Gross, Thilo

    2016-08-01

    We consider a class of adaptive network models where links can only be created or deleted between nodes in different states. These models provide an approximate description of a set of systems where nodes represent agents moving in physical or abstract space, the state of each node represents the agent's heading direction, and links indicate mutual awareness. We show analytically that the adaptive network description captures a phase transition to collective motion in some swarming systems, such as the Vicsek model, and that the properties of this transition are determined by the number of states (discrete heading directions) that can be accessed by each agent.

  16. Adaptive network models of collective decision making in swarming systems.

    PubMed

    Chen, Li; Huepe, Cristián; Gross, Thilo

    2016-08-01

    We consider a class of adaptive network models where links can only be created or deleted between nodes in different states. These models provide an approximate description of a set of systems where nodes represent agents moving in physical or abstract space, the state of each node represents the agent's heading direction, and links indicate mutual awareness. We show analytically that the adaptive network description captures a phase transition to collective motion in some swarming systems, such as the Vicsek model, and that the properties of this transition are determined by the number of states (discrete heading directions) that can be accessed by each agent. PMID:27627342

  17. Decision training: the effects of complex instruction, variable practice and reduced delayed feedback on the acquisition and transfer of a motor skill.

    PubMed

    Vickers, J N; Livingston, L F; Umeris-Bohnert, S; Holden, D

    1999-05-01

    Novice, intermediate and advanced baseball hitters followed a 7-week training programme, in which they received either behavioural training or decision training. Participants in the behavioural training group received simple-to-complex instruction, variable practice and an abundance of feedback throughout the acquisition period; the decision training group received complex instruction, variable practice and reduced delayed feedback. As predicted, the intermediate and advanced hitters who received decision training hit at a lower level (%) during acquisition but at a higher level during a transfer test in week 7. Novices in the behavioural training group were better than novices in the decision training group over both acquisition and transfer trials.

  18. An adaptive approach to invasive plant management on U.S. Fish and Wildlife Service-owned native prairies in the Prairie Pothole Region: decision support under uncertainity

    USGS Publications Warehouse

    Gannon, Jill J.; Moore, Clinton T.; Shaffer, Terry L.; Flanders-Wanner, Bridgette

    2011-01-01

    Much of the native prairie managed by the U.S. Fish and Wildlife Service (Service) in the Prairie Pothole Region (PPR) is extensively invaded by the introduced cool-season grasses smooth brome (Bromus inermis) and Kentucky bluegrass (Poa pratensis). The central challenge to managers is selecting appropriate management actions in the face of biological and environmental uncertainties. We describe the technical components of a USGS management project, and explain how the components integrate and inform each other, how data feedback from individual cooperators serves to reduce uncertainty across the whole region, and how a successful adaptive management project is coordinated and maintained on a large scale. In partnership with the Service, the U.S. Geological Survey is developing an adaptive decision support framework to assist managers in selecting management actions under uncertainty and maximizing learning from management outcomes. The framework is built around practical constraints faced by refuge managers and includes identification of the management objective and strategies, analysis of uncertainty and construction of competing decision models, monitoring, and mechanisms for model feedback and decision selection. Nineteen Service field stations, spanning four states of the PPR, are participating in the project. They share a common management objective, available management strategies, and biological uncertainties. While the scope is broad, the project interfaces with individual land managers who provide refuge-specific information and receive updated decision guidance that incorporates understanding gained from the collective experience of all cooperators.

  19. Adaptive neural control for cooperative path following of marine surface vehicles: state and output feedback

    NASA Astrophysics Data System (ADS)

    Wang, H.; Wang, D.; Peng, Z. H.

    2016-01-01

    This paper addresses the cooperative path-following problem of multiple marine surface vehicles subject to dynamical uncertainties and ocean disturbances induced by unknown wind, wave and ocean current. The control design falls neatly into two parts. One is to steer individual marine surface vehicle to track a predefined path and the other is to synchronise the along-path speed and path variables under the constraints of an underlying communication network. Within these two formulations, a robust adaptive path-following controller is first designed for individual vehicles based on backstepping and neural network techniques. Then, a decentralised synchronisation control law is derived by means of consensus on along-path speed and path variables based on graph theory. The distinct feature of this design lies in that synchronised path following can be reached for any undirected connected communication graphs without accurate knowledge of the model. This result is further extended to the output feedback case, where an observer-based cooperative path-following controller is developed without measuring the velocity of each vehicle. For both designs, rigorous theoretical analysis demonstrate that all signals in the closed-loop system are semi-global uniformly ultimately bounded. Simulation results validate the performance and robustness improvement of the proposed strategy.

  20. Adaptive fuzzy control with output feedback for H infinity tracking of SISO nonlinear systems.

    PubMed

    Rigatos, Gerasimos G

    2008-08-01

    Observer-based adaptive fuzzy H(infinity) control is proposed to achieve H(infinity) tracking performance for a class of nonlinear systems, which are subject to model uncertainty and external disturbances and in which only a measurement of the output is available. The key ideas in the design of the proposed controller are (i) to transform the nonlinear control problem into a regulation problem through suitable output feedback, (ii) to design a state observer for the estimation of the non-measurable elements of the system's state vector, (iii) to design neuro-fuzzy approximators that receive as inputs the parameters of the reconstructed state vector and give as output an estimation of the system's unknown dynamics, (iv) to use an H(infinity) control term for the compensation of external disturbances and modelling errors, (v) to use Lyapunov stability analysis in order to find the learning law for the neuro-fuzzy approximators, and a supervisory control term for disturbance and modelling error rejection. The control scheme is tested in the cart-pole balancing problem and in a DC-motor model.

  1. Negative Feedback Enables Fast and Flexible Collective Decision-Making in Ants

    PubMed Central

    Grüter, Christoph; Schürch, Roger; Czaczkes, Tomer J.; Taylor, Keeley; Durance, Thomas; Jones, Sam M.; Ratnieks, Francis L. W.

    2012-01-01

    Positive feedback plays a major role in the emergence of many collective animal behaviours. In many ants pheromone trails recruit and direct nestmate foragers to food sources. The strong positive feedback caused by trail pheromones allows fast collective responses but can compromise flexibility. Previous laboratory experiments have shown that when the environment changes, colonies are often unable to reallocate their foragers to a more rewarding food source. Here we show both experimentally, using colonies of Lasius niger, and with an agent-based simulation model, that negative feedback caused by crowding at feeding sites allows ant colonies to maintain foraging flexibility even with strong recruitment to food sources. In a constant environment, negative feedback prevents the frequently found bias towards one feeder (symmetry breaking) and leads to equal distribution of foragers. In a changing environment, negative feedback allows a colony to quickly reallocate the majority of its foragers to a superior food patch that becomes available when foraging at an inferior patch is already well underway. The model confirms these experimental findings and shows that the ability of colonies to switch to a superior food source does not require the decay of trail pheromones. Our results help to resolve inconsistencies between collective foraging patterns seen in laboratory studies and observations in the wild, and show that the simultaneous action of negative and positive feedback is important for efficient foraging in mass-recruiting insect colonies. PMID:22984518

  2. Negative feedback enables fast and flexible collective decision-making in ants.

    PubMed

    Grüter, Christoph; Schürch, Roger; Czaczkes, Tomer J; Taylor, Keeley; Durance, Thomas; Jones, Sam M; Ratnieks, Francis L W

    2012-01-01

    Positive feedback plays a major role in the emergence of many collective animal behaviours. In many ants pheromone trails recruit and direct nestmate foragers to food sources. The strong positive feedback caused by trail pheromones allows fast collective responses but can compromise flexibility. Previous laboratory experiments have shown that when the environment changes, colonies are often unable to reallocate their foragers to a more rewarding food source. Here we show both experimentally, using colonies of Lasius niger, and with an agent-based simulation model, that negative feedback caused by crowding at feeding sites allows ant colonies to maintain foraging flexibility even with strong recruitment to food sources. In a constant environment, negative feedback prevents the frequently found bias towards one feeder (symmetry breaking) and leads to equal distribution of foragers. In a changing environment, negative feedback allows a colony to quickly reallocate the majority of its foragers to a superior food patch that becomes available when foraging at an inferior patch is already well underway. The model confirms these experimental findings and shows that the ability of colonies to switch to a superior food source does not require the decay of trail pheromones. Our results help to resolve inconsistencies between collective foraging patterns seen in laboratory studies and observations in the wild, and show that the simultaneous action of negative and positive feedback is important for efficient foraging in mass-recruiting insect colonies.

  3. Negative feedback enables fast and flexible collective decision-making in ants.

    PubMed

    Grüter, Christoph; Schürch, Roger; Czaczkes, Tomer J; Taylor, Keeley; Durance, Thomas; Jones, Sam M; Ratnieks, Francis L W

    2012-01-01

    Positive feedback plays a major role in the emergence of many collective animal behaviours. In many ants pheromone trails recruit and direct nestmate foragers to food sources. The strong positive feedback caused by trail pheromones allows fast collective responses but can compromise flexibility. Previous laboratory experiments have shown that when the environment changes, colonies are often unable to reallocate their foragers to a more rewarding food source. Here we show both experimentally, using colonies of Lasius niger, and with an agent-based simulation model, that negative feedback caused by crowding at feeding sites allows ant colonies to maintain foraging flexibility even with strong recruitment to food sources. In a constant environment, negative feedback prevents the frequently found bias towards one feeder (symmetry breaking) and leads to equal distribution of foragers. In a changing environment, negative feedback allows a colony to quickly reallocate the majority of its foragers to a superior food patch that becomes available when foraging at an inferior patch is already well underway. The model confirms these experimental findings and shows that the ability of colonies to switch to a superior food source does not require the decay of trail pheromones. Our results help to resolve inconsistencies between collective foraging patterns seen in laboratory studies and observations in the wild, and show that the simultaneous action of negative and positive feedback is important for efficient foraging in mass-recruiting insect colonies. PMID:22984518

  4. Regret and adaptive decision making in young children.

    PubMed

    O'Connor, Eimear; McCormack, Teresa; Beck, Sarah R; Feeney, Aidan

    2015-07-01

    In line with the claim that regret plays a role in decision making, O'Connor, McCormack, and Feeney (Child Development, 85 (2014) 1995-2010) found that children who reported feeling sadder on discovering they had made a non-optimal choice were more likely to make a different choice the next time around. We examined two issues of interpretation regarding this finding: whether the emotion measured was indeed regret and whether it was the experience of this emotion, rather than the ability to anticipate it, that affected decision making. To address the first issue, we varied the degree to which children aged 6 or 7 years were responsible for an outcome, assuming that responsibility is a necessary condition for regret. The second issue was addressed by examining whether children could accurately anticipate that they would feel worse on discovering they had made a non-optimal choice. Children were more likely to feel sad if they were responsible for the outcome; however, even if they were not responsible, children were more likely than chance to report feeling sadder. Moreover, across all conditions, feeling sadder was associated with making a better subsequent choice. In a separate task, we demonstrated that children of this age cannot accurately anticipate feeling sadder on discovering that they had not made the best choice. These findings suggest that although children may feel regret following a non-optimal choice, even if they were not responsible for an outcome, they may experience another negative emotion such as frustration. Experiencing either of these emotions seems to be sufficient to support better decision making.

  5. The Carpe Diem West Academy: Connecting Water Resources Practitioners and Decision Support Tool Developers in Pursuit of Climate Change Adaptation

    NASA Astrophysics Data System (ADS)

    Hartmann, H. C.; morino, K.; Wiltshire, K.

    2012-12-01

    Water resources practitioners face a confusing and often overwhelming plethora of evolving tools and methods for considering climate change in planning and management. Many tools require substantial investments in data gathering, analysis, or stakeholder engagement. Many address only pieces of the climate change adaptation challenge without clear interconnection. Additionally, there are few standards of practice in the application of these tools. The Carpe Diem West Academy provides knowledge sharing, community building, and collaboration among water resources practitioners and decision support tool developers to facilitate use of science in adaptation efforts. The technical core of the Academy is a web portal (carpediemwestacademy.org) that uses multiple frameworks, including iterative risk management, to organize an interactive compendium of over 150 tools and training resources developed by others, that are useful for water resources planning and management, including consideration of interconnections with other resources such as energy and ecosystem services. Academy users are supported through a variety of experimental approaches, including webinars and facilitated web discussion, for efficiently engaging water resources practitioners, at a scale that is practical to sustain, that fosters shared learning about tools and their application in adaptation efforts, and that can support establishment of best practices for incorporating uncertainty and climate change. The Academy has also been useful for identifying gaps where additional tools, methods, or professional development training are needed, and for providing feedback to tool developers. We report on key findings on the effectiveness of the Academy's multiple approaches.

  6. To Know or Not to Know? Theta and Delta Reflect Complementary Information about an Advanced Cue before Feedback in Decision-Making

    PubMed Central

    Wang, Jing; Chen, Zhaofeng; Peng, Xiaozhe; Yang, Tiantian; Li, Peng; Cong, Fengyu; Li, Hong

    2016-01-01

    To investigate brain activity during the reinforcement learning process in social contexts is a topic of increasing research interest. Previous studies have mainly focused on using electroencephalograms (EEGs) for feedback evaluation in reinforcement learning tasks by measuring event-related potentials. Few studies have investigated the time–frequency (TF) profiles of a cue that manifested whether a following feedback is available or not after decision-making. Moreover, it remains unclear whether the TF profiles of the cue interact with different agents to whom the feedback related. In this study we used the TF approach to test EEG oscillations of the cue stimuli in three agents (‘Self’, ‘Other’, and ‘Computer’) conditions separately. The results showed that the increased central-posterior delta power was elicited by the feedback unavailable cues more so than with the feedback available cue within 200–350 ms after the onset of the cue, but only in the self-condition. Moreover, a frontal-central theta oscillation had enhanced power when following the feedback unavailable cue as opposed to the feedback available cue across three agencies. These findings demonstrated that the cue for knowing an outcome produced reward prediction error-like signals, which were mirrored by the delta and theta oscillations during decision-making. More importantly, the present study demonstrated that the theta and delta oscillations reflected separable components of the advanced cue processing before the feedback in decision-making. PMID:27766090

  7. Online adaptive policy learning algorithm for H∞ state feedback control of unknown affine nonlinear discrete-time systems.

    PubMed

    Zhang, Huaguang; Qin, Chunbin; Jiang, Bin; Luo, Yanhong

    2014-12-01

    The problem of H∞ state feedback control of affine nonlinear discrete-time systems with unknown dynamics is investigated in this paper. An online adaptive policy learning algorithm (APLA) based on adaptive dynamic programming (ADP) is proposed for learning in real-time the solution to the Hamilton-Jacobi-Isaacs (HJI) equation, which appears in the H∞ control problem. In the proposed algorithm, three neural networks (NNs) are utilized to find suitable approximations of the optimal value function and the saddle point feedback control and disturbance policies. Novel weight updating laws are given to tune the critic, actor, and disturbance NNs simultaneously by using data generated in real-time along the system trajectories. Considering NN approximation errors, we provide the stability analysis of the proposed algorithm with Lyapunov approach. Moreover, the need of the system input dynamics for the proposed algorithm is relaxed by using a NN identification scheme. Finally, simulation examples show the effectiveness of the proposed algorithm. PMID:25095274

  8. Adaptive Disturbance Tracking Theory with State Estimation and State Feedback for Region II Control of Large Wind Turbines

    NASA Technical Reports Server (NTRS)

    Balas, Mark J.; Thapa Magar, Kaman S.; Frost, Susan A.

    2013-01-01

    A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.

  9. Studies on effects of feedback delay on the convergence performance of adaptive time-domain equalizers for fiber dispersive channels

    NASA Astrophysics Data System (ADS)

    Guo, Qun; Xu, Bo; Qiu, Kun

    2016-04-01

    Adaptive time-domain equalizer (TDE) is an important module for digital optical coherent receivers. From an implementation perspective, we analyze and compare in detail the effects of error signal feedback delay on the convergence performance of TDE using either least-mean square (LMS) or constant modulus algorithm (CMA). For this purpose, a simplified theoretical model is proposed based on which iterative equations on the mean value and the variance of the tap coefficient are derived with or without error signal feedback delay for both LMS- and CMA-based methods for the first time. The analytical results show that decreased step size has to be used for TDE to converge and a slower convergence speed cannot be avoided as the feedback delay increases. Compared with the data-aided LMS-based method, the CMA-based method has a slower convergence speed and larger variation after convergence. Similar results are confirmed using numerical simulations for fiber dispersive channels. As the step size increases, a feedback delay of 20 clock cycles might cause the TDE to diverge. Compared with the CMA-based method, the LMS-based method has a higher tolerance on the feedback delay and allows a larger step size for a faster convergence speed.

  10. Different strategies underlying uncertain decision making: higher executive performance is associated with enhanced feedback-related negativity.

    PubMed

    Kóbor, Andrea; Takács, Ádám; Janacsek, Karolina; Németh, Dezső; Honbolygó, Ferenc; Csépe, Valéria

    2015-03-01

    The aim of the present study was to investigate the role of executive functions (EFs) in different strategies underlying risky decision making. Adult participants from a nonclinical sample were assigned to low or high EF groups based on their performance on EF tasks measuring shifting, updating, and inhibition. ERPs were recorded while participants performed the Balloon Analogue Risk Task (BART). In this task, each balloon pump was associated with either a reward or a balloon pop with unknown probability. The BART behavioral measures did not show between-group differences. However, the feedback-related negativity (FRN) associated with undesirable outcomes was larger in the high EF group than in the low EF group. Since the FRN represents salience prediction error, our results suggest that the high EF group formed internal models that were violated by the outcomes. Thus, we provided ERP evidence for EFs influencing risky decision-making processes. PMID:25224177

  11. Adult Vocational Education Follow Through. A System for Participant Feedback for Decision Makers. Final Report.

    ERIC Educational Resources Information Center

    White, Thomas R.

    The objectives of this project were (1) to develop participant feedback materials that can be used by local adult vocational education (AVE) administrators for program planning, implementation, and evaluation and (2) to determine why participants enroll in AVE programs. A follow-up survey which contained key items from the follow-through system…

  12. Can Conservation Contracts Co-exist with Change? Payment for Ecosystem Services in the Context of Adaptive Decision-Making and Sustainability

    NASA Astrophysics Data System (ADS)

    Hayes, Tanya; Murtinho, Felipe; Cárdenas Camacho, Luis Mario; Crespo, Patricio; McHugh, Sarah; Salmerón, David

    2015-01-01

    This paper considers the ability of payment for ecosystem services (PES) programs to operate in the context of dynamic and complex social-ecological systems. Drawing on the experiences of two different PES programs in Latin America, we examine how PES institutions fit with the tenets of adaptive decision-making for sustainable resource management. We identify how the program goals and the connection to the market influence the incentive structure, information gathering, learning and feedback processes, and the structure of decision-making rights, specifically the ability to make and modify resource-use rules. Although limited in their generalizability, findings from the two case studies suggest a tension between the contractual model of PES and adaptive decision-making in natural resource systems. PES programs are not inherently decentralized, flexible management tools, as PES contracts tend to restrict decision-making rights and offer minimal flexibility mechanisms to change resource-use practices over the duration of the contract period. Furthermore, PES design and flexibility is heavily dependent on the goals and mission of the buyer and the respective market. If PES is to facilitate sustainable resource management, greater attention is needed to assess how the institutional design of the PES contracts influence the motivation and capacity of participants and program officers alike to adaptively manage the respective resource systems.

  13. Optimizing Decision Preparedness by Adapting Scenario Complexity and Automating Scenario Generation

    NASA Technical Reports Server (NTRS)

    Dunne, Rob; Schatz, Sae; Flore, Stephen M.; Nicholson, Denise

    2011-01-01

    Klein's recognition-primed decision (RPD) framework proposes that experts make decisions by recognizing similarities between current decision situations and previous decision experiences. Unfortunately, military personnel arQ often presented with situations that they have not experienced before. Scenario-based training (S8T) can help mitigate this gap. However, SBT remains a challenging and inefficient training approach. To address these limitations, the authors present an innovative formulation of scenario complexity that contributes to the larger research goal of developing an automated scenario generation system. This system will enable trainees to effectively advance through a variety of increasingly complex decision situations and experiences. By adapting scenario complexities and automating generation, trainees will be provided with a greater variety of appropriately calibrated training events, thus broadening their repositories of experience. Preliminary results from empirical testing (N=24) of the proof-of-concept formula are presented, and future avenues of scenario complexity research are also discussed.

  14. Self-reported strategies in decisions under risk: role of feedback, reasoning abilities, executive functions, short-term-memory, and working memory.

    PubMed

    Schiebener, Johannes; Brand, Matthias

    2015-11-01

    In decisions under objective risk conditions information about the decision options' possible outcomes and the rules for outcomes' occurrence are provided. Thus, deciders can base decision-making strategies on probabilistic laws. In many laboratory decision-making tasks, choosing the option with the highest winning probability in all trials (=maximization strategy) is probabilistically regarded the most rational behavior. However, individuals often behave less optimal, especially in case the individuals have lower cognitive functions or in case no feedback about consequences is provided in the situation. It is still unclear which cognitive functions particularly predispose individuals for using successful strategies and which strategies profit from feedback. We investigated 195 individuals with two decision-making paradigms, the Game of Dice Task (GDT) (with and without feedback), and the Card Guessing Game. Thereafter, participants reported which strategies they had applied. Interaction effects (feedback × strategy), effect sizes, and uncorrected single group comparisons suggest that feedback in the GDT tended to be more beneficial to individuals reporting exploratory strategies (e.g., use intuition). In both tasks, the self-reported use of more principled and more rational strategies was accompanied by better decision-making performance and better performances in reasoning and executive functioning tasks. The strategy groups did not significantly differ in most short-term and working-memory tasks. Thus, particularly individual differences in reasoning and executive functions seem to predispose individuals toward particular decision-making strategies. Feedback seems to be useful for individuals who rather explore the decision-making situation instead of following a certain plan. PMID:26289475

  15. Response-adaptive decision-theoretic trial design: operating characteristics and ethics.

    PubMed

    Lipsky, Ari M; Lewis, Roger J

    2013-09-20

    Adaptive randomization is used in clinical trials to increase statistical efficiency. In addition, some clinicians and researchers believe that using adaptive randomization leads necessarily to more ethical treatment of subjects in a trial. We develop Bayesian, decision-theoretic, clinical trial designs with response-adaptive randomization and a primary goal of estimating treatment effect and then contrast these designs with designs that also include in their loss function a cost for poor subject outcome. When the loss function did not incorporate a cost for poor subject outcome, the gains in efficiency from response-adaptive randomization were accompanied by ethically concerning subject allocations. Conversely, including a cost for poor subject outcome demonstrated a more acceptable balance between the competing needs in the trial. A subsequent, parallel set of trials designed to control explicitly types I and II error rates showed that much of the improvement achieved through modification of the loss function was essentially negated. Therefore, gains in efficiency from the use of a decision-theoretic, response-adaptive design using adaptive randomization may only be assumed to apply to those goals that are explicitly included in the loss function. Trial goals, including ethical ones, which do not appear in the loss function, are ignored and may even be compromised; it is thus inappropriate to assume that all adaptive trials are necessarily more ethical. Controlling types I and II error rates largely negates the benefit of including competing needs in favor of the goal of parameter estimation.

  16. Lost in Search: (Mal-)Adaptation to Probabilistic Decision Environments in Children and Adults

    ERIC Educational Resources Information Center

    Betsch, Tilmann; Lehmann, Anne; Lindow, Stefanie; Lang, Anna; Schoemann, Martin

    2016-01-01

    Adaptive decision making in probabilistic environments requires individuals to use probabilities as weights in predecisional information searches and/or when making subsequent choices. Within a child-friendly computerized environment (Mousekids), we tracked 205 children's (105 children 5-6 years of age and 100 children 9-10 years of age) and 103…

  17. Quantifying the Value of Downscaled Climate Model Information for Adaptation Decisions: When is Downscaling a Smart Decision?

    NASA Astrophysics Data System (ADS)

    Terando, A. J.; Wootten, A.; Eaton, M. J.; Runge, M. C.; Littell, J. S.; Bryan, A. M.; Carter, S. L.

    2015-12-01

    Two types of decisions face society with respect to anthropogenic climate change: (1) whether to enact a global greenhouse gas abatement policy, and (2) how to adapt to the local consequences of current and future climatic changes. The practice of downscaling global climate models (GCMs) is often used to address (2) because GCMs do not resolve key features that will mediate global climate change at the local scale. In response, the development of downscaling techniques and models has accelerated to aid decision makers seeking adaptation guidance. However, quantifiable estimates of the value of information are difficult to obtain, particularly in decision contexts characterized by deep uncertainty and low system-controllability. Here we demonstrate a method to quantify the additional value that decision makers could expect if research investments are directed towards developing new downscaled climate projections. As a proof of concept we focus on a real-world management problem: whether to undertake assisted migration for an endangered tropical avian species. We also take advantage of recently published multivariate methods that account for three vexing issues in climate impacts modeling: maximizing climate model quality information, accounting for model dependence in ensembles of opportunity, and deriving probabilistic projections. We expand on these global methods by including regional (Caribbean Basin) and local (Puerto Rico) domains. In the local domain, we test whether a high resolution (2km) dynamically downscaled GCM reduces the multivariate error estimate compared to the original coarse-scale GCM. Initial tests show little difference between the downscaled and original GCM multivariate error. When propagated through to a species population model, the Value of Information analysis indicates that the expected utility that would accrue to the manager (and species) if this downscaling were completed may not justify the cost compared to alternative actions.

  18. Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development

    PubMed Central

    Hauser, Tobias U.; Iannaccone, Reto; Walitza, Susanne; Brandeis, Daniel; Brem, Silvia

    2015-01-01

    Adolescence is associated with quickly changing environmental demands which require excellent adaptive skills and high cognitive flexibility. Feedback-guided adaptive learning and cognitive flexibility are driven by reward prediction error (RPE) signals, which indicate the accuracy of expectations and can be estimated using computational models. Despite the importance of cognitive flexibility during adolescence, only little is known about how RPE processing in cognitive flexibility deviates between adolescence and adulthood. In this study, we investigated the developmental aspects of cognitive flexibility by means of computational models and functional magnetic resonance imaging (fMRI). We compared the neural and behavioral correlates of cognitive flexibility in healthy adolescents (12–16 years) to adults performing a probabilistic reversal learning task. Using a modified risk-sensitive reinforcement learning model, we found that adolescents learned faster from negative RPEs than adults. The fMRI analysis revealed that within the RPE network, the adolescents had a significantly altered RPE-response in the anterior insula. This effect seemed to be mainly driven by increased responses to negative prediction errors. In summary, our findings indicate that decision making in adolescence goes beyond merely increased reward-seeking behavior and provides a developmental perspective to the behavioral and neural mechanisms underlying cognitive flexibility in the context of reinforcement learning. PMID:25234119

  19. Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

    PubMed

    Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

    2014-06-01

    This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

  20. Using social network analysis to evaluate health-related adaptation decision-making in Cambodia.

    PubMed

    Bowen, Kathryn J; Alexander, Damon; Miller, Fiona; Dany, Va

    2014-01-30

    Climate change adaptation in the health sector requires decisions across sectors, levels of government, and organisations. The networks that link these different institutions, and the relationships among people within these networks, are therefore critical influences on the nature of adaptive responses to climate change in the health sector. This study uses social network research to identify key organisational players engaged in developing health-related adaptation activities in Cambodia. It finds that strong partnerships are reported as developing across sectors and different types of organisations in relation to the health risks from climate change. Government ministries are influential organisations, whereas donors, development banks and non-government organisations do not appear to be as influential in the development of adaptation policy in the health sector. Finally, the study highlights the importance of informal partnerships (or 'shadow networks') in the context of climate change adaptation policy and activities. The health governance 'map' in relation to health and climate change adaptation that is developed in this paper is a novel way of identifying organisations that are perceived as key agents in the decision-making process, and it holds substantial benefits for both understanding and intervening in a broad range of climate change-related policy problems where collaboration is paramount for successful outcomes.

  1. Using social network analysis to evaluate health-related adaptation decision-making in Cambodia.

    PubMed

    Bowen, Kathryn J; Alexander, Damon; Miller, Fiona; Dany, Va

    2014-02-01

    Climate change adaptation in the health sector requires decisions across sectors, levels of government, and organisations. The networks that link these different institutions, and the relationships among people within these networks, are therefore critical influences on the nature of adaptive responses to climate change in the health sector. This study uses social network research to identify key organisational players engaged in developing health-related adaptation activities in Cambodia. It finds that strong partnerships are reported as developing across sectors and different types of organisations in relation to the health risks from climate change. Government ministries are influential organisations, whereas donors, development banks and non-government organisations do not appear to be as influential in the development of adaptation policy in the health sector. Finally, the study highlights the importance of informal partnerships (or 'shadow networks') in the context of climate change adaptation policy and activities. The health governance 'map' in relation to health and climate change adaptation that is developed in this paper is a novel way of identifying organisations that are perceived as key agents in the decision-making process, and it holds substantial benefits for both understanding and intervening in a broad range of climate change-related policy problems where collaboration is paramount for successful outcomes. PMID:24487452

  2. Using Social Network Analysis to Evaluate Health-Related Adaptation Decision-Making in Cambodia

    PubMed Central

    Bowen, Kathryn J.; Alexander, Damon; Miller, Fiona; Dany, Va

    2014-01-01

    Climate change adaptation in the health sector requires decisions across sectors, levels of government, and organisations. The networks that link these different institutions, and the relationships among people within these networks, are therefore critical influences on the nature of adaptive responses to climate change in the health sector. This study uses social network research to identify key organisational players engaged in developing health-related adaptation activities in Cambodia. It finds that strong partnerships are reported as developing across sectors and different types of organisations in relation to the health risks from climate change. Government ministries are influential organisations, whereas donors, development banks and non-government organisations do not appear to be as influential in the development of adaptation policy in the health sector. Finally, the study highlights the importance of informal partnerships (or ‘shadow networks’) in the context of climate change adaptation policy and activities. The health governance ‘map’ in relation to health and climate change adaptation that is developed in this paper is a novel way of identifying organisations that are perceived as key agents in the decision-making process, and it holds substantial benefits for both understanding and intervening in a broad range of climate change-related policy problems where collaboration is paramount for successful outcomes. PMID:24487452

  3. Application of Adaptive Decision Aiding Systems to Computer-Assisted Instruction. Final Report, January-December 1974.

    ERIC Educational Resources Information Center

    May, Donald M.; And Others

    The minicomputer-based Computerized Diagnostic and Decision Training (CDDT) system described combines the principles of artificial intelligence, decision theory, and adaptive computer assisted instruction for training in electronic troubleshooting. The system incorporates an adaptive computer program which learns the student's diagnostic and…

  4. Designing adaptive integral sliding mode control for heart rate regulation during cycle-ergometer exercise using bio-feedback.

    PubMed

    Argha, Ahmadreza; Su, Steven W; Nguyen, Hung; Celler, Branko G

    2015-01-01

    This paper considers our developed control system which aims to regulate the exercising subjects' heart rate (HR) to a predefined profile. The controller would be an adaptive integral sliding mode controller. Here it is assumed that the controller commands are interpreted as biofeedback auditory commands. These commands can be heard and implemented by the exercising subject as a part of the control-loop. However, transmitting a feedback signal while the pedals are not in the appropriate position to efficiently exert force may lead to a cognitive disengagement of the user from the feedback controller. To address this problem this paper will employ a different form of control system regarding as "actuator-based event-driven control system". This paper will claim that the developed event-driven controller makes it possible to effectively regulate HR to a predetermined HR profile.

  5. Spacecraft Formation Flying near Sun-Earth L2 Lagrange Point: Trajectory Generation and Adaptive Full-State Feedback Control

    NASA Technical Reports Server (NTRS)

    Wong, Hong; Kapila, Vikram

    2004-01-01

    In this paper, we present a method for trajectory generation and adaptive full-state feedback control to facilitate spacecraft formation flying near the Sun-Earth L2 Lagrange point. Specifically, the dynamics of a spacecraft in the neighborhood of a Halo orbit reveals that there exist quasi-periodic orbits surrounding the Halo orbit. Thus, a spacecraft formation is created by placing a leader spacecraft on a desired Halo orbit and placing follower spacecraft on desired quasi-periodic orbits. To produce a formation maintenance controller, we first develop the nonlinear dynamics of a follower spacecraft relative to the leader spacecraft. We assume that the leader spacecraft is on a desired Halo orbit trajectory and the follower spacecraft is to track a desired quasi-periodic orbit surrounding the Halo orbit. Then, we design an adaptive, full-state feedback position tracking controller for the follower spacecraft providing an adaptive compensation for the unknown mass of the follower spacecraft. The proposed control law is simulated for the case of the leader and follower spacecraft pair and is shown to yield global, asymptotic convergence of the relative position tracking errors.

  6. Wearable real-time and adaptive feedback device to face the stuttering: a knowledge-based telehealthcare proposal.

    PubMed

    Prado, Manuel; Roa, Laura M

    2007-01-01

    Despite first written references to permanent developmental stuttering occurred more than 2500 years ago, the mechanisms underlying this disorder are still unknown. This paper briefly reviews stuttering causal hypothesis and treatments, and presents the requirements that a new stuttering therapeutic device should verify. As a result of the analysis, an adaptive altered auditory feedback device based on a multimodal intelligent monitor, within the framework of a knowledge-based telehealthcare system, is presented. The subsequent discussion, based partly on the successful outcomes of a similar intelligent monitor, suggests that this novel device is feasible and could help to fill the gap between research and clinic.

  7. Wearable real-time and adaptive feedback device to face the stuttering: a knowledge-based telehealthcare proposal.

    PubMed

    Prado, Manuel; Roa, Laura M

    2007-01-01

    Despite first written references to permanent developmental stuttering occurred more than 2500 years ago, the mechanisms underlying this disorder are still unknown. This paper briefly reviews stuttering causal hypothesis and treatments, and presents the requirements that a new stuttering therapeutic device should verify. As a result of the analysis, an adaptive altered auditory feedback device based on a multimodal intelligent monitor, within the framework of a knowledge-based telehealthcare system, is presented. The subsequent discussion, based partly on the successful outcomes of a similar intelligent monitor, suggests that this novel device is feasible and could help to fill the gap between research and clinic. PMID:17901608

  8. What works for you? Using teacher feedback to inform adaptations of pivotal response training for classroom use.

    PubMed

    Stahmer, Aubyn C; Suhrheinrich, Jessica; Reed, Sarah; Schreibman, Laura

    2012-01-01

    Several evidence-based practices (EBPs) have been identified as efficacious for the education of students with autism spectrum disorders (ASD). However, effectiveness research has rarely been conducted in schools and teachers express skepticism about the clinical utility of EBPs for the classroom. Innovative methods are needed to optimally adapt EBPs for community use. This study utilizes qualitative methods to identify perceived benefits and barriers of classroom implementation of a specific EBP for ASD, Pivotal Response Training (PRT). Teachers' perspectives on the components of PRT, use of PRT as a classroom intervention strategy, and barriers to the use of PRT were identified through guided discussion. Teachers found PRT valuable; however, they also found some components challenging. Specific teacher recommendations for adaptation and resource development are discussed. This process of obtaining qualitative feedback from frontline practitioners provides a generalizable model for researchers to collaborate with teachers to optimally promote EBPs for classroom use.

  9. Adaptive neural tracking control of a class of MIMO pure-feedback time-delay nonlinear systems with input saturation

    NASA Astrophysics Data System (ADS)

    Yang, Yang; Yue, Dong; Yuan, Deming

    2016-11-01

    Considering interconnections among subsystems, we propose an adaptive neural tracking control scheme for a class of multiple-input-multiple-output (MIMO) non-affine pure-feedback time-delay nonlinear systems with input saturation. Neural networks (NNs) are employed to approximate unknown functions in the design procedure, and the separation technology is introduced here to tackle the problem induced from unknown time-delay items. The adaptive neural tracking control scheme is constructed by combining Lyapunov-Krasovskii functionals, NNs, the auxiliary system, the implicit function theory and the mean value theorem along with the dynamic surface control technique. Also, it is proven that the strategy guarantees tracking errors converge to a small neighbourhood around the origin by appropriate choice of design parameters and all signals in the closed-loop system uniformly ultimately bounded. Numerical simulation results are presented to demonstrate the effectiveness of the proposed control strategy.

  10. What Works for You? Using Teacher Feedback to Inform Adaptations of Pivotal Response Training for Classroom Use

    PubMed Central

    Stahmer, Aubyn C.; Suhrheinrich, Jessica; Reed, Sarah; Schreibman, Laura

    2012-01-01

    Several evidence-based practices (EBPs) have been identified as efficacious for the education of students with autism spectrum disorders (ASD). However, effectiveness research has rarely been conducted in schools and teachers express skepticism about the clinical utility of EBPs for the classroom. Innovative methods are needed to optimally adapt EBPs for community use. This study utilizes qualitative methods to identify perceived benefits and barriers of classroom implementation of a specific EBP for ASD, Pivotal Response Training (PRT). Teachers' perspectives on the components of PRT, use of PRT as a classroom intervention strategy, and barriers to the use of PRT were identified through guided discussion. Teachers found PRT valuable; however, they also found some components challenging. Specific teacher recommendations for adaptation and resource development are discussed. This process of obtaining qualitative feedback from frontline practitioners provides a generalizable model for researchers to collaborate with teachers to optimally promote EBPs for classroom use. PMID:23209896

  11. Uncertainty assessment of urban pluvial flood risk in a context of climate change adaptation decision making

    NASA Astrophysics Data System (ADS)

    Arnbjerg-Nielsen, Karsten; Zhou, Qianqian

    2014-05-01

    There has been a significant increase in climatic extremes in many regions. In Central and Northern Europe, this has led to more frequent and more severe floods. Along with improved flood modelling technologies this has enabled development of economic assessment of climate change adaptation to increasing urban flood risk. Assessment of adaptation strategies often requires a comprehensive risk-based economic analysis of current risk, drivers of change of risk over time, and measures to reduce the risk. However, such studies are often associated with large uncertainties. The uncertainties arise from basic assumptions in the economic analysis and the hydrological model, but also from the projection of future societies to local climate change impacts and suitable adaptation options. This presents a challenge to decision makers when trying to identify robust measures. We present an integrated uncertainty analysis, which can assess and quantify the overall uncertainty in relation to climate change adaptation to urban flash floods. The analysis is based on an uncertainty cascade that by means of Monte Carlo simulations of flood risk assessments incorporates climate change impacts as a key driver of risk changes over time. The overall uncertainty is then attributed to six bulk processes: climate change impact, urban rainfall-runoff processes, stage-depth functions, unit cost of repair, cost of adaptation measures, and discount rate. We apply the approach on an urban hydrological catchment in Odense, Denmark, and find that the uncertainty on the climate change impact appears to have the least influence on the net present value of the studied adaptation measures-. This does not imply that the climate change impact is not important, but that the uncertainties are not dominating when deciding on action or in-action. We then consider the uncertainty related to choosing between adaptation options given that a decision of action has been taken. In this case the major part of the

  12. Together, slowly but surely: the role of social interaction and feedback on the build-up of benefit in collective decision-making.

    PubMed

    Bahrami, Bahador; Olsen, Karsten; Bang, Dan; Roepstorff, Andreas; Rees, Geraint; Frith, Chris

    2012-02-01

    That objective reference is necessary for formation of reliable beliefs about the external world is almost axiomatic. However, Condorcet (1785) suggested that purely subjective information--if shared and combined via social interaction--is enough for accurate understanding of the external world. We asked if social interaction and objective reference contribute differently to the formation and build-up of collective perceptual beliefs. In three experiments, dyads made individual and collective perceptual decisions in a two-interval, forced-choice, visual search task. In Experiment 1, participants negotiated their collective decisions with each other verbally and received feedback about accuracy at the end of each trial. In Experiment 2, feedback was not given. In Experiment 3, communication was not allowed but feedback was provided. Social interaction (Experiments 1 and 2 vs. 3) resulted in a significant collective benefit in perceptual decisions. When feedback was not available a collective benefit was not initially obtained but emerged through practice to the extent that in the second half of the experiments, collective benefits obtained with (Experiment 1) and without (Experiment 2) feedback were robust and statistically indistinguishable. Taken together, this work demonstrates that social interaction was necessary for build-up of reliable collaborative benefit, whereas objective reference only accelerated the process but--given enough opportunity for practice--was not necessary for building up successful cooperation.

  13. Neural network-based optimal adaptive output feedback control of a helicopter UAV.

    PubMed

    Nodland, David; Zargarzadeh, Hassan; Jagannathan, Sarangapani

    2013-07-01

    Helicopter unmanned aerial vehicles (UAVs) are widely used for both military and civilian operations. Because the helicopter UAVs are underactuated nonlinear mechanical systems, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via an output feedback for trajectory tracking of a helicopter UAV, using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic and dynamic controllers and an NN observer. The online approximator-based dynamic controller learns the infinite-horizon Hamilton-Jacobi-Bellman equation in continuous time and calculates the corresponding optimal control input by minimizing a cost function, forward-in-time, without using the value and policy iterations. Optimal tracking is accomplished by using a single NN utilized for the cost function approximation. The overall closed-loop system stability is demonstrated using Lyapunov analysis. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control design for trajectory tracking.

  14. When to throw the switch: The adaptiveness of modifying emotion regulation strategies based on affective and physiological feedback.

    PubMed

    Birk, Jeffrey L; Bonanno, George A

    2016-08-01

    Particular emotion regulation (ER) strategies are beneficial in certain contexts, but little is known about the adaptiveness of switching strategies after implementing an initial strategy. Research and theory on regulatory flexibility suggest that people switch strategies dynamically and that internal states provide feedback indicating when switches are appropriate. Frequent switching may predict positive outcomes among people who respond to this feedback. We investigated whether internal feedback (particularly corrugator activity, heart rate, or subjective negative intensity) guides people to switch to an optimal (i.e., distraction) but not nonoptimal (i.e., reappraisal) strategy for regulating strong emotion. We also tested whether switching frequency and responsiveness to internal feedback (RIF) together predict well-being. While attempting to regulate emotion elicited by unpleasant pictures, participants could switch to an optimal (Study 1; reappraisal-to-distraction order; N = 90) or nonoptimal (Study 2; distraction-to-reappraisal order; N = 95) strategy for high-arousal emotion. A RIF score for each emotion measure indexed the relative strength of emotion during the initial phase for trials on which participants later switched strategies. As hypothesized, negative intensity, corrugator activity, and the magnitude of heart rate deceleration during this early phase were higher on switch than maintain trials in Study 1 only. Critically, in Study 1 only, greater switching frequency predicted higher and lower life satisfaction for participants with high and low corrugator RIF, respectively, even after controlling for reappraisal success. Individual differences in RIF may contribute to subjective well-being provided that the direction of strategy switching aligns well with regulatory preferences for high emotion. (PsycINFO Database Record PMID:26900993

  15. Enhanced Adaptive Management: Integrating Decision Analysis, Scenario Analysis and Environmental Modeling for the Everglades

    NASA Astrophysics Data System (ADS)

    Convertino, Matteo; Foran, Christy M.; Keisler, Jeffrey M.; Scarlett, Lynn; Loschiavo, Andy; Kiker, Gregory A.; Linkov, Igor

    2013-10-01

    We propose to enhance existing adaptive management efforts with a decision-analytical approach that can guide the initial selection of robust restoration alternative plans and inform the need to adjust these alternatives in the course of action based on continuously acquired monitoring information and changing stakeholder values. We demonstrate an application of enhanced adaptive management for a wetland restoration case study inspired by the Florida Everglades restoration effort. We find that alternatives designed to reconstruct the pre-drainage flow may have a positive ecological impact, but may also have high operational costs and only marginally contribute to meeting other objectives such as reduction of flooding. Enhanced adaptive management allows managers to guide investment in ecosystem modeling and monitoring efforts through scenario and value of information analyses to support optimal restoration strategies in the face of uncertain and changing information.

  16. A two-neuron system for adaptive goal-directed decision-making in Lymnaea

    PubMed Central

    Crossley, Michael; Staras, Kevin; Kemenes, György

    2016-01-01

    During goal-directed decision-making, animals must integrate information from the external environment and their internal state to maximize resource localization while minimizing energy expenditure. How this complex problem is solved by the nervous system remains poorly understood. Here, using a combined behavioural and neurophysiological approach, we demonstrate that the mollusc Lymnaea performs a sophisticated form of decision-making during food-searching behaviour, using a core system consisting of just two neuron types. The first reports the presence of food and the second encodes motivational state acting as a gain controller for adaptive behaviour in the absence of food. Using an in vitro analogue of the decision-making process, we show that the system employs an energy management strategy, switching between a low- and high-use mode depending on the outcome of the decision. Our study reveals a parsimonious mechanism that drives a complex decision-making process via regulation of levels of tonic inhibition and phasic excitation. PMID:27257106

  17. A two-neuron system for adaptive goal-directed decision-making in Lymnaea.

    PubMed

    Crossley, Michael; Staras, Kevin; Kemenes, György

    2016-01-01

    During goal-directed decision-making, animals must integrate information from the external environment and their internal state to maximize resource localization while minimizing energy expenditure. How this complex problem is solved by the nervous system remains poorly understood. Here, using a combined behavioural and neurophysiological approach, we demonstrate that the mollusc Lymnaea performs a sophisticated form of decision-making during food-searching behaviour, using a core system consisting of just two neuron types. The first reports the presence of food and the second encodes motivational state acting as a gain controller for adaptive behaviour in the absence of food. Using an in vitro analogue of the decision-making process, we show that the system employs an energy management strategy, switching between a low- and high-use mode depending on the outcome of the decision. Our study reveals a parsimonious mechanism that drives a complex decision-making process via regulation of levels of tonic inhibition and phasic excitation. PMID:27257106

  18. Neural correlates of rules and conflict in medial prefrontal cortex during decision and feedback epochs

    PubMed Central

    Bissonette, Gregory B.; Roesch, Matthew R.

    2015-01-01

    The ability to properly adjust behavioral responses to cues in a changing environment is crucial for survival. Activity in the medial Prefrontal Cortex (mPFC) is thought to both represent rules to guide behavior as well as detect and resolve conflicts between rules in changing contingencies. However, while lesion and pharmacological studies have supported a crucial role for mPFC in this type of set-shifting, an understanding of how mPFC represents current rules or detects and resolves conflict between different rules is unclear. Here, we directly address the role of rat mPFC in shifting rule based behavioral strategies using a novel behavioral task designed to tease apart neural signatures of rules, conflict and direction. We demonstrate that activity of single neurons in rat mPFC represent distinct rules. Further, we show increased firing on high conflict trials in a separate population of mPFC neurons. Reduced firing in both populations of neurons was associated with poor performance. Moreover, activity in both populations increased and decreased firing during the outcome epoch when reward was and was not delivered on correct and incorrect trials, respectively. In addition, outcome firing was modulated by the current rule and the degree of conflict associated with the previous decision. These results promote a greater understanding of the role that mPFC plays in switching between rules, signaling both rule and conflict to promote improved behavioral performance. PMID:26500516

  19. Adaptive decision systems with extended learning for deployment in partially exposed environments

    NASA Astrophysics Data System (ADS)

    Dasarathy, Belur V.

    1995-05-01

    The design and development of decision systems capable of adaptively learning in the operational environment is presented. Innovative adaptive learning concepts and methodologies are offered that are designed for enhancing the performance of decision systems, such as automatic target recognition systems, wherein robustness of performance is a significant issue. The fundamental concept underlying this design is that of learning in partially exposed environments, wherein, at the start, the system is not necessarily aware of all the pattern classes that may be encountered in the future phase of operations. The decision system is based on a variant to the widely popular nearest-neighbor concept. Several stages of sophistication of the system design are presented. The potential problem of increase in computational loads is addressed in detail by exploring the benefits of employing the recently proposed concept of minimal consistent set. The effectiveness of the system design is experimentally illustrated using two data sets, the now classical IRIS data and some real-world TV image data.

  20. Neural network-based optimal adaptive output feedback control of a helicopter UAV.

    PubMed

    Nodland, David; Zargarzadeh, Hassan; Jagannathan, Sarangapani

    2013-07-01

    Helicopter unmanned aerial vehicles (UAVs) are widely used for both military and civilian operations. Because the helicopter UAVs are underactuated nonlinear mechanical systems, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via an output feedback for trajectory tracking of a helicopter UAV, using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic and dynamic controllers and an NN observer. The online approximator-based dynamic controller learns the infinite-horizon Hamilton-Jacobi-Bellman equation in continuous time and calculates the corresponding optimal control input by minimizing a cost function, forward-in-time, without using the value and policy iterations. Optimal tracking is accomplished by using a single NN utilized for the cost function approximation. The overall closed-loop system stability is demonstrated using Lyapunov analysis. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control design for trajectory tracking. PMID:24808521

  1. The diapause decision as a cascade switch for adaptive developmental plasticity in body mass in a butterfly.

    PubMed

    Gotthard, Karl; Berger, D

    2010-06-01

    Switch-induced developmental plasticity, such as the diapause decision in insects, is a major form of adaptation to variable environments. As individuals that follow alternative developmental pathways will experience different selective environments the diapause decision may evolve to a cascade switch that induces additional adaptive developmental differences downstream of the diapause decision. Here, we show that individuals following alternative developmental pathways in a Swedish population of the butterfly, Pararge aegeria, display differential optimization of adult body mass as a likely response to predictable differences in thermal conditions during reproduction. In a more northern population where this type of selection is absent no similar difference in adult mass among pathways was found. We conclude that the diapause decision in the southern population appears to act as a cascade switch, coordinating development downstream of the diapause decision, to produce adult phenotypes adapted to the typical thermal conditions of their expected reproductive period.

  2. Adaptive fuzzy output-feedback controller design for nonlinear systems via backstepping and small-gain approach.

    PubMed

    Liu, Zhi; Wang, Fang; Zhang, Yun; Chen, Xin; Chen, C L Philip

    2014-10-01

    This paper focuses on an input-to-state practical stability (ISpS) problem of nonlinear systems which possess unmodeled dynamics in the presence of unstructured uncertainties and dynamic disturbances. The dynamic disturbances depend on the states and the measured output of the system, and its assumption conditions are relaxed compared with the common restrictions. Based on an input-driven filter, fuzzy logic systems are directly used to approximate the unknown and desired control signals instead of the unknown nonlinear functions, and an integrated backstepping technique is used to design an adaptive output-feedback controller that ensures robustness with respect to unknown parameters and uncertain nonlinearities. This paper, by applying the ISpS theory and the generalized small-gain approach, shows that the proposed adaptive fuzzy controller guarantees the closed-loop system being semi-globally uniformly ultimately bounded. A main advantage of the proposed controller is that it contains only three adaptive parameters that need to be updated online, no matter how many states there are in the systems. Finally, the effectiveness of the proposed approach is illustrated by two simulation examples. PMID:25222716

  3. 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.

  4. Real-Time Feedback Control of Flow-Induced Cavity Tones. Part 2; Adaptive Control

    NASA Technical Reports Server (NTRS)

    Kegerise, M. A.; Cabell, R. H.; Cattafesta, L. N., III

    2006-01-01

    An adaptive generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The algorithm employs gradient descent to update the GPC coefficients at each time step. Past input-output data and an estimate of the open-loop pulse response sequence are all that is needed to implement the algorithm for application at fixed Mach numbers. Transient measurements made during controller adaptation revealed that the controller coefficients converged to a steady state in the mean, and this implies that adaptation can be turned off at some point with no degradation in control performance. When converged, the control algorithm demonstrated multiple Rossiter mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. However, as in the case of fixed-gain GPC, the adaptive GPC performance was limited by spillover in sidebands around the suppressed Rossiter modes. The algorithm was also able to maintain suppression of multiple cavity tones as the freestream Mach number was varied over a modest range (0.275 to 0.29). Beyond this range, stable operation of the control algorithm was not possible due to the fixed plant model in the algorithm.

  5. A Feedback Control Strategy for Enhancing Item Selection Efficiency in Computerized Adaptive Testing

    ERIC Educational Resources Information Center

    Weissman, Alexander

    2006-01-01

    A computerized adaptive test (CAT) may be modeled as a closed-loop system, where item selection is influenced by trait level ([theta]) estimation and vice versa. When discrepancies exist between an examinee's estimated and true [theta] levels, nonoptimal item selection is a likely result. Nevertheless, examinee response behavior consistent with…

  6. Adaptive learning in a compartmental model of visual cortex—how feedback enables stable category learning and refinement

    PubMed Central

    Layher, Georg; Schrodt, Fabian; Butz, Martin V.; Neumann, Heiko

    2014-01-01

    The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, both of which are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in computational neuroscience. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of additional (sub-) category representations. We demonstrate the temporal evolution of such learning and show how the proposed combination of an associative memory with a modulatory feedback integration successfully establishes category and subcategory representations

  7. Decentralised adaptive output feedback stabilisation for stochastic time-delay systems via LaSalle-Yoshizawa-type theorem

    NASA Astrophysics Data System (ADS)

    Jiao, Ticao; Xu, Shengyuan; Lu, Junwei; Wei, Yunliang; Zou, Yun

    2016-01-01

    This paper deals with the decentralised output feedback stabilisation problem for a class of large-scale stochastic time-delay nonlinear systems. A general theorem is firstly given to guarantee the global existence and uniqueness of the solution for stochastic time-delay systems. In addition, a stochastic version of the well-known LaSalle-Yoshizawa theorem with time-varying delay is initially proposed for the controller design and stability analysis. Then, for a class of large-scale stochastic systems with time-varying delays, totally decentralised adaptive delay-dependent controllers are designed by using K-filter and backstepping approach. Via LaSalle-Yoshizawa-type theorem and constructing a general Lyapunov function, it is shown that all signals in the closed-loop system are bounded almost surely and the solution is almost surely asymptotically stable. Finally, a simulation example is given to illustrate the effectiveness of the results of this paper.

  8. Adaptive output feedback NN control of a class of discrete-time MIMO nonlinear systems with unknown control directions.

    PubMed

    Li, Yanan; Yang, Chenguang; Ge, Shuzhi Sam; Lee, Tong Heng

    2011-04-01

    In this paper, adaptive neural network (NN) control is investigated for a class of block triangular multiinput-multioutput nonlinear discrete-time systems with each subsystem in pure-feedback form with unknown control directions. These systems are of couplings in every equation of each subsystem, and different subsystems may have different orders. To avoid the noncausal problem in the control design, the system is transformed into a predictor form by rigorous derivation. By exploring the properties of the block triangular form, implicit controls are developed for each subsystem such that the couplings of inputs and states among subsystems have been completely decoupled. The radial basis function NN is employed to approximate the unknown control. Each subsystem achieves a semiglobal uniformly ultimately bounded stability with the proposed control, and simulation results are presented to demonstrate its efficiency.

  9. Autogenic-feedback training: A preventive method for space adaptation syndrome

    NASA Technical Reports Server (NTRS)

    Cowings, Patricia S.; Sharp, Joseph C.; Toscano, William B.; Kamiya, Joe; Miller, Neal E.

    1987-01-01

    The progress made to date on the reduction of data for Spacelab 3 Shuttle experiment, No. 3AFT23 is reported. Four astronauts participated as subjects in this experiment. Crewmen A and B served as treatment subjects (i.e., received preflight training for control of their own motion sickness symptoms) and Crewmen C and D served as control (i.e., did not receive training). A preliminary evaluation of Autogenic Feedback Training (AFT) was made from visual inspections of graphs that were generated from the preflight and inflight and inflight physiological data which included: (1) Baseline rotating chair tests for all crewmen; (2) Posttraining rotating chair tests of treatment groups subjects; (3) Preflight data from Joint Integrated Simulations for all crewmen; and (4) Flight data for all crewmen during mission days 0 through 4, and mission day 6 for treatment subjects only. A summary of the findings suggested by these data is outlined.

  10. Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention.

    PubMed

    Aenishaenslin, Cécile; Gern, Lise; Michel, Pascal; Ravel, André; Hongoh, Valérie; Waaub, Jean-Philippe; Milord, François; Bélanger, Denise

    2015-01-01

    Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector

  11. Impacts of Agricultural Decision Making and Adaptive Management on Food Security in Africa

    NASA Astrophysics Data System (ADS)

    Caylor, K. K.; Evans, T. P.; Estes, L. D.; Sheffield, J.; Plale, B. A.; Attari, S.

    2014-12-01

    Despite massive investments in food aid, agricultural extension, and seed/fertilizer subsidies, nearly 1 billion people in the developing world are food insecure and vulnerable to climate variability. Sub-Saharan Africa is most vulnerable, as approximately 25% of its people are undernourished (FAO/FAOSTAT 2013) and 96% of its cropland is rainfed (FAO 2002). The ability of subsistence farmers to respond to changes in water availability involves both inter-and intra-seasonal adaptation. Adaptive capacity diminishes over the season as decisions are made, resources are used, and the set of possible futures becomes restricted. Assessing the intra-seasonal adaptive capacity of smallholders requires integrating physical models of hydrological and agricultural dynamics with farmer decision-making at fine temporal (e.g. weekly) and spatial (e.g. crop field) scales. However, there is an intrinsic challenge to modeling the dynamics of these sociohydrologic systems, because important and uncharacterized spatial and temporal scale mismatches exist between the level at which the water resource is best understood and the level at which human dynamics are more predictable. For example, the skill of current process-based land surface models is primarily confined to short-term (daily to weekly), national- to regional-scale assessments, and reliable agricultural yield estimates and forecasts for small-scale farming systems remain elusive. In contrast, process-based social science modeling has focused on agent-based approaches that generate fine-scale (individual to community) dynamics over rather coarse time scales (yearly to decadal). A major obstacle to addressing this mismatch is the fundamental fact that the highest skill domain of one framework is essentially unpredictable in the other. We present a coupled sociohydrological observation framework designed to addressing this gap, and demonstrate its utility to understand relationships between climate variability, decision making

  12. Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention

    PubMed Central

    Aenishaenslin, Cécile; Gern, Lise; Michel, Pascal; Ravel, André; Hongoh, Valérie; Waaub, Jean-Philippe; Milord, François; Bélanger, Denise

    2015-01-01

    Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector

  13. An Iterative Information-Reduced Quadriphase-Shift-Keyed Carrier Synchronization Scheme Using Decision Feedback for Low Signal-to-Noise Ratio Applications

    NASA Technical Reports Server (NTRS)

    Simon, M.; Tkacenko, A.

    2006-01-01

    In a previous publication [1], an iterative closed-loop carrier synchronization scheme for binary phase-shift keyed (BPSK) modulation was proposed that was based on feeding back data decisions to the input of the loop, the purpose being to remove the modulation prior to carrier synchronization as opposed to the more conventional decision-feedback schemes that incorporate such feedback inside the loop. The idea there was that, with sufficient independence between the received data and the decisions on it that are fed back (as would occur in an error-correction coding environment with sufficient decoding delay), a pure tone in the presence of noise would ultimately be produced (after sufficient iteration and low enough error probability) and thus could be tracked without any squaring loss. This article demonstrates that, with some modification, the same idea of iterative information reduction through decision feedback can be applied to quadrature phase-shift keyed (QPSK) modulation, something that was mentioned in the previous publication but never pursued.

  14. Interactive Genetic Algorithm - An Adaptive and Interactive Decision Support Framework for Design of Optimal Groundwater Monitoring Plans

    NASA Astrophysics Data System (ADS)

    Babbar-Sebens, M.; Minsker, B. S.

    2006-12-01

    In the water resources management field, decision making encompasses many kinds of engineering, social, and economic constraints and objectives. Representing all of these problem dependant criteria through models (analytical or numerical) and various formulations (e.g., objectives, constraints, etc.) within an optimization- simulation system can be a very non-trivial issue. Most models and formulations utilized for discerning desirable traits in a solution can only approximate the decision maker's (DM) true preference criteria, and they often fail to consider important qualitative and incomputable phenomena related to the management problem. In our research, we have proposed novel decision support frameworks that allow DMs to actively participate in the optimization process. The DMs explicitly indicate their true preferences based on their subjective criteria and the results of various simulation models and formulations. The feedback from the DMs is then used to guide the search process towards solutions that are "all-rounders" from the perspective of the DM. The two main research questions explored in this work are: a) Does interaction between the optimization algorithm and a DM assist the system in searching for groundwater monitoring designs that are robust from the DM's perspective?, and b) How can an interactive search process be made more effective when human factors, such as human fatigue and cognitive learning processes, affect the performance of the algorithm? The application of these frameworks on a real-world groundwater long-term monitoring (LTM) case study in Michigan highlighted the following salient advantages: a) in contrast to the non-interactive optimization methodology, the proposed interactive frameworks were able to identify low cost monitoring designs whose interpolation maps respected the expected spatial distribution of the contaminants, b) for many same-cost designs, the interactive methodologies were able to propose multiple alternatives

  15. Adaptation of reproductive phenology to climate change with ecological feedback via dominance hierarchies.

    PubMed

    Johansson, Jacob; Smith, Henrik G; Jonzén, Niclas

    2014-03-01

    Phenological shifts belong to the most commonly observed biological responses to recent climate change. It is, however, often unclear how these shifts are linked to demography and competitive interactions. We develop an eco-evolutionary model to study adaptation of timing of reproduction in organisms with social dominance hierarchies. We focus on residential birds with winter flocks, where success in competition for territories among offspring depends on ranking given by prior residence. We study the effects of environmental change on breeding population densities, ensuing selection pressures and long-term evolutionary equilibria. We consider changes in food peak date, in winter survival, in total reproductive output and in the width of the food distribution. We show that the evolutionarily stable hatching date will advance with increasing winter survival and reproductive output since these parameters increase habitat saturation and post-fledging competition. Increasing the length of the breeding season also selects for earlier hatching date due to the reduced costs for producing offspring with high ranking. Our analysis shows that there is little correlation between short-term and long-term population responses across different scenarios of environmental change. However, short-term population growth consistently predicts selection for earlier reproduction. Hence, the model identifies changed breeding population density as a key factor to understanding phenological adaptation in systems with prior residence advantages. While selection for change in reproductive phenology is often explained by changed seasonal variation in environmental variables, such as food abundance, we show that environmental change without apparent effects on seasonality can critically affect phenological adaptation. Such factors can mask or even override influences of changed seasonality on phenology. The model thus offers a conceptually new set of explanations for understanding phenological

  16. Rapid adaptation of herbivore consumers to nutrient limitation: eco-evolutionary feedbacks to population demography and resource control.

    PubMed

    Declerck, Steven A J; Malo, Andrea R; Diehl, Sebastian; Waasdorp, Dennis; Lemmen, Kimberley D; Proios, Konstantinos; Papakostas, Spiros

    2015-06-01

    Humans alter biogeochemical cycles of essential elements such as phosphorus (P). Prediction of ecosystem consequences of altered elemental cycles requires integration of ecology, evolutionary biology and the framework of ecological stoichiometry. We studied micro-evolutionary responses of a herbivorous rotifer to P-limited food and the potential consequences for its population demography and for ecosystem properties. We subjected field-derived, replicate rotifer populations to P-deficient and P-replete algal food, and studied adaptation in common garden transplant experiments after 103 and 209 days of selection. When fed P-limited food, populations with a P-limitation selection history suffered 37% lower mortality, reached twice the steady state biomass, and reduced algae by 40% compared to populations with a P-replete selection history. Adaptation involved no change in rotifer elemental composition but reduced investment in sex. This study demonstrates potentially strong eco-evolutionary feedbacks from shifting elemental balances to ecosystem properties, including grazing pressure and the ratio of grazer:producer biomass.

  17. Functional Assessment of Genetic Variants with Outcomes Adapted to Clinical Decision-Making

    PubMed Central

    Thouvenot, Pierre; Ben Yamin, Barbara; Fourrière, Lou; Lescure, Aurianne; Boudier, Thomas; Del Nery, Elaine; Chauchereau, Anne; Goldgar, David E.; Stoppa-Lyonnet, Dominique; Nicolas, Alain; Millot, Gaël A.

    2016-01-01

    Understanding the medical effect of an ever-growing number of human variants detected is a long term challenge in genetic counseling. Functional assays, based on in vitro or in vivo evaluations of the variant effects, provide essential information, but they require robust statistical validation, as well as adapted outputs, to be implemented in the clinical decision-making process. Here, we assessed 25 pathogenic and 15 neutral missense variants of the BRCA1 breast/ovarian cancer susceptibility gene in four BRCA1 functional assays. Next, we developed a novel approach that refines the variant ranking in these functional assays. Lastly, we developed a computational system that provides a probabilistic classification of variants, adapted to clinical interpretation. Using this system, the best functional assay exhibits a variant classification accuracy estimated at 93%. Additional theoretical simulations highlight the benefit of this ready-to-use system in the classification of variants after functional assessment, which should facilitate the consideration of functional evidences in the decision-making process after genetic testing. Finally, we demonstrate the versatility of the system with the classification of siRNAs tested for human cell growth inhibition in high throughput screening. PMID:27272900

  18. Cultural and Linguistic Adaptation of a Multimedia Colorectal Cancer Screening Decision Aid for Spanish Speaking Latinos

    PubMed Central

    Ko, Linda K.; Reuland, Daniel; Jolles, Monica; Clay, Rebecca; Pignone, Michael

    2014-01-01

    As the United States becomes more linguistically and culturally diverse, there is a need for effective health communication interventions that target diverse and most vulnerable populations. Latinos also have the lowest colorectal (CRC) screening rates of any ethnic group in the U.S. To address such disparities, health communication interventionists are often faced with the challenge to adapt existing interventions from English into Spanish in a way that retains essential elements of the original intervention while also addressing the linguistic needs and cultural perspectives of the target population. We describe the conceptual framework, context, rationale, methods, and findings of a formative research process used in creating a Spanish language version of an evidenced-based (English language) multimedia CRC screening decision aid. Our multi-step process included identification of essential elements of the existing intervention, literature review, assessment of the regional context and engagement of key stakeholders, and solicitation of direct input from target population. We integrated these findings in the creation of the new adapted intervention. We describe how we used this process to identify and integrate socio-cultural themes such as personalism (personalismo), familism (familismo), fear (miedo), embarrassment (verguenza), power distance (respeto), machismo, and trust (confianza) into the Spanish language decision aid. PMID:24328496

  19. Climate Change Adaptation Decision Making for Glacial Lake Outburst Floods From Palcacocha Lake in Peru

    NASA Astrophysics Data System (ADS)

    Cuellar, A. D.; McKinney, D. C.

    2014-12-01

    Climate change has accelerated glacial retreat in high altitude glaciated regions of Peru leading to the growth and formation of glacier lakes. Glacial lake outburst floods (GLOF) are sudden events triggered by an earthquake, avalanche into the lake or other shock that causes a sudden outflow of water. These floods are catastrophic because of their sudden onset, the difficulty predicting them, and enormous quantity of water and debris rapidly flooding downstream areas. Palcacocha Lake in the Peruvian Andes has experienced accelerated growth since it burst in 1941 and threatens the major city of Huaraz and surrounding communities. Since the 1941 flood stakeholders have advocated for projects to adapt to the increasing threat posed by Palcacocha Lake. Nonetheless, discussions surrounding projects for Palcacocha have not included a rigorous analysis of the potential consequences of a flood, probability of an event, or costs of mitigation projects. This work presents the first step to rationally analyze the risks posed by Palcacocha Lake and the various adaptation projects proposed. In this work the authors use decision analysis to asses proposed adaptation measures that would mitigate damage in downstream communities from a GLOF. We use an existing hydrodynamic model of the at-risk area to determine how adaptation projects will affect downstream flooding. Flood characteristics are used in the HEC-FIA software to estimate fatalities and injuries from an outburst flood, which we convert to monetary units using the value of a statistical life. We combine the monetary consequences of a GLOF with the cost of the proposed projects and a diffuse probability distribution for the likelihood of an event to estimate the expected cost of the adaptation plans. From this analysis we found that lowering the lake level by 15 meters has the least expected cost of any proposal despite uncertainty in the effect of lake lowering on flooding downstream.

  20. 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…

  1. The Adaptability of Career Decision-Making Profiles: Associations with Self-Efficacy, Emotional Difficulties, and Decision Status

    ERIC Educational Resources Information Center

    Gadassi, Reuma; Gati, Itamar; Wagman-Rolnick, Halleli

    2013-01-01

    The present study investigated a new model for characterizing the way individuals make career decisions (career decision-making profiles [CDMP]). Using data from 285 students in a preacademic program, the present study assessed the association of the CDMP's dimensions with the Emotional and Personality-related Career decision-making…

  2. Facilitating adaptive management in the Chesapeake Bay Watershed through the use of online decision support tools

    USGS Publications Warehouse

    Mullinx, Cassandra; Phillips, Scott; Shenk, Kelly; Hearn, Paul; Devereux, Olivia

    2009-01-01

    The Chesapeake Bay Program (CBP) is attempting to more strategically implement management actions to improve the health of the Nation’s largest estuary. In 2007 the U.S. Geological Survey (USGS) and U.S. Environmental Protection Agency (USEPA) CBP office began a joint effort to develop a suite of Internetaccessible decision-support tools and to help meet the needs of CBP partners to improve water quality and habitat conditions in the Chesapeake Bay and its watersheds. An adaptive management framework is being used to provide a structured decision process for information and individual tools needed to implement and assess practices to improve the condition of the Chesapeake Bay ecosystem. The Chesapeake Online Adaptive Support Toolkit (COAST) is a collection of web-based analytical tools and information, organized in an adaptive management framework, intended to aid decisionmakers in protecting and restoring the integrity of the Bay ecosystem. The initial version of COAST is focused on water quality issues. During early and mid- 2008, initial ideas for COAST were shared and discussed with various CBP partners and other potential user groups. At these meetings, test cases were selected to help improve understanding of the types of information and analytical functionality that would be most useful for specific partners’ needs. These discussions added considerable knowledge about the nature of decisionmaking for Federal, State, local and nongovernmental partners. Version 1.0 of COAST, released in early winter of 2008, will be further reviewed to determine improvements needed to address implementation and assessment of water quality practices. Future versions of COAST may address other aspects of ecosystem restoration, including restoration of habitat and living resources and maintaining watershed health.

  3. IMRT planning on adaptive volume structures--a decisive reduction in computational complexity.

    PubMed

    Scherrer, Alexander; Küfer, Karl-Heinz; Bortfeld, Thomas; Monz, Michael; Alonso, Fernando

    2005-05-01

    The objective of radiotherapy planning is to find a compromise between the contradictive goals of delivering a sufficiently high dose to the target volume while widely sparing critical structures. The search for such a compromise requires the computation of several plans, which mathematically means solving several optimization problems. In the case of intensity modulated radiotherapy (IMRT) these problems are large-scale, hence the accumulated computational expense is very high. The adaptive clustering method presented in this paper overcomes this difficulty. The main idea is to use a preprocessed hierarchy of aggregated dose-volume information as a basis for individually adapted approximations of the original optimization problems. This leads to a decisively reduced computational expense: numerical experiments on several sets of real clinical data typically show computation times decreased by a factor of about 10. In contrast to earlier work in this field, this reduction in computational complexity will not lead to a loss in accuracy: the adaptive clustering method produces the optimum of the original optimization problem.

  4. Atmospheric Feedback of Urban Boundary Layer with Implications for Climate Adaptation.

    PubMed

    Liang, Marissa S; Keener, Timothy C

    2015-09-01

    Atmospheric structure changes in response to the urban form, land use, and the type of land cover (LULC). This interaction controls thermal and air pollutant transport and distribution. The interrelationships among LULC, ambient temperature, and air quality were analyzed and found to be significant in a case study in Cincinnati, Ohio, U.S.A. Within the urban canopy layer (UCL), traffic-origin PM2.5 and black carbon followed Gaussian dispersion in the near road area in the daytime, while higher concentrations, over 1 order of magnitude, were correlated to the lapse rate under nocturnal inversions. In the overlying urban boundary layer (UBL), ambient temperature and PM2.5 variations were correlated among urban-wide locations indicating effective thermal and mass communications. Beyond the spatial correlation, LULC-related local urban heat island effects are noteworthy. The high-density urbanized zone along a narrow highway-following corridor is marked by higher nighttime temperature by ∼1.6 °C with a long-term increase by 2.0 °C/decade, and by a higher PM2.5 concentration, than in the low-density residential LULC. These results indicate that the urban LULC may have contributed to the nocturnal thermal inversion affecting urban air circulation and air quality in UCL and UBL. Such relationships point to the potentials of climate adaptation through urban planning.

  5. 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.

  6. Feedback promotes learning success! Which kind of feedback for the faculty is given by an interdisciplinary OSCE with focus on decision-making?

    PubMed Central

    Stibane, Tina; Sitter, Helmut; Neuhof, Despina; Wiechens, Helena; Schönbauer, Andrea; Bösner, Stefan; Baum, Erika

    2016-01-01

    Clinical skills such as history taking, diagnostic reasoning, therapy planning, and giving advice are even more complex than practical skills like lung auscultation and have to be applied in complex clinical situations. We judged this competence in an interdisciplinary formative OSCE conducted with students of Marburg University. Results of 218 students passing 643 OSCE stations composed of 37 different scenarios were analyzed. As a competence based examination that reflects the practical skills gained during clinical training, the here presented analysis serves also as a feedback instrument for clinical teachers, their respective disciplines and the medical faculty as a whole. PMID:27579353

  7. Adaptive traffic management in cities--comparing decision-making methods.

    PubMed

    van den Elshout, Sef; Molenaar, Rinkje; Wester, Bart

    2014-08-01

    Traffic is the dominant source of air pollution in cities. We simulated 'adaptive traffic management' (temporary traffic interventions that are invoked based on preset conditions such as high ambient concentrations) aimed at reducing traffic related air pollution. We compared these results with the effect of permanent temporary traffic interventions (measures that are always invoked for a few hours, irrespective of other criteria). The potential impact of the traffic interventions was assessed using Black Carbon and NOx-concentration observations in a busy urban street in Rotterdam, The Netherlands. Results show that generic traffic information (counts, speed, composition) in combination with general knowledge about the atmospheric conditions, provide sufficient information for operational decision making. However, the results also show that the overall net benefits of temporary measures are very small. The impact of permanent measures such as lowering the traffic density during rush hours is higher than measures taken for short time periods when air pollution is high or expected to be high.

  8. Adapting a GIS-Based Multicriteria Decision Analysis Approach for Evaluating New Power Generating Sites

    SciTech Connect

    Omitaomu, Olufemi A; Blevins, Brandon R; Jochem, Warren C; Mays, Gary T; Belles, Randy; Hadley, Stanton W; Harrison, Thomas J; Bhaduri, Budhendra L; Neish, Bradley S; Rose, Amy N

    2012-01-01

    There is a growing need to site new power generating plants that use cleaner energy sources due to increased regulations on air and water pollution and a sociopolitical desire to develop more clean energy sources. To assist utility and energy companies as well as policy-makers in evaluating potential areas for siting new plants in the contiguous United States, a geographic information system (GIS)-based multicriteria decision analysis approach is presented in this paper. The presented approach has led to the development of the Oak Ridge Siting Analysis for power Generation Expansion (OR-SAGE) tool. The tool takes inputs such as population growth, water availability, environmental indicators, and tectonic and geological hazards to provide an in-depth analysis for siting options. To the utility and energy companies, the tool can quickly and effectively provide feedback on land suitability based on technology specific inputs. However, the tool does not replace the required detailed evaluation of candidate sites. To the policy-makers, the tool provides the ability to analyze the impacts of future energy technology while balancing competing resource use.

  9. Video-feedback Intervention to promote Positive Parenting adapted to Autism (VIPP-AUTI): A randomized controlled trial.

    PubMed

    Poslawsky, Irina E; Naber, Fabiënne Ba; Bakermans-Kranenburg, Marian J; van Daalen, Emma; van Engeland, Herman; van IJzendoorn, Marinus H

    2015-07-01

    In a randomized controlled trial, we evaluated the early intervention program Video-feedback Intervention to promote Positive Parenting adapted to Autism (VIPP-AUTI) with 78 primary caregivers and their child (16-61 months) with Autism Spectrum Disorder. VIPP-AUTI is a brief attachment-based intervention program, focusing on improving parent-child interaction and reducing the child's individual Autism Spectrum Disorder-related symptomatology in five home visits. VIPP-AUTI, as compared with usual care, demonstrated efficacy in reducing parental intrusiveness. Moreover, parents who received VIPP-AUTI showed increased feelings of self-efficacy in child rearing. No significant group differences were found on other aspects of parent-child interaction or on child play behavior. At 3-months follow-up, intervention effects were found on child-initiated joint attention skills, not mediated by intervention effects on parenting. Implementation of VIPP-AUTI in clinical practice is facilitated by the use of a detailed manual and a relatively brief training of interveners.

  10. Industrial wideband noise reduction for hearing aids using a headset with adaptive-feedback active noise cancellation.

    PubMed

    Lin, J H; Li, P C; Tang, S T; Liu, P T; Young, S T

    2005-11-01

    High-intensity noises are a health hazard for industrial workers, and hearing protection is necessary to prevent hearing loss. Passive methods, such as ear muffs, are ineffective against low-frequency noise. Moreover, many hearing-impaired workers must wear hearing aids to enable communication at their workplace, and such aids can amplify ambient noise. To overcome this problem, the present study developed a headset equipped with a digital signal processing system to implement adaptive-feedback active noise cancellation (AFANC) to reduce low-frequency noise. The proposed AFANC headset was effective against wideband industrial noise, with a maximum noise spectrum power reduction of 30 dB. Furthermore, when used with a hearing aid, it improved the speech signal-to-noise ratio by up to 14 dB. These results suggest that a headset with AFANC would be useful for hearing protection in workplaces with high levels of low-frequency industrial noise, especially for hearing-impaired workers. PMID:16594300

  11. Spacelab 3 flight experiment No. 3AFT23: Autogenic-feedback training as a preventive method for space adaptation syndrome

    NASA Technical Reports Server (NTRS)

    Cowings, Patricia S.; Toscano, William B.; Kamiya, Joe; Miller, Neal E.; Sharp, Joseph C.

    1988-01-01

    Space adaptation syndrome is a motion sickness-like disorder which affects up to 50 percent of all people exposed to microgravity in space. This experiment tested a physiological conditioning procedure (Autogenic-Feedback Training, AFT) as an alternative to pharmacological management. Four astronauts participated as subjects in this experiment. Crewmembers A and B served as treatment subjects. Both received preflight training for control of heart rate, respiration rate, peripheral blood volume, and skin conductance. Crewmembers C and D served as controls (i.e., did not receive training). Crewmember A showed reliable control of his own physiological responses, and a significant increase in motion sickness tolerance after training. Crewmember B, however, demonstrated much less control and only a moderate increase in motion sickness tolerance was observed after training. The inflight symptom reports and physiological data recordings revealed that Crewmember A did not experience any severe symptom episodes during the mission, while Crewmember B reported one severe symptom episode. Both control group subjects, C and D (who took antimotion sickness medication), reported multiple symptom episodes on mission day 0. Both inflight data and crew reports indicate that AFT may be an effective countermeasure. Additional data must be obtained inflight (a total of eight treatment and eight control subjects) before final evaluation of this treatment can be made.

  12. Adaptive and selective seed abortion reveals complex conditional decision making in plants.

    PubMed

    Meyer, Katrin M; Soldaat, Leo L; Auge, Harald; Thulke, Hans-Hermann

    2014-03-01

    Behavior is traditionally attributed to animals only. Recently, evidence for plant behavior is accumulating, mostly from plant physiological studies. Here, we provide ecological evidence for complex plant behavior in the form of seed abortion decisions conditional on internal and external cues. We analyzed seed abortion patterns of barberry plants exposed to seed parasitism and different environmental conditions. Without abortion, parasite infestation of seeds can lead to loss of all seeds in a fruit. We statistically tested a series of null models with Monte Carlo simulations to establish selectivity and adaptiveness of the observed seed abortion patterns. Seed abortion was more frequent in parasitized fruits and fruits from dry habitats. Surprisingly, seed abortion occurred with significantly greater probability if there was a second intact seed in the fruit. This strategy provides a fitness benefit if abortion can prevent a sibling seed from coinfestation and if nonabortion of an infested but surviving single seed saves resources invested in the fruit coat. Ecological evidence for complex decision making in plants thus includes a structural memory (the second seed), simple reasoning (integration of inner and outer conditions), conditional behavior (abortion), and anticipation of future risks (seed predation). PMID:24561600

  13. CALM: Complex Adaptive System (CAS)-Based Decision Support for Enabling Organizational Change

    NASA Astrophysics Data System (ADS)

    Adler, Richard M.; Koehn, David J.

    Guiding organizations through transformational changes such as restructuring or adopting new technologies is a daunting task. Such changes generate workforce uncertainty, fear, and resistance, reducing morale, focus and performance. Conventional project management techniques fail to mitigate these disruptive effects, because social and individual changes are non-mechanistic, organic phenomena. CALM (for Change, Adaptation, Learning Model) is an innovative decision support system for enabling change based on CAS principles. CALM provides a low risk method for validating and refining change strategies that combines scenario planning techniques with "what-if" behavioral simulation. In essence, CALM "test drives" change strategies before rolling them out, allowing organizations to practice and learn from virtual rather than actual mistakes. This paper describes the CALM modeling methodology, including our metrics for measuring organizational readiness to respond to change and other major CALM scenario elements: prospective change strategies; alternate futures; and key situational dynamics. We then describe CALM's simulation engine for projecting scenario outcomes and its associated analytics. CALM's simulator unifies diverse behavioral simulation paradigms including: adaptive agents; system dynamics; Monte Carlo; event- and process-based techniques. CALM's embodiment of CAS dynamics helps organizations reduce risk and improve confidence and consistency in critical strategies for enabling transformations.

  14. Decision Support from Local Data: Creating Adaptive Order Menus from Past Clinician Behavior

    PubMed Central

    Klann, Jeffrey G.; Szolovits, Peter; Downs, Stephen; Schadow, Gunther

    2014-01-01

    Objective Reducing care variability through guidelines has significantly benefited patients. Nonetheless, guideline-based clinical decision support (CDS) systems are not widely implemented or used, are frequently out-of-date, and cannot address complex care for which guidelines do not exist. Here, we develop and evaluate a complementary approach - using Bayesian network (BN) learning to generate adaptive, context-specific treatment menus based on local order-entry data. These menus can be used as a draft for expert review, in order to minimize development time for local decision support content. This is in keeping with the vision outlined in the US Health Information Technology Strategic Plan, which describes a healthcare system that learns from itself. Materials and Methods We used the Greedy Equivalence Search algorithm to learn four 50-node domain-specific BNs from 11,344 encounters: abdominal pain in the emergency department, inpatient pregnancy, hypertension in the urgent visit clinic, and altered mental state in the intensive care unit. We developed a system to produce situation-specific, rank-ordered treatment menus from these networks. We evaluated this system with a hospital-simulation methodology and computed Area Under the Receiver-Operator Curve (AUC) and average menu position at time of selection. We also compared this system with a similar association-rule-mining approach. Results A short order menu on average contained the next order (weighted average length 3.91–5.83 items). Overall predictive ability was good: average AUC above 0.9 for 25% of order types and overall average AUC .714–.844 (depending on domain). However, AUC had high variance (.50–.99). Higher AUC correlated with tighter clusters and more connections in the graphs, indicating importance of appropriate contextual data. Comparison with an association rule mining approach showed similar performance for only the most common orders with dramatic divergence as orders are less

  15. Online Visual Feedback during Error-Free Channel Trials Leads to Active Unlearning of Movement Dynamics: Evidence for Adaptation to Trajectory Prediction Errors

    PubMed Central

    Lago-Rodriguez, Angel; Miall, R. Chris

    2016-01-01

    Prolonged exposure to movement perturbations leads to creation of motor memories which decay towards previous states when the perturbations are removed. However, it remains unclear whether this decay is due only to a spontaneous and passive recovery of the previous state. It has recently been reported that activation of reinforcement-based learning mechanisms delays the onset of the decay. This raises the question whether other motor learning mechanisms may also contribute to the retention and/or decay of the motor memory. Therefore, we aimed to test whether mechanisms of error-based motor adaptation are active during the decay of the motor memory. Forty-five right-handed participants performed point-to-point reaching movements under an external dynamic perturbation. We measured the expression of the motor memory through error-clamped (EC) trials, in which lateral forces constrained movements to a straight line towards the target. We found greater and faster decay of the motor memory for participants who had access to full online visual feedback during these EC trials (Cursor group), when compared with participants who had no EC feedback regarding movement trajectory (Arc group). Importantly, we did not find between-group differences in adaptation to the external perturbation. In addition, we found greater decay of the motor memory when we artificially increased feedback errors through the manipulation of visual feedback (Augmented-Error group). Our results then support the notion of an active decay of the motor memory, suggesting that adaptive mechanisms are involved in correcting for the mismatch between predicted movement trajectories and actual sensory feedback, which leads to greater and faster decay of the motor memory. PMID:27721748

  16. Alaska Center for Climate Assessment and Policy: Partnering with Decision-Makers in Climate Change Adaptation

    NASA Astrophysics Data System (ADS)

    White, D.; Trainor, S.; Walsh, J.; Gerlach, C.

    2008-12-01

    The Alaska Center for Climate Assessment and Policy (ACCAP; www.uaf.edu/accap) is one of several, NOAA funded, Regional Integrated Science and Policy (RISA) programs nation-wide (http://www.climate.noaa.gov/cpo_pa/risa/). Our mission is to assess the socio-economic and biophysical impacts of climate variability in Alaska, make this information available to local and regional decision-makers, and improve the ability of Alaskans to adapt to a changing climate. We partner with the University of Alaska?s Scenario Network for Alaska Planning (SNAP; http://www.snap.uaf.edu/), state and local government, state and federal agencies, industry, and non-profit organizations to communicate accurate and up-to-date climate science and assist in formulating adaptation and mitigation plans. ACCAP and SNAP scientists are members of the Governor?s Climate Change Sub-Cabinet Adaptation and Mitigation Advisory and Technical Working Groups (http://www.climatechange.alaska.gov/), and apply their scientific expertise to provide down-scaled, state-wide maps of temperature and precipitation projections for these groups. An ACCAP scientist also serves as co-chair for the Fairbanks North Star Borough Climate Change Task Force, assisting this group as they work through the five-step model for climate change planning put forward by the International Council for Local Environmental Initiatives (http://www.investfairbanks.com/Taskforces/climate.php). ACCAP scientists work closely with federal resource managers in on a range of projects including: partnering with the U.S. Fish and Wildlife Service to analyze hydrologic changes associated with climate change and related ecological impacts and wildlife management and development issues on Alaska?s North Slope; partnering with members of the Alaska Interagency Wildland Fire Coordinating Group in statistical modeling to predict seasonal wildfire activity and coordinate fire suppression resources state-wide; and working with Alaska Native Elders and

  17. Adaptive Management for Decision Making at the Program and Project Levels of the Missouri River Recovery Program

    SciTech Connect

    Thom, Ronald M.; Anderson, Michael G.; Tyre, Drew; Fleming, Craig A.

    2009-02-28

    The paper, “Adaptive Management: Background for Stakeholders in the Missouri River Recovery Program,” introduced the concept of adaptive management (AM), its principles and how they relate to one-another, how AM is applied, and challenges for its implementation. This companion paper describes how the AM principles were applied to specific management actions within the Missouri River Recovery Program to facilitate understanding, decision-making, and stakeholder engagement. For context, we begin with a brief synopsis of the Missouri River Recovery Program (MRRP) and the strategy for implementing adaptive management (AM) within the program; we finish with an example of AM in action within Phase I of the MRPP.

  18. The Role of Decision Support in Adapting to Climate Change: Findings from Three Place-based Regional Assessments

    EPA Science Inventory

    This report summarizes the methodologies and findings of three regional assessments and considers the role of decision support in assisting adaptation to climate change. Background. In conjunction with the US Global Change Research Program’s (USGCRP’s) National Assessment of ...

  19. 10 Gb/s full-duplex bidirectional transmission with RSOA-based ONU using detuned optical filtering and decision feedback equalization.

    PubMed

    Omella, M; Papagiannakis, I; Schrenk, B; Klonidis, D; Lázaro, J A; Birbas, A N; Kikidis, J; Prat, J; Tomkos, I

    2009-03-30

    Full-duplex bidirectional transmission at 10 Gb/s is demonstrated for extended wavelength division multiplexed passive optical network (WDM-PON) applications, achieving transmission distances up to 25 km of standard single mode fiber (SSMF) when using a low-bandwidth (approximately 1.2 GHz) reflective semiconductor optical amplifier (RSOA) for signal re-modulation at the optical network unit (ONU). The system is assisted by optimum offset filtering at the optical line terminal (OLT)-receiver and the performance is further improved with the use of decision-feedback equalization (DFE). Chromatic dispersion (CD) and Rayleigh Backscattering (RB) effects are considered and analyzed.

  20. Informing Adaptation Decisions: What Do We Need to Know and What Do We Need to Do?

    NASA Astrophysics Data System (ADS)

    Pulwarty, R. S.; Webb, R. S.

    2014-12-01

    The demand for improved climate knowledge and information is well documented. As noted in the IPCC Reports (SREX, AR5) and other assessments, this demand has increased pressure for better information to support planning under changing rates of extremes event occurrence. This demand has focused on mechanisms used to respond to past variability and change, including, integrated resource management (watersheds, coasts), infrastructure design, information systems, technological optimization, financial risk management, and behavioral and institutional change. Climate inputs range from static site design statistics (return periods) to dynamic, emergent thresholds and transitions preceded by steep response curves and punctuated equilibria. Tradeoffs are evident in the use of risk-based anticipatory strategies vs. resilience measures. In such settings, annual decision calendars for operational requirements can confound adaptation expectations. Key knowledge assessment questions include: (1) How predictable are potential impacts of events in the context of other stressors, (2) how is action to anticipate such impacts informed, and (3) How often should criteria for "robustness" be reconsidered? To illustrate, we will discuss the climate information needs and uses for two areas of concern for both short and long-term risks (i) climate and disaster risk financing, and (ii) watershed management. The presentation will focus on the climate information needed for (1) improved monitoring, modeling and methods for understanding and analyzing exposure risks, (2) generating risk profiles, (3) developing information systems and scenarios for critical thresholds across climate time and space scales, (4) embedding annual decision calendars in the context of longer-term risk management, (5) gaming experiments to show the net benefits of new information. We will conclude with a discussion of the essential climate variables needed to implement services-delivery and development efforts such

  1. An adaptive decision framework for the conservation of a threatened plant

    USGS Publications Warehouse

    Moore, Clinton T.; Fonnesbeck, Christopher J.; Shea, Katriona; Lah, Kristopher J.; McKenzie, Paul M.; Ball, Lianne C.; Runge, Michael C.; Alexander, Helen M.

    2011-01-01

    Mead's milkweed Asclepias meadii, a long-lived perennial herb of tallgrass prairie and glade communities of the central United States, is a species designated as threatened under the U.S. Endangered Species Act. Challenges to its successful management include the facts that much about its life history is unknown, its age at reproductive maturity is very advanced, certain life stages are practically unobservable, its productivity is responsive to unpredictable environmental events, and most of the known populations occur on private lands unprotected by any legal conservation instrument. One critical source of biological uncertainty is the degree to which fire promotes growth and reproductive response in the plant. To aid in its management, we developed a prototype population-level state-dependent decision-making framework that explicitly accounts for this uncertainty and for uncertainties related to stochastic environmental effects and vital rates. To parameterize the decision model, we used estimates found in the literature, and we analyzed data from a long-term monitoring program where fates of individual plants were observed through time. We demonstrate that different optimal courses of action are followed according to how one believes that fire influences reproductive response, and we show that the action taken for certain population states is informative for resolving uncertainty about competing beliefs regarding the effect of fire. We advocate the use of a model-predictive approach for the management of rare populations, particularly when management uncertainty is profound. Over time, an adaptive management approach should reduce uncertainty and improve management performance as predictions of management outcome generated under competing models are continually informed and updated by monitoring data.

  2. A composite control method based on the adaptive RBFNN feedback control and the ESO for two-axis inertially stabilized platforms.

    PubMed

    Lei, Xusheng; Zou, Ying; Dong, Fei

    2015-11-01

    Due to the nonlinearity and time variation of a two-axis inertially stabilized platform (ISP) system, the conventional feedback control cannot be utilized directly. To realize the control performance with fast dynamic response and high stabilization precision, the dynamic model of the ISP system is expected to match the ideal model which satisfies the desired control performance. Therefore, a composite control method based on the adaptive radial basis function neural network (RBFNN) feedback control and the extended state observer (ESO), is proposed for ISP. The adaptive RBFNN is proposed to generate the feedback control parameters online. Based on the state error information in the working process, the adaptive RBFNN can be constructed and optimized directly. Therefore, no priori training data is needed for the construction of the RBFNN. Furthermore, a linear second-order ESO is constructed to compensate for the composite disturbance. The asymptotic stability of the proposed control method has been proven by the Lyapunov stability theory. The applicability of the proposed method is validated by a series of simulations and flight tests.

  3. A composite control method based on the adaptive RBFNN feedback control and the ESO for two-axis inertially stabilized platforms.

    PubMed

    Lei, Xusheng; Zou, Ying; Dong, Fei

    2015-11-01

    Due to the nonlinearity and time variation of a two-axis inertially stabilized platform (ISP) system, the conventional feedback control cannot be utilized directly. To realize the control performance with fast dynamic response and high stabilization precision, the dynamic model of the ISP system is expected to match the ideal model which satisfies the desired control performance. Therefore, a composite control method based on the adaptive radial basis function neural network (RBFNN) feedback control and the extended state observer (ESO), is proposed for ISP. The adaptive RBFNN is proposed to generate the feedback control parameters online. Based on the state error information in the working process, the adaptive RBFNN can be constructed and optimized directly. Therefore, no priori training data is needed for the construction of the RBFNN. Furthermore, a linear second-order ESO is constructed to compensate for the composite disturbance. The asymptotic stability of the proposed control method has been proven by the Lyapunov stability theory. The applicability of the proposed method is validated by a series of simulations and flight tests. PMID:26434418

  4. [Scale of conflict in health care decision-making: an instrument adapted and validated for the Portuguese language].

    PubMed

    Martinho, Maria Júlia Costa Marques; da Silva, Martins Maria Manuela Ferreira Pereira; Angelo, Margareth

    2013-06-01

    The different options available to patients in the health environment now are implicated in increasingly difficult processes of decision-making, and may trigger conflict about them. This study had as its purpose, to develop an instrument that enabled us to know about this variable. Therefore, we decided to effect a transcultural adaptation and evaluation of psychometric properties of the Portuguese version of the Decisional Conflict Scale, which seeks information about decision-making and the factors that influence the choices made. The sample consisted of 521 nursing students, with a focus on decision-making regarding the flu syndrome. The results obtained on the reliability tests showed good internal consistency for all items (Cronbach a=0.94). The psychometric study allowed us to affirm that the Portuguese version of the Decisional Conflict Scale, which we call Scale of Conflicts in Decision-Making in Health (ECTDS), was a reliable and valid instrument.

  5. Adapting the SLIM diabetes prevention intervention to a Dutch real-life setting: joint decision making by science and practice

    PubMed Central

    2013-01-01

    Background Although many evidence-based diabetes prevention interventions exist, they are not easily applicable in real-life settings. Moreover, there is a lack of examples which describe the adaptation process of these interventions to practice. In this paper we present an example of such an adaptation. We adapted the SLIM (Study on Lifestyle intervention and Impaired glucose tolerance Maastricht) diabetes prevention intervention to a Dutch real-life setting, in a joint decision making process of intervention developers and local health care professionals. Methods We used 3 adaptation steps in accordance with current adaptation frameworks. In the first step, the elements of the SLIM intervention were identified. In the second step, these elements were judged for their applicability in a real-life setting. In the third step, adaptations were proposed and discussed for those elements which were deemed not applicable. Participants invited for this process included intervention developers and local health care professionals (n=19). Results In the first adaptation step, a total of 22 intervention elements were identified. In the second step, 12 of these 22 intervention elements were judged as inapplicable. In the third step, a consensus was achieved for the adaptations of all 12 elements. The adapted elements were in the following categories: target population, techniques, intensity, delivery mode, materials, organisational structure, and political and financial conditions. The adaptations either lay in changing the SLIM protocol (6 elements) or the real-life working procedures (1 element), or a combination of both (4 elements). Conclusions The positive result of this study is that a consensus was achieved within a relatively short time period (nine months) between the developers of the SLIM intervention and local health care professionals on the adaptations needed to make SLIM applicable in a Dutch real-life setting. Our example shows that it is possible to combine

  6. Usability of clinical decision support system as a facilitator for learning the assistive technology adaptation process.

    PubMed

    Danial-Saad, Alexandra; Kuflik, Tsvi; Weiss, Patrice L Tamar; Schreuer, Naomi

    2016-01-01

    The aim of this study was to evaluate the usability of Ontology Supported Computerized Assistive Technology Recommender (OSCAR), a Clinical Decision Support System (CDSS) for the assistive technology adaptation process, its impact on learning the matching process, and to determine the relationship between its usability and learnability. Two groups of expert and novice clinicians (total, n = 26) took part in this study. Each group filled out system usability scale (SUS) to evaluate OSCAR's usability. The novice group completed a learning questionnaire to assess OSCAR's effect on their ability to learn the matching process. Both groups rated OSCAR's usability as "very good", (M [SUS] = 80.7, SD = 11.6, median = 83.7) by the novices, and (M [SUS] = 81.2, SD = 6.8, median = 81.2) by the experts. The Mann-Whitney results indicated that no significant differences were found between the expert and novice groups in terms of OSCAR's usability. A significant positive correlation existed between the usability of OSCAR and the ability to learn the adaptation process (rs = 0.46, p = 0.04). Usability is an important factor in the acceptance of a system. The successful application of user-centered design principles during the development of OSCAR may serve as a case study that models the significant elements to be considered, theoretically and practically in developing other systems. Implications for Rehabilitation Creating a CDSS with a focus on its usability is an important factor for its acceptance by its users. Successful usability outcomes can impact the learning process of the subject matter in general, and the AT prescription process in particular. The successful application of User-Centered Design principles during the development of OSCAR may serve as a case study that models the significant elements to be considered, theoretically and practically. The study emphasizes the importance of close collaboration between the developers and

  7. Evaluations of an adaptive planning technique incorporating dose feedback in image-guided radiotherapy of prostate cancer

    SciTech Connect

    Liu Han; Wu Qiuwen

    2011-12-15

    Purpose: Online image guidance (IG) has been used to effectively correct the setup error and inter-fraction rigid organ motion for prostate cancer. However, planning margins are still necessary to account for uncertainties such as deformation and intra-fraction motion. The purpose of this study is to investigate the effectiveness of an adaptive planning technique incorporating offline dose feedback to manage inter-fraction motion and residuals from online correction. Methods: Repeated helical CT scans from 28 patients were included in the study. The contours of prostate and organs-at-risk (OARs) were delineated on each CT, and online IG was simulated by matching center-of-mass of prostate between treatment CTs and planning CT. A seven beam intensity modulated radiation therapy (IMRT) plan was designed for each patient on planning CT for a total of 15 fractions. Dose distribution at each fraction was evaluated based on actual contours of the target and OARs from that fraction. Cumulative dose up to each fraction was calculated by tracking each voxel based on a deformable registration algorithm. The cumulative dose was compared with the dose from initial plan. If the deviation exceeded the pre-defined threshold, such as 2% of the D{sub 99} to the prostate, an adaptive planning technique called dose compensation was invoked, in which the cumulative dose distribution was fed back to the treatment planning system and the dose deficit was made up through boost radiation in future treatment fractions. The dose compensation was achieved by IMRT inverse planning. Two weekly compensation delivery strategies were simulated: one intended to deliver the boost dose in all future fractions (schedule A) and the other in the following week only (schedule B). The D{sub 99} to prostate and generalized equivalent uniform dose (gEUD) to rectal wall and bladder were computed and compared with those without the dose compensation. Results: If only 2% underdose is allowed at the end of the

  8. The psychological and neurological bases of leader self-complexity and effects on adaptive decision-making.

    PubMed

    Hannah, Sean T; Balthazard, Pierre A; Waldman, David A; Jennings, Peter L; Thatcher, Robert W

    2013-05-01

    Complex contexts and environments require leaders to be highly adaptive and to adjust their behavioral responses to meet diverse role demands. Such adaptability may be contingent upon leaders having requisite complexity to facilitate effectiveness across a range of roles. However, there exists little empirical understanding of the etiology or basis of leader complexity. To this end, we conceptualized a model of leader self-complexity that is inclusive of both the mind (the complexity of leaders' self-concepts) and the brain (the neuroscientific basis for complex leadership). We derived psychometric and neurologically based measures, the latter based on quantitative electroencephalogram (qEEG) profiles of leader self-complexity, and tested their separate effects on the adaptive decision-making of 103 military leaders. Results demonstrated that both measures accounted for unique variance in external ratings of adaptive decision-making. We discuss how these findings provide a deeper understanding of the latent and dynamic mechanisms that underpin leaders' self-complexity and their adaptability.

  9. The psychological and neurological bases of leader self-complexity and effects on adaptive decision-making.

    PubMed

    Hannah, Sean T; Balthazard, Pierre A; Waldman, David A; Jennings, Peter L; Thatcher, Robert W

    2013-05-01

    Complex contexts and environments require leaders to be highly adaptive and to adjust their behavioral responses to meet diverse role demands. Such adaptability may be contingent upon leaders having requisite complexity to facilitate effectiveness across a range of roles. However, there exists little empirical understanding of the etiology or basis of leader complexity. To this end, we conceptualized a model of leader self-complexity that is inclusive of both the mind (the complexity of leaders' self-concepts) and the brain (the neuroscientific basis for complex leadership). We derived psychometric and neurologically based measures, the latter based on quantitative electroencephalogram (qEEG) profiles of leader self-complexity, and tested their separate effects on the adaptive decision-making of 103 military leaders. Results demonstrated that both measures accounted for unique variance in external ratings of adaptive decision-making. We discuss how these findings provide a deeper understanding of the latent and dynamic mechanisms that underpin leaders' self-complexity and their adaptability. PMID:23544481

  10. Adaptive neural network tracking control for a class of switched stochastic pure-feedback nonlinear systems with backlash-like hysteresis

    NASA Astrophysics Data System (ADS)

    Niu, Ben; Qin, Tian; Fan, Xiaodong

    2016-10-01

    In this paper, an adaptive neural network tracking control approach is proposed for a class of switched stochastic pure-feedback nonlinear systems with backlash-like hysteresis. In the design procedure, an affine variable is constructed, which avoids the use of the mean value theorem, and the additional first-order low-pass filter is employed to deal with the problem of explosion of complexity. Then, a common Lyapunov function and a state feedback controller are explicitly obtained for all subsystems. It is proved that the proposed controller that guarantees all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error remains an adjustable neighbourhood of the origin. Finally, simulation results show the effectiveness of the presented control design approach.

  11. Supporting adaptation decisions to address climate related impacts and hazards in the Caribbean (the CARIWIG project)

    NASA Astrophysics Data System (ADS)

    Burton, Aidan

    2015-04-01

    Managers and policy makers from regional and national institutions in the Caribbean require knowledge of the likely impacts and hazards arising from the present and future climate that are specific to their responsibility and geographical range, and relevant to their planning time-horizons. Knowledge, experience and the political support to develop appropriate adaptation strategies are also required. However, the climate information available for the region is of limited use as: observational records are intermittent and typically of short duration; climate model projections of the weather suffer from scale and bias issues; and statistical downscaling to provide locally relevant unbiased climate change information remains sporadic. Tropical cyclone activity is a considerable sporadic hazard in the region and yet related weather information is limited to historic events. Further, there is a lack of guidance for managers and policy makers operating with very limited resources to utilize such information within their remit. The CARIWIG project (June 2012 - May 2015) will be presented, reflecting on stakeholder impact, best practice and lessons learned. This project seeks to address the climate service needs of the Caribbean region through a combination of capacity building and improved provision of climate information services. An initial workshop with regional-scale stakeholders initiated a dialogue to develop a realistic shared vision of the needed information services which could be provided by the project. Capacity building is then achieved on a number of levels: knowledge and expertise sharing between project partners; raising understanding and knowledge of resources that support national and regional institutions' adaptation decisions; developing case studies in key sectors to test and demonstrate the information services; training for stakeholder technical staff in the use of the provided services; the development of a support network within and out

  12. Decision support for hospital bed management using adaptable individual length of stay estimations and shared resources

    PubMed Central

    2013-01-01

    Background Elective patient admission and assignment planning is an important task of the strategic and operational management of a hospital and early on became a central topic of clinical operations research. The management of hospital beds is an important subtask. Various approaches have been proposed, involving the computation of efficient assignments with regard to the patients’ condition, the necessity of the treatment, and the patients’ preferences. However, these approaches are mostly based on static, unadaptable estimates of the length of stay and, thus, do not take into account the uncertainty of the patient’s recovery. Furthermore, the effect of aggregated bed capacities have not been investigated in this context. Computer supported bed management, combining an adaptable length of stay estimation with the treatment of shared resources (aggregated bed capacities) has not yet been sufficiently investigated. The aim of our work is: 1) to define a cost function for patient admission taking into account adaptable length of stay estimations and aggregated resources, 2) to define a mathematical program formally modeling the assignment problem and an architecture for decision support, 3) to investigate four algorithmic methodologies addressing the assignment problem and one base-line approach, and 4) to evaluate these methodologies w.r.t. cost outcome, performance, and dismissal ratio. Methods The expected free ward capacity is calculated based on individual length of stay estimates, introducing Bernoulli distributed random variables for the ward occupation states and approximating the probability densities. The assignment problem is represented as a binary integer program. Four strategies for solving the problem are applied and compared: an exact approach, using the mixed integer programming solver SCIP; and three heuristic strategies, namely the longest expected processing time, the shortest expected processing time, and random choice. A baseline approach

  13. The Search for Relevant Climate Change Information to Support Adaptation Decision Makers: Lessons from Reductionism, Emergence and the Past (Invited)

    NASA Astrophysics Data System (ADS)

    Stainforth, D.; Harrison, S.; Smith, L. A.

    2009-12-01

    The reality of anthropogenic climate change is founded on well understood scientific principles and is now widely accepted. The need for international efforts to limit the extent of future changes in climate - climate change mitigation - is therefore clear. Since anthropogenic climate change is well underway, however, and the planet is committed to further changes based on past emissions alone, there will certainly be a need for global society to adapt to the consequences. The physical sciences are increasingly being looked to as sources of information and guidance on adaptation policy and decision making. Unlike mitigation efforts such decisions generally require information on local or regional scales. What is the source of such information? How can we tell when it is robust and fit for the purpose of supporting a specific decision? The availability of rapidly increasing computational resources has led to a steady increase in the resolution of global climate models and of embedded regional climate models. They are approaching a point where they can provide data at a resolution which may be usable in adaptation decision support. Yet models are not equivalent to reality and model errors are significant even at the global scale. By contrast scientific understanding of climatic processes now and in the past can provide information about plausible responses which are more qualitative but may be equally useful. This talk will focus on the relative roles of fundamentally reductionist, model approaches with alternatives based on observations and process understanding. The latter, although more qualitative, are able to inform us about emergent properties; properties which may be difficult or impossible to reproduce within a reductionist paradigm. The contrast between emergent and reductionist approaches has a long history in the physical sciences; a history which provides valuable lessons for the relationship between climate science and societal / policy decisions. Here

  14. Multi-disciplinary assessments of climate change impacts on agriculture to support adaptation decision making in developing countries

    NASA Astrophysics Data System (ADS)

    Fujisawa, Mariko; Kanamaru, Hideki

    2016-04-01

    Many existing climate change impact studies, carried out by academic researchers, are disconnected from decision making processes of stakeholders. On the other hand many climate change adaptation projects in developing countries lack a solid evidence base of current and future climate impacts as well as vulnerabilities assessment at different scales. In order to fill this information gap, FAO has developed and implemented a tool "MOSAICC (Modelling System for Agricultural Impacts of Climate Change)" in several developing countries such as Morocco, the Philippines and Peru, and recently in Malawi and Zambia. MOSAICC employs a multi-disciplinary assessment approach to addressing climate change impacts and adaptation planning in the agriculture and food security sectors, and integrates five components from different academic disciplines: 1. Statistical downscaling of climate change projections, 2. Yield simulation of major crops at regional scale under climate change, 3. Surface hydrology simulation model, 4. Macroeconomic model, and 5. Forestry model. Furthermore MOSAICC has been developed as a capacity development tool for the national scientists so that they can conduct the country assessment themselves, using their own data, and reflect the outcome into the national adaptation policies. The outputs are nation-wide coverage, disaggregated at sub-national level to support strategic planning, investments and decisions by national policy makers. MOSAICC is designed in such a way to promote stakeholders' participation and strengthen technical capacities in developing countries. The paper presents MOSAICC and projects that used MOSAICC as a tool with case studies from countries.

  15. Adaptive learning and decision-making under uncertainty by metaplastic synapses guided by a surprise detection system

    PubMed Central

    Iigaya, Kiyohito

    2016-01-01

    Recent experiments have shown that animals and humans have a remarkable ability to adapt their learning rate according to the volatility of the environment. Yet the neural mechanism responsible for such adaptive learning has remained unclear. To fill this gap, we investigated a biophysically inspired, metaplastic synaptic model within the context of a well-studied decision-making network, in which synapses can change their rate of plasticity in addition to their efficacy according to a reward-based learning rule. We found that our model, which assumes that synaptic plasticity is guided by a novel surprise detection system, captures a wide range of key experimental findings and performs as well as a Bayes optimal model, with remarkably little parameter tuning. Our results further demonstrate the computational power of synaptic plasticity, and provide insights into the circuit-level computation which underlies adaptive decision-making. DOI: http://dx.doi.org/10.7554/eLife.18073.001 PMID:27504806

  16. Tracking with asymptotic sliding mode and adaptive input delay effect compensation of nonlinearly perturbed delayed systems applied to traffic feedback control

    NASA Astrophysics Data System (ADS)

    Mirkin, Boris; Haddad, Jack; Shtessel, Yuri

    2016-09-01

    Asymptotical sliding mode-model reference adaptive control design for a class of systems with parametric uncertainty, unknown nonlinear perturbation and external disturbance, and with known input and state delays is proposed. To overcome the difficulty to directly predict the plant state under uncertainties, a control design is based on a developed decomposition procedure, where a 'generalised error' in conjunction with auxiliary linear dynamic blocks with adjustable gains is introduced and the sliding variable is formed on the basis of this error. The effect of such a decomposition is to pull the input delay out of first step of the design procedure. As a result, similarly to the classical Smith predictor, the adaptive control architecture based only on the lumped-delays, i.e. without conventional in such cases difficult-implemented distributed-delay blocks. Two new adaptive control schemes are proposed. A linearisation-based control design is constructed for feedback control of an urban traffic region model with uncertain dynamics. Simulation results demonstrate the effectiveness of the developed adaptive control method.

  17. Audio Feedback -- Better Feedback?

    ERIC Educational Resources Information Center

    Voelkel, Susanne; Mello, Luciane V.

    2014-01-01

    National Student Survey (NSS) results show that many students are dissatisfied with the amount and quality of feedback they get for their work. This study reports on two case studies in which we tried to address these issues by introducing audio feedback to one undergraduate (UG) and one postgraduate (PG) class, respectively. In case study one…

  18. How to Cope with Bias While Adapting for Inclusion in Physical Education and Sports: A Judgment and Decision-Making Perspective

    ERIC Educational Resources Information Center

    Hutzler, Yeshayahu; Bar-Eli, Michael

    2013-01-01

    The purpose of this article is to describe a theoretical model and practice examples of judgment and decision making bias within the context of inclusion in physical education and sports. After presenting the context of adapting for inclusion, the theoretical roots of judgment and decision are described, and are linked to the practice of physical…

  19. Horseshoe bats make adaptive prey-selection decisions, informed by echo cues.

    PubMed

    Koselj, Klemen; Schnitzler, Hans-Ulrich; Siemers, Björn M

    2011-10-22

    Foragers base their prey-selection decisions on the information acquired by the sensory systems. In bats that use echolocation to find prey in darkness, it is not clear whether the specialized diet, as sometimes found by faecal analysis, is a result of active decision-making or rather of biased sensory information. Here, we tested whether greater horseshoe bats decide economically when to attack a particular prey item and when not. This species is known to recognize different insects based on their wing-beat pattern imprinted in the echoes. We built a simulation of the natural foraging process in the laboratory, where the bats scanned for prey from a perch and, upon reaching the decision to attack, intercepted the prey in flight. To fully control echo information available to the bats and assure its unambiguity, we implemented computer-controlled propellers that produced echoes resembling those from natural insects of differing profitability. The bats monitored prey arrivals to sample the supply of prey categories in the environment and to inform foraging decisions. The bats adjusted selectivity for the more profitable prey to its inter-arrival intervals as predicted by foraging theory (an economic strategy known to benefit fitness). Moreover, unlike in previously studied vertebrates, foraging performance of horseshoe bats was not limited by costly rejections of the profitable prey. This calls for further research into the evolutionary selection pressures that sharpened the species's decision-making capacity.

  20. Horseshoe bats make adaptive prey-selection decisions, informed by echo cues

    PubMed Central

    Koselj, Klemen; Schnitzler, Hans-Ulrich; Siemers, Björn M.

    2011-01-01

    Foragers base their prey-selection decisions on the information acquired by the sensory systems. In bats that use echolocation to find prey in darkness, it is not clear whether the specialized diet, as sometimes found by faecal analysis, is a result of active decision-making or rather of biased sensory information. Here, we tested whether greater horseshoe bats decide economically when to attack a particular prey item and when not. This species is known to recognize different insects based on their wing-beat pattern imprinted in the echoes. We built a simulation of the natural foraging process in the laboratory, where the bats scanned for prey from a perch and, upon reaching the decision to attack, intercepted the prey in flight. To fully control echo information available to the bats and assure its unambiguity, we implemented computer-controlled propellers that produced echoes resembling those from natural insects of differing profitability. The bats monitored prey arrivals to sample the supply of prey categories in the environment and to inform foraging decisions. The bats adjusted selectivity for the more profitable prey to its inter-arrival intervals as predicted by foraging theory (an economic strategy known to benefit fitness). Moreover, unlike in previously studied vertebrates, foraging performance of horseshoe bats was not limited by costly rejections of the profitable prey. This calls for further research into the evolutionary selection pressures that sharpened the species's decision-making capacity. PMID:21367788

  1. A Novel Clinical Decision Support System Using Improved Adaptive Genetic Algorithm for the Assessment of Fetal Well-Being

    PubMed Central

    Jambek, Asral Bahari; Neoh, Siew-Chin

    2015-01-01

    A novel clinical decision support system is proposed in this paper for evaluating the fetal well-being from the cardiotocogram (CTG) dataset through an Improved Adaptive Genetic Algorithm (IAGA) and Extreme Learning Machine (ELM). IAGA employs a new scaling technique (called sigma scaling) to avoid premature convergence and applies adaptive crossover and mutation techniques with masking concepts to enhance population diversity. Also, this search algorithm utilizes three different fitness functions (two single objective fitness functions and multi-objective fitness function) to assess its performance. The classification results unfold that promising classification accuracy of 94% is obtained with an optimal feature subset using IAGA. Also, the classification results are compared with those of other Feature Reduction techniques to substantiate its exhaustive search towards the global optimum. Besides, five other benchmark datasets are used to gauge the strength of the proposed IAGA algorithm. PMID:25793009

  2. Adaptation for Planting and Irrigation Decisions to Changing Monsoon Regime in Northeast India: Risk-based Hydro-economic Optimization

    NASA Astrophysics Data System (ADS)

    Zhu, T.; Cai, X.

    2013-12-01

    Delay in onset of Indian summer monsoon becomes increasingly frequent. Delayed monsoon and occasional monsoon failures seriously affect agricultural production in the northeast as well as other parts of India. In the Vaishali district of the Bihar State, Monsoon rainfall is very skewed and erratic, often concentrating in shorter durations. Farmers in Vaishali reported that delayed Monsoon affected paddy planting and, consequently delayed cropping cycle, putting crops under the risks of 'terminal heat.' Canal system in the district does not function due to lack of maintenance; irrigation relies almost entirely on groundwater. Many small farmers choose not to irrigate when monsoon onset is delayed due to high diesel price, leading to reduced production or even crop failure. Some farmers adapt to delayed onset of Monsoon by planting short-duration rice, which gives the flexibility for planting the next season crops. Other sporadic autonomous adaptation activities were observed as well, with various levels of success. Adaptation recommendations and effective policy interventions are much needed. To explore robust options to adapt to the changing Monsoon regime, we build a stochastic programming model to optimize revenues of farmer groups categorized by landholding size, subject to stochastic Monsoon onset and rainfall amount. Imperfect probabilistic long-range forecast is used to inform the model onset and rainfall amount probabilities; the 'skill' of the forecasting is measured using probabilities of correctly predicting events in the past derived through hindcasting. Crop production functions are determined using self-calibrating Positive Mathematical Programming approach. The stochastic programming model aims to emulate decision-making behaviors of representative farmer agents through making choices in adaptation, including crop mix, planting dates, irrigation, and use of weather information. A set of technological and policy intervention scenarios are tested

  3. Adapting a Driving Simulator to Study Pedestrians' Street-Crossing Decisions: A Feasibility Study.

    PubMed

    Jäger, M; Nyffeler, T; Müri, R; Mosimann, U P; Nef, T

    2015-01-01

    The decision when to cross a street safely is a challenging task that poses high demands on perception and cognition. Both can be affected by normal aging, neurodegenerative disorder, and brain injury, and there is an increasing interest in studying street-crossing decisions. In this article, we describe how driving simulators can be modified to study pedestrians' street-crossing decisions. The driving simulator's projection system and the virtual driving environment were used to present street-crossing scenarios to the participants. New sensors were added to measure when the test person starts to cross the street. Outcome measures were feasibility, usability, task performance, and visual exploration behavior, and were measured in 15 younger persons, 15 older persons, and 5 post-stroke patients. The experiments showed that the test is feasible and usable, and the selected difficulty level was appropriate. Significant differences in the number of crashes between young participants and patients (p = .001) as well as between healthy older participants and patients (p = .003) were found. When the approaching vehicle's speed is high, significant differences between younger and older participants were found as well (p = .038). Overall, the new test setup was well accepted, and we demonstrated that driving simulators can be used to study pedestrians' street-crossing decisions.

  4. Adapting a Driving Simulator to Study Pedestrians' Street-Crossing Decisions: A Feasibility Study.

    PubMed

    Jäger, M; Nyffeler, T; Müri, R; Mosimann, U P; Nef, T

    2015-01-01

    The decision when to cross a street safely is a challenging task that poses high demands on perception and cognition. Both can be affected by normal aging, neurodegenerative disorder, and brain injury, and there is an increasing interest in studying street-crossing decisions. In this article, we describe how driving simulators can be modified to study pedestrians' street-crossing decisions. The driving simulator's projection system and the virtual driving environment were used to present street-crossing scenarios to the participants. New sensors were added to measure when the test person starts to cross the street. Outcome measures were feasibility, usability, task performance, and visual exploration behavior, and were measured in 15 younger persons, 15 older persons, and 5 post-stroke patients. The experiments showed that the test is feasible and usable, and the selected difficulty level was appropriate. Significant differences in the number of crashes between young participants and patients (p = .001) as well as between healthy older participants and patients (p = .003) were found. When the approaching vehicle's speed is high, significant differences between younger and older participants were found as well (p = .038). Overall, the new test setup was well accepted, and we demonstrated that driving simulators can be used to study pedestrians' street-crossing decisions. PMID:26132219

  5. Sea Level Rise Decision Support Tools for Adaptation Planning in Vulnerable Coastal Communities

    NASA Astrophysics Data System (ADS)

    Rozum, J. S.; Marcy, D.

    2015-12-01

    NOAA is involved in a myriad of climate related research and projects that help decision makers and the public understand climate science as well as climate change impacts. The NOAA Office for Coastal Management (OCM) provides data, tools, trainings and technical assistance to coastal resource managers. Beginning in 2011, NOAA OCM began developing a sea level rise and coastal flooding impacts viewer which provides nationally consistent data sets and analyses to help communities with coastal management goals such as: understanding and communicating coastal flood hazards, performing vulnerability assessments and increasing coastal resilience, and prioritizing actions for different inundation/flooding scenarios. The Viewer is available on NOAA's Digital Coast platform: (coast.noaa.gov/ditgitalcoast/tools/slr). In this presentation we will share the lessons learned from our work with coastal decision-makers on the role of coastal flood risk data and tools in helping to shape future land use decisions and policies. We will also focus on a recent effort in California to help users understand the similarities and differences of a growing array of sea level rise decision support tools. NOAA staff and other partners convened a workshop entitled, "Lifting the Fog: Bringing Clarity to Sea Level Rise and Shoreline Change Models and Tools," which was attended by tool develops, science translators and coastal managers with the goal to create a collaborative communication framework to help California coastal decision-makers navigate the range of available sea level rise planning tools, and to inform tool developers of future planning needs. A sea level rise tools comparison matrix will be demonstrated. This matrix was developed as part of this effort and has been expanded to many other states via a partnership with NOAA, Climate Central, and The Nature Conservancy.

  6. Cultural and linguistic adaptation of a multimedia colorectal cancer screening decision aid for Spanish-speaking Latinos.

    PubMed

    Ko, Linda K; Reuland, Daniel; Jolles, Monica; Clay, Rebecca; Pignone, Michael

    2014-01-01

    As the United States becomes more linguistically and culturally diverse, there is a need for effective health communication interventions that target diverse, vulnerable populations, including Latinos. To address such disparities, health communication interventionists often face the challenge to adapt existing interventions from English into Spanish in a way that retains essential elements of the original intervention while also addressing the linguistic needs and cultural perspectives of the target population. The authors describe the conceptual framework, context, rationale, methods, and findings of a formative research process used in creating a Spanish-language version of an evidence-based (English language) multimedia colorectal cancer screening decision aid. The multistep process included identification of essential elements of the existing intervention, literature review, assessment of the regional context and engagement of key stakeholders, and solicitation of direct input from target population. The authors integrated these findings in the creation of the new adapted intervention. They describe how they used this process to identify and integrate sociocultural themes such as personalism (personalismo), familism (familismo), fear (miedo), embarrassment (verguenza), power distance (respeto), machismo, and trust (confianza) into the Spanish-language decision aid.

  7. iRESM INITIATIVE UNDERSTANDING DECISION SUPPORT NEEDS FOR CLIMATE CHANGE MITIGATION AND ADAPTATION --US Midwest Region—

    SciTech Connect

    Rice, Jennie S.; Runci, Paul J.; Moss, Richard H.; Anderson, Kate L.

    2010-10-01

    The impacts of climate change are already affecting human and environmental systems worldwide, yet many uncertainties persist in the prediction of future climate changes and impacts due to limitations in scientific understanding of relevant causal factors. In particular, there is mounting urgency to efforts to improve models of human and environmental systems at the regional scale, and to integrate climate, ecosystem and energy-economic models to support policy, investment, and risk management decisions related to climate change mitigation (i.e., reducing greenhouse gas emissions) and adaptation (i.e., responding to climate change impacts). The Pacific Northwest National Laboratory (PNNL) is developing a modeling framework, the integrated Regional Earth System Model (iRESM), to address regional human-environmental system interactions in response to climate change and the uncertainties therein. The framework will consist of a suite of integrated models representing regional climate change, regional climate policy, and the regional economy, with a focus on simulating the mitigation and adaptation decisions made over time in the energy, transportation, agriculture, and natural resource management sectors.

  8. M-Learning: Implications in Learning Domain Specificities, Adaptive Learning, Feedback, Augmented Reality, and the Future of Online Learning

    ERIC Educational Resources Information Center

    Squires, David R.

    2014-01-01

    The aim of this paper is to examine the potential and effectiveness of m-learning in the field of Education and Learning domains. The purpose of this research is to illustrate how mobile technology can and is affecting novel change in instruction, from m-learning and the link to adaptive learning, to the uninitiated learner and capacities of…

  9. Adaptation to a Changing Environment by Modifications in Organizational Decision Unit Structure.

    ERIC Educational Resources Information Center

    Duncan, Robert B.

    This paper presents a model of how organizations adapt to the uncertainty in their environment by making changes in the way they structure themselves for decisionmaking. The research reported here indicates that it is not just a single change in organizational structure, but rather a shifting between a more rigid and more flexible decision…

  10. Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system

    USGS Publications Warehouse

    Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.; Rocky, Durrans S.

    2000-01-01

    Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorial data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

  11. Decentralized Output Feedback Adaptive NN Tracking Control for Time-Delay Stochastic Nonlinear Systems With Prescribed Performance.

    PubMed

    Hua, Changchun; Zhang, Liuliu; Guan, Xinping

    2015-11-01

    This paper studies the dynamic output feedback tracking control problem for stochastic interconnected time-delay systems with the prescribed performance. The subsystems are in the form of triangular structure. First, we design a reduced-order observer independent of time delay to estimate the unmeasured state variables online instead of the traditional full-order observer. Then, a new state transformation is proposed in consideration of the prescribed performance requirement. Using neural network to approximate the composite unknown nonlinear function, the corresponding decentralized output tracking controller is designed. It is strictly proved that the resulting closed-loop system is stable in probability in the sense of uniformly ultimately boundedness and that both transient-state and steady-state performances are preserved. Finally, a simulation example is given, and the result shows the effectiveness of the proposed control design method.

  12. Fast subpel motion estimation for H.264/advanced video coding with an adaptive motion vector accuracy decision

    NASA Astrophysics Data System (ADS)

    Lee, Hoyoung; Jung, Bongsoo; Jung, Jooyoung; Jeon, Byeungwoo

    2012-11-01

    The quarter-pel motion vector accuracy supported by H.264/advanced video coding (AVC) in motion estimation (ME) and compensation (MC) provides high compression efficiency. However, it also increases the computational complexity. While various well-known fast integer-pel ME methods are already available, lack of a good, fast subpel ME method results in problems associated with relatively high computational complexity. This paper presents one way of solving the complexity problem of subpel ME by making adaptive motion vector (MV) accuracy decisions in inter-mode selection. The proposed MV accuracy decision is made using inter-mode selection of a macroblock with two decision criteria. Pixels are classified as stationary (and/or homogeneous) or nonstationary (and/or nonhomogeneous). In order to avoid unnecessary interpolation and processing, a proper subpel ME level is chosen among four different combinations, each of which has a different MV accuracy and number of subpel ME iterations based on the classification. Simulation results using an open source x264 software encoder show that without any noticeable degradation (by -0.07 dB on average), the proposed method reduces total encoding time and subpel ME time, respectively, by 51.78% and by 76.49% on average, as compared to the conventional full-pel pixel search.

  13. Does fertility status influence impulsivity and risk taking in human females? Adaptive influences on intertemporal choice and risky decision making

    PubMed Central

    Stevens, Jeffrey R.

    2013-01-01

    Informed by the research on adaptive decision making in other animal species, this study investigated human female’s intertemporal and risky choices across the ovulatory cycle. We tested the hypothesis that at peak fertility, women who are exposed to environments that signal availability of higher quality mates, by viewing images of attractive males, become more impulsive and risk seeking in economic decision tasks. To test this, we collected intertemporal and risky choice before and after exposure to images of either attractive males or neutral landscapes both at peak and low fertility conditions. The results showed an interaction between women’s fertility status and image type, such that women at peak fertility viewing images of attractive men chose the smaller, sooner monetary reward option less than women at peak fertility viewing neutral images. Neither fertility status nor image type influenced risky choice. Thus, though exposure to images of men altered intertemporal choices at peak fertility, this occurred in the opposite direction as predicted—women at peak fertility became less impulsive. Nevertheless, the results of the current study provide evidence for shifts in preferences over the ovulatory cycle and opens future research on economic decision making. PMID:23864300

  14. Perceptual decision processes flexibly adapt to avoid change-of-mind motor costs.

    PubMed

    Moher, Jeff; Song, Joo-Hyun

    2014-07-01

    The motor system is tightly linked with perception and cognition. Recent studies have shown that even anticipated biophysical action costs associated with competing response options can be incorporated into decision-making processes. As a result, choices associated with high energy costs are less likely to be selected. However, some action costs may be harder to predict. For example, a person choosing among apples at a grocery store may change his or her mind suddenly about which apple to put into the cart. This change of mind may be reflected in motor output as the initial decision triggers a motor response toward a Granny Smith that is subsequently redirected toward a Red Delicious. In the present study, to examine how motor costs associated with changes of mind affect perceptual decision making, participants performed a difficult random dot–motion discrimination task in which they had to indicate the direction of motion by reaching to one of two response options. Although each response box was always equidistant from the starting position, the physical distance between the two response options was varied. We found that when the boxes were far apart from one another, and thus changes of mind incurred greater redirection motor costs, change-of-mind frequency decreased while latency to initiate movement increased. This occurred even when response box distance varied randomly from trial to trial and was cued only 1 s before each trial began. Thus, we demonstrated that observers can dynamically adjust perceptual decision-making processes to avoid high motor costs incurred by a change of mind.

  15. Science-policy interface in transformative adaptive flood risk management - decision-making in Austria

    NASA Astrophysics Data System (ADS)

    Thaler, Thomas; Attems, Marie-Sophie; Rauter, Magdalena; Fuchs, Sven

    2016-04-01

    Facing the challenges of climate change, this paper aims to analyse and to evaluate the multiple use of flood alleviation schemes with respect to social transformation in communities exposed to flood hazards in Europe. The overall goals are: (1) the identification of indicators and parameters necessary for strategies to increase societal resilience, (2) an analysis of the institutional settings needed for societal transformation, and (3) perspectives of changing divisions of responsibilities between public and private actors necessary to arrive at more resilient societies. As such, governance is done by people interacting and defining risk mitigation measures as well as climate change adaptation are therefore simultaneously both outcomes of, and productive to, public and private responsibilities. Building off current knowledge this paper focussed on different dimensions of adaptation and mitigation strategies based on social, economic and institutional incentives and settings, centring on the linkages between these different dimensions and complementing existing flood risk governance arrangements. As such, the challenges of adaptation to flood risk will be tackled by converting scientific frameworks into practical assessment and policy advice. This paper used the Formative Scenario Analysis (FSA) as a method to construct well-defined sets of assumptions to gain insight into a system and its potential future development, based on qualitatively assessed impact factors and rated quantitative relations between these factors, such as impact and consistency analysis. The purpose of this approach was to develop scenarios, where participations develop their own strategies how to implement a transformative adaptation strategy in flood risk management. In particular, the interaction between researcher, the public and policy makers was analysed. Challenges and limitations were assessed, such as benefits on costs of adaptation measures, for the implementation of visions to

  16. Decision making in concurrent multitasking: do people adapt to task interference?

    PubMed

    Nijboer, Menno; Taatgen, Niels A; Brands, Annelies; Borst, Jelmer P; van Rijn, Hedderik

    2013-01-01

    While multitasking has received a great deal of attention from researchers, we still know little about how well people adapt their behavior to multitasking demands. In three experiments, participants were presented with a multicolumn subtraction task, which required working memory in half of the trials. This primary task had to be combined with a secondary task requiring either working memory or visual attention, resulting in different types of interference. Before each trial, participants were asked to choose which secondary task they wanted to perform concurrently with the primary task. We predicted that if people seek to maximize performance or minimize effort required to perform the dual task, they choose task combinations that minimize interference. While performance data showed that the predicted optimal task combinations indeed resulted in minimal interference between tasks, the preferential choice data showed that a third of participants did not show any adaptation, and for the remainder it took a considerable number of trials before the optimal task combinations were chosen consistently. On the basis of these results we argue that, while in principle people are able to adapt their behavior according to multitasking demands, selection of the most efficient combination of strategies is not an automatic process.

  17. The development of adaptive decision making: Recognition-based inference in children and adolescents.

    PubMed

    Horn, Sebastian S; Ruggeri, Azzurra; Pachur, Thorsten

    2016-09-01

    Judgments about objects in the world are often based on probabilistic information (or cues). A frugal judgment strategy that utilizes memory (i.e., the ability to discriminate between known and unknown objects) as a cue for inference is the recognition heuristic (RH). The usefulness of the RH depends on the structure of the environment, particularly the predictive power (validity) of recognition. Little is known about developmental differences in use of the RH. In this study, the authors examined (a) to what extent children and adolescents recruit the RH when making judgments, and (b) around what age adaptive use of the RH emerges. Primary schoolchildren (M = 9 years), younger adolescents (M = 12 years), and older adolescents (M = 17 years) made comparative judgments in task environments with either high or low recognition validity. Reliance on the RH was measured with a hierarchical multinomial model. Results indicated that primary schoolchildren already made systematic use of the RH. However, only older adolescents adaptively adjusted their strategy use between environments and were better able to discriminate between situations in which the RH led to correct versus incorrect inferences. These findings suggest that the use of simple heuristics does not progress unidirectionally across development but strongly depends on the task environment, in line with the perspective of ecological rationality. Moreover, adaptive heuristic inference seems to require experience and a developed base of domain knowledge. (PsycINFO Database Record PMID:27505696

  18. Decision Making in Concurrent Multitasking: Do People Adapt to Task Interference?

    PubMed Central

    Nijboer, Menno; Taatgen, Niels A.; Brands, Annelies; Borst, Jelmer P.; van Rijn, Hedderik

    2013-01-01

    While multitasking has received a great deal of attention from researchers, we still know little about how well people adapt their behavior to multitasking demands. In three experiments, participants were presented with a multicolumn subtraction task, which required working memory in half of the trials. This primary task had to be combined with a secondary task requiring either working memory or visual attention, resulting in different types of interference. Before each trial, participants were asked to choose which secondary task they wanted to perform concurrently with the primary task. We predicted that if people seek to maximize performance or minimize effort required to perform the dual task, they choose task combinations that minimize interference. While performance data showed that the predicted optimal task combinations indeed resulted in minimal interference between tasks, the preferential choice data showed that a third of participants did not show any adaptation, and for the remainder it took a considerable number of trials before the optimal task combinations were chosen consistently. On the basis of these results we argue that, while in principle people are able to adapt their behavior according to multitasking demands, selection of the most efficient combination of strategies is not an automatic process. PMID:24244527

  19. A Decision Support System for Climate Change Adaptation in Rainfed Sectors of Agriculture for Central Europe

    NASA Astrophysics Data System (ADS)

    Mátyás, Csaba; Berki, Imre; Drüszler, Áron; Eredics, Attila; Gálos, Borbála; Illés, Gábor; Móricz, Norbert; Rasztovits, Ervin; Czimber, Kornél

    2013-04-01

    • Background and aims: Rainfed sectors of agriculture such as nature-close forestry, non-irrigated agriculture and animal husbandry on nature-close pastures are threatened by projected climate change especially in low-elevation regions in Southeast Europe, where precipitation is the limiting factor of production and ecosystem stability. Therefore the importance of complex, long term management planning and of land use optimization is increasing. The aim of the Decision Support System under development is to raise awareness and initiate preparation for frequency increase of extreme events, disasters and economic losses in the mentioned sectors. • Services provided: The Decision Support System provides GIS-supported information about the most important regional and local risks and mitigation options regarding climate change impacts, projected for reference periods until 2100 (e.g. land cover/use and expectable changes, potential production, water and carbon cycle, biodiversity and other ecosystem services, potential pests and diseases, tolerance limits etc.). The projections are referring first of all on biological production (natural produce), but the System includes also social and economic consequences. • Methods: In the raster based system, the latest image processing technology is used. We apply fuzzy membership functions, Support Vector Machine and Maximum Likelihood classifier. The System is developed in the first step for a reference area in SW Hungary (Zala county). • Novelty: The coherent, fine-scale regional system integrates the basic information about present and projected climates, extremes, hydrology and soil conditions and expected production potential for three sectors of agriculture as options for land use and conservation. • Funding: The development of the Decision Support System "Agrárklíma" is supported by TÁMOP-4.2.2.A-11/1/KONV and 4.2.2.B-10/1-2010-0018 "Talentum" joint EU-national research projects. Keywords: climate change

  20. Statistical learning and adaptive decision-making underlie human response time variability in inhibitory control

    PubMed Central

    Ma, Ning; Yu, Angela J.

    2015-01-01

    Response time (RT) is an oft-reported behavioral measure in psychological and neurocognitive experiments, but the high level of observed trial-to-trial variability in this measure has often limited its usefulness. Here, we combine computational modeling and psychophysics to examine the hypothesis that fluctuations in this noisy measure reflect dynamic computations in human statistical learning and corresponding cognitive adjustments. We present data from the stop-signal task (SST), in which subjects respond to a go stimulus on each trial, unless instructed not to by a subsequent, infrequently presented stop signal. We model across-trial learning of stop signal frequency, P(stop), and stop-signal onset time, SSD (stop-signal delay), with a Bayesian hidden Markov model, and within-trial decision-making with an optimal stochastic control model. The combined model predicts that RT should increase with both expected P(stop) and SSD. The human behavioral data (n = 20) bear out this prediction, showing P(stop) and SSD both to be significant, independent predictors of RT, with P(stop) being a more prominent predictor in 75% of the subjects, and SSD being more prominent in the remaining 25%. The results demonstrate that humans indeed readily internalize environmental statistics and adjust their cognitive/behavioral strategy accordingly, and that subtle patterns in RT variability can serve as a valuable tool for validating models of statistical learning and decision-making. More broadly, the modeling tools presented in this work can be generalized to a large body of behavioral paradigms, in order to extract insights about cognitive and neural processing from apparently quite noisy behavioral measures. We also discuss how this behaviorally validated model can then be used to conduct model-based analysis of neural data, in order to help identify specific brain areas for representing and encoding key computational quantities in learning and decision-making. PMID:26321966

  1. Obstacles to adaptation decisions in the developing world: A case study of coastal protection measures and sea-level rise in Kiribati

    NASA Astrophysics Data System (ADS)

    Donner, S. D.; Webber, S.

    2014-12-01

    International aid is increasingly focused on adaptation to climate change. At recent meetings of the parties to the United Nations Framework Convention on Climate Change, the developed world agreed to rapidly increase international assistance to help the developing world respond to the impacts of climate change. Here, we examine the decision-making challenges facing internationally supported climate change adaptation projects given the large uncertainty in future climate predictions, using the example of efforts to implement coastal protection measures (e.g. sea walls, mangrove planting) in Kiribati. The central equatorial Pacific country is home to the Kiribati Adaptation Project, the first national-level climate change adaptation project supported by the World Bank. Drawing on interview and document research conducted over an 8-year period, we trace the forces influencing decisions about coastal protection measures, starting from the variability and uncertainty in climate change projections, through the trade-offs between different measures, to the social, political, and economic context in which decisions are finally made. We then discuss how sub-optimal adaptation measures may be implemented despite years of planning, consultation, and technical studies. This qualitative analysis of the real-world process of climate change adaptation reveals that embracing a culturally appropriate and short-term (~20 years) planning horizon, while not ignoring the longer-term future, may reduce the influence of scientific uncertainty on decisions and provide opportunities to learn from mistakes, reassess the science, and adjust suboptimal investments.

  2. Multiple feedbacks between chloroplast and whole plant in the context of plant adaptation and acclimation to the environment

    PubMed Central

    Demmig-Adams, Barbara; Stewart, Jared J.; Adams, William W.

    2014-01-01

    This review focuses on feedback pathways that serve to match plant energy acquisition with plant energy utilization, and thereby aid in the optimization of chloroplast and whole-plant function in a given environment. First, the role of source–sink signalling in adjusting photosynthetic capacity (light harvesting, photochemistry and carbon fixation) to meet whole-plant carbohydrate demand is briefly reviewed. Contrasting overall outcomes, i.e. increased plant growth versus plant growth arrest, are described and related to respective contrasting environments that either do or do not present opportunities for plant growth. Next, new insights into chloroplast-generated oxidative signals, and their modulation by specific components of the chloroplast's photoprotective network, are reviewed with respect to their ability to block foliar phloem-loading complexes, and, thereby, affect both plant growth and plant biotic defences. Lastly, carbon export capacity is described as a newly identified tuning point that has been subjected to the evolution of differential responses in plant varieties (ecotypes) and species from different geographical origins with contrasting environmental challenges. PMID:24591724

  3. Cooperative fuzzy adaptive output feedback control for synchronisation of nonlinear multi-agent systems under directed graphs

    NASA Astrophysics Data System (ADS)

    Wang, W.; Wang, D.; Peng, Z. H.

    2015-12-01

    This paper considers the leader-following synchronisation problem of nonlinear multi-agent systems with unmeasurable states and a dynamic leader whose input is not available to any follower. Each follower is governed by a nonlinear system with unknown dynamics. Two distributed fuzzy adaptive protocols, based on local and neighbourhood observers, respectively, are proposed to guarantee that the states of all followers synchronise to that of the leader, under the condition that the communication graph among the followers contains a directed spanning tree. Based on Lyapunov stability theory, the synchronisation errors are guaranteed to be cooperatively uniformly ultimately bounded. Two examples are provided to show the effectiveness of the proposed controllers.

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

    NASA Astrophysics Data System (ADS)

    Yoon, Susan A.; Klopfer, Eric

    2006-12-01

    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 computational modeling tools. We demonstrate that structuring a professional development program around the FANS framework facilitates the development of important strategies and processes for program organizers such as the identification of salient system variables, effectively distributing expertise, adaptation and improvement of professional development resources and activities and building technological, human and social capital. For participants, there is evidence to show that the FANS framework encourages: professional goal setting, engagement in a strong professional community and personal autonomy by enabling individualized purpose—all fundamental components in promoting self-organization. We discuss three meta-level themes that may account for the success of the FANS framework: structure versus agency, exploration versus exploitation and short-term versus long-term goals. Each illustrates the tension that exists between competing variables that need to be considered in order to work effectively in real world complex educational systems.

  5. Decision Making in Recurrent Neuronal Circuits

    PubMed Central

    Wang, Xiao-Jing

    2009-01-01

    Decision making has recently emerged as a central theme in neurophysiological studies of cognition, and experimental and computational work has led to the proposal of a cortical circuit mechanism of elemental decision computations. This mechanism depends on slow recurrent synaptic excitation balanced by fast feedback inhibition, which not only instantiates attractor states for forming categorical choices but also long transients for gradually accumulating evidence in favor of or against alternative options. Such a circuit endowed with reward-dependent synaptic plasticity is able to produce adaptive choice behavior. While decision threshold is a core concept for reaction time tasks, it can be dissociated from a general decision rule. Moreover, perceptual decisions and value-based economic choices are described within a unified framework in which probabilistic choices result from irregular neuronal activity as well as iterative interactions of a decision maker with an uncertain environment or other unpredictable decision makers in a social group. PMID:18957215

  6. Application of flood risk modelling in a web-based geospatial decision support tool for coastal adaptation to climate change

    NASA Astrophysics Data System (ADS)

    Knight, P. J.; Prime, T.; Brown, J. M.; Morrissey, K.; Plater, A. J.

    2015-02-01

    A pressing problem facing coastal decision makers is the conversion of "high level" but plausible climate change assessments into an effective basis for climate change adaptation at the local scale. Here, we describe a web-based, geospatial decision-support tool (DST) that provides an assessment of the potential flood risk for populated coastal lowlands arising from future sea-level rise, coastal storms and high river flows. This DST has been developed to support operational and strategic decision making by enabling the user to explore the flood hazard from extreme events, changes in the extent of the flood-prone areas with sea-level rise, and thresholds of sea-level rise where current policy and resource options are no longer viable. The DST is built in an open source GIS that uses freely available geospatial data. Flood risk assessments from a combination of LISFLOOD-FP and SWAB models are embedded within the tool; the user interface enables interrogation of different combinations of coastal and river events under rising sea-level scenarios. Users can readily vary the input parameters (sea level, storms, wave height and river flow) relative to the present-day topography and infrastructure to identify combinations where significant regime shifts or "tipping points" occur. Two case studies are used to demonstrate the attributes of the DST with respect to the wider coastal community and the UK energy sector. Examples report on the assets at risk and illustrate the extent of flooding in relation to infrastructure access. This informs an economic assessment of potential losses due to climate change and thus provides local authorities and energy operators with essential information on the feasibility of investment for building resilience into vulnerable components of their area of responsibility.

  7. Application of flood risk modelling in a web-based geospatial decision support tool for coastal adaptation to climate change

    NASA Astrophysics Data System (ADS)

    Knight, P. J.; Prime, T.; Brown, J. M.; Morrissey, K.; Plater, A. J.

    2015-07-01

    A pressing problem facing coastal decision makers is the conversion of "high-level" but plausible climate change assessments into an effective basis for climate change adaptation at the local scale. Here, we describe a web-based, geospatial decision support tool (DST) that provides an assessment of the potential flood risk for populated coastal lowlands arising from future sea-level rise, coastal storms, and high river flows. This DST has been developed to support operational and strategic decision making by enabling the user to explore the flood hazard from extreme events, changes in the extent of the flood-prone areas with sea-level rise, and thresholds of sea-level rise where current policy and resource options are no longer viable. The DST is built in an open-source GIS that uses freely available geospatial data. Flood risk assessments from a combination of LISFLOOD-FP and SWAB (Shallow Water And Boussinesq) models are embedded within the tool; the user interface enables interrogation of different combinations of coastal and river events under rising-sea-level scenarios. Users can readily vary the input parameters (sea level, storms, wave height and river flow) relative to the present-day topography and infrastructure to identify combinations where significant regime shifts or "tipping points" occur. Two case studies demonstrate the attributes of the DST with respect to the wider coastal community and the UK energy sector. Examples report on the assets at risk and illustrate the extent of flooding in relation to infrastructure access. This informs an economic assessment of potential losses due to climate change and thus provides local authorities and energy operators with essential information on the feasibility of investment for building resilience into vulnerable components of their area of responsibility.

  8. Complexity reduction in the H.264/AVC using highly adaptive fast mode decision based on macroblock motion activity

    NASA Astrophysics Data System (ADS)

    Abdellah, Skoudarli; Mokhtar, Nibouche; Amina, Serir

    2015-11-01

    The H.264/AVC video coding standard is used in a wide range of applications from video conferencing to high-definition television according to its high compression efficiency. This efficiency is mainly acquired from the newly allowed prediction schemes including variable block modes. However, these schemes require a high complexity to select the optimal mode. Consequently, complexity reduction in the H.264/AVC encoder has recently become a very challenging task in the video compression domain, especially when implementing the encoder in real-time applications. Fast mode decision algorithms play an important role in reducing the overall complexity of the encoder. In this paper, we propose an adaptive fast intermode algorithm based on motion activity, temporal stationarity, and spatial homogeneity. This algorithm predicts the motion activity of the current macroblock from its neighboring blocks and identifies temporal stationary regions and spatially homogeneous regions using adaptive threshold values based on content video features. Extensive experimental work has been done in high profile, and results show that the proposed source-coding algorithm effectively reduces the computational complexity by 53.18% on average compared with the reference software encoder, while maintaining the high-coding efficiency of H.264/AVC by incurring only 0.097 dB in total peak signal-to-noise ratio and 0.228% increment on the total bit rate.

  9. A decision support system for adaptive real-time management ofseasonal wetlands in California

    SciTech Connect

    Quinn, Nigel W.T.; Hanna, W. Mark

    2001-10-16

    This paper describes the development of a comprehensive flow and salinity monitoring system and application of a decision support system (DSS) to improve management of seasonal wetlands in the San Joaquin Valley of California. The Environmental Protection Agency regulates salinity discharges from non-point sources to the San Joaquin River using a procedure known as the Total Maximum Daily Load (TMDL) to allocate the assimilative capacity of the River for salt among watershed sources. Management of wetland sources of salt load will require the development of monitoring systems, more integrative management strategies and coordination with other entities. To obtain local cooperation the Grassland Water District, whose primary function is to supply surface water to private duck clubs and managed wetlands, needs to communicate to local landowners the likely impacts of salinity regulation on the long term health and function of wildfowl habitat. The project described in this paper will also provide this information. The models that form the backbone of the DSS develop salinity balances at both a regional and local scale. The regional scale concentrates on deliveries to and exports from the Grasland Water District while the local scale focuses on an individual wetland unit where more intensive monitoring is being conducted. The design of the DSS is constrained to meet the needs of busy wetland managers and is being designed from the bottom up utilizing tools and procedures familiar to these individuals.

  10. Adaptive control of interface by temperature and interface profile feedback in transparent multi-zone crystal growth furnace

    NASA Technical Reports Server (NTRS)

    Batur, Celal

    1991-01-01

    The objective of this research is to control the dynamics of multizone programmable crystal growth furnaces. Due to the inevitable heat exchange among different heating zones and the transient nature of the process, the dynamics of multizone furnaces is time varying, distributed, and therefore complex in nature. Electrical power to heating zones and the translational speed of the ampoule are employed as inputs to control the dynamics. Structural properties of the crystal is the ultimate aim of this adaptive control system. These properties can be monitored in different ways. Following an order of complexity, these may include: (1) on line measurement of the material optical properties such as the refractive index of crystal; (2) on line x-ray imaging of the interface topology; (3) on line optical quantification of the interface profile such as the determination of concavity or convexity of the interface shape; and (4) on line temperature measurement at points closest to the material such as measurements of the ampoule's outside and inside surface temperatures. The research performed makes use of the temperature and optical measurements, specified in (3) and (4) as the outputs of furnace dynamics. However, if the instrumentation is available, the proposed control methodology can be extended to the measurements listed in (1) and (2).

  11. Adapt

    NASA Astrophysics Data System (ADS)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  12. Supervisor Feedback.

    ERIC Educational Resources Information Center

    Hayman, Marilyn J.

    1981-01-01

    Investigated the effectiveness of supervisor feedback in contributing to learning counseling skills. Counselor trainees (N=64) were assigned to supervisor feedback, no supervisor feedback, or control groups for three training sessions. Results indicated counseling skills were learned best by students with no supervisor feedback but self and peer…

  13. A GIS-based Adaptive Management Decision Support System to Develop a Multi-Objective Framework: A case study utilizing GIS technologies and physically-based models to archieve improved decision making for site management.

    SciTech Connect

    Coleman, Andre M.; Wigmosta, Mark S.; Lane, Leonard J.; Tagestad, Jerry D.; Roberts, Damon

    2008-06-26

    The notion of Adaptive Management (AM) allows for the realization and adjustment of management practices in response to elements of uncertainty. In terms of natural resource management, this will typically integrate monitoring, databases, simulation modeling, decision theory, and expert judgment to evaluate management alternatives and adapt them as necessary to continually improve the natural resource condition as defined by the stakeholders. Natural resource management scenarios can often be expressed, viewed, and understood as a spatial and temporal problem. The integration of Geographic Information System (GIS) technologies and physically-based models provide an effective state-of-the-art solution for deriving, understanding, and applying AM scenarios for land use and remediation. A recently developed GIS-based adaptive management decision support system is presented for the U.S. Department of Defense Yakima Training Center near Yakima, Washington.

  14. Designing Genetic Feedback Controllers.

    PubMed

    Harris, Andreas W K; Dolan, James A; Kelly, Ciarán L; Anderson, James; Papachristodoulou, Antonis

    2015-08-01

    By incorporating feedback around systems we wish to manipulate, it is possible to improve their performance and robustness properties to meet pre-specified design objectives. For decades control engineers have been successfully implementing feedback controllers for complex mechanical and electrical systems such as aircraft and sports cars. Natural biological systems use feedback extensively for regulation and adaptation but apart from the most basic designs, there is no systematic framework for designing feedback controllers in Synthetic Biology. In this paper we describe how classical approaches from linear control theory can be used to close the loop. This includes the design of genetic circuits using feedback control and the presentation of a biological phase lag controller. PMID:26390502

  15. Benefits of social vs. non-social feedback on learning and generosity. Results from the Tipping Game.

    PubMed

    Colombo, Matteo; Stankevicius, Aistis; Seriès, Peggy

    2014-01-01

    Although much work has recently been directed at understanding social decision-making, relatively little is known about how different types of feedback impact adaptive changes in social behavior. To address this issue quantitatively, we designed a novel associative learning task called the "Tipping Game," in which participants had to learn a social norm of tipping in restaurants. Participants were found to make more generous decisions from feedback in the form of facial expressions, in comparison to feedback in the form of symbols such as ticks and crosses. Furthermore, more participants displayed learning in the condition where they received social feedback than participants in the non-social condition. Modeling results showed that the pattern of performance displayed by participants receiving social feedback could be explained by a lower sensitivity to economic costs. PMID:25346715

  16. Benefits of social vs. non-social feedback on learning and generosity. Results from the Tipping Game.

    PubMed

    Colombo, Matteo; Stankevicius, Aistis; Seriès, Peggy

    2014-01-01

    Although much work has recently been directed at understanding social decision-making, relatively little is known about how different types of feedback impact adaptive changes in social behavior. To address this issue quantitatively, we designed a novel associative learning task called the "Tipping Game," in which participants had to learn a social norm of tipping in restaurants. Participants were found to make more generous decisions from feedback in the form of facial expressions, in comparison to feedback in the form of symbols such as ticks and crosses. Furthermore, more participants displayed learning in the condition where they received social feedback than participants in the non-social condition. Modeling results showed that the pattern of performance displayed by participants receiving social feedback could be explained by a lower sensitivity to economic costs.

  17. Benefits of social vs. non-social feedback on learning and generosity. Results from the Tipping Game

    PubMed Central

    Colombo, Matteo; Stankevicius, Aistis; Seriès, Peggy

    2014-01-01

    Although much work has recently been directed at understanding social decision-making, relatively little is known about how different types of feedback impact adaptive changes in social behavior. To address this issue quantitatively, we designed a novel associative learning task called the “Tipping Game,” in which participants had to learn a social norm of tipping in restaurants. Participants were found to make more generous decisions from feedback in the form of facial expressions, in comparison to feedback in the form of symbols such as ticks and crosses. Furthermore, more participants displayed learning in the condition where they received social feedback than participants in the non-social condition. Modeling results showed that the pattern of performance displayed by participants receiving social feedback could be explained by a lower sensitivity to economic costs. PMID:25346715

  18. Effectiveness of instruction and video feedback on staff's use of prompts and children's adaptive responses during one-to-one training in children with severe to profound intellectual disability.

    PubMed

    van Vonderen, Annemarie; de Swart, Charlotte; Didden, Robert

    2010-01-01

    Although relatively many studies have addressed staff training and its effect on trainer behavior, the effects of staff training on trainee's adaptive behaviors have seldom been examined. We therefore assessed effectiveness of staff training, consisting of instruction and video feedback, on (a) staff's response prompting, and (b) staff's trainer behavior during one-to-one training with four direct-care staff who acted as trainers. Next to this, we evaluated the effects of staff training on adaptive skills in four children with severe to profound intellectual disability. A non-concurrent multiple baseline design across staff-trainee dyads was used. Intervention resulted in an immediate and substantial increase in percentage correct response prompting and percentage correct trainer behavior by staff. The intervention was also effective in increasing percentage of trainee's correct responses. Staff rated instruction and video feedback as effective and acceptable. Results are discussed in terms of their implications for future research.

  19. Constructivist coding: learning from selective feedback.

    PubMed

    Elwin, Ebba; Juslin, Peter; Olsson, Henrik; Enkvist, Tommy

    2007-02-01

    Although much learning in real-life environments relies on highly selective feedback about outcomes, virtually all cognitive models of learning, judgment, and categorization assume complete and representative feedback. We investigated empirically the effect of selective feedback on decision making and how people code experience with selective feedback. The results showed that, in contrast to a commonly raised concern, performance was not impaired following learning with selective and biased feedback. Furthermore, even in a simple decision task, the experience that people acquired was not a mere recording of the observed outcomes, but rather a reconstruction from general task knowledge. PMID:17425527

  20. Adaptive management on the central Platte River--science, engineering, and decision analysis to assist in the recovery of four species.

    PubMed

    Smith, Chadwin B

    2011-05-01

    Active adaptive management is the centerpiece of a major species recovery program now underway on the central Platte River in Nebraska. The Platte River Recovery Implementation Program initiated on January 1, 2007 and is a joint effort between the states of Colorado, Wyoming, and Nebraska; the U.S. Department of the Interior; waters users; and conservation groups. This program is intended to address issues related to endangered species and loss of habitat along the Platte River in central Nebraska by managing land and water resources and using adaptive management as its science framework. The adaptive management plan provides a systematic process to test hypotheses and apply the information learned to improve management on the ground, and is centered on conceptual models and priority hypotheses that reflect different interpretations of how river processes work and the best approach to meeting key objectives. This framework reveals a shared attempt to use the best available science to implement experiments, learn, and revise management actions accordingly on the Platte River. This paper focuses on the status of adaptive management implementation on the Platte, experimental and habitat design issues, and the use of decision analysis tools to help set objectives and guide decisions.

  1. Adaptive error detection for HDR/PDR brachytherapy: Guidance for decision making during real-time in vivo point dosimetry

    SciTech Connect

    Kertzscher, Gustavo Andersen, Claus E.; Tanderup, Kari

    2014-05-15

    Purpose: This study presents an adaptive error detection algorithm (AEDA) for real-timein vivo point dosimetry during high dose rate (HDR) or pulsed dose rate (PDR) brachytherapy (BT) where the error identification, in contrast to existing approaches, does not depend on an a priori reconstruction of the dosimeter position. Instead, the treatment is judged based on dose rate comparisons between measurements and calculations of the most viable dosimeter position provided by the AEDA in a data driven approach. As a result, the AEDA compensates for false error cases related to systematic effects of the dosimeter position reconstruction. Given its nearly exclusive dependence on stable dosimeter positioning, the AEDA allows for a substantially simplified and time efficient real-time in vivo BT dosimetry implementation. Methods: In the event of a measured potential treatment error, the AEDA proposes the most viable dosimeter position out of alternatives to the original reconstruction by means of a data driven matching procedure between dose rate distributions. If measured dose rates do not differ significantly from the most viable alternative, the initial error indication may be attributed to a mispositioned or misreconstructed dosimeter (false error). However, if the error declaration persists, no viable dosimeter position can be found to explain the error, hence the discrepancy is more likely to originate from a misplaced or misreconstructed source applicator or from erroneously connected source guide tubes (true error). Results: The AEDA applied on twoin vivo dosimetry implementations for pulsed dose rate BT demonstrated that the AEDA correctly described effects responsible for initial error indications. The AEDA was able to correctly identify the major part of all permutations of simulated guide tube swap errors and simulated shifts of individual needles from the original reconstruction. Unidentified errors corresponded to scenarios where the dosimeter position was

  2. Cocaine Dependent Individuals and Gamblers Present Different Associative Learning Anomalies in Feedback-Driven Decision Making: A Behavioral and ERP Study

    PubMed Central

    Torres, Ana; Catena, Andrés; Cándido, Antonio; Maldonado, Antonio; Megías, Alberto; Perales, José C.

    2013-01-01

    Several recent studies have demonstrated that addicts behave less flexibly than healthy controls in the probabilistic reversal learning task (PRLT), in which participants must gradually learn to choose between a probably rewarded option and an improbably rewarded one, on the basis of corrective feedback, and in which preferences must adjust to abrupt reward contingency changes (reversals). In the present study, pathological gamblers (PG) and cocaine dependent individuals (CDI) showed different learning curves in the PRLT. PG also showed a reduced electroencephalographic response to feedback (Feedback-Related Negativity, FRN) when compared to controls. CDI’s FRN was not significantly different either from PG or from healthy controls. Additionally, according to Standardized Low-Resolution Electromagnetic Tomography analysis, cortical activity in regions of interest (previously selected by virtue of their involvement in FRN generation in controls) strongly differed between CDI and PG. However, the nature of such anomalies varied within-groups across individuals. Cocaine use severity had a strong deleterious impact on the learning asymptote, whereas gambling intensity significantly increased reversal cost. These two effects have remained confounded in most previous studies, which can be hiding important associative learning differences between different populations of addicts. PMID:23516173

  3. Adaptive Allocation of Decision Making Responsibility Between Human and Computer in Multi-Task Situations. Ph.D. Thesis

    NASA Technical Reports Server (NTRS)

    Chu, Y. Y.

    1978-01-01

    A unified formulation of computer-aided, multi-task, decision making is presented. Strategy for the allocation of decision making responsibility between human and computer is developed. The plans of a flight management systems are studied. A model based on the queueing theory was implemented.

  4. Application of stakeholder-based and modelling approaches for supporting robust adaptation decision making under future climatic uncertainty and changing urban-agricultural water demand

    NASA Astrophysics Data System (ADS)

    Bhave, Ajay; Dessai, Suraje; Conway, Declan; Stainforth, David

    2016-04-01

    Deep uncertainty in future climate change and socio-economic conditions necessitates the use of assess-risk-of-policy approaches over predict-then-act approaches for adaptation decision making. Robust Decision Making (RDM) approaches embody this principle and help evaluate the ability of adaptation options to satisfy stakeholder preferences under wide-ranging future conditions. This study involves the simultaneous application of two RDM approaches; qualitative and quantitative, in the Cauvery River Basin in Karnataka (population ~23 million), India. The study aims to (a) determine robust water resources adaptation options for the 2030s and 2050s and (b) compare the usefulness of a qualitative stakeholder-driven approach with a quantitative modelling approach. For developing a large set of future scenarios a combination of climate narratives and socio-economic narratives was used. Using structured expert elicitation with a group of climate experts in the Indian Summer Monsoon, climatic narratives were developed. Socio-economic narratives were developed to reflect potential future urban and agricultural water demand. In the qualitative RDM approach, a stakeholder workshop helped elicit key vulnerabilities, water resources adaptation options and performance criteria for evaluating options. During a second workshop, stakeholders discussed and evaluated adaptation options against the performance criteria for a large number of scenarios of climatic and socio-economic change in the basin. In the quantitative RDM approach, a Water Evaluation And Planning (WEAP) model was forced by precipitation and evapotranspiration data, coherent with the climatic narratives, together with water demand data based on socio-economic narratives. We find that compared to business-as-usual conditions options addressing urban water demand satisfy performance criteria across scenarios and provide co-benefits like energy savings and reduction in groundwater depletion, while options reducing

  5. Neural correlates of feedback processing in toddlers.

    PubMed

    Meyer, Marlene; Bekkering, Harold; Janssen, Denise J C; de Bruijn, Ellen R A; Hunnius, Sabine

    2014-07-01

    External feedback provides essential information for successful learning. Feedback is especially important for learning in early childhood, as toddlers strongly rely on external signals to determine the consequences of their actions. In adults, many electrophysiological studies have elucidated feedback processes using a neural marker called the feedback-related negativity (FRN). The neural generator of the FRN is assumed to be the ACC, located in medial frontal cortex. As frontal brain regions are the latest to mature during brain development, it is unclear when in early childhood a functional feedback system develops. Is feedback differentiated on a neural level in toddlers and in how far is neural feedback processing related to children's behavioral adjustment? In an EEG experiment, we addressed these questions by measuring the brain activity and behavioral performance of 2.5-year-old toddlers while they played a feedback-guided game on a touchscreen. Electrophysiological results show differential brain activity for feedback with a more negative deflection for incorrect than correct outcomes, resembling the adult FRN. This provides the first neural evidence for feedback processing in toddlers. Notably, FRN amplitudes were predictive of adaptive behavior: the stronger the differential brain activity for feedback, the better the toddlers' adaptive performance during the game. Thus, already in early childhood toddlers' feedback-guided performance directly relates to the functionality of their neural feedback processing. Implications for early feedback-based learning as well as structural and functional brain development are discussed.

  6. Effects of affective arousal on choice behavior, reward prediction errors, and feedback-related negativities in human reward-based decision making.

    PubMed

    Liu, Hong-Hsiang; Hsieh, Ming H; Hsu, Yung-Fong; Lai, Wen-Sung

    2015-01-01

    Emotional experience has a pervasive impact on choice behavior, yet the underlying mechanism remains unclear. Introducing facial-expression primes into a probabilistic learning task, we investigated how affective arousal regulates reward-related choice based on behavioral, model fitting, and feedback-related negativity (FRN) data. Sixty-six paid subjects were randomly assigned to the Neutral-Neutral (NN), Angry-Neutral (AN), and Happy-Neutral (HN) groups. A total of 960 trials were conducted. Subjects in each group were randomly exposed to half trials of the pre-determined emotional faces and another half of the neutral faces before choosing between two cards drawn from two decks with different assigned reward probabilities. Trial-by-trial data were fit with a standard reinforcement learning model using the Bayesian estimation approach. The temporal dynamics of brain activity were simultaneously recorded and analyzed using event-related potentials. Our analyses revealed that subjects in the NN group gained more reward values than those in the other two groups; they also exhibited comparatively differential estimated model-parameter values for reward prediction errors. Computing the difference wave of FRNs in reward vs. non-reward trials, we found that, compared to the NN group, subjects in the AN and HN groups had larger "General" FRNs (i.e., FRNs in no-reward trials minus FRNs in reward trials) and "Expected" FRNs (i.e., FRNs in expected reward-omission trials minus FRNs in expected reward-delivery trials), indicating an interruption in predicting reward. Further, both AN and HN groups appeared to be more sensitive to negative outcomes than the NN group. Collectively, our study suggests that affective arousal negatively regulates reward-related choice, probably through overweighting with negative feedback.

  7. Effects of affective arousal on choice behavior, reward prediction errors, and feedback-related negativities in human reward-based decision making

    PubMed Central

    Liu, Hong-Hsiang; Hsieh, Ming H.; Hsu, Yung-Fong; Lai, Wen-Sung

    2015-01-01

    Emotional experience has a pervasive impact on choice behavior, yet the underlying mechanism remains unclear. Introducing facial-expression primes into a probabilistic learning task, we investigated how affective arousal regulates reward-related choice based on behavioral, model fitting, and feedback-related negativity (FRN) data. Sixty-six paid subjects were randomly assigned to the Neutral-Neutral (NN), Angry-Neutral (AN), and Happy-Neutral (HN) groups. A total of 960 trials were conducted. Subjects in each group were randomly exposed to half trials of the pre-determined emotional faces and another half of the neutral faces before choosing between two cards drawn from two decks with different assigned reward probabilities. Trial-by-trial data were fit with a standard reinforcement learning model using the Bayesian estimation approach. The temporal dynamics of brain activity were simultaneously recorded and analyzed using event-related potentials. Our analyses revealed that subjects in the NN group gained more reward values than those in the other two groups; they also exhibited comparatively differential estimated model-parameter values for reward prediction errors. Computing the difference wave of FRNs in reward vs. non-reward trials, we found that, compared to the NN group, subjects in the AN and HN groups had larger “General” FRNs (i.e., FRNs in no-reward trials minus FRNs in reward trials) and “Expected” FRNs (i.e., FRNs in expected reward-omission trials minus FRNs in expected reward-delivery trials), indicating an interruption in predicting reward. Further, both AN and HN groups appeared to be more sensitive to negative outcomes than the NN group. Collectively, our study suggests that affective arousal negatively regulates reward-related choice, probably through overweighting with negative feedback. PMID:26042057

  8. Effectiveness of a Video-Feedback and Questioning Programme to Develop Cognitive Expertise in Sport

    PubMed Central

    García-González, Luis; Moreno, M. Perla; Moreno, Alberto; Gil, Alexander; del Villar, Fernando

    2013-01-01

    The importance within sport expertise of cognitive factors has been emphasised in many research studies. Adaptations that take place in athletes’ long-term memories are going to condition their decision-making and performance, and training programmes must be developed that improve these adaptations. In our study, we provide a tactical-cognitive training programme based on video-feedback and questioning in order to improve tactical knowledge in tennis players and verify its effect when transferred to athletes’ decision-making. 11 intermediate tennis players participated in this study (12.9±0.7 years old), distributed into two groups (experimental, n = 5; control, n = 6). Tactical knowledge was measured by problem representation and strategy planning with a verbal protocol. Decision-making was measured by a systematic observation instrument. Results confirm the effectiveness of a combination of video-feedback and questioning on cognitive expertise, developing adaptations in long-term memory that produce an improvement in the quality of tactical knowledge (content, sophistication and structure). This, in turn, is transferred to the athletes’ decision-making capacity, leading to a higher percentage of successful decisions made during game play. Finally, we emphasise the need to develop effective programmes to develop cognitive expertise and improve athletes' performance, and include it in athletes’ formative stages. PMID:24340012

  9. Collective decisions among bacterial viruses

    NASA Astrophysics Data System (ADS)

    Joh, Richard; Mileyko, Yuriy; Voit, Eberhard; Weitz, Joshua

    2010-03-01

    For many temperate bacteriophages, the decision of whether to kill hosts or enter a latent state depends on the multiplicity of infection. In this talk, I present a quantitative model of gene regulatory dynamics to describe how phages make collective decisions within host cells. Unlike most previous studies, the copy number of viral genomes is treated as a variable. In the absence of feedback loops, viral mRNA transcription is expected to be proportional to the viral copy number. However, when there are nonlinear feedback loops in viral gene regulation, our model shows that gene expression patterns are sensitive to changes in viral copy number and there can be a domain of copy number where the system becomes bistable. Hence, the viral copy number is a key control parameter determining host cell fates. This suggests that bacterial viruses can respond adaptively to changes in population dynamics, and can make alternative decisions as a bet-hedging strategy. Finally, I present a stochastic version of viral gene regulation and discuss speed-accuracy trade-offs in the context of cell fate determination by viruses.

  10. Temporal dynamics of prediction error processing during reward-based decision making.

    PubMed

    Philiastides, Marios G; Biele, Guido; Vavatzanidis, Niki; Kazzer, Philipp; Heekeren, Hauke R

    2010-10-15

    Adaptive decision making depends on the accurate representation of rewards associated with potential choices. These representations can be acquired with reinforcement learning (RL) mechanisms, which use the prediction error (PE, the difference between expected and received rewards) as a learning signal to update reward expectations. While EEG experiments have highlighted the role of feedback-related potentials during performance monitoring, important questions about the temporal sequence of feedback processing and the specific function of feedback-related potentials during reward-based decision making remain. Here, we hypothesized that feedback processing starts with a qualitative evaluation of outcome-valence, which is subsequently complemented by a quantitative representation of PE magnitude. Results of a model-based single-trial analysis of EEG data collected during a reversal learning task showed that around 220ms after feedback outcomes are initially evaluated categorically with respect to their valence (positive vs. negative). Around 300ms, and parallel to the maintained valence-evaluation, the brain also represents quantitative information about PE magnitude, thus providing the complete information needed to update reward expectations and to guide adaptive decision making. Importantly, our single-trial EEG analysis based on PEs from an RL model showed that the feedback-related potentials do not merely reflect error awareness, but rather quantitative information crucial for learning reward contingencies.

  11. Temporal dynamics of prediction error processing during reward-based decision making.

    PubMed

    Philiastides, Marios G; Biele, Guido; Vavatzanidis, Niki; Kazzer, Philipp; Heekeren, Hauke R

    2010-10-15

    Adaptive decision making depends on the accurate representation of rewards associated with potential choices. These representations can be acquired with reinforcement learning (RL) mechanisms, which use the prediction error (PE, the difference between expected and received rewards) as a learning signal to update reward expectations. While EEG experiments have highlighted the role of feedback-related potentials during performance monitoring, important questions about the temporal sequence of feedback processing and the specific function of feedback-related potentials during reward-based decision making remain. Here, we hypothesized that feedback processing starts with a qualitative evaluation of outcome-valence, which is subsequently complemented by a quantitative representation of PE magnitude. Results of a model-based single-trial analysis of EEG data collected during a reversal learning task showed that around 220ms after feedback outcomes are initially evaluated categorically with respect to their valence (positive vs. negative). Around 300ms, and parallel to the maintained valence-evaluation, the brain also represents quantitative information about PE magnitude, thus providing the complete information needed to update reward expectations and to guide adaptive decision making. Importantly, our single-trial EEG analysis based on PEs from an RL model showed that the feedback-related potentials do not merely reflect error awareness, but rather quantitative information crucial for learning reward contingencies. PMID:20510376

  12. Age-Specific Effects of Mirror-Muscle Activity on Cross-Limb Adaptations Under Mirror and Non-Mirror Visual Feedback Conditions

    PubMed Central

    Reissig, Paola; Stöckel, Tino; Garry, Michael I.; Summers, Jeffery J.; Hinder, Mark R.

    2015-01-01

    Cross-limb transfer (CLT) describes the observation of bilateral performance gains due to unilateral motor practice. Previous research has suggested that CLT may be reduced, or absent, in older adults, possibly due to age-related structural and functional brain changes. Based on research showing increases in CLT due to the provision of mirror visual feedback (MVF) during task execution in young adults, our study aimed to investigate whether MVF can facilitate CLT in older adults, who are known to be more reliant on visual feedback for accurate motor performance. Participants (N = 53) engaged in a short-term training regime (300 movements) involving a ballistic finger task using their dominant hand, while being provided with either visual feedback of their active limb, or a mirror reflection of their active limb (superimposed over the quiescent limb). Performance in both limbs was examined before, during and following the unilateral training. Furthermore, we measured corticospinal excitability (using TMS) at these time points, and assessed muscle activity bilaterally during the task via EMG; these parameters were used to investigate the mechanisms mediating and predicting CLT. Training resulted in significant bilateral performance gains that did not differ as a result of age or visual feedback (both p > 0.1). Training also elicited bilateral increases in corticospinal excitability (p < 0.05). For younger adults, CLT was significantly predicted by performance gains in the trained hand (β = 0.47), whereas for older adults it was significantly predicted by mirror activity in the untrained hand during training (β = 0.60). The present study suggests that older adults are capable of exhibiting CLT to a similar degree to younger adults. The prominent role of mirror activity in the untrained hand for CLT in older adults indicates that bilateral cortical activity during unilateral motor tasks is a compensatory mechanism. In this particular task, MVF did not facilitate the

  13. Conflict adaptation within but not across NoGo decision criteria: Event-related-potential evidence of specificity in the contextual modulation of cognitive control.

    PubMed

    Feldman, Julia L; Clark, Sheri L; Freitas, Antonio L

    2015-07-01

    From the standpoint of conflict-monitoring theory (Botvinick et al., 2001), detecting an incident of information-processing conflict should attenuate the disruptive influence of information-processing conflicts encountered subsequently, by which time cognitive-control operations will have been engaged. To examine the generality of this conflict-adaptation process across task dimensions, the present research analyzed event-related potentials in a Go/NoGo task that randomly varied the NoGo decision criterion applied across trials. Sequential analyses revealed reduced-amplitude fronto-central N2 and NoGo P3 responses on the second of two consecutive NoGo trials. Importantly, both of these conflict-adaptation effects were present only when the same NoGo decision criterion was applied across trials n and n-1. These findings support the theory that encountering information-processing conflict focuses attention on specific stimulus-response contingencies (Verguts & Notebaert, 2009) rather than engages general cognitive-control mechanisms (Freitas & Clark, 2015). Further implications for the generality of cognitive control are discussed.

  14. LandCaRe DSS--an interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies.

    PubMed

    Wenkel, Karl-Otto; Berg, Michael; Mirschel, Wilfried; Wieland, Ralf; Nendel, Claas; Köstner, Barbara

    2013-09-01

    Decision support to develop viable climate change adaptation strategies for agriculture and regional land use management encompasses a wide range of options and issues. Up to now, only a few suitable tools and methods have existed for farmers and regional stakeholders that support the process of decision-making in this field. The interactive model-based spatial information and decision support system LandCaRe DSS attempts to close the existing methodical gap. This system supports interactive spatial scenario simulations, multi-ensemble and multi-model simulations at the regional scale, as well as the complex impact assessment of potential land use adaptation strategies at the local scale. The system is connected to a local geo-database and via the internet to a climate data server. LandCaRe DSS uses a multitude of scale-specific ecological impact models, which are linked in various ways. At the local scale (farm scale), biophysical models are directly coupled with a farm economy calculator. New or alternative simulation models can easily be added, thanks to the innovative architecture and design of the DSS. Scenario simulations can be conducted with a reasonable amount of effort. The interactive LandCaRe DSS prototype also offers a variety of data analysis and visualisation tools, a help system for users and a farmer information system for climate adaptation in agriculture. This paper presents the theoretical background, the conceptual framework, and the structure and methodology behind LandCaRe DSS. Scenario studies at the regional and local scale for the two Eastern German regions of Uckermark (dry lowlands, 2600 km(2)) and Weißeritz (humid mountain area, 400 km(2)) were conducted in close cooperation with stakeholders to test the functionality of the DSS prototype. The system is gradually being transformed into a web version (http://www.landcare-dss.de) to ensure the broadest possible distribution of LandCaRe DSS to the public. The system will be continuously

  15. Coress feedback

    PubMed Central

    2012-01-01

    This issue of CORESS feedback highlights yet again the importance of checking medications before administration and of adequate handover. Documentation of important medical data including drug allergies, as failed to happen in the case described below, is vital. We are grateful to the clinicians who have provided the material for these reports. The online reporting form is on our website (www.coress.org.uk), which also includes all previous feedback reports. Published contributions will be acknowledged by a ‘Certificate of Contribution’, which may be included in the contributor’s record of continuing professional development.

  16. 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.

  17. Adapting an Evidence-Based Intervention for Homeless Women: Engaging the Community in Shared Decision-making

    PubMed Central

    Cederbaum, Julie A.; Song, Ahyoung; Hsu, Hsun-Ta; Tucker, Joan S.; Wenzel, Suzanne L.

    2014-01-01

    As interest grows in the diffusion of evidence-based interventions (EBIs), there is increasing concern about how to mitigate implementation challenges; this paper concerns adapting an EBI for homeless women. Complementing earlier focus groups with homeless women, homeless service providers (n = 32) were engaged in focus groups to assess capacity, needs, and barriers with implementation of EBIs. Deductive analyses of data led to the selection of four EBIs. Six consensus groups were then undertaken; three each with homeless women (n = 24) and homeless service providers (n = 21). The selected EBI was adapted and pretested with homeless women (n = 9) and service providers (n = 6). The structured consensus group process provided great utility and affirmed the expertise of homeless women and service providers as experts in their domain. Engaging providers in the selection process reduced the structural barriers within agencies as obstacles to diffusion. PMID:25418227

  18. Recent advances in applying decision science to managing national forests

    USGS Publications Warehouse

    Marcot, Bruce G.; Thompson, Matthew P.; Runge, Michael C.; Thompson, Frank R.; McNulty, Steven; Cleaves, David; Tomosy, Monica; Fisher, Larry A.; Andrew, Bliss

    2012-01-01

    Management of federal public forests to meet sustainability goals and multiple use regulations is an immense challenge. To succeed, we suggest use of formal decision science procedures and tools in the context of structured decision making (SDM). SDM entails four stages: problem structuring (framing the problem and defining objectives and evaluation criteria), problem analysis (defining alternatives, evaluating likely consequences, identifying key uncertainties, and analyzing tradeoffs), decision point (identifying the preferred alternative), and implementation and monitoring the preferred alternative with adaptive management feedbacks. We list a wide array of models, techniques, and tools available for each stage, and provide three case studies of their selected use in National Forest land management and project plans. Successful use of SDM involves participation by decision-makers, analysts, scientists, and stakeholders. We suggest specific areas for training and instituting SDM to foster transparency, rigor, clarity, and inclusiveness in formal decision processes regarding management of national forests.

  19. The combination of positive and negative feedback loops confers exquisite flexibility to biochemical switches

    NASA Astrophysics Data System (ADS)

    Pfeuty, Benjamin; Kaneko, Kunihiko

    2009-12-01

    A wide range of cellular processes require molecular regulatory pathways to convert a graded signal into a discrete response. One prevalent switching mechanism relies on the coexistence of two stable states (bistability) caused by positive feedback regulations. Intriguingly, positive feedback is often supplemented with negative feedback, raising the question of whether and how these two types of feedback can cooperate to control discrete cellular responses. To address this issue, we formulate a canonical model of a protein-protein interaction network and analyze the dynamics of a prototypical two-component circuit. The appropriate combination of negative and positive feedback loops can bring a bistable circuit close to the oscillatory regime. Notably, sharply activated negative feedback can give rise to a bistable regime wherein two stable fixed points coexist and may collide pairwise with two saddle points. This specific type of bistability is found to allow for separate and flexible control of switch-on and switch-off events, for example (i) to combine fast and reversible transitions, (ii) to enable transient switching responses and (iii) to display tunable noise-induced transition rates. Finally, we discuss the relevance of such bistable switching behavior, and the circuit topologies considered, to specific biological processes such as adaptive metabolic responses, stochastic fate decisions and cell-cycle transitions. Taken together, our results suggest an efficient mechanism by which positive and negative feedback loops cooperate to drive the flexible and multifaceted switching behaviors arising in biological systems.

  20. Dynamics of the interlocked positive feedback loops explaining the robust epigenetic switching in Candida albicans.

    PubMed

    Sriram, K; Soliman, Sylvain; Fages, François

    2009-05-01

    The two element mutual activation and inhibitory positive feedback loops are a common motifs that occur in many biological systems in both isolated and interlocked form, as for example, in the cell division cycle and thymus differentiation in eukaryotes. The properties of three element interlocked positive feedback loops that embeds both mutual activation and inhibition are studied in depth for their bistable properties by performing bifurcation and stochastic simulations. Codimension one and two bifurcations reveal important properties like robustness to parameter variations and adaptability under various conditions by its ability to fine tune the threshold to a wide range of values and to maintain a wide bistable regime. Furthermore, we show that in the interlocked circuit, mutual inhibition controls the decision to switch from OFF to ON state, while mutual activation enforces the decision. This view is supported through a concrete biological example Candida albicans, a human fungal pathogen that can exist in two distinctive cell types; one in the default white state and the other in an opaque form. Stochastic switching between these two forms takes place due to the epigenetic alternation induced by the transcriptional regulators in the circuit, albeit without any rearrangement of the nuclear chromosomes. The transcriptional regulators constitute interlocked mutual activation and inhibition feedback circuits that provide adaptable threshold and wide bistable regime. These positive feedback loops are shown to be responsible for robust noise induced transitions without chattering, persistence of particular phenotypes for many generations and selective exhibition of one particular form of phenotype when mutated. Finally, we propose for synthetic biology constructs to use interlocked positive feedback loops instead of two element positive feedback loops because they are better controlled than isolated mutual activation and mutual inhibition feedback circuits. PMID

  1. Adaptive Thermal Therapy using Planar Ultrasound Transducers with Real-time MR Temperature Feedback: Demonstration in Gel Phantoms and Ex-vivo Tissues

    NASA Astrophysics Data System (ADS)

    Tang, Kee; Choy, Vanessa; Chopra, Rajiv; Bronskill, Michael

    2007-05-01

    MRI-guided transurethral ultrasound therapy offers a minimally invasive approach for the treatment of localized prostate cancer. The main goal of this study was to evaluate active temperature feedback on a clinical 1.5T MR imager to control conformal thermal therapy. MR thermometry was performed during heating in both thermal gel phantoms and ex-vivo tissue with a single-element transurethral heating applicator. The applicator rotation rate and power were controlled based on MRI-temperature measurements. The influence of a cooling gradient (to simulate cooling of the rectum or urethra) was also investigated in gel phantoms. The 55°C isotherm generated during heating closely matched the targeted prostate shape, with an average distance error of 0.9 mm ± 0.4 mm in turkey breasts, 1.3 mm ± 0.5 mm in gel phantoms without rectal cooling and 1.4 mm ± 0.6 mm in gel phantoms with rectal cooling. Accurate, MRI-guided, active feedback has been successfully demonstrated experimentally and has the capability to adjust for unpredictable and varying tissue properties during the treatment.

  2. How to not get stuck-negative feedback due to crowding maintains flexibility in ant foraging.

    PubMed

    Czaczkes, Tomer J

    2014-11-01

    Ant foraging is an important model system in the study of adaptive complex systems. Many ants use trail pheromones to recruit nestmates to resources. Differential recruitment depending on resource quality coupled with positive feedback allows ant colonies to make rapid and accurate collective decisions about how best to allocate their work-force. However, ant colonies can become trapped in sub-optimal foraging decisions if recruitment to a poor resource becomes too strong before a better resource is discovered. Genetic algorithms and Ant Colony Optimisation heuristics can also suffer from being trapped in such local optima. Recently, two negative feedback effects were described, in which an increase in crowding (crowding negative feedback-CNF) or trail pheromones (pheromone negative feedback-PNF) caused a decrease in subsequent pheromone deposition. Using agent based simulations with realistic parameters I test whether these negative feedback effects can prevent simulated ant colonies from becoming trapped in sub-optimal foraging decisions. Colonies are presented with two food sources of different qualities, and these qualities switch part way through the experiment. When either no negative feedback effects are implemented or only PNF is implemented colonies are completely unable to refocus their foraging effort to the high quality feeder. However, when CNF alone is implemented at a realistic level 97% of colonies successfully refocus their foraging effort. This ability to refocus colony foraging efforts is due to the strong reduction of pheromone deposition caused by CNF. This suggests that CNF is an important behaviour enabling ant colonies to maintain foraging flexibility. However, CNF comes at a slight cost to colonies when making their initial foraging decision.

  3. How to not get stuck-negative feedback due to crowding maintains flexibility in ant foraging.

    PubMed

    Czaczkes, Tomer J

    2014-11-01

    Ant foraging is an important model system in the study of adaptive complex systems. Many ants use trail pheromones to recruit nestmates to resources. Differential recruitment depending on resource quality coupled with positive feedback allows ant colonies to make rapid and accurate collective decisions about how best to allocate their work-force. However, ant colonies can become trapped in sub-optimal foraging decisions if recruitment to a poor resource becomes too strong before a better resource is discovered. Genetic algorithms and Ant Colony Optimisation heuristics can also suffer from being trapped in such local optima. Recently, two negative feedback effects were described, in which an increase in crowding (crowding negative feedback-CNF) or trail pheromones (pheromone negative feedback-PNF) caused a decrease in subsequent pheromone deposition. Using agent based simulations with realistic parameters I test whether these negative feedback effects can prevent simulated ant colonies from becoming trapped in sub-optimal foraging decisions. Colonies are presented with two food sources of different qualities, and these qualities switch part way through the experiment. When either no negative feedback effects are implemented or only PNF is implemented colonies are completely unable to refocus their foraging effort to the high quality feeder. However, when CNF alone is implemented at a realistic level 97% of colonies successfully refocus their foraging effort. This ability to refocus colony foraging efforts is due to the strong reduction of pheromone deposition caused by CNF. This suggests that CNF is an important behaviour enabling ant colonies to maintain foraging flexibility. However, CNF comes at a slight cost to colonies when making their initial foraging decision. PMID:25034339

  4. Adaptation of a Published Risk Model to Point-of-care Clinical Decision Support Tailored to Local Workflow.

    PubMed

    Sobel, Jeffrey L; Baker, Craig C; Levy, David; Cain, Carol H

    2015-01-01

    Electronic clinical decision support can bring newly published knowledge to the point of care. However, local organizational buy-in, support for team workflows, IT system ease of use and other sociotechnical factors are needed to promote adoption. We successfully implemented a multi-variate cardiac risk stratification model from another institution into ours. We recreated the model and integrated it into our workflow, accessing it from our EHR with patient-specific data and facilitating clinical documentation if the user accepts the model results. Our clinical leaders championed the change and led educational dissemination efforts. We describe the ad-hoc social and technical collaboration needed to build and deploy the tool. The tool complements a clinical initiative within a community of practice, and is correlated with appropriate use of nuclear imaging. PMID:26958255

  5. Understanding Perceptions of Climate Change, Priorities, and Decision-Making among Municipalities in Lima, Peru to Better Inform Adaptation and Mitigation Planning.

    PubMed

    Siña, Mariella; Wood, Rachel C; Saldarriaga, Enrique; Lawler, Joshua; Zunt, Joseph; Garcia, Patricia; Cárcamo, César

    2016-01-01

    Climate change poses multiple risks to the population of Lima, the largest city and capital of Peru, located on the Pacific coast in a desert ecosystem. These risks include increased water scarcity, increased heat, and the introduction and emergence of vector-borne and other climate sensitive diseases. To respond to these threats, it is necessary for the government, at every level, to adopt more mitigation and adaptation strategies. Here, focus groups were conducted with representatives from five Lima municipalities to determine priorities, perception of climate change, and decision-making processes for implementing projects within each municipality. These factors can affect the ability and desire of a community to implement climate change adaptation and mitigation strategies. The results show that climate change and other environmental factors are of relatively low priority, whereas public safety and water and sanitation services are of highest concern. Perhaps most importantly, climate change is not well understood among the municipalities. Participants had trouble distinguishing climate change from other environmental issues and did not fully understand its causes and effects. Greater understanding of what climate change is and why it is important is necessary for it to become a priority for the municipalities. Different aspects of increased climate change awareness seem to be connected to having experienced extreme weather events, whether related or not to climate change, and to higher socioeconomic status. PMID:26808087

  6. Understanding Perceptions of Climate Change, Priorities, and Decision-Making among Municipalities in Lima, Peru to Better Inform Adaptation and Mitigation Planning

    PubMed Central

    Saldarriaga, Enrique; Lawler, Joshua; Zunt, Joseph; Garcia, Patricia; Cárcamo, César

    2016-01-01

    Climate change poses multiple risks to the population of Lima, the largest city and capital of Peru, located on the Pacific coast in a desert ecosystem. These risks include increased water scarcity, increased heat, and the introduction and emergence of vector-borne and other climate sensitive diseases. To respond to these threats, it is necessary for the government, at every level, to adopt more mitigation and adaptation strategies. Here, focus groups were conducted with representatives from five Lima municipalities to determine priorities, perception of climate change, and decision-making processes for implementing projects within each municipality. These factors can affect the ability and desire of a community to implement climate change adaptation and mitigation strategies. The results show that climate change and other environmental factors are of relatively low priority, whereas public safety and water and sanitation services are of highest concern. Perhaps most importantly, climate change is not well understood among the municipalities. Participants had trouble distinguishing climate change from other environmental issues and did not fully understand its causes and effects. Greater understanding of what climate change is and why it is important is necessary for it to become a priority for the municipalities. Different aspects of increased climate change awareness seem to be connected to having experienced extreme weather events, whether related or not to climate change, and to higher socioeconomic status. PMID:26808087

  7. Understanding Perceptions of Climate Change, Priorities, and Decision-Making among Municipalities in Lima, Peru to Better Inform Adaptation and Mitigation Planning.

    PubMed

    Siña, Mariella; Wood, Rachel C; Saldarriaga, Enrique; Lawler, Joshua; Zunt, Joseph; Garcia, Patricia; Cárcamo, César

    2016-01-01

    Climate change poses multiple risks to the population of Lima, the largest city and capital of Peru, located on the Pacific coast in a desert ecosystem. These risks include increased water scarcity, increased heat, and the introduction and emergence of vector-borne and other climate sensitive diseases. To respond to these threats, it is necessary for the government, at every level, to adopt more mitigation and adaptation strategies. Here, focus groups were conducted with representatives from five Lima municipalities to determine priorities, perception of climate change, and decision-making processes for implementing projects within each municipality. These factors can affect the ability and desire of a community to implement climate change adaptation and mitigation strategies. The results show that climate change and other environmental factors are of relatively low priority, whereas public safety and water and sanitation services are of highest concern. Perhaps most importantly, climate change is not well understood among the municipalities. Participants had trouble distinguishing climate change from other environmental issues and did not fully understand its causes and effects. Greater understanding of what climate change is and why it is important is necessary for it to become a priority for the municipalities. Different aspects of increased climate change awareness seem to be connected to having experienced extreme weather events, whether related or not to climate change, and to higher socioeconomic status.

  8. Feedback control of sound

    NASA Astrophysics Data System (ADS)

    Rafaely, Boaz

    This thesis is concerned with the development an application of feedback control techniques for active sound control. Both fixed and adaptive controllers are considered. The controller design problem for active sound control is formulated as a constrained optimisation problem with an H2 performance objective, of minimising the variance of the control error, and H2 and H∞ design constraints involving control power output, disturbance enhancement, and robust stability. An Internal Model Controller with an FIR control filter is assumed. Conventional H2 design methods for feedback controllers are studied first. Although such controllers can satisfy the design constraints by employing effort terms in the quadratic cost function, they do not achieve the best possible performance, and when adapted using LMS-based algorithms, they suffer from instabilities if the plant response varies significantly. Improved H2/H∞ design methods for fixed and adaptive controllers are then developed, which achieve the best H2 performance under the design constraints, offer an improved stability when made adaptive, and in general outperform the conventional H2 controllers. The H2/H∞ design problems employ convex programming to ensure a unique solution. The Sequential Quadratic Programming methods is used for the off-line design of fixed controllers, and penalty and barrier function methods, together with frequency domain LMS-based algorithms are employed in the H2/H∞ adaptive controllers. The controllers studied and developed here were applied to three active sound control systems: a noise-reducing headset, an active headrest, and a sound radiating panel. The emphasis was put on developing control strategies that improve system performance. First, a high performance controller for the noise-reducing headset was implemented in real-time, which combines analogue and adaptive digital controllers, and can thus reject disturbances which has both broad-band and periodic components. Then

  9. What is coded into memory in the absence of outcome feedback?

    PubMed

    Henriksson, Maria P; Elwin, Ebba; Juslin, Peter

    2010-01-01

    Although people often have to learn from environments with scarce and highly selective outcome feedback, the question of how nonfeedback trials are represented in memory and affect later performance has received little attention in models of learning and decision making. In this article, the authors use the generalized context model (Nosofsky, 1986) as a vehicle to test contrasting hypotheses about the coding of nonfeedback trials. Data across 3 experiments with selective decision-contingent and selective outcome-contingent feedback provide support for the hypothesis of constructivist coding (Elwin, Juslin, Olsson, & Enkvist, 2007), according to which the outcomes on nonfeedback trials are coded with the most likely outcome, as inferred by the individual. The relation to sampling-based approaches to judgment, and the adaptive significance of constructivist coding, are discussed. (PsycINFO Database Record (c) 2009 APA, all rights reserved). PMID:20053041

  10. Robust model reference adaptive output feedback tracking for uncertain linear systems with actuator fault based on reinforced dead-zone modification.

    PubMed

    Bagherpoor, H M; Salmasi, Farzad R

    2015-07-01

    In this paper, robust model reference adaptive tracking controllers are considered for Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) linear systems containing modeling uncertainties, unknown additive disturbances and actuator fault. Two new lemmas are proposed for both SISO and MIMO, under which dead-zone modification rule is improved such that the tracking error for any reference signal tends to zero in such systems. In the conventional approach, adaption of the controller parameters is ceased inside the dead-zone region which results tracking error, while preserving the system stability. In the proposed scheme, control signal is reinforced with an additive term based on tracking error inside the dead-zone which results in full reference tracking. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed approach. Closed loop system stability and zero tracking error are proved by considering a suitable Lyapunov functions candidate. It is shown that the proposed control approach can assure that all the signals of the close loop system are bounded in faulty conditions. Finally, validity and performance of the new schemes have been illustrated through numerical simulations of SISO and MIMO systems in the presence of actuator faults, modeling uncertainty and output disturbance.

  11. An engineered approach to stem cell culture: automating the decision process for real-time adaptive subculture of stem cells.

    PubMed

    Ker, Dai Fei Elmer; Weiss, Lee E; Junkers, Silvina N; Chen, Mei; Yin, Zhaozheng; Sandbothe, Michael F; Huh, Seung-il; Eom, Sungeun; Bise, Ryoma; Osuna-Highley, Elvira; Kanade, Takeo; Campbell, Phil G

    2011-01-01

    Current cell culture practices are dependent upon human operators and remain laborious and highly subjective, resulting in large variations and inconsistent outcomes, especially when using visual assessments of cell confluency to determine the appropriate time to subculture cells. Although efforts to automate cell culture with robotic systems are underway, the majority of such systems still require human intervention to determine when to subculture. Thus, it is necessary to accurately and objectively determine the appropriate time for cell passaging. Optimal stem cell culturing that maintains cell pluripotency while maximizing cell yields will be especially important for efficient, cost-effective stem cell-based therapies. Toward this goal we developed a real-time computer vision-based system that monitors the degree of cell confluency with a precision of 0.791±0.031 and recall of 0.559±0.043. The system consists of an automated phase-contrast time-lapse microscope and a server. Multiple dishes are sequentially imaged and the data is uploaded to the server that performs computer vision processing, predicts when cells will exceed a pre-defined threshold for optimal cell confluency, and provides a Web-based interface for remote cell culture monitoring. Human operators are also notified via text messaging and e-mail 4 hours prior to reaching this threshold and immediately upon reaching this threshold. This system was successfully used to direct the expansion of a paradigm stem cell population, C2C12 cells. Computer-directed and human-directed control subcultures required 3 serial cultures to achieve the theoretical target cell yield of 50 million C2C12 cells and showed no difference for myogenic and osteogenic differentiation. This automated vision-based system has potential as a tool toward adaptive real-time control of subculturing, cell culture optimization and quality assurance/quality control, and it could be integrated with current and developing robotic cell

  12. Randomised prior feedback modulates neural signals of outcome monitoring

    PubMed Central

    Mushtaq, Faisal; Wilkie, Richard M.; Mon-Williams, Mark A.; Schaefer, Alexandre

    2016-01-01

    Substantial evidence indicates that decision outcomes are typically evaluated relative to expectations learned from relatively long sequences of previous outcomes. This mechanism is thought to play a key role in general learning and adaptation processes but relatively little is known about the determinants of outcome evaluation when the capacity to learn from series of prior events is difficult or impossible. To investigate this issue, we examined how the feedback-related negativity (FRN) is modulated by information briefly presented before outcome evaluation. The FRN is a brain potential time-locked to the delivery of decision feedback and it is widely thought to be sensitive to prior expectations. We conducted a multi-trial gambling task in which outcomes at each trial were fully randomised to minimise the capacity to learn from long sequences of prior outcomes. Event-related potentials for outcomes (Win/Loss) in the current trial (Outcomet) were separated according to the type of outcomes that occurred in the preceding two trials (Outcomet-1 and Outcomet-2). We found that FRN voltage was more positive during the processing of win feedback when it was preceded by wins at Outcomet-1 compared to win feedback preceded by losses at Outcomet-1. However, no influence of preceding outcomes was found on FRN activity relative to the processing of loss feedback. We also found no effects of Outcomet-2 on FRN amplitude relative to current feedback. Additional analyses indicated that this effect was largest for trials in which participants selected a decision different to the gamble chosen in the previous trial. These findings are inconsistent with models that solely relate the FRN to prediction error computation. Instead, our results suggest that if stable predictions about future events are weak or non-existent, then outcome processing can be determined by affective systems. More specifically, our results indicate that the FRN is likely to reflect the activity of positive

  13. Randomised prior feedback modulates neural signals of outcome monitoring.

    PubMed

    Mushtaq, Faisal; Wilkie, Richard M; Mon-Williams, Mark A; Schaefer, Alexandre

    2016-01-15

    Substantial evidence indicates that decision outcomes are typically evaluated relative to expectations learned from relatively long sequences of previous outcomes. This mechanism is thought to play a key role in general learning and adaptation processes but relatively little is known about the determinants of outcome evaluation when the capacity to learn from series of prior events is difficult or impossible. To investigate this issue, we examined how the feedback-related negativity (FRN) is modulated by information briefly presented before outcome evaluation. The FRN is a brain potential time-locked to the delivery of decision feedback and it is widely thought to be sensitive to prior expectations. We conducted a multi-trial gambling task in which outcomes at each trial were fully randomised to minimise the capacity to learn from long sequences of prior outcomes. Event-related potentials for outcomes (Win/Loss) in the current trial (Outcomet) were separated according to the type of outcomes that occurred in the preceding two trials (Outcomet-1 and Outcomet-2). We found that FRN voltage was more positive during the processing of win feedback when it was preceded by wins at Outcomet-1 compared to win feedback preceded by losses at Outcomet-1. However, no influence of preceding outcomes was found on FRN activity relative to the processing of loss feedback. We also found no effects of Outcomet-2 on FRN amplitude relative to current feedback. Additional analyses indicated that this effect was largest for trials in which participants selected a decision different to the gamble chosen in the previous trial. These findings are inconsistent with models that solely relate the FRN to prediction error computation. Instead, our results suggest that if stable predictions about future events are weak or non-existent, then outcome processing can be determined by affective systems. More specifically, our results indicate that the FRN is likely to reflect the activity of positive

  14. Feedback produces divergence from prospect theory in descriptive choice.

    PubMed

    Jessup, Ryan K; Bishara, Anthony J; Busemeyer, Jerome R

    2008-10-01

    A recent study demonstrated that individuals making experience-based choices underweight small probabilities, in contrast to the overweighting observed in a typical descriptive paradigm. We tested whether trial-by-trial feedback in a repeated descriptive paradigm would engender choices more correspondent with experiential or descriptive paradigms. The results of a repeated gambling task indicated that individuals receiving feedback underweighted small probabilities, relative to their no-feedback counterparts. These results implicate feedback as a critical component during the decision-making process, even in the presence of fully specified descriptive information. A model comparison at the individual-subject level suggested that feedback drove individuals' decision weights toward objective probability weighting.

  15. Social closeness and feedback modulate susceptibility to the framing effect

    PubMed Central

    Sip, Kamila E.; Smith, David V.; Porcelli, Anthony J.; Kar, Kohitij; Delgado, Mauricio R.

    2014-01-01

    Although, we often seek social feedback from others to help us make decisions, little is known about how social feedback affects decisions under risk, particularly from a close peer. We conducted two experiments using an established framing task to probe how decision making is modulated by social feedback valence (positive, negative) and the level of closeness with feedback provider (friend, confederate). Participants faced mathematically equivalent decisions framed as either an opportunity to keep (gain frame) or lose (loss frame) part of an initial endowment. Periodically, participants were provided with positive (e.g., “Nice!”) or negative (e.g., “Lame!”) feedback about their choices. Such feedback was provided by either a confederate (Experiment 1), or a gender-matched close friend (Experiment 2). As expected, the framing effect was observed in both experiments. Critically, an individual’s susceptibility to the framing effect was modulated by the valence of the social feedback, but only when the feedback provider was a close friend. This effect was reflected in the activation patterns of ventromedial prefrontal cortex and posterior cingulate cortex, regions involved in complex decision making. Taken together, these results highlight social closeness as an important factor in understanding the impact of social feedback on neural mechanisms of decision making. PMID:25074501

  16. Developmental and Gender Related Differences in Response Switches after Nonrepresentative Negative Feedback

    ERIC Educational Resources Information Center

    Jansen, Brenda R. J.; van Duijvenvoorde, Anna C. K.; Huizenga, Hilde M.

    2014-01-01

    In many decision making tasks negative feedback is probabilistic and, as a consequence, may be given when the decision is actually correct. This feedback can be referred to as nonrepresentative negative feedback. In the current study, we investigated developmental and gender related differences in such switching after nonrepresentative negative…

  17. Room reverberation effects in hearing aid feedback cancellation.

    PubMed

    Kates, J M

    2001-01-01

    Room reverberation can affect feedback cancellation in hearing aids, with the strength of the effects depending on the acoustical conditions. These effects were studied using a behind the ear (BTE) hearing aid mounted on a dummy head and coupled to the ear canal via an open fitting. The hearing aid impulse response was measured for the dummy head placed at eight closely spaced locations in a typical office. The feedback cancellation in the hearing aid used a set of filter coefficients that were initialized for one location within the room, and then allowed to adapt to the feedback path measured at the same or to a different location. The maximum stable gain for the hearing aid was then estimated without feedback cancellation, for the initial set of feedback cancellation filter coefficients prior to adaptation, and for the feedback cancellation filter after adaptation. A low-order ARMA model combining a fixed set of poles with an adaptive FIR filter is shown to be effective in representing the feedback path exclusive of reverberation. Increasing the adaptive filter length has only a small benefit in improving the feedback cancellation performance due to the inability of the system to model the room reverberation. The mismatch between the modeled and actual feedback paths limits the headroom increase that can be achieved when using feedback cancellation, and varies with the location within the room. PMID:11206165

  18. Collective decision making in bacterial viruses.

    PubMed

    Weitz, Joshua S; Mileyko, Yuriy; Joh, Richard I; Voit, Eberhard O

    2008-09-15

    For many bacterial viruses, the choice of whether to kill host cells or enter a latent state depends on the multiplicity of coinfection. Here, we present a mathematical theory of how bacterial viruses can make collective decisions concerning the fate of infected cells. We base our theory on mechanistic models of gene regulatory dynamics. Unlike most previous work, we treat the copy number of viral genes as variable. Increasing the viral copy number increases the rate of transcription of viral mRNAs. When viral regulation of cell fate includes nonlinear feedback loops, very small changes in transcriptional rates can lead to dramatic changes in steady-state gene expression. Hence, we prove that deterministic decisions can be reached, e.g., lysis or latency, depending on the cellular multiplicity of infection within a broad class of gene regulatory models of viral decision-making. Comparisons of a parameterized version of the model with molecular studies of the decision structure in the temperate bacteriophage lambda are consistent with our conclusions. Because the model is general, it suggests that bacterial viruses can respond adaptively to changes in population dynamics, and that features of collective decision-making in viruses are evolvable life history traits.

  19. Net-zero Building Cluster Simulations and On-line Energy Forecasting for Adaptive and Real-Time Control and Decisions

    NASA Astrophysics Data System (ADS)

    Li, Xiwang

    Buildings consume about 41.1% of primary energy and 74% of the electricity in the U.S. Moreover, it is estimated by the National Energy Technology Laboratory that more than 1/4 of the 713 GW of U.S. electricity demand in 2010 could be dispatchable if only buildings could respond to that dispatch through advanced building energy control and operation strategies and smart grid infrastructure. In this study, it is envisioned that neighboring buildings will have the tendency to form a cluster, an open cyber-physical system to exploit the economic opportunities provided by a smart grid, distributed power generation, and storage devices. Through optimized demand management, these building clusters will then reduce overall primary energy consumption and peak time electricity consumption, and be more resilient to power disruptions. Therefore, this project seeks to develop a Net-zero building cluster simulation testbed and high fidelity energy forecasting models for adaptive and real-time control and decision making strategy development that can be used in a Net-zero building cluster. The following research activities are summarized in this thesis: 1) Development of a building cluster emulator for building cluster control and operation strategy assessment. 2) Development of a novel building energy forecasting methodology using active system identification and data fusion techniques. In this methodology, a systematic approach for building energy system characteristic evaluation, system excitation and model adaptation is included. The developed methodology is compared with other literature-reported building energy forecasting methods; 3) Development of the high fidelity on-line building cluster energy forecasting models, which includes energy forecasting models for buildings, PV panels, batteries and ice tank thermal storage systems 4) Small scale real building validation study to verify the performance of the developed building energy forecasting methodology. The outcomes of

  20. Supernova Feedback in Galaxy Formation

    NASA Astrophysics Data System (ADS)

    Dubois, Y.; Teyssier, R.

    2008-06-01

    The hierarchical model of galaxy formation is known to suffer from the ``over-cooling'' problem: the high efficiency of radiative cooling results in too much baryonic matter in a condensed phase (namely, cold gas or stars) when compared to observations. A solution proposed by many authors (see Springel & Hernquist 2003; Fujita et al. 2004; Rasera & Teyssier 2005) is feedback due to supernova (SN) driven winds or active galactic nuclei. Modeling SN feedback by direct injection of thermal energy usually turns out to be inefficient in galaxy-scale simulations, due to the quasi-instantaneous radiation of the SN energy. To avoid this effect, we have developed a new method to incorporate SN feedback in cosmological simulations: using temporary test particles, we reproduce explicitly a local Sedov blast wave solution in the gas distribution. We have performed several self-consistent runs of isolated Navarro, Frenk, & White (1996, hereafter NFW) halos with radiative cooling, star formation, SN feedback and metal enrichment using the adaptive mesh refinement code RAMSES (Teyssier 2002). We have explored the influence of SN feedback on the formation and the evolution of galaxies with different masses. We have studied the efficiency of the resulting galactic winds, as a function of the mass of the parent halo.

  1. Bayesian integrated testing strategy (ITS) for skin sensitization potency assessment: a decision support system for quantitative weight of evidence and adaptive testing strategy.

    PubMed

    Jaworska, Joanna S; Natsch, Andreas; Ryan, Cindy; Strickland, Judy; Ashikaga, Takao; Miyazawa, Masaaki

    2015-12-01

    The presented Bayesian network Integrated Testing Strategy (ITS-3) for skin sensitization potency assessment is a decision support system for a risk assessor that provides quantitative weight of evidence, leading to a mechanistically interpretable potency hypothesis, and formulates adaptive testing strategy for a chemical. The system was constructed with an aim to improve precision and accuracy for predicting LLNA potency beyond ITS-2 (Jaworska et al., J Appl Toxicol 33(11):1353-1364, 2013) by improving representation of chemistry and biology. Among novel elements are corrections for bioavailability both in vivo and in vitro as well as consideration of the individual assays' applicability domains in the prediction process. In ITS-3 structure, three validated alternative assays, DPRA, KeratinoSens and h-CLAT, represent first three key events of the adverse outcome pathway for skin sensitization. The skin sensitization potency prediction is provided as a probability distribution over four potency classes. The probability distribution is converted to Bayes factors to: 1) remove prediction bias introduced by the training set potency distribution and 2) express uncertainty in a quantitative manner, allowing transparent and consistent criteria to accept a prediction. The novel ITS-3 database includes 207 chemicals with a full set of in vivo and in vitro data. The accuracy for predicting LLNA outcomes on the external test set (n = 60) was as follows: hazard (two classes)-100 %, GHS potency classification (three classes)-96 %, potency (four classes)-89 %. This work demonstrates that skin sensitization potency prediction based on data from three key events, and often less, is possible, reliable over broad chemical classes and ready for practical applications.

  2. Critical appraisal of assumptions in chains of model calculations used to project local climate impacts for adaptation decision support—the case of Baakse Beek

    NASA Astrophysics Data System (ADS)

    van der Sluijs, Jeroen P.; Arjan Wardekker, J.

    2015-04-01

    In order to enable anticipation and proactive adaptation, local decision makers increasingly seek detailed foresight about regional and local impacts of climate change. To this end, the Netherlands Models and Data-Centre implemented a pilot chain of sequentially linked models to project local climate impacts on hydrology, agriculture and nature under different national climate scenarios for a small region in the east of the Netherlands named Baakse Beek. The chain of models sequentially linked in that pilot includes a (future) weather generator and models of respectively subsurface hydrogeology, ground water stocks and flows, soil chemistry, vegetation development, crop yield and nature quality. These models typically have mismatching time step sizes and grid cell sizes. The linking of these models unavoidably involves the making of model assumptions that can hardly be validated, such as those needed to bridge the mismatches in spatial and temporal scales. Here we present and apply a method for the systematic critical appraisal of model assumptions that seeks to identify and characterize the weakest assumptions in a model chain. The critical appraisal of assumptions presented in this paper has been carried out ex-post. For the case of the climate impact model chain for Baakse Beek, the three most problematic assumptions were found to be: land use and land management kept constant over time; model linking of (daily) ground water model output to the (yearly) vegetation model around the root zone; and aggregation of daily output of the soil hydrology model into yearly input of a so called ‘mineralization reduction factor’ (calculated from annual average soil pH and daily soil hydrology) in the soil chemistry model. Overall, the method for critical appraisal of model assumptions presented and tested in this paper yields a rich qualitative insight in model uncertainty and model quality. It promotes reflectivity and learning in the modelling community, and leads to

  3. Bayesian integrated testing strategy (ITS) for skin sensitization potency assessment: a decision support system for quantitative weight of evidence and adaptive testing strategy.

    PubMed

    Jaworska, Joanna S; Natsch, Andreas; Ryan, Cindy; Strickland, Judy; Ashikaga, Takao; Miyazawa, Masaaki

    2015-12-01

    The presented Bayesian network Integrated Testing Strategy (ITS-3) for skin sensitization potency assessment is a decision support system for a risk assessor that provides quantitative weight of evidence, leading to a mechanistically interpretable potency hypothesis, and formulates adaptive testing strategy for a chemical. The system was constructed with an aim to improve precision and accuracy for predicting LLNA potency beyond ITS-2 (Jaworska et al., J Appl Toxicol 33(11):1353-1364, 2013) by improving representation of chemistry and biology. Among novel elements are corrections for bioavailability both in vivo and in vitro as well as consideration of the individual assays' applicability domains in the prediction process. In ITS-3 structure, three validated alternative assays, DPRA, KeratinoSens and h-CLAT, represent first three key events of the adverse outcome pathway for skin sensitization. The skin sensitization potency prediction is provided as a probability distribution over four potency classes. The probability distribution is converted to Bayes factors to: 1) remove prediction bias introduced by the training set potency distribution and 2) express uncertainty in a quantitative manner, allowing transparent and consistent criteria to accept a prediction. The novel ITS-3 database includes 207 chemicals with a full set of in vivo and in vitro data. The accuracy for predicting LLNA outcomes on the external test set (n = 60) was as follows: hazard (two classes)-100 %, GHS potency classification (three classes)-96 %, potency (four classes)-89 %. This work demonstrates that skin sensitization potency prediction based on data from three key events, and often less, is possible, reliable over broad chemical classes and ready for practical applications. PMID:26612363

  4. Feedback on flood risk management

    NASA Astrophysics Data System (ADS)

    Moreau, K.; Roumagnac, A.

    2009-09-01

    For several years, as floods were increasing in South of France, local communities felt deprive to assume their mission of protection and information of citizens, and were looking for assistance in flood management. In term of flood disaster, the fact is that physical protection is necessary but inevitably limited. Tools and structures of assistance to anticipation remain slightly developed. To manage repeated crisis, local authorities need to be able to base their policy against flood on prevention, warnings, post-crisis analysis and feedback from former experience. In this objective, after 3 years of test and improvement since 2003, the initiative Predict-Services was developed in South of France: it aims at helping communities and companies to face repeated flood crisis. The principle is to prepare emergency plans, to organize crisis management and reduce risks; to help and assist communities and companies during crisis to activate and adapt their emergency plans with enough of anticipation; and to analyse floods effects and improve emergency plans afterwards. With the help of Meteo France datas and experts, Predict services helps local communities and companies in decision making for flood management. In order to reduce risks, and to keep the benefits of such an initiative, local communities and companies have to maintain the awareness of risk of the citizens and employees. They also have to maintain their safety plans to keep them constantly operational. This is a part of the message relayed. Companies, Local communities, local government authorities and basin stakeholders are the decision makers. Companies and local communities have to involve themselves in the elaboration of safety plans. They are also completely involved in their activation that is their own responsability. This applies to other local government authorities, like districts one's and basin stakeholders, which participle in the financing community safety plans and adminitrative district which

  5. Can corrective feedback improve recognition memory?

    PubMed

    Kantner, Justin; Lindsay, D Stephen

    2010-06-01

    An understanding of the effects of corrective feedback on recognition memory can inform both recognition theory and memory training programs, but few published studies have investigated the issue. Although the evidence to date suggests that feedback does not improve recognition accuracy, few studies have directly examined its effect on sensitivity, and fewer have created conditions that facilitate a feedback advantage by encouraging controlled processing at test. In Experiment 1, null effects of feedback were observed following both deep and shallow encoding of categorized study lists. In Experiment 2, feedback robustly influenced response bias by allowing participants to discern highly uneven base rates of old and new items, but sensitivity remained unaffected. In Experiment 3, a false-memory procedure, feedback failed to attenuate false recognition of critical lures. In Experiment 4, participants were unable to use feedback to learn a simple category rule separating old items from new items, despite the fact that feedback was of substantial benefit in a nearly identical categorization task. The recognition system, despite a documented ability to utilize controlled strategic or inferential decision-making processes, appears largely impenetrable to a benefit of corrective feedback.

  6. Polya’s bees: A model of decentralized decision-making

    PubMed Central

    Golman, Russell; Hagmann, David; Miller, John H.

    2015-01-01

    How do social systems make decisions with no single individual in control? We observe that a variety of natural systems, including colonies of ants and bees and perhaps even neurons in the human brain, make decentralized decisions using common processes involving information search with positive feedback and consensus choice through quorum sensing. We model this process with an urn scheme that runs until hitting a threshold, and we characterize an inherent tradeoff between the speed and the accuracy of a decision. The proposed common mechanism provides a robust and effective means by which a decentralized system can navigate the speed-accuracy tradeoff and make reasonably good, quick decisions in a variety of environments. Additionally, consensus choice exhibits systemic risk aversion even while individuals are idiosyncratically risk-neutral. This too is adaptive. The model illustrates how natural systems make decentralized decisions, illuminating a mechanism that engineers of social and artificial systems could imitate. PMID:26601255

  7. Student Engagement with Feedback

    ERIC Educational Resources Information Center

    Scott, Jon; Shields, Cathy; Gardner, James; Hancock, Alysoun; Nutt, Alex

    2011-01-01

    This report considers Biological Sciences students' perceptions of feedback, compared with those of the University as a whole, this includes what forms of feedback were considered most useful and how feedback used. Compared with data from previous studies, Biological Sciences students gave much greater recognition to oral feedback, placing it on a…

  8. Research of personal decision process using event-related potentials

    NASA Astrophysics Data System (ADS)

    Li, Xiaofeng

    2011-10-01

    To gain insights into the neural basis of such adaptive decision-making processes, we investigated the nature of learning process in humans playing a competitive game with binary choices, using a matching pennies game. As in reinforcement learning, the subject's choice during a competitive game was biased by its choice and reward history, as well as by the strategies of its opponent. Analyses of ERP data focused on the feedback-related negativity (FRN), we found that the magnitude of ERPs after losing to the computer opponent predicted whether subjects would change decision behavior on the subsequent trial. These findings provide novel evidence that humans engage a reinforcement learning process to adjust representations of competing decision options.

  9. Learning from delayed feedback: neural responses in temporal credit assignment

    PubMed Central

    Walsh, Matthew M.; Anderson, John R.

    2011-01-01

    When feedback follows a sequence of decisions, relationships between actions and outcomes can be difficult to learn. We used event-related potentials (ERPs) to understand how people overcome this temporal credit assignment problem. Participants performed a sequential decision task that required two decisions on each trial. The first decision led to an intermediate state that was predictive of the trial outcome, and the second decision was followed by positive or negative trial feedback. The feedback-related negativity (fERN), a component thought to reflect reward prediction error, followed negative feedback and negative intermediate states. This suggests that participants evaluated intermediate states in terms of expected future reward, and that these evaluations supported learning of earlier actions within sequences. We examine the predictions of several temporal-difference models to determine whether the behavioral and ERP results reflected a reinforcement-learning process. PMID:21416212

  10. Terminal feedback outperforms concurrent visual, auditory, and haptic feedback in learning a complex rowing-type task.

    PubMed

    Sigrist, Roland; Rauter, Georg; Riener, Robert; Wolf, Peter

    2013-01-01

    Augmented feedback, provided by coaches or displays, is a well-established strategy to accelerate motor learning. Frequent terminal feedback and concurrent feedback have been shown to be detrimental for simple motor task learning but supportive for complex motor task learning. However, conclusions on optimal feedback strategies have been mainly drawn from studies on artificial laboratory tasks with visual feedback only. Therefore, the authors compared the effectiveness of learning a complex, 3-dimensional rowing-type task with either concurrent visual, auditory, or haptic feedback to self-controlled terminal visual feedback. Results revealed that terminal visual feedback was most effective because it emphasized the internalization of task-relevant aspects. In contrast, concurrent feedback fostered the correction of task-irrelevant errors, which hindered learning. The concurrent visual and haptic feedback group performed much better during training with the feedback than in nonfeedback trials. Auditory feedback based on sonification of the movement error was not practical for training the 3-dimensional movement for most participants. Concurrent multimodal feedback in combination with terminal feedback may be most effective, especially if the feedback strategy is adapted to individual preferences and skill level.

  11. Neural Correlates of Sequence Learning with Stochastic Feedback

    ERIC Educational Resources Information Center

    Averbeck, Bruno B.; Kilner, James; Frith, Christopher D.

    2011-01-01

    Although much is known about decision making under uncertainty when only a single step is required in the decision process, less is known about sequential decision making. We carried out a stochastic sequence learning task in which subjects had to use noisy feedback to learn sequences of button presses. We compared flat and hierarchical behavioral…

  12. Investigating the Relationship between Quality, Format and Delivery of Feedback for Written Assignments in Higher Education

    ERIC Educational Resources Information Center

    Sopina, Elizaveta; McNeill, Rob

    2015-01-01

    Feedback can have a great impact on student learning. However, in order for it to be effective, feedback needs to be of high quality. Electronic marking has been one of the latest adaptations of technology in teaching and offers a new format of delivering feedback. There is little research investigating the impact the format of feedback has on…

  13. Prediction feedback in intelligent traffic systems

    NASA Astrophysics Data System (ADS)

    Dong, Chuan-Fei; Ma, Xu; Wang, Guan-Wen; Sun, Xiao-Yan; Wang, Bing-Hong

    2009-11-01

    The optimal information feedback has a significant effect on many socioeconomic systems like stock market and traffic systems aiming to make full use of resources. In this paper, we studied dynamics of traffic flow with real-time information provided and the influence of a feedback strategy named prediction feedback strategy is introduced, based on a two-route scenario in which dynamic information can be generated and displayed on the board to guide road users to make a choice. Our model incorporates the effects of adaptability into the cellular automaton models of traffic flow and simulation results adopting this optimal information feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other three information feedback strategies, i.e., vehicle number and flux.

  14. Feedback on Feedback--Does It Work?

    ERIC Educational Resources Information Center

    Speicher, Oranna; Stollhans, Sascha

    2015-01-01

    It is well documented that providing assessment feedback through the medium of screencasts is favourably received by students and encourages deeper engagement with the feedback given by the language teacher (inter alia Abdous & Yoshimura, 2010; Brick & Holmes, 2008; Cann, 2007; Stannard, 2007). In this short paper we will report the…

  15. Adaptive management of urban watersheds

    NASA Astrophysics Data System (ADS)

    Garmestani, A.; Shuster, W.; Green, O. O.

    2013-12-01

    Consent decree settlements for violations of the Clean Water Act (1972) increasingly include provisions for redress of combined sewer overflow activity through hybrid approaches that incorporate the best of both gray (e.g., storage tunnels) and green infrastructure (e.g., rain gardens). Adaptive management is an environmental management strategy that uses an iterative process of decision-making to improve environmental management via system monitoring. A central tenet of adaptive management is that management involves a learning process that can help regulated communities achieve environmental quality objectives. We are using an adaptive management approach to guide a green infrastructure retrofit of a neighborhood in the Slavic Village Development Corporation area (Cleveland, Ohio). We are in the process of gathering hydrologic and ecosystem services data and will use this data as a basis for collaboration with area citizens on a plan to use green infrastructure to contain stormflows. Monitoring data provides researchers with feedback on the impact of green infrastructure implementation and suggest where improvements can be made.

  16. A SCORING SYSTEM TO IMPROVE DECISION MAKING AND OUTCOMES IN THE ADAPTATION OF RECENTLY CAPTURED WHITE RHINOCEROSES (CERATOTHERIUM SIMUM) TO CAPTIVITY.

    PubMed

    Miller, Michele; Kruger, Milandie; Kruger, Marius; Olea-Popelka, Francisco; Buss, Peter

    2016-04-01

    Ninety-four subadult and adult white rhinoceroses (Ceratotherium simum) were captured between February and October, 2009-11, in Kruger National Park and placed in holding bomas prior to translocation to other locations within South Africa. A simple three-category system was developed based on appetite, fecal consistency/volume, and behavior to assess adaptation to bomas. Individual animal and group daily median scores were used to determine trends and when rhinoceroses had successfully adapted to the boma. Seventeen rhinoceroses did not adapt to boma confinement, and 16 were released (1 mortality). No differences in boma scores were observed between rhinoceroses that adapted and those that did not, until day 8, when the first significant differences were observed (adapted score=13 versus nonadapted score=10). The time to reach a boma score determined as successful adaptation (median 19 d) matched subjective observations, which was approximately 3 wk for most rhinoceroses. Unsuccessful adaptation was indicated by an individual boma score of less than 15, typically during the first 2 wk, or a declining trend in scores within the first 7-14 d. This scoring system can be used for most locations and could also be easily adapted to other areas in which rhinoceroses are held in captivity. This tool also provides important information for assessing welfare in newly captured rhinoceroses.

  17. A SCORING SYSTEM TO IMPROVE DECISION MAKING AND OUTCOMES IN THE ADAPTATION OF RECENTLY CAPTURED WHITE RHINOCEROSES (CERATOTHERIUM SIMUM) TO CAPTIVITY.

    PubMed

    Miller, Michele; Kruger, Milandie; Kruger, Marius; Olea-Popelka, Francisco; Buss, Peter

    2016-04-01

    Ninety-four subadult and adult white rhinoceroses (Ceratotherium simum) were captured between February and October, 2009-11, in Kruger National Park and placed in holding bomas prior to translocation to other locations within South Africa. A simple three-category system was developed based on appetite, fecal consistency/volume, and behavior to assess adaptation to bomas. Individual animal and group daily median scores were used to determine trends and when rhinoceroses had successfully adapted to the boma. Seventeen rhinoceroses did not adapt to boma confinement, and 16 were released (1 mortality). No differences in boma scores were observed between rhinoceroses that adapted and those that did not, until day 8, when the first significant differences were observed (adapted score=13 versus nonadapted score=10). The time to reach a boma score determined as successful adaptation (median 19 d) matched subjective observations, which was approximately 3 wk for most rhinoceroses. Unsuccessful adaptation was indicated by an individual boma score of less than 15, typically during the first 2 wk, or a declining trend in scores within the first 7-14 d. This scoring system can be used for most locations and could also be easily adapted to other areas in which rhinoceroses are held in captivity. This tool also provides important information for assessing welfare in newly captured rhinoceroses. PMID:26845302

  18. Feedback on flood risk management

    NASA Astrophysics Data System (ADS)

    Moreau, K.; Roumagnac, A.

    2009-09-01

    For several years, as floods were increasing in South of France, local communities felt deprive to assume their mission of protection and information of citizens, and were looking for assistance in flood management. In term of flood disaster, the fact is that physical protection is necessary but inevitably limited. Tools and structures of assistance to anticipation remain slightly developed. To manage repeated crisis, local authorities need to be able to base their policy against flood on prevention, warnings, post-crisis analysis and feedback from former experience. In this objective, after 3 years of test and improvement since 2003, the initiative Predict-Services was developped in South of France: it aims at helping communities and companies to face repeated flood crisis. The principle is to prepare emergency plans, to organize crisis management and reduce risks; to help and assist communities and companies during crisis to activate and adapt their emergency plans with enough of anticipation; and to analyse floods effects and improve emergency plans afterwards. In order to reduce risks, and to keep the benefits of such an initiative, local communities and companies have to maintain the awareness of risk of the citizens and employees. They also have to maintain their safety plans to keep them constantly operational. This is a part of the message relayed. Companies, Local communities, local government authorities and basin stakeholders are the decision makers. Companies and local communities have to involve themselves in the elaboration of safety plans. They are also completely involved in their activation that is their own responsability. This applies to other local government authorities, like districts one's and basin stakeholders, which participle in the financing community safety plans and adminitrative district which are responsible of the transmission of meteorological alert and of rescue actions. In the crossing of the géo-information stemming from the

  19. Haptic feedback for multilayer cutting.

    PubMed

    Rianto, Sugeng; Li, Ling; Hartley, Bruce

    2008-01-01

    An approach in effectively estimating the force feedback for a tactile haptic based on multi-proxy rendering for 3D surface cuttings for a virtual surgery simulation is described in this paper. The force-models representing haptic force-feedback are approximated using D'Alembert's principle in the mechanic case of spring-damper-stiffness interaction of the surfaces. We also propose a combination between mesh refinement and adaptive re-meshing to create a progressive cutting over the layering surfaces. Experimental results prove that the physical interaction to create cutting paths over the multilayer surfaces can be deliver smoothly with haptic in real time with 3D visual stereo on a PC.

  20. Diversity in School Performance Feedback Systems

    ERIC Educational Resources Information Center

    Verhaeghe, Goedele; Schildkamp, Kim; Luyten, Hans; Valcke, Martin

    2015-01-01

    As data-based decision making is receiving increased attention in education, more and more school performance feedback systems (SPFSs) are being developed and used worldwide. These systems provide schools with data on their functioning. However, little research is available on the characteristics of the different SPFSs. Therefore, this study…

  1. Chromaticity Feedback at RHIC

    SciTech Connect

    Marusic, A.; Minty, M.; Tepikian, S.

    2010-05-23

    Chromaticity feedback during the ramp to high beam energies has been demonstrated in the Relativistic Heavy Ion Collider (RHIC). In this report we review the feedback design and measurement technique. Commissioning experiences including interaction with existing tune and coupling feedback are presented together with supporting experimental data.

  2. The Mythology of Feedback

    ERIC Educational Resources Information Center

    Adcroft, Andy

    2011-01-01

    Much of the general education and discipline-specific literature on feedback suggests that it is a central and important element of student learning. This paper examines feedback from a social process perspective and suggests that feedback is best understood through an analysis of the interactions between academics and students. The paper argues…

  3. Preventing Feedback Fizzle

    ERIC Educational Resources Information Center

    Brookhart, Susan M.

    2012-01-01

    Feedback is certainly about saying or writing helpful, learning-focused comments. But that is only part of it. What happens beforehand? What happens afterward? Feedback that is helpful and learning-focused fits into a context. Before a teacher gives feedback, students need to know the learning target so they have a purpose for using the feedback…

  4. Developing Sustainable Feedback Practices

    ERIC Educational Resources Information Center

    Carless, David; Salter, Diane; Yang, Min; Lam, Joy

    2011-01-01

    Feedback is central to the development of student learning, but within the constraints of modularized learning in higher education it is increasingly difficult to handle effectively. This article makes a case for sustainable feedback as a contribution to the reconceptualization of feedback processes. The data derive from the Student Assessment and…

  5. Internal Representations of Temporal Statistics and Feedback Calibrate Motor-Sensory Interval Timing

    PubMed Central

    Acerbi, Luigi; Wolpert, Daniel M.; Vijayakumar, Sethu

    2012-01-01

    Humans have been shown to adapt to the temporal statistics of timing tasks so as to optimize the accuracy of their responses, in agreement with the predictions of Bayesian integration. This suggests that they build an internal representation of both the experimentally imposed distribution of time intervals (the prior) and of the error (the loss function). The responses of a Bayesian ideal observer depend crucially on these internal representations, which have only been previously studied for simple distributions. To study the nature of these representations we asked subjects to reproduce time intervals drawn from underlying temporal distributions of varying complexity, from uniform to highly skewed or bimodal while also varying the error mapping that determined the performance feedback. Interval reproduction times were affected by both the distribution and feedback, in good agreement with a performance-optimizing Bayesian observer and actor model. Bayesian model comparison highlighted that subjects were integrating the provided feedback and represented the experimental distribution with a smoothed approximation. A nonparametric reconstruction of the subjective priors from the data shows that they are generally in agreement with the true distributions up to third-order moments, but with systematically heavier tails. In particular, higher-order statistical features (kurtosis, multimodality) seem much harder to acquire. Our findings suggest that humans have only minor constraints on learning lower-order statistical properties of unimodal (including peaked and skewed) distributions of time intervals under the guidance of corrective feedback, and that their behavior is well explained by Bayesian decision theory. PMID:23209386

  6. Feedback Practices: Faculty Perception on the Influence of Course Design on Feedback Delivery in Higher Education Online Classrooms

    ERIC Educational Resources Information Center

    Hinze, Laurie E.

    2013-01-01

    As the online education environment continues to grow and evolve, a greater understanding of faculty perception of the influence of course design features on providing feedback will inform course design decisions and suggest future improvements in the design and facilitation of online courses. This dissertation explored faculty feedback practices…

  7. Neurophysiology of performance monitoring and adaptive behavior.

    PubMed

    Ullsperger, Markus; Danielmeier, Claudia; Jocham, Gerhard

    2014-01-01

    Successful goal-directed behavior requires not only correct action selection, planning, and execution but also the ability to flexibly adapt behavior when performance problems occur or the environment changes. A prerequisite for determining the necessity, type, and magnitude of adjustments is to continuously monitor the course and outcome of one's actions. Feedback-control loops correcting deviations from intended states constitute a basic functional principle of adaptation at all levels of the nervous system. Here, we review the neurophysiology of evaluating action course and outcome with respect to their valence, i.e., reward and punishment, and initiating short- and long-term adaptations, learning, and decisions. Based on studies in humans and other mammals, we outline the physiological principles of performance monitoring and subsequent cognitive, motivational, autonomic, and behavioral adaptation and link them to the underlying neuroanatomy, neurochemistry, psychological theories, and computational models. We provide an overview of invasive and noninvasive systemic measures, such as electrophysiological, neuroimaging, and lesion data. We describe how a wide network of brain areas encompassing frontal cortices, basal ganglia, thalamus, and monoaminergic brain stem nuclei detects and evaluates deviations of actual from predicted states indicating changed action costs or outcomes. This information is used to learn and update stimulus and action values, guide action selection, and recruit adaptive mechanisms that compensate errors and optimize goal achievement.

  8. Biased feedback in brain-computer interfaces

    PubMed Central

    2010-01-01

    Even though feedback is considered to play an important role in learning how to operate a brain-computer interface (BCI), to date no significant influence of feedback design on BCI-performance has been reported in literature. In this work, we adapt a standard motor-imagery BCI-paradigm to study how BCI-performance is affected by biasing the belief subjects have on their level of control over the BCI system. Our findings indicate that subjects already capable of operating a BCI are impeded by inaccurate feedback, while subjects normally performing on or close to chance level may actually benefit from an incorrect belief on their performance level. Our results imply that optimal feedback design in BCIs should take into account a subject's current skill level. PMID:20659350

  9. The Positive Supervisor: Using Feedback as a Tool.

    ERIC Educational Resources Information Center

    Reyes, Donald J.

    1984-01-01

    Argues that systematic positive feedback techniques such as those currently used in industry can and should be adapted as a management technique in schools--between administrators and teachers and between teachers and students as well. (TE)

  10. Online participation in climate change adaptation: A case study of agricultural adaptation measures in Northern Italy.

    PubMed

    Bojovic, Dragana; Bonzanigo, Laura; Giupponi, Carlo; Maziotis, Alexandros

    2015-07-01

    The new EU strategy on adaptation to climate change suggests flexible and participatory approaches. Face-to-face contact, although it involves time-consuming procedures with a limited audience, has often been considered the most effective participatory approach. In recent years, however, there has been an increase in the visibility of different citizens' initiatives in the online world, which strengthens the possibility of greater citizen agency. This paper investigates whether the Internet can ensure efficient public participation with meaningful engagement in climate change adaptation. In elucidating issues regarding climate change adaptation, we developed an eParticipation framework to explore adaptation capacity of agriculture to climate change in Northern Italy. Farmers were mobilised using a pre-existing online network. First they took part in an online questionnaire for revealing their perceptions of and reactions to the impacts of ongoing changes in agriculture. We used these results to suggest a portfolio of policy measures and to set evaluation criteria. Farmers then evaluated these policy options, using a multi criteria analysis tool with a simple user-friendly interface. Our results showed that eParticipation is efficient: it supports a rapid data collection, while involving high number of participants. Moreover, we demonstrated that the digital divide is decreasingly an obstacle for using online spaces for public engagement. This research does not present eParticipation as a panacea. Rather, eParticipation was implemented with well-established participatory approaches to both validate the results and, consequently, communicate meaningful messages on local agricultural adaptation practices to regional decision-makers. Feedbacks from the regional decision-makers showed their interest in using eParticipation to improve communication with farmers in the future. We expect that, with further Internet proliferation, eParticipation may allow the inclusion of

  11. Online participation in climate change adaptation: A case study of agricultural adaptation measures in Northern Italy.

    PubMed

    Bojovic, Dragana; Bonzanigo, Laura; Giupponi, Carlo; Maziotis, Alexandros

    2015-07-01

    The new EU strategy on adaptation to climate change suggests flexible and participatory approaches. Face-to-face contact, although it involves time-consuming procedures with a limited audience, has often been considered the most effective participatory approach. In recent years, however, there has been an increase in the visibility of different citizens' initiatives in the online world, which strengthens the possibility of greater citizen agency. This paper investigates whether the Internet can ensure efficient public participation with meaningful engagement in climate change adaptation. In elucidating issues regarding climate change adaptation, we developed an eParticipation framework to explore adaptation capacity of agriculture to climate change in Northern Italy. Farmers were mobilised using a pre-existing online network. First they took part in an online questionnaire for revealing their perceptions of and reactions to the impacts of ongoing changes in agriculture. We used these results to suggest a portfolio of policy measures and to set evaluation criteria. Farmers then evaluated these policy options, using a multi criteria analysis tool with a simple user-friendly interface. Our results showed that eParticipation is efficient: it supports a rapid data collection, while involving high number of participants. Moreover, we demonstrated that the digital divide is decreasingly an obstacle for using online spaces for public engagement. This research does not present eParticipation as a panacea. Rather, eParticipation was implemented with well-established participatory approaches to both validate the results and, consequently, communicate meaningful messages on local agricultural adaptation practices to regional decision-makers. Feedbacks from the regional decision-makers showed their interest in using eParticipation to improve communication with farmers in the future. We expect that, with further Internet proliferation, eParticipation may allow the inclusion of

  12. Striatal prediction errors support dynamic control of declarative memory decisions

    PubMed Central

    Scimeca, Jason M.; Katzman, Perri L.; Badre, David

    2016-01-01

    Adaptive memory requires context-dependent control over how information is retrieved, evaluated and used to guide action, yet the signals that drive adjustments to memory decisions remain unknown. Here we show that prediction errors (PEs) coded by the striatum support control over memory decisions. Human participants completed a recognition memory test that incorporated biased feedback to influence participants' recognition criterion. Using model-based fMRI, we find that PEs—the deviation between the outcome and expected value of a memory decision—correlate with striatal activity and predict individuals' final criterion. Importantly, the striatal PEs are scaled relative to memory strength rather than the expected trial outcome. Follow-up experiments show that the learned recognition criterion transfers to free recall, and targeting biased feedback to experimentally manipulate the magnitude of PEs influences criterion consistent with PEs scaled relative to memory strength. This provides convergent evidence that declarative memory decisions can be regulated via striatally mediated reinforcement learning signals. PMID:27713407

  13. Neural cryptography with feedback.

    PubMed

    Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido

    2004-04-01

    Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.

  14. Cortical potentials evoked by confirming and disconfirming feedback following an auditory discrimination.

    NASA Technical Reports Server (NTRS)

    Squires, K. C.; Hillyard, S. A.; Lindsay, P. H.

    1973-01-01

    Vertex potentials elicited by visual feedback signals following an auditory intensity discrimination have been studied with eight subjects. Feedback signals which confirmed the prior sensory decision elicited small P3s, while disconfirming feedback elicited P3s that were larger. On the average, the latency of P3 was also found to increase with increasing disparity between the judgment and the feedback information. These effects were part of an overall dichotomy in wave shape following confirming vs disconfirming feedback. These findings are incorporated in a general model of the role of P3 in perceptual decision making.

  15. Feedback stabilization initiative

    SciTech Connect

    1997-06-01

    Much progress has been made in attaining high confinement regimes in magnetic confinement devices. These operating modes tend to be transient, however, due to the onset of MHD instabilities, and their stabilization is critical for improved performance at steady state. This report describes the Feedback Stabilization Initiative (FSI), a broad-based, multi-institutional effort to develop and implement methods for raising the achievable plasma betas through active MHD feedback stabilization. A key element in this proposed effort is the Feedback Stabilization Experiment (FSX), a medium-sized, national facility that would be specifically dedicated to demonstrating beta improvement in reactor relevant plasmas by using a variety of MHD feedback stabilization schemes.

  16. Comparing Simulations of AGN Feedback

    NASA Astrophysics Data System (ADS)

    Richardson, Mark L. A.; Scannapieco, Evan; Devriendt, Julien; Slyz, Adrianne; Thacker, Robert J.; Dubois, Yohan; Wurster, James; Silk, Joseph

    2016-07-01

    We perform adaptive mesh refinement (AMR) and smoothed particle hydrodynamics (SPH) cosmological zoom simulations of a region around a forming galaxy cluster, comparing the ability of the methods to handle successively more complex baryonic physics. In the simplest, non-radiative case, the two methods are in good agreement with each other, but the SPH simulations generate central cores with slightly lower entropies and virial shocks at slightly larger radii, consistent with what has been seen in previous studies. The inclusion of radiative cooling, star formation, and stellar feedback leads to much larger differences between the two methods. Most dramatically, at z=5, rapid cooling in the AMR case moves the accretion shock to well within the virial radius, while this shock remains near the virial radius in the SPH case, due to excess heating, coupled with poorer capturing of the shock width. On the other hand, the addition of feedback from active galactic nuclei (AGNs) to the simulations results in much better agreement between the methods. For our AGN model, both simulations display halo gas entropies of 100 keV cm2, similar decrements in the star formation rate, and a drop in the halo baryon content of roughly 30%. This is consistent with the AGN growth being self-regulated, regardless of the numerical method. However, the simulations with AGN feedback continue to differ in aspects that are not self-regulated, such that in SPH a larger volume of gas is impacted by feedback, and the cluster still has a lower entropy central core.

  17. Social closeness and feedback modulate susceptibility to the framing effect.

    PubMed

    Sip, Kamila E; Smith, David V; Porcelli, Anthony J; Kar, Kohitij; Delgado, Mauricio R

    2015-01-01

    Although we often seek social feedback (SFB) from others to help us make decisions, little is known about how SFB affects decisions under risk, particularly from a close peer. We conducted two experiments using an established framing task to probe how decision-making is modulated by SFB valence (positive, negative) and the level of closeness with feedback provider (friend, confederate). Participants faced mathematically equivalent decisions framed as either an opportunity to keep (gain frame) or lose (loss frame) part of an initial endowment. Periodically, participants were provided with positive (e.g., "Nice!") or negative (e.g., "Lame!") feedback about their choices. Such feedback was provided by either a confederate (Experiment 1) or a gender-matched close friend (Experiment 2). As expected, the framing effect was observed in both experiments. Critically, an individual's susceptibility to the framing effect was modulated by the valence of the SFB, but only when the feedback provider was a close friend. This effect was reflected in the activation patterns of ventromedial prefrontal cortex and posterior cingulate cortex, regions involved in complex decision-making. Taken together, these results highlight social closeness as an important factor in understanding the impact of SFB on neural mechanisms of decision-making.

  18. The Power of Feedback

    ERIC Educational Resources Information Center

    Hattie, John; Timperley, Helen

    2007-01-01

    Feedback is one of the most powerful influences on learning and achievement, but this impact can be either positive or negative. Its power is frequently mentioned in articles about learning and teaching, but surprisingly few recent studies have systematically investigated its meaning. This article provides a conceptual analysis of feedback and…

  19. Four perspectives on climate feedbacks

    NASA Astrophysics Data System (ADS)

    Feldl, N.; Roe, G. H.

    2013-08-01

    The spatial pattern of climate feedbacks depends on how the feedbacks are defined. We employ an idealized aquaplanet simulation with radiative kernels diagnosed for the precise model setup and characterize the meridional structure of feedbacks under four different definitions: local feedbacks, global feedbacks, nondimensional feedback factors, and relative humidity feedbacks. First, the spatial pattern of the reference response (i.e., the Planck feedback) is found to vary with definition, largely as a consequence of polar-amplified warming, which affects other high-latitude feedbacks as well. Second, locally defined feedbacks allow for decomposition of the surface temperature response as a function of feedbacks, forcing, and heat transport. Third, different insights into the dynamical and thermodynamical underpinnings of the subtropical moisture response are gained by comparing different versions of humidity feedbacks. Thus, alternative approaches to the conventional, global definition of feedbacks offer several advantages for understanding patterns of warming and, ultimately, regional climate predictability.

  20. Water Resource Adaptation Program

    EPA Science Inventory

    The Water Resource Adaptation Program (WRAP) contributes to the U.S. Environmental Protection Agency’s (U.S. EPA) efforts to provide water resource managers and decision makers with the tools needed to adapt water resources to demographic and economic development, and future clim...

  1. Feedback delays eliminate auditory-motor learning in speech production.

    PubMed

    Max, Ludo; Maffett, Derek G

    2015-03-30

    Neurologically healthy individuals use sensory feedback to alter future movements by updating internal models of the effector system and environment. For example, when visual feedback about limb movements or auditory feedback about speech movements is experimentally perturbed, the planning of subsequent movements is adjusted - i.e., sensorimotor adaptation occurs. A separate line of studies has demonstrated that experimentally delaying the sensory consequences of limb movements causes the sensory input to be attributed to external sources rather than to one's own actions. Yet similar feedback delays have remarkably little effect on visuo-motor adaptation (although the rate of learning varies, the amount of adaptation is only moderately affected with delays of 100-200ms, and adaptation still occurs even with a delay as long as 5000ms). Thus, limb motor learning remains largely intact even in conditions where error assignment favors external factors. Here, we show a fundamentally different result for sensorimotor control of speech articulation: auditory-motor adaptation to formant-shifted feedback is completely eliminated with delays of 100ms or more. Thus, for speech motor learning, real-time auditory feedback is critical. This novel finding informs theoretical models of human motor control in general and speech motor control in particular, and it has direct implications for the application of motor learning principles in the habilitation and rehabilitation of individuals with various sensorimotor speech disorders.

  2. Performance analysis of approximate Affine Projection Algorithm in acoustic feedback cancellation.

    PubMed

    Nikjoo S, Mohammad; Seyedi, Amir; Tehrani, Arash Saber

    2008-01-01

    Acoustic feedback is an annoying problem in several audio applications and especially in hearing aids. Adaptive feedback cancellation techniques have attracted recent attention and show great promise in reducing the deleterious effects of feedback. In this paper, we investigated the performance of a class of adaptive feedback cancellation algorithms viz. the approximated Affine Projection Algorithms (APA). Mixed results were obtained with the natural speech and music data collected from five different commercial hearing aids in a variety of sub-oscillatory and oscillatory feedback conditions. The performance of the approximated APA was significantly better with music stimuli than natural speech stimuli. PMID:19162642

  3. Strategies for effective feedback.

    PubMed

    Kritek, Patricia A

    2015-04-01

    Provision of regular feedback to trainees on clinical performance by supervising providers is increasingly recognized as an essential component of undergraduate and graduate health sciences education; however, many individuals have not been formally trained in this pedagogical skill. At the bedside or in the clinic, effective performance feedback can be accomplished by following four key steps. Begin by setting expectations that incorporate the trainee's personal goals and external objectives. Delineate how and when you will provide feedback to the learner. Next, directly observe the trainee's performance. This can be challenging while engaged on a busy clinical service, but a focus on discrete activities or interactions (e.g., family meeting, intravascular volume assessment using bedside ultrasound, or obtaining informed consent) is helpful. The third step is to plan and prioritize the feedback session. Feedback is most effective when given in a timely fashion and delivered in a safe environment. Limit the issues addressed because learners often disengage if confronted with too many deficiencies. Finally, when delivering feedback, begin by listening to the trainee's self-evaluation and then take a balanced approach. Describe in detail what the trainee does well and discuss opportunities for improvement with emphasis on specific, modifiable behaviors. The feedback loop is completed with a plan for follow-up reassessment. Through the use of these relatively simple practices, both the trainee and teacher can have a more productive learning experience.

  4. Feedback in distance education.

    PubMed

    Hudspeth, D

    1988-01-01

    Some tips, strategies, and techniques are presented for incorporating learner feedback into distance education courses. The most common form of learner feedback is immediate Knowledge of Response (KR). This general term can be delineated further as either Knowledge of Correct Response (KCR) or Knowledge of Incorrect Response (KIR). KCR is most useful for learning tasks that require a high level of automatic response such as vocabulary development and naming chemical structures. It also can be used for higher levels of learning. KIR occurs when the learner makes a response and knows only whether the response was correct or incorrect. If the learner was incorrect, the correct answer is not provided. Distant learners, as well as learners in a typical classroom, benefit from positive feedback, e.g., a few words written on the side of an assignment or a short note of encouragement. Personalized feedback tells students if they are performing satisfactorily and, if provided early in a course, can help reduce student attrition. If immediate feedback after an examination cannot be provided, every effort should be made to score and return the test as soon as possible before the student is expected to begin study on subsequent lessons. If this is not possible, a test review sheet could be mailed back upon receipt of the examination. Microcomputers are devices that can provide rapid and useful feedback, yet many methods that do not rely on computers can provide feedback. These include practice tests, small group exercises, and checklist response sheets. In addition to formally providing feedback after an assignment or examination, it is possible to use the principles of feedback by embedding questions and answers in text, audio, or video materials.

  5. Global Feedback Simulator

    SciTech Connect

    Carlos Serrano, Lawrence Doolittle

    2015-10-29

    GFS is a simulation engine that is used for the characterization of Accelerator performance parameters based on the machine layout, configuration and noise sources. It combines extensively tested Feedback models with a longitudinal phase space tracking simulator along with the interaction between the two via beam-based feedback using a computationally efficient simulation engine. The models include beam instrumentation, considerations on loop delays for in both the R and beam-based feedback loops, as well as the ability to inject noise (both correlated and uncorrelated) at different points of the machine including a full characterization of the electron gun performance parameters.

  6. Global Feedback Simulator

    2015-10-29

    GFS is a simulation engine that is used for the characterization of Accelerator performance parameters based on the machine layout, configuration and noise sources. It combines extensively tested Feedback models with a longitudinal phase space tracking simulator along with the interaction between the two via beam-based feedback using a computationally efficient simulation engine. The models include beam instrumentation, considerations on loop delays for in both the R and beam-based feedback loops, as well as themore » ability to inject noise (both correlated and uncorrelated) at different points of the machine including a full characterization of the electron gun performance parameters.« less

  7. Decision support for patient care: implementing cybernetics.

    PubMed

    Ozbolt, Judy; Ozdas, Asli; Waitman, Lemuel R; Smith, Janis B; Brennan, Grace V; Miller, Randolph A

    2004-01-01

    The application of principles and methods of cybernetics permits clinicians and managers to use feedback about care effectiveness and resource expenditure to improve quality and to control costs. Keys to the process are the specification of therapeutic goals and the creation of an organizational culture that supports the use of feedback to improve care. Daily feedback on the achievement of each patient's therapeutic goals provides tactical decision support, enabling clinicians to adjust care as needed. Monthly or quarterly feedback on aggregated goal achievement for all patients on a clinical pathway provides strategic decision support, enabling clinicians and managers to identify problems with supposed "best practices" and to test hypotheses about solutions. Work is underway at Vanderbilt University Medical Center to implement feedback loops in care and management processes and to evaluate the effects.

  8. Modelling human decision-making in coupled human and natural systems

    NASA Astrophysics Data System (ADS)

    Feola, G.

    2012-12-01

    A solid understanding of human decision-making is essential to analyze the complexity of coupled human and natural systems (CHANS) and inform policies to promote resilience in the face of environmental change. Human decisions drive and/or mediate the interactions and feedbacks, and contribute to the heterogeneity and non-linearity that characterize CHANS. However, human decision-making is usually over-simplistically modeled, whereby human agents are represented deterministically either as dumb or clairvoyant decision-makers. Decision-making models fall short in the integration of both environmental and human behavioral drivers, and concerning the latter, tend to focus on only one category, e.g. economic, cultural, or psychological. Furthermore, these models render a linear decision-making process and therefore fail to account for the recursive co-evolutionary dynamics in CHANS. As a result, these models constitute only a weak basis for policy-making. There is therefore scope and an urgent need for better approaches to human decision-making, to produce the knowledge that can inform vulnerability reduction policies in the face of environmental change. This presentation synthesizes the current state-of-the-art of modelling human decision-making in CHANS, with particular reference to agricultural systems, and delineates how the above mentioned shortcomings can be overcome. Through examples from research on pesticide use and adaptation to climate change, both based on the integrative agent-centered framework (Feola and Binder, 2010), the approach for an improved understanding of human agents in CHANS are illustrated. This entails: integrative approach, focus on behavioral dynamics more than states, feedbacks between individual and system levels, and openness to heterogeneity.

  9. A Closer Look at the Effects of Repeated Cocaine Exposure on Adaptive Decision-Making under Conditions That Promote Goal-Directed Control.

    PubMed

    Halbout, Briac; Liu, Angela T; Ostlund, Sean B

    2016-01-01

    It has been proposed that compulsive drug seeking reflects an underlying dysregulation in adaptive behavior that favors habitual (automatic and inflexible) over goal-directed (deliberative and highly flexible) action selection. Rodent studies have established that repeated exposure to cocaine or amphetamine facilitates the development of habits, producing behavior that becomes unusually insensitive to a reduction in the value of its outcome. The current study more directly investigated the effects of cocaine pre-exposure on goal-directed learning and action selection using an approach that discourages habitual performance. After undergoing a 15-day series of cocaine (15 or 30 mg/kg, i.p.) or saline injections and a drug withdrawal period, rats were trained to perform two different lever-press actions for distinct reward options. During a subsequent outcome devaluation test, both cocaine- and saline-treated rats showed a robust bias in their choice between the two actions, preferring whichever action had been trained with the reward that retained its value. Thus, it appears that the tendency for repeated cocaine exposure to promote habit formation does not extend to a more complex behavioral scenario that encourages goal-directed control. To further explore this issue, we assessed how prior cocaine treatment would affect the rats' ability to learn about a selective reduction in the predictive relationship between one of the two actions and its outcome, which is another fundamental feature of goal-directed behavior. Interestingly, we found that cocaine-treated rats showed enhanced, rather than diminished, sensitivity to this action-outcome contingency degradation manipulation. Given their mutual dependence on striatal dopamine signaling, we suggest that cocaine's effects on habit formation and contingency learning may stem from a common adaptation in this neurochemical system. PMID:27047400

  10. A Closer Look at the Effects of Repeated Cocaine Exposure on Adaptive Decision-Making under Conditions That Promote Goal-Directed Control

    PubMed Central

    Halbout, Briac; Liu, Angela T.; Ostlund, Sean B.

    2016-01-01

    It has been proposed that compulsive drug seeking reflects an underlying dysregulation in adaptive behavior that favors habitual (automatic and inflexible) over goal-directed (deliberative and highly flexible) action selection. Rodent studies have established that repeated exposure to cocaine or amphetamine facilitates the development of habits, producing behavior that becomes unusually insensitive to a reduction in the value of its outcome. The current study more directly investigated the effects of cocaine pre-exposure on goal-directed learning and action selection using an approach that discourages habitual performance. After undergoing a 15-day series of cocaine (15 or 30 mg/kg, i.p.) or saline injections and a drug withdrawal period, rats were trained to perform two different lever-press actions for distinct reward options. During a subsequent outcome devaluation test, both cocaine- and saline-treated rats showed a robust bias in their choice between the two actions, preferring whichever action had been trained with the reward that retained its value. Thus, it appears that the tendency for repeated cocaine exposure to promote habit formation does not extend to a more complex behavioral scenario that encourages goal-directed control. To further explore this issue, we assessed how prior cocaine treatment would affect the rats’ ability to learn about a selective reduction in the predictive relationship between one of the two actions and its outcome, which is another fundamental feature of goal-directed behavior. Interestingly, we found that cocaine-treated rats showed enhanced, rather than diminished, sensitivity to this action–outcome contingency degradation manipulation. Given their mutual dependence on striatal dopamine signaling, we suggest that cocaine’s effects on habit formation and contingency learning may stem from a common adaptation in this neurochemical system. PMID:27047400

  11. Clinical Decision Making of Rural Novice Nurses

    ERIC Educational Resources Information Center

    Seright, Teresa J.

    2010-01-01

    The purpose of this study was to develop substantive theory regarding decision making by the novice nurse in a rural hospital setting. Interviews were guided by the following research questions: What cues were used by novice rural registered nurses in order to make clinical decisions? What were the sources of feedback which influenced subsequent…

  12. Making Time for Feedback

    ERIC Educational Resources Information Center

    Fisher, Douglas; Frey, Nancy

    2012-01-01

    Ask any teacher what he or she needs more of, and it is a good bet that time will top the list. Anything that promises to recoup a little bit of their workday time is sure to be a best seller. One overlooked time-saver is in how they use feedback. Teachers know that feedback is important for teaching and learning. Unfortunately, most secondary…

  13. Feedback and rewards, part II: formal and informal feedback reviews.

    PubMed

    Harolds, Jay

    2013-02-01

    There are 2 major classes of feedback. One class of feedback consists of the informal, numerous conversations between various people in the organization regarding the performance, behavior, and goals of an individual. Another class of feedback consists of formal reviews held once or twice a year between a supervisor and an individual. This article discusses both types of feedback.

  14. Optimal Parametric Feedback Excitation of Nonlinear Oscillators

    NASA Astrophysics Data System (ADS)

    Braun, David J.

    2016-01-01

    An optimal parametric feedback excitation principle is sought, found, and investigated. The principle is shown to provide an adaptive resonance condition that enables unprecedentedly robust movement generation in a large class of oscillatory dynamical systems. Experimental demonstration of the theory is provided by a nonlinear electronic circuit that realizes self-adaptive parametric excitation without model information, signal processing, and control computation. The observed behavior dramatically differs from the one achievable using classical parametric modulation, which is fundamentally limited by uncertainties in model information and nonlinear effects inevitably present in real world applications.

  15. Optimal Parametric Feedback Excitation of Nonlinear Oscillators.

    PubMed

    Braun, David J

    2016-01-29

    An optimal parametric feedback excitation principle is sought, found, and investigated. The principle is shown to provide an adaptive resonance condition that enables unprecedentedly robust movement generation in a large class of oscillatory dynamical systems. Experimental demonstration of the theory is provided by a nonlinear electronic circuit that realizes self-adaptive parametric excitation without model information, signal processing, and control computation. The observed behavior dramatically differs from the one achievable using classical parametric modulation, which is fundamentally limited by uncertainties in model information and nonlinear effects inevitably present in real world applications. PMID:26871336

  16. Feedback and rewards, Part I: Introduction to effective feedback.

    PubMed

    Harolds, Jay A

    2013-01-01

    This series of articles discusses conversations regarding feedback. Feedback can include input from numerous sources, including one's supervisor, peers, subordinates, suppliers, customers, patients, and/or society members. Effective feedback is very important to the operation of any organization and to the growth of the individual. However, feedback done poorly does not appear to be rare and can be highly destructive to all. A variety of tips on how to do feedback well are included in this article.

  17. Seven Keys to Effective Feedback

    ERIC Educational Resources Information Center

    Wiggins, Grant

    2012-01-01

    The term "feedback" is often used to describe all kinds of comments made after the fact, including advice, praise, and evaluation. But none of these are feedback, strictly speaking. Basically, feedback is information about how one is doing in his or her efforts to reach a goal. Whether feedback is just there to be grasped or is provided by another…

  18. Feedback: How Does It Function?

    ERIC Educational Resources Information Center

    Bardwell, Rebecca

    1981-01-01

    A study of feedback delay, expectation, and development was conducted in grades four, six, and eight, to assess whether feedback on a school related learning task serves an informational or reinforcing function. Results indicate that feedback serves an informational function and delayed feedback facilitates retention, contrary to reinforcement…

  19. Global climate feedbacks

    SciTech Connect

    Manowitz, B.

    1990-10-01

    The important physical, chemical, and biological events that affect global climate change occur on a mesoscale -- requiring high spatial resolution for their analysis. The Department of Energy has formulated two major initiatives under the US Global Change Program: ARM (Atmospheric Radiation Measurements), and CHAMMP (Computer Hardware Advanced Mathematics and Model Physics). ARM is designed to use ground and air-craft based observations to document profiles of atmospheric composition, clouds, and radiative fluxes. With research and models of important physical processes, ARM will delineate the relationships between trace gases, aerosol and cloud structure, and radiative transfer in the atmosphere, and will improve the parameterization of global circulation models. The present GCMs do not model important feedbacks, including those from clouds, oceans, and land processes. The purpose of this workshop is to identify such potential feedbacks, to evaluate the uncertainties in the feedback processes (and, if possible, to parameterize the feedback processes so that they can be treated in a GCM), and to recommend research programs that will reduce the uncertainties in important feedback processes. Individual reports are processed separately for the data bases.

  20. Enabling Philippine Farmers to Adapt to Climate Variability Using Seasonal Climate and Weather Forecast with a Crop Simulation Model in an SMS-based Farmer Decision Support System

    NASA Astrophysics Data System (ADS)

    Ebardaloza, J. B. R.; Trogo, R.; Sabido, D. J.; Tongson, E.; Bagtasa, G.; Balderama, O. F.

    2015-12-01

    Corn farms in the Philippines are rainfed farms, hence, it is of utmost importance to choose the start of planting date so that the critical growth stages that are in need of water will fall on dates when there is rain. Most farmers in the Philippines use superstitions and traditions as basis for farming decisions such as when to start planting [1]. Before climate change, superstitions like planting after a feast day of a saint has worked for them but with the recent progression of climate change, farmers now recognize that there is a need for technological intervention [1]. The application discussed in this paper presents a solution that makes use of meteorological station sensors, localized seasonal climate forecast, localized weather forecast and a crop simulation model to provide recommendations to farmers based on the crop cultivar, soil type and fertilizer type used by farmers. It is critical that the recommendations given to farmers are not generic as each farmer would have different needs based on their cultivar, soil, fertilizer, planting schedule and even location [2]. This application allows the farmer to inquire about whether it will rain in the next seven days, the best date to start planting based on the potential yield upon harvest, when to apply fertilizer and by how much, when to water and by how much. Short messaging service (SMS) is the medium chosen for this application because while mobile penetration in the Philippines is as high as 101%, the smart phone penetration is only at 15% [3]. SMS has been selected as it has been identified as the most effective way of reaching farmers with timely agricultural information and knowledge [4,5]. The recommendations while derived from making use of Automated Weather Station (AWS) sensor data, Weather Research Forecasting (WRF) models and DSSAT 4.5 [9], are translated into the local language of the farmers and in a format that is easily understood as recommended in [6,7,8]. A pilot study has been started

  1. Corresponding Angle Feedback in an innovative weighted transportation system

    NASA Astrophysics Data System (ADS)

    Dong, Chuanfei; Ma, Xu

    2010-05-01

    The optimal information feedback has a significant effect on many socioeconomic systems like stock market and traffic systems aiming to make full use of resources. In this Letter, we study dynamics of traffic flow with real-time information. The influence of a feedback strategy named Corresponding Angle Feedback Strategy (CAFS) is introduced, based on a two-route scenario in which dynamic information can be generated and displayed on the board to guide road users to make a choice. Our model incorporates the effects of adaptability into the cellular automaton models of traffic flow and simulation results adopting this optimal information feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other three information feedback strategies, i.e., vehicle number and flux.

  2. Prediction, Bayesian inference and feedback in speech recognition

    PubMed Central

    Norris, Dennis; McQueen, James M.; Cutler, Anne

    2016-01-01

    ABSTRACT Speech perception involves prediction, but how is that prediction implemented? In cognitive models prediction has often been taken to imply that there is feedback of activation from lexical to pre-lexical processes as implemented in interactive-activation models (IAMs). We show that simple activation feedback does not actually improve speech recognition. However, other forms of feedback can be beneficial. In particular, feedback can enable the listener to adapt to changing input, and can potentially help the listener to recognise unusual input, or recognise speech in the presence of competing sounds. The common feature of these helpful forms of feedback is that they are all ways of optimising the performance of speech recognition using Bayesian inference. That is, listeners make predictions about speech because speech recognition is optimal in the sense captured in Bayesian models. PMID:26740960

  3. Weighted congestion coefficient feedback in intelligent transportation systems

    NASA Astrophysics Data System (ADS)

    Dong, Chuan-Fei; Ma, Xu; Wang, Bing-Hong

    2010-03-01

    In traffic systems, a reasonable information feedback can improve road capacity. In this Letter, we study dynamics of traffic flow with real-time information. And the influence of a feedback strategy named Weighted Congestion Coefficient Feedback Strategy (WCCFS) is introduced, based on a two-route scenario in which dynamic information can be generated and displayed on the board to guide road users to make a choice. Our model incorporates the effects of adaptability into the cellular automaton models of traffic flow and simulation results adopting this optimal information feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other three information feedback strategies, i.e., vehicle number and flux.

  4. STABILIZED FEEDBACK AMPLIFIER

    DOEpatents

    Fishbine, H.L.; Sewell, C. Jr.

    1957-08-01

    Negative feedback amplifiers, and particularly a negative feedback circuit which is economical on amode power consumption, are described. Basically, the disclosed circuit comprises two tetrode tubes where the output of the first tube is capacitamce coupled to the grid of the second tube, which in turn has its plate coupled to the cathode of the first tube to form a degenerative feedback circuit. Operating potential for screen of the second tube is supplied by connecting the cathode resistor of the first tube to the screen, while the screen is by-passed to the cathode of its tube for the amplified frequencies. Also, the amplifier incorporates a circuit to stabilize the transconductance of the tubes by making the grid potential of each tube interdependent on anode currents of both lubes by voltage divider circuitry.

  5. Stratospheric water vapor feedback.

    PubMed

    Dessler, A E; Schoeberl, M R; Wang, T; Davis, S M; Rosenlof, K H

    2013-11-01

    We show here that stratospheric water vapor variations play an important role in the evolution of our climate. This comes from analysis of observations showing that stratospheric water vapor increases with tropospheric temperature, implying the existence of a stratospheric water vapor feedback. We estimate the strength of this feedback in a chemistry-climate model to be +0.3 W/(m(2)⋅K), which would be a significant contributor to the overall climate sensitivity. One-third of this feedback comes from increases in water vapor entering the stratosphere through the tropical tropopause layer, with the rest coming from increases in water vapor entering through the extratropical tropopause. PMID:24082126

  6. Stratospheric water vapor feedback

    PubMed Central

    Dessler, A. E.; Schoeberl, M. R.; Wang, T.; Davis, S. M.; Rosenlof, K. H.

    2013-01-01

    We show here that stratospheric water vapor variations play an important role in the evolution of our climate. This comes from analysis of observations showing that stratospheric water vapor increases with tropospheric temperature, implying the existence of a stratospheric water vapor feedback. We estimate the strength of this feedback in a chemistry–climate model to be +0.3 W/(m2⋅K), which would be a significant contributor to the overall climate sensitivity. One-third of this feedback comes from increases in water vapor entering the stratosphere through the tropical tropopause layer, with the rest coming from increases in water vapor entering through the extratropical tropopause. PMID:24082126

  7. Augmented kinematic feedback system

    NASA Astrophysics Data System (ADS)

    Andert, Ed P., Jr.; Archipley-Smith, Donna K.

    1994-07-01

    This paper discusses a real-time augmented kinematic feedback system which can be used as a diagnosis tool for individuals with motor disabilities. The system captures and analyzes movement via color targets attached to an individual and then feeds back information about movement kinematics. This target tracking approach has a high potential for achieving a real- time kinematic assessment capability. The approach recognizes distinct moving colored targets using video data. Multiple colored targets are attached to an individual at strategic locations and then target movement is tracked using a video data acquisition system. The ability to track and assess movement in real-time allows researchers and practitioners to better study and potentially treat various motor disabilities. Recent research has suggested that kinematic feedback can enhance motor recovery of disabled individuals. This approach addresses the need for a real-time measure of human movement and discusses using kinematic feedback to enhance disability recovery.

  8. TUNE FEEDBACK AT RHIC

    SciTech Connect

    CAMERON,P.; CERNIGLIA,P.; CONNOLLY,R.; CUPOLO,J.; DAWSON,W.C.; DEGEN,C.; DELLAPENNA,A.; DELONG,J.; DREES,A.; HUHN,A.; KESSELMAN,M.; MARUSIC,A.; OERTER,B.; MEAD,J.; SCHULTHEISS,C.; SIKORA,R.; VAN ZEIJTS,J.

    2001-06-18

    Preliminary phase-locked loop betatron tune measurement results were obtained during RHIC 2000 with a resonant Beam Position Monitor. These results suggested the possibility of incorporating PLL tune measurement into a tune feedback system for RHIC 2001. Tune feedback is useful in a superconducting accelerator, where the machine cycle time is long and inefficient acceleration due to resonance crossing is not comfortably tolerated. This is particularly true with the higher beam intensities planned for RHIC 2001. We present descriptions of a PLL tune measurement system implemented in the DSP/FPGA environment of a RHIC BPM electronics module and the feedback system into which the measurement is incorporated to regulate tune. In addition, we present results from the commissioning of this system during RHIC 2001.

  9. Adaptive Activity and Environment Recognition for Mobile Phones

    PubMed Central

    Parviainen, Jussi; Bojja, Jayaprasad; Collin, Jussi; Leppänen, Jussi; Eronen, Antti

    2014-01-01

    In this paper, an adaptive activity and environment recognition algorithm running on a mobile phone is presented. The algorithm makes inferences based on sensor and radio receiver data provided by the phone. A wide set of features that can be extracted from these data sources were investigated, and a Bayesian maximum a posteriori classifier was used for classifying between several user activities and environments. The accuracy of the method was evaluated on a dataset collected in a real-life trial. In addition, comparison to other state-of-the-art classifiers, namely support vector machines and decision trees, was performed. To make the system adaptive for individual user characteristics, an adaptation algorithm for context model parameters was designed. Moreover, a confidence measure for the classification correctness was designed. The proposed adaptation algorithm and confidence measure were evaluated on a second dataset obtained from another real-life trial, where the users were requested to provide binary feedback on the classification correctness. The results show that the proposed adaptation algorithm is effective at improving the classification accuracy. PMID:25372620

  10. Adaptive activity and environment recognition for mobile phones.

    PubMed

    Parviainen, Jussi; Bojja, Jayaprasad; Collin, Jussi; Leppänen, Jussi; Eronen, Antti

    2014-11-03

    In this paper, an adaptive activity and environment recognition algorithm running on a mobile phone is presented. The algorithm makes inferences based on sensor and radio receiver data provided by the phone. A wide set of features that can be extracted from these data sources were investigated, and a Bayesian maximum a posteriori classifier was used for classifying between several user activities and environments. The accuracy of the method was evaluated on a dataset collected in a real-life trial. In addition, comparison to other state-of-the-art classifiers, namely support vector machines and decision trees, was performed. To make the system adaptive for individual user characteristics, an adaptation algorithm for context model parameters was designed. Moreover, a confidence measure for the classification correctness was designed. The proposed adaptation algorithm and confidence measure were evaluated on a second dataset obtained from another real-life trial, where the users were requested to provide binary feedback on the classification correctness. The results show that the proposed adaptation algorithm is effective at improving the classification accuracy.

  11. Climate forcings and feedbacks

    NASA Technical Reports Server (NTRS)

    Hansen, James

    1993-01-01

    Global temperature has increased significantly during the past century. Understanding the causes of observed global temperature change is impossible in the absence of adequate monitoring of changes in global climate forcings and radiative feedbacks. Climate forcings are changes imposed on the planet's energy balance, such as change of incoming sunlight or a human-induced change of surface properties due to deforestation. Radiative feedbacks are radiative changes induced by climate change, such as alteration of cloud properties or the extent of sea ice. Monitoring of global climate forcings and feedbacks, if sufficiently precise and long-term, can provide a very strong constraint on interpretation of observed temperature change. Such monitoring is essential to eliminate uncertainties about the relative importance of various climate change mechanisms including tropospheric sulfate aerosols from burning of coal and oil smoke from slash and burn agriculture, changes of solar irradiance changes of several greenhouse gases, and many other mechanisms. The considerable variability of observed temperature, together with evidence that a substantial portion of this variability is unforced indicates that observations of climate forcings and feedbacks must be continued for decades. Since the climate system responds to the time integral of the forcing, a further requirement is that the observations be carried out continuously. However, precise observations of forcings and feedbacks will also be able to provide valuable conclusions on shorter time scales. For example, knowledge of the climate forcing by increasing CFC's relative to the forcing by changing ozone is important to policymakers, as is information on the forcing by CO2 relative to the forcing by sulfate aerosols. It will also be possible to obtain valuable tests of climate models on short time scales, if there is precise monitoring of all forcings and feedbacks during and after events such as a large volcanic eruption

  12. How Supernova Feedback Affects Observed Galaxy Sizes and Structures

    NASA Astrophysics Data System (ADS)

    Joung, M. K. Ryan; Cen, R.; Bryan, G. L.

    2009-01-01

    Feedback from massive stars is perhaps the least understood aspect of galaxy formation. Based on adaptive mesh refinement (AMR) cosmological simulations and stellar population synthesis models, we compute half-light radii of high redshift galaxies and use them to compare simulated and observed size-mass and size-luminosity relations in the rest-frame UV/optical. The sizes of the simulated galaxies depend on the assumed strength of supernova feedback; we investigate the origin of this relation. We discuss minimum requirements for correct numerical modeling of supernova feedback in starburst galaxies.

  13. Feedback strategy on real-time multiple target tracking in cognitive vision system

    NASA Astrophysics Data System (ADS)

    Shao, Jie; Jia, Zhen; Li, Zhipeng; Liu, Fuqiang; Zhao, Jianwei; Peng, Pei-Yuan

    2011-10-01

    Under pedestrian and vehicle mixed traffic conditions, the potential accident rate is high due to a complex traffic environment. In order to solve this problem, we present a real-time cognitive vision system. In the scene-capture level, foreground objects are extracted based on the combination of spatial and temporal information. Then, a coarse-to-fine algorithm is employed in tracking. After filtering-based normal tracking, problems of the target blob missing, merging, and splitting are resolved by the adaptive tracking modification method in fine tracking. For greater robustness, the key idea of our approach is adaptively adjusting the classification sensibility of each pixel by employing tracking results as feedback cues for target detection in the next frame. On the basis of the target trajectories, behavior models are evaluated according to a decision logic table in the behavior-evaluation level. The decision logic table is set based on rules of real scenes. The resulting system interprets different kinds of traffic behavior and warns in advance. Experiments show robust and accurate results of abnormality detection and forewarning under different conditions. All the experimental results run at real-time frame rates (>=25 fps) on standard hardware. Therefore, the system is suitable for actual Intelligent Traffic System applications.

  14. Addressing Climate Change Adaptation in Regional Transportation Plans in California: A Guide and Online Visualization Tool for Planners to Incorporate Risks of Climate Change Impacts in Policy and Decision-Making

    NASA Astrophysics Data System (ADS)

    Tao, W.; Tucker, K.; DeFlorio, J.

    2012-12-01

    for the strategy framework. The strategy framework for MPOs and RTPAs is used to: 1) Assess the relative risks to their transportation system infrastructure and services of different climate stressors (sea level rise, temperature changes, snow melt, precipita¬tion changes, flooding, extreme weather events); 2) Conduct an asset inventory and vulnerability assessment of existing infrastructure; 3) Prioritize segments and facilities for adaptation action; 4) Identify appropriate and cost-effective adaptation strategies; and 5) Incorporate climate impact considerations into future long-range transportation planning and investment decisions. This framework complements the broader planning and investment processes that MPOs and RTPAs already manage. It recognizes the varying capacities and resources among MPOs and RTPAs and provide methods that can be used by organizations seeking to conduct in-depth analysis or a more sketch-level assessment.

  15. Empirical Analysis of EEG and ERPs for Psychophysiological Adaptive Task Allocation

    NASA Technical Reports Server (NTRS)

    Prinzel, Lawrence J., III; Pope, Alan T.; Freeman, Frederick G.; Scerbo, Mark W.; Mikulka, Peter J.

    2001-01-01

    The present study was designed to test the efficacy of using Electroencephalogram (EEG) and Event-Related Potentials (ERPs) for making task allocation decisions. Thirty-six participants were randomly assigned to an experimental, yoked, or control group condition. Under the experimental condition, a tracking task was switched between task modes based upon the participant's EEG. The results showed that the use of adaptive aiding improved performance and lowered subjective workload under negative feedback as predicted. Additionally, participants in the adaptive group had significantly lower RMSE and NASA-TLX ratings than participants in either the yoked or control group conditions. Furthermore, the amplitudes of the N1 and P3 ERP components were significantly larger under the experimental group condition than under either the yoked or control group conditions. These results are discussed in terms of the implications for adaptive automation design.

  16. Adaptive control for accelerators

    DOEpatents

    Eaton, Lawrie E.; Jachim, Stephen P.; Natter, Eckard F.

    1991-01-01

    An adaptive feedforward control loop is provided to stabilize accelerator beam loading of the radio frequency field in an accelerator cavity during successive pulses of the beam into the cavity. A digital signal processor enables an adaptive algorithm to generate a feedforward error correcting signal functionally determined by the feedback error obtained by a beam pulse loading the cavity after the previous correcting signal was applied to the cavity. Each cavity feedforward correcting signal is successively stored in the digital processor and modified by the feedback error resulting from its application to generate the next feedforward error correcting signal. A feedforward error correcting signal is generated by the digital processor in advance of the beam pulse to enable a composite correcting signal and the beam pulse to arrive concurrently at the cavity.

  17. Accountability and feedback, part IV: destructive feedback.

    PubMed

    Harolds, Jay A

    2013-04-01

    There are times that feedback is destructive rather than helpful to the employee and the organization. Occasionally, this is deliberate, such as when a boss does not like someone for reasons that have nothing to do with his/her performance as an employee, or his/her character. More often, it is inadvertent. This could be due to erroneous information from others or the leader's failure to take the time to adequately observe or supervise others. It could also be due to a lack of understanding of the individual's communication style, or failure to take into account age, cultural, religious, or sex differences. This article addresses some of these issues and what to do about it.

  18. Neural correlates of uncertain decision making: ERP evidence from the Iowa Gambling Task.

    PubMed

    Cui, Ji-Fang; Chen, Ying-He; Wang, Ya; Shum, David H K; Chan, Raymond C K

    2013-01-01

    In our daily life, it is very common to make decisions in uncertain situations. The Iowa Gambling Task (IGT) has been widely used in laboratory studies because of its good simulation of uncertainty in real life activities. The present study aimed to examine the neural correlates of uncertain decision making with the IGT. Twenty-six university students completed this study. An adapted IGT was administered to them, and the EEG data were recorded. The adapted IGT we used allowed us to analyze the choice evaluation, response selection, and feedback evaluation stages of uncertain decision making within the same paradigm. In the choice evaluation stage, the advantageous decks evoked larger P3 amplitude in the left hemisphere, while the disadvantageous decks evoked larger P3 in the right hemisphere. In the response selection stage, the response of "pass" (the card was not turned over; the participants neither won nor lost money) evoked larger negativity preceding the response compared to that of "play" (the card was turned over; the participant either won or lost money). In the feedback evaluation stage, feedback-related negativity (FRN) was only sensitive to the valence (win/loss) but not the magnitude (large/small) of the outcome, and P3 was sensitive to both the valence and the magnitude of the outcome. These results were consistent with the notion that a positive somatic state was represented in the left hemisphere and a negative somatic state was represented in the right hemisphere. There were also anticipatory ERP effects that guided the participants' responses and provided evidence for the somatic marker hypothesis with more precise timing. PMID:24298248

  19. A holistic strategy for adaptive land management

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Adaptive management is widely applied to natural resources management. Adaptive management can be generally defined as an iterative decision-making process that incorporates formulation of management objectives, actions designed to address these objectives, monitoring of results, and repeated adapta...

  20. Adaptive Heat Engine.

    PubMed

    Allahverdyan, A E; Babajanyan, S G; Martirosyan, N H; Melkikh, A V

    2016-07-15

    A major limitation of many heat engines is that their functioning demands on-line control and/or an external fitting between the environmental parameters (e.g., temperatures of thermal baths) and internal parameters of the engine. We study a model for an adaptive heat engine, where-due to feedback from the functional part-the engine's structure adapts to given thermal baths. Hence, no on-line control and no external fitting are needed. The engine can employ unknown resources; it can also adapt to results of its own functioning that make the bath temperatures closer. We determine resources of adaptation and relate them to the prior information available about the environment.

  1. Adaptive Heat Engine.

    PubMed

    Allahverdyan, A E; Babajanyan, S G; Martirosyan, N H; Melkikh, A V

    2016-07-15

    A major limitation of many heat engines is that their functioning demands on-line control and/or an external fitting between the environmental parameters (e.g., temperatures of thermal baths) and internal parameters of the engine. We study a model for an adaptive heat engine, where-due to feedback from the functional part-the engine's structure adapts to given thermal baths. Hence, no on-line control and no external fitting are needed. The engine can employ unknown resources; it can also adapt to results of its own functioning that make the bath temperatures closer. We determine resources of adaptation and relate them to the prior information available about the environment. PMID:27472104

  2. Adaptive Heat Engine

    NASA Astrophysics Data System (ADS)

    Allahverdyan, A. E.; Babajanyan, S. G.; Martirosyan, N. H.; Melkikh, A. V.

    2016-07-01

    A major limitation of many heat engines is that their functioning demands on-line control and/or an external fitting between the environmental parameters (e.g., temperatures of thermal baths) and internal parameters of the engine. We study a model for an adaptive heat engine, where—due to feedback from the functional part—the engine's structure adapts to given thermal baths. Hence, no on-line control and no external fitting are needed. The engine can employ unknown resources; it can also adapt to results of its own functioning that make the bath temperatures closer. We determine resources of adaptation and relate them to the prior information available about the environment.

  3. Polarization feedback laser stabilization

    DOEpatents

    Esherick, Peter; Owyoung, Adelbert

    1988-01-01

    A system for locking two Nd:YAG laser oscillators includes an optical path for feeding the output of one laser into the other with different polarizations. Elliptical polarization is incorporated into the optical path so that the change in polarization that occurs when the frequencies coincide may be detected to provide a feedback signal to control one laser relative to the other.

  4. Feedback and Job Satisfaction.

    ERIC Educational Resources Information Center

    Mangelsdorff, A. David

    The purpose of the study was to determine the effects of providing feedback (results of how frequently a variety of tasks had been performed) on the job satisfaction of Dental Therapy Assistants (DTA's) during the course of several levels of training, i.e., up to three months, four to nine months and 10 to 18 months. Trainees were predominantly…

  5. School Formative Feedback Systems

    ERIC Educational Resources Information Center

    Halverson, Richard

    2010-01-01

    Data-driven instructional improvement relies on developing coherent systems that allow school staff to generate, interpret, and act upon quality formative information on students and school programs. This article offers a formative feedback system model that captures how school leaders and teachers structure artifacts and practices to create…

  6. Real, Fast, Feedback

    ERIC Educational Resources Information Center

    Hill, Paul

    2013-01-01

    To better comprehend the needs of your clientele and colleagues, it is essential to use survey website applications. Doing so will help you become more efficient in obtaining constructive, timely feedback in order to adjust programming, therefore optimizing the impacts of Extension activities. Citing the most influential survey experts both in and…

  7. Feedback and Prior Achievement.

    ERIC Educational Resources Information Center

    Hyman, Cynthia; Tobias, Sigmund

    The hypothesis that feedback in programmed instruction is an important variable in the learning of novel, but not familiar, content was investigated. A linear, constructed response program dealing with the Sabbath rituals in the synagogue was chosen due to wide variability in student familiarity with this topic. Subjects were randomly assigned to…

  8. Review of Assessment Feedback

    ERIC Educational Resources Information Center

    Li, Jinrui; De Luca, Rosemary

    2014-01-01

    This article reviews 37 empirical studies, selected from 363 articles and 20 journals, on assessment feedback published between 2000 and 2011. The reviewed articles, many of which came out of studies in the UK and Australia, reflect the most current issues and developments in the area of assessing disciplinary writing. The article aims to outline…

  9. Feedback in Information Retrieval.

    ERIC Educational Resources Information Center

    Spink, Amanda; Losee, Robert M.

    1996-01-01

    As Information Retrieval (IR) has evolved, it has become a highly interactive process, rooted in cognitive and situational contexts. Consequently the traditional cybernetic-based IR model does not suffice for interactive IR or the human approach to IR. Reviews different views of feedback in IR and their relationship to cybernetic and social…

  10. Feedback: A Basic Ingredient

    ERIC Educational Resources Information Center

    Skenderis, Theodoros; Laskaridou, Chryssa

    2010-01-01

    The way we, teachers, talk to learners in general and, more specifically, the way we respond to what they have/haven't said or done affects them both as personalities and as learners. Even if we could agree that all teacher feedback is meant well, we could equally well agree that it does not always have the expected effects: learners do not always…

  11. Perceptual learning in sensorimotor adaptation.

    PubMed

    Darainy, Mohammad; Vahdat, Shahabeddin; Ostry, David J

    2013-11-01

    Motor learning often involves situations in which the somatosensory targets of movement are, at least initially, poorly defined, as for example, in learning to speak or learning the feel of a proper tennis serve. Under these conditions, motor skill acquisition presumably requires perceptual as well as motor learning. That is, it engages both the progressive shaping of sensory targets and associated changes in motor performance. In the present study, we test the idea that perceptual learning alters somatosensory function and in so doing produces changes to human motor performance and sensorimotor adaptation. Subjects in these experiments undergo perceptual training in which a robotic device passively moves the subject's arm on one of a set of fan-shaped trajectories. Subjects are required to indicate whether the robot moved the limb to the right or the left and feedback is provided. Over the course of training both the perceptual boundary and acuity are altered. The perceptual learning is observed to improve both the rate and extent of learning in a subsequent sensorimotor adaptation task and the benefits persist for at least 24 h. The improvement in the present studies varies systematically with changes in perceptual acuity and is obtained regardless of whether the perceptual boundary shift serves to systematically increase or decrease error on subsequent movements. The beneficial effects of perceptual training are found to be substantially dependent on reinforced decision-making in the sensory domain. Passive-movement training on its own is less able to alter subsequent learning in the motor system. Overall, this study suggests perceptual learning plays an integral role in motor learning.

  12. Quantum entanglement capacity with classical feedback

    NASA Astrophysics Data System (ADS)

    Leung, Alan W.

    2008-01-01

    For any quantum discrete memoryless channel, we define a quantity called quantum entanglement capacity with classical feedback (EB) , and we show that this quantity lies between two other well-studied quantities. These two quantities—namely the quantum capacity assisted by two-way classical communication (Q2) and the quantum capacity with classical feedback (QB) —are widely conjectured to be different: There exists a quantum discrete memoryless channel for which Q2>QB . We then present a general scheme to convert any quantum error-correcting codes into adaptive protocols for this newly defined quantity of the quantum depolarizing channel, and illustrate with the repetition code and Shor code. We contrast the present notion with entanglement purification protocols by showing that, whilst the Leung-Shor protocol can be applied directly, recurrence methods need to be supplemented with other techniques but at the same time offer a way to improve the aforementioned repetition code. For the quantum depolarizing channel, we prove a formula that gives lower bounds on the quantum capacity with classical feedback from any EB protocols. We then apply this formula to the EB protocols that we discuss to obtain lower bounds on the quantum capacity with classical feedback of the quantum depolarizing channel.

  13. Rehabilitation and motor learning through vibrotactile feedback

    NASA Astrophysics Data System (ADS)

    Panchanathan, Roshan; Rosenthal, Jacob; McDaniel, Troy

    2014-05-01

    Group instruction is the most common delivery method of motor skill training given its cost and time effectiveness. This is also the case during rehabilitation where therapists divide their attention among several patients. Compared to dedicated one-on-one instruction, group instruction often suffers from reduced quality and quantity of instruction and feedback. Further, during rehabilitation programs, patients struggle outside of therapy sessions given the lack of instruction and feedback found only during clinic visits. We propose a wearable, low-cost motion sensing and actuation system capable of providing real-time vibrotactile feedback for trainer-defined goal movements and repetitions. The trainer inputs movement goals for the user, and adapts these values (joint angles, movement speeds) over time for continued progress. In this paper, we present a novel second generation design, and introduce a flexible vibrotactile strip to overcome construction challenges of these types of systems. The flexible display is constructed using commercial LED strips that have been modified by attaching pancake style vibration motors. The flexible display does not require external microcontrollers to enable or disable motors, and may allow these systems to be expanded to the whole body. We also summarize two previous studies that have assessed appropriate body sites and pattern designs for vibrotactile motor instructions and feedback signals.

  14. Adaptive Distributed Environment for Procedure Training (ADEPT)

    NASA Technical Reports Server (NTRS)

    Domeshek, Eric; Ong, James; Mohammed, John

    2013-01-01

    ADEPT (Adaptive Distributed Environment for Procedure Training) is designed to provide more effective, flexible, and portable training for NASA systems controllers. When creating a training scenario, an exercise author can specify a representative rationale structure using the graphical user interface, annotating the results with instructional texts where needed. The author's structure may distinguish between essential and optional parts of the rationale, and may also include "red herrings" - hypotheses that are essential to consider, until evidence and reasoning allow them to be ruled out. The system is built from pre-existing components, including Stottler Henke's SimVentive? instructional simulation authoring tool and runtime. To that, a capability was added to author and exploit explicit control decision rationale representations. ADEPT uses SimVentive's Scalable Vector Graphics (SVG)- based interactive graphic display capability as the basis of the tool for quickly noting aspects of decision rationale in graph form. The ADEPT prototype is built in Java, and will run on any computer using Windows, MacOS, or Linux. No special peripheral equipment is required. The software enables a style of student/ tutor interaction focused on the reasoning behind systems control behavior that better mimics proven Socratic human tutoring behaviors for highly cognitive skills. It supports fast, easy, and convenient authoring of such tutoring behaviors, allowing specification of detailed scenario-specific, but content-sensitive, high-quality tutor hints and feedback. The system places relatively light data-entry demands on the student to enable its rationale-centered discussions, and provides a support mechanism for fostering coherence in the student/ tutor dialog by including focusing, sequencing, and utterance tuning mechanisms intended to better fit tutor hints and feedback into the ongoing context.

  15. Building Adaptive Capacity with the Delphi Method and Mediated Modeling for Water Quality and Climate Change Adaptation in Lake Champlain Basin

    NASA Astrophysics Data System (ADS)

    Coleman, S.; Hurley, S.; Koliba, C.; Zia, A.; Exler, S.

    2014-12-01

    Eutrophication and nutrient pollution of surface waters occur within complex governance, social, hydrologic and biophysical basin contexts. The pervasive and perennial nutrient pollution in Lake Champlain Basin, despite decades of efforts, exemplifies problems found across the world's surface waters. Stakeholders with diverse values, interests, and forms of explicit and tacit knowledge determine water quality impacts through land use, agricultural and water resource decisions. Uncertainty, ambiguity and dynamic feedback further complicate the ability to promote the continual provision of water quality and ecosystem services. Adaptive management of water resources and land use requires mechanisms to allow for learning and integration of new information over time. The transdisciplinary Research on Adaptation to Climate Change (RACC) team is working to build regional adaptive capacity in Lake Champlain Basin while studying and integrating governance, land use, hydrological, and biophysical systems to evaluate implications for adaptive management. The RACC team has engaged stakeholders through mediated modeling workshops, online forums, surveys, focus groups and interviews. In March 2014, CSS2CC.org, an interactive online forum to source and identify adaptive interventions from a group of stakeholders across sectors was launched. The forum, based on the Delphi Method, brings forward the collective wisdom of stakeholders and experts to identify potential interventions and governance designs in response to scientific uncertainty and ambiguity surrounding the effectiveness of any strategy, climate change impacts, and the social and natural systems governing water quality and eutrophication. A Mediated Modeling Workshop followed the forum in May 2014, where participants refined and identified plausible interventions under different governance, policy and resource scenarios. Results from the online forum and workshop can identify emerging consensus across scales and sectors

  16. Composite collective decision-making

    PubMed Central

    Czaczkes, Tomer J.; Czaczkes, Benjamin; Iglhaut, Carolin; Heinze, Jürgen

    2015-01-01

    Individual animals are adept at making decisions and have cognitive abilities, such as memory, which allow them to hone their decisions. Social animals can also share information. This allows social animals to make adaptive group-level decisions. Both individual and collective decision-making systems also have drawbacks and limitations, and while both are well studied, the interaction between them is still poorly understood. Here, we study how individual and collective decision-making interact during ant foraging. We first gathered empirical data on memory-based foraging persistence in the ant Lasius niger. We used these data to create an agent-based model where ants may use social information (trail pheromones), private information (memories) or both to make foraging decisions. The combined use of social and private information by individuals results in greater efficiency at the group level than when either information source was used alone. The modelled ants couple consensus decision-making, allowing them to quickly exploit high-quality food sources, and combined decision-making, allowing different individuals to specialize in exploiting different resource patches. Such a composite collective decision-making system reaps the benefits of both its constituent parts. Exploiting such insights into composite collective decision-making may lead to improved decision-making algorithms. PMID:26019155

  17. Composite collective decision-making.

    PubMed

    Czaczkes, Tomer J; Czaczkes, Benjamin; Iglhaut, Carolin; Heinze, Jürgen

    2015-06-22

    Individual animals are adept at making decisions and have cognitive abilities, such as memory, which allow them to hone their decisions. Social animals can also share information. This allows social animals to make adaptive group-level decisions. Both individual and collective decision-making systems also have drawbacks and limitations, and while both are well studied, the interaction between them is still poorly understood. Here, we study how individual and collective decision-making interact during ant foraging. We first gathered empirical data on memory-based foraging persistence in the ant Lasius niger. We used these data to create an agent-based model where ants may use social information (trail pheromones), private information (memories) or both to make foraging decisions. The combined use of social and private information by individuals results in greater efficiency at the group level than when either information source was used alone. The modelled ants couple consensus decision-making, allowing them to quickly exploit high-quality food sources, and combined decision-making, allowing different individuals to specialize in exploiting different resource patches. Such a composite collective decision-making system reaps the benefits of both its constituent parts. Exploiting such insights into composite collective decision-making may lead to improved decision-making algorithms.

  18. Composite collective decision-making.

    PubMed

    Czaczkes, Tomer J; Czaczkes, Benjamin; Iglhaut, Carolin; Heinze, Jürgen

    2015-06-22

    Individual animals are adept at making decisions and have cognitive abilities, such as memory, which allow them to hone their decisions. Social animals can also share information. This allows social animals to make adaptive group-level decisions. Both individual and collective decision-making systems also have drawbacks and limitations, and while both are well studied, the interaction between them is still poorly understood. Here, we study how individual and collective decision-making interact during ant foraging. We first gathered empirical data on memory-based foraging persistence in the ant Lasius niger. We used these data to create an agent-based model where ants may use social information (trail pheromones), private information (memories) or both to make foraging decisions. The combined use of social and private information by individuals results in greater efficiency at the group level than when either information source was used alone. The modelled ants couple consensus decision-making, allowing them to quickly exploit high-quality food sources, and combined decision-making, allowing different individuals to specialize in exploiting different resource patches. Such a composite collective decision-making system reaps the benefits of both its constituent parts. Exploiting such insights into composite collective decision-making may lead to improved decision-making algorithms. PMID:26019155

  19. Modifying Evaluations and Decisions in Risky Situations.

    PubMed

    Maldonado, Antonio; Serra, Sara; Catena, Andrés; Cándido, Antonio; Megías, Alberto

    2016-01-01

    The main aim of this research was to investigate the decision making process in risky situations. We studied how different types of feedback on risky driving behaviors modulate risk evaluation and risk-taking. For a set of risky traffic situations, participants had to make evaluative judgments (judge the situation as risky or not) and urgent decisions (brake or not). In Experiment 1, participants received feedback with and without negative emotional content when they made risky behaviors. In Experiment 2 we investigated the independent effects of feedback and negative emotional stimuli. The results showed three important findings: First, urgent decisions were faster [F(1, 92) = 6.76, p = .01] and more cautious [F(1, 92) = 17.16, p < .001] than evaluative judgments. These results suggest that evaluative judgments of risk and actual risk-taking may not always coincide, and that they seem to be controlled by two different processing systems as proposed by dual process theories. Second, feedback made participants' responses even faster [F(1, 111) = 71.53, p < .001], allowing greater risk sensitivity [F(1, 111) = 22.12, p < .001] and skewing towards more cautious responses [F(1, 111) = 14.09, p < .001]. Finally, emotional stimuli had an effect only when they were presented as feedback. The results of this research increase our understanding of the processes involved in risky driving behavior and suggest efficient ways to control risk taking through the use of feedback. PMID:27647040

  20. Modifying Evaluations and Decisions in Risky Situations.

    PubMed

    Maldonado, Antonio; Serra, Sara; Catena, Andrés; Cándido, Antonio; Megías, Alberto

    2016-09-20

    The main aim of this research was to investigate the decision making process in risky situations. We studied how different types of feedback on risky driving behaviors modulate risk evaluation and risk-taking. For a set of risky traffic situations, participants had to make evaluative judgments (judge the situation as risky or not) and urgent decisions (brake or not). In Experiment 1, participants received feedback with and without negative emotional content when they made risky behaviors. In Experiment 2 we investigated the independent effects of feedback and negative emotional stimuli. The results showed three important findings: First, urgent decisions were faster [F(1, 92) = 6.76, p = .01] and more cautious [F(1, 92) = 17.16, p < .001] than evaluative judgments. These results suggest that evaluative judgments of risk and actual risk-taking may not always coincide, and that they seem to be controlled by two different processing systems as proposed by dual process theories. Second, feedback made participants' responses even faster [F(1, 111) = 71.53, p < .001], allowing greater risk sensitivity [F(1, 111) = 22.12, p < .001] and skewing towards more cautious responses [F(1, 111) = 14.09, p < .001]. Finally, emotional stimuli had an effect only when they were presented as feedback. The results of this research increase our understanding of the processes involved in risky driving behavior and suggest efficient ways to control risk taking through the use of feedback.

  1. Dubious decision evidence and criterion flexibility in recognition memory

    PubMed Central

    Kantner, Justin; Vettel, Jean M.; Miller, Michael B.

    2015-01-01

    When old–new recognition judgments must be based on ambiguous memory evidence, a proper criterion for responding “old” can substantially improve accuracy, but participants are typically suboptimal in their placement of decision criteria. Various accounts of suboptimal criterion placement have been proposed. The most parsimonious, however, is that subjects simply over-rely on memory evidence – however faulty – as a basis for decisions. We tested this account with a novel recognition paradigm in which old–new discrimination was minimal and critical errors were avoided by adopting highly liberal or conservative biases. In Experiment 1, criterion shifts were necessary to adapt to changing target probabilities or, in a “security patrol” scenario, to avoid either letting dangerous people go free (misses) or harming innocent people (false alarms). Experiment 2 added a condition in which financial incentives drove criterion shifts. Critical errors were frequent, similar across sources of motivation, and only moderately reduced by feedback. In Experiment 3, critical errors were only modestly reduced in a version of the security patrol with no study phase. These findings indicate that participants use even transparently non-probative information as an alternative to heavy reliance on a decision rule, a strategy that precludes optimal criterion placement. PMID:26441706

  2. User Feedback--Influence on Online System Operators.

    ERIC Educational Resources Information Center

    Williams, Martha E.

    The users of online retrieval systems can and should provide feedback to the system operators or vendors to influence them to make changes and further improvements, or to reinforce operator's decisions to make changes in the systems. All members of the database chain--database producers, processors, search service brokers, searchers, and end users…

  3. Effects of Strong Interest Inventory Feedback on Career Beliefs.

    ERIC Educational Resources Information Center

    Day, Michael Andrew; Luzzo, Darrell Anthony

    A study evaluated the effects of Strong Interest Inventory (SII) completion and participation in a theoretically based model of SII feedback/interpretation on the social cognitive career beliefs of 99 first-year students at a southwestern university. The Career Decision-Making Self-Efficacy Scale--Short Form (CDMSES-SF) measured each participant's…

  4. Initial Decision and Risk Analysis

    SciTech Connect

    Engel, David W.

    2012-02-29

    Decision and Risk Analysis capabilities will be developed for industry consideration and possible adoption within Year 1. These tools will provide a methodology for merging qualitative ranking of technology maturity and acknowledged risk contributors with quantitative metrics that drive investment decision processes. Methods and tools will be initially introduced as applications to the A650.1 case study, but modular spreadsheets and analysis routines will be offered to industry collaborators as soon as possible to stimulate user feedback and co-development opportunities.

  5. Assessing the Quality of Feedback in the Peer-Review Process

    ERIC Educational Resources Information Center

    Dobele, A. R.

    2015-01-01

    The feedback provided to authors by reviewers as part of a double-blind peer-review process was examined for two Australian conferences, one special international edition book and six international special edition journals (originating in the UK). The research sought to identify consistency of decision-making and the effectiveness of feedback for…

  6. Reward feedback accelerates motor learning.

    PubMed

    Nikooyan, Ali A; Ahmed, Alaa A

    2015-01-15

    Recent findings have demonstrated that reward feedback alone can drive motor learning. However, it is not yet clear whether reward feedback alone can lead to learning when a perturbation is introduced abruptly, or how a reward gradient can modulate learning. In this study, we provide reward feedback that decays continuously with increasing error. We asked whether it is possible to learn an abrupt visuomotor rotation by reward alone, and if the learning process could be modulated by combining reward and sensory feedback and/or by using different reward landscapes. We designed a novel visuomotor learning protocol during which subjects experienced an abruptly introduced rotational perturbation. Subjects received either visual feedback or reward feedback, or a combination of the two. Two different reward landscapes, where the reward decayed either linearly or cubically with distance from the target, were tested. Results demonstrate that it is possible to learn from reward feedback alone and that the combination of reward and sensory feedback accelerates learning. An analysis of the underlying mechanisms reveals that although reward feedback alone does not allow for sensorimotor remapping, it can nonetheless lead to broad generalization, highlighting a dissociation between remapping and generalization. Also, the combination of reward and sensory feedback accelerates learning without compromising sensorimotor remapping. These findings suggest that the use of reward feedback is a promising approach to either supplement or substitute sensory feedback in the development of improved neurorehabilitation techniques. More generally, they point to an important role played by reward in the motor learning process.

  7. Feedback: Focusing Attention on Engagement

    ERIC Educational Resources Information Center

    Price, Margaret; Handley, Karen; Millar, Jill

    2011-01-01

    Within many higher education systems there is a search for means to increase levels of student satisfaction with assessment feedback. This article suggests that the search is under way in the wrong place by concentrating on feedback as a product rather than looking more widely to feedback as a long-term dialogic process in which all parties are…

  8. Engaging Students with Audio Feedback

    ERIC Educational Resources Information Center

    Cann, Alan

    2014-01-01

    Students express widespread dissatisfaction with academic feedback. Teaching staff perceive a frequent lack of student engagement with written feedback, much of which goes uncollected or unread. Published evidence shows that audio feedback is highly acceptable to students but is underused. This paper explores methods to produce and deliver audio…

  9. Feedback: Part of a System

    ERIC Educational Resources Information Center

    Wiliam, Dylan

    2012-01-01

    Just as a thermostat adjusts room temperature, effective feedback helps maintain a supportive environment for learning. Because of the many factors affecting how recipients respond to feedback, research offers no simple prescription for making feedback work effectively. What works in one classroom for one teacher will not work for another teacher.…

  10. How to Give Professional Feedback

    ERIC Educational Resources Information Center

    Brookhart, Susan M.; Moss, Connie M.

    2015-01-01

    Professional learning "should be a joy," the authors write, "not an affliction." Feedback experts Brookhart and Moss show how professional feedback can best motivate educators to learn. Professional conversations should be dialogs between the teacher and the principal, and feedback should feed teacher professional learning…

  11. Reinforcement learning improves behaviour from evaluative feedback.

    PubMed

    Littman, Michael L

    2015-05-28

    Reinforcement learning is a branch of machine learning concerned with using experience gained through interacting with the world and evaluative feedback to improve a system's ability to make behavioural decisions. It has been called the artificial intelligence problem in a microcosm because learning algorithms must act autonomously to perform well and achieve their goals. Partly driven by the increasing availability of rich data, recent years have seen exciting advances in the theory and practice of reinforcement learning, including developments in fundamental technical areas such as generalization, planning, exploration and empirical methodology, leading to increasing applicability to real-life problems. PMID:26017443

  12. Reinforcement learning improves behaviour from evaluative feedback.

    PubMed

    Littman, Michael L

    2015-05-28

    Reinforcement learning is a branch of machine learning concerned with using experience gained through interacting with the world and evaluative feedback to improve a system's ability to make behavioural decisions. It has been called the artificial intelligence problem in a microcosm because learning algorithms must act autonomously to perform well and achieve their goals. Partly driven by the increasing availability of rich data, recent years have seen exciting advances in the theory and practice of reinforcement learning, including developments in fundamental technical areas such as generalization, planning, exploration and empirical methodology, leading to increasing applicability to real-life problems.

  13. Reinforcement learning improves behaviour from evaluative feedback

    NASA Astrophysics Data System (ADS)

    Littman, Michael L.

    2015-05-01

    Reinforcement learning is a branch of machine learning concerned with using experience gained through interacting with the world and evaluative feedback to improve a system's ability to make behavioural decisions. It has been called the artificial intelligence problem in a microcosm because learning algorithms must act autonomously to perform well and achieve their goals. Partly driven by the increasing availability of rich data, recent years have seen exciting advances in the theory and practice of reinforcement learning, including developments in fundamental technical areas such as generalization, planning, exploration and empirical methodology, leading to increasing applicability to real-life problems.

  14. DISTRIBUTED AMPLIFIER INCORPORATING FEEDBACK

    DOEpatents

    Bell, P.R. Jr.

    1958-10-21

    An improved distributed amplifier system employing feedback for stabilization is presented. In accordance with the disclosed invention, a signal to be amplified is applled to one end of a suitable terminated grid transmission line. At intervals along the transmission line, the signal is fed to stable, resistance-capacitance coupled amplifiers incorporating feedback loops therein. The output current from each amplifier is passed through an additional tube to minimize the electrostatic capacitance between the tube elements of the last stage of the amplifier, and fed to appropriate points on an output transmission line, similar to the grid line, but terminated at the opposite (input) end. The output taken from the unterminated end of the plate transmission line is proportional to the input voltage impressed upon the grid line.

  15. Polarization feedback laser stabilization

    DOEpatents

    Esherick, P.; Owyoung, A.

    1987-09-28

    A system for locking two Nd:YAG laser oscillators includes an optical path for feeding the output of one laser into the other with different polarizations. Elliptical polarization is incorporated into the optical path so that the change in polarization that occurs when the frequencies coincide may be detected to provide a feedback signal to control one laser relative to the other. 4 figs.

  16. Fiber distributed feedback laser

    NASA Technical Reports Server (NTRS)

    Elachi, C.; Evans, G. A.; Yeh, C. (Inventor)

    1976-01-01

    Utilizing round optical fibers as communication channels in optical communication networks presents the problem of obtaining a high efficiency coupling between the optical fiber and the laser. A laser is made an integral part of the optical fiber channel by either diffusing active material into the optical fiber or surrounding the optical fiber with the active material. Oscillation within the active medium to produce lasing action is established by grating the optical fiber so that distributed feedback occurs.

  17. Regenerative feedback resonant circuit

    DOEpatents

    Jones, A. Mark; Kelly, James F.; McCloy, John S.; McMakin, Douglas L.

    2014-09-02

    A regenerative feedback resonant circuit for measuring a transient response in a loop is disclosed. The circuit includes an amplifier for generating a signal in the loop. The circuit further includes a resonator having a resonant cavity and a material located within the cavity. The signal sent into the resonator produces a resonant frequency. A variation of the resonant frequency due to perturbations in electromagnetic properties of the material is measured.

  18. INITIATE: An Intelligent Adaptive Alert Environment.

    PubMed

    Jafarpour, Borna; Abidi, Samina Raza; Ahmad, Ahmad Marwan; Abidi, Syed Sibte Raza

    2015-01-01

    Exposure to a large volume of alerts generated by medical Alert Generating Systems (AGS) such as drug-drug interaction softwares or clinical decision support systems over-whelms users and causes alert fatigue in them. Some of alert fatigue effects are ignoring crucial alerts and longer response times. A common approach to avoid alert fatigue is to devise mechanisms in AGS to stop them from generating alerts that are deemed irrelevant. In this paper, we present a novel framework called INITIATE: an INtellIgent adapTIve AlerT Environment to avoid alert fatigue by managing alerts generated by one or more AGS. We have identified and categories the lifecycle of different alerts and have developed alert management logic as per the alerts' lifecycle. Our framework incorporates an ontology that represents the alert management strategy and an alert management engine that executes this strategy. Our alert management framework offers the following features: (1) Adaptability based on users' feedback; (2) Personalization and aggregation of messages; and (3) Connection to Electronic Medical Records by implementing a HL7 Clinical Document Architecture parser.

  19. Adaptive Criterion Setting in Perceptual Decision Making

    ERIC Educational Resources Information Center

    Stuttgen, Maik C.; Yildiz, Ali; Gunturkun, Onur

    2011-01-01

    Pigeons responded in a perceptual categorization task with six different stimuli (shades of gray), three of which were to be classified as "light" or "dark", respectively. Reinforcement probability for correct responses was varied from 0.2 to 0.6 across blocks of sessions and was unequal for correct light and dark responses. Introduction of a new…

  20. 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…

  1. An integrated architecture of adaptive neural network control for dynamic systems

    SciTech Connect

    Ke, Liu; Tokar, R.; Mcvey, B.

    1994-07-01

    In this study, an integrated neural network control architecture for nonlinear dynamic systems is presented. Most of the recent emphasis in the neural network control field has no error feedback as the control input which rises the adaptation problem. The integrated architecture in this paper combines feed forward control and error feedback adaptive control using neural networks. The paper reveals the different internal functionality of these two kinds of neural network controllers for certain input styles, e.g., state feedback and error feedback. Feed forward neural network controllers with state feedback establish fixed control mappings which can not adapt when model uncertainties present. With error feedbacks, neural network controllers learn the slopes or the gains respecting to the error feedbacks, which are error driven adaptive control systems. The results demonstrate that the two kinds of control scheme can be combined to realize their individual advantages. Testing with disturbances added to the plant shows good tracking and adaptation.

  2. Feedback on Feedback: Eliciting Learners' Responses to Written Feedback through Student-Generated Screencasts

    ERIC Educational Resources Information Center

    Fernández-Toro, María; Furnborough, Concha

    2014-01-01

    Despite the potential benefits of assignment feedback, learners often fail to use it effectively. This study examines the ways in which adult distance learners engage with written feedback on one of their assignments. Participants were 10 undergraduates studying Spanish at the Open University, UK. Their responses to feedback were elicited by means…

  3. Generalized Adaptive Artificial Neural Networks

    NASA Technical Reports Server (NTRS)

    Tawel, Raoul

    1993-01-01

    Mathematical model of supervised learning by artificial neural network provides for simultaneous adjustments of both temperatures of neurons and synaptic weights, and includes feedback as well as feedforward synaptic connections. Extension of mathematical model described in "Adaptive Neurons For Artificial Neural Networks" (NPO-17803). Dynamics of neural network represented in new model by less-restrictive continuous formalism.

  4. Adaptive Control Of Remote Manipulator

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun

    1989-01-01

    Robotic control system causes remote manipulator to follow closely reference trajectory in Cartesian reference frame in work space, without resort to computationally intensive mathematical model of robot dynamics and without knowledge of robot and load parameters. System, derived from linear multivariable theory, uses relatively simple feedforward and feedback controllers with model-reference adaptive control.

  5. A wireless sensory feedback system for real-time gait modification.

    PubMed

    Redd, Christian B; Bamberg, Stacy J Morris

    2011-01-01

    Current rehabilitation technology and techniques have proven effective at modifying and correcting gait abnormalities. They are however limited to laboratory and clinical settings, under the supervision of a specialist. Conventional techniques for quantifying gait asymmetries can be combined with sensory feedback methods to provide an intuitive and inexpensive feedback system for extra-clinical rehabilitation. A wireless feedback system has been designed to collect gait information, process it in real-time, and provide corrective feedback to the user. The corrective feedback can be presented through visual, audible, or vibrotactile methods, or a combination thereof. Initial results have led to improvement in the sensory interface of the device to maximize the corrective influence on inexperienced subjects. These preliminary findings suggest that the wireless feedback device can influence the gait of the user, and effectively adapt to their personal feedback preferences.

  6. Perfect and Near-Perfect Adaptation in Cell Signaling.

    PubMed

    Ferrell, James E

    2016-02-24

    Adaptation is an important basic feature of cellular regulation. Previous theoretical work has identified three types of circuits-negative feedback loops, incoherent feedforward systems, and state-dependent inactivation systems-that can achieve perfect or near-perfect adaptation. Recent work has added another strategy, termed antithetic integral feedback, to the list of motifs capable of robust perfect adaptation. Here, we discuss the properties, limitations, and biological relevance of each of these circuits. PMID:27135159

  7. Precipitation-Regulated Feedback

    NASA Astrophysics Data System (ADS)

    Voit, Mark

    2016-07-01

    Star formation in the central galaxies of galaxy clusters appears to be fueled by precipitation of cold clouds out of hot circumgalactic gas via thermal instability. I will present both observational and theoretical support for the precipitation mode in large galaxies and discuss how it can be implemented in cosmological simulations of galaxy evolution. Galaxy cluster cores are unique laboratories for studying the astrophysics of thermal instability and may be teaching us valuable lessons about how feedback works in galaxies spanning the entire mass spectrum.

  8. From Positivity to Negativity Bias: Ambiguity Affects the Neurophysiological Signatures of Feedback Processing.

    PubMed

    Gibbons, Henning; Schnuerch, Robert; Stahl, Jutta

    2016-04-01

    Previous studies on the neurophysiological underpinnings of feedback processing almost exclusively used low-ambiguity feedback, which does not fully address the diversity of situations in everyday life. We therefore used a pseudo trial-and-error learning task to investigate ERPs of low- versus high-ambiguity feedback. Twenty-eight participants tried to deduce the rule governing visual feedback to their button presses in response to visual stimuli. In the blocked condition, the same two feedback words were presented across several consecutive trials, whereas in the random condition feedback was randomly drawn on each trial from sets of five positive and five negative words. The feedback-related negativity (FRN-D), a frontocentral ERP difference between negative and positive feedback, was significantly larger in the blocked condition, whereas the centroparietal late positive complex indicating controlled attention was enhanced for negative feedback irrespective of condition. Moreover, FRN-D in the blocked condition was due to increased reward positivity (Rew-P) for positive feedback, rather than increased (raw) FRN for negative feedback. Our findings strongly support recent lines of evidence that the FRN-D, one of the most widely studied signatures of reinforcement learning in the human brain, critically depends on feedback discriminability and is primarily driven by the Rew-P. A novel finding concerned larger frontocentral P2 for negative feedback in the random but not the blocked condition. Although Rew-P points to a positivity bias in feedback processing under conditions of low feedback ambiguity, P2 suggests a specific adaptation of information processing in case of highly ambiguous feedback, involving an early negativity bias. Generalizability of the P2 findings was demonstrated in a second experiment using explicit valence categorization of highly emotional positive and negative adjectives. PMID:26765948

  9. Disconfirmatory feedback in families of schizophrenics.

    PubMed

    Holte, A; Wichstrøm, L

    1990-01-01

    A new approach to the study of family communication and psychopathology, in particular schizophrenia, using Saugstad's theory about use of language as its point of departure is presented. Conflicts between family members were observed and measured using a new unrevealed difference technique, the Colour Conflict Method (CCM). Communication was analysed in terms of continuous feedback processes, using the new computerized method, Confirmation-Disconfirmation Coding System (CONDIS). Feedback mechanisms in the internal communication of families of schizophrenics, normals, and non-schizophrenic pathological controls (n = 21) are described. The findings show that families of schizophrenics lack the ability to adapt their communication to changing situational requirements. When conflicts were introduced, families of schizophrenics-in contrast to non-schizophrenics within the extended schizophrenia spectrum and normals-increased their frequency of disconfirmatory feedback reactions instead of expressing disagreements openly. This was due to active disqualifications occurring between the parents and from the parents towards their schizophrenic offspring, who reacted with incomprehensible egocentric communication acts. PMID:2259901

  10. Torque feedback transmission

    SciTech Connect

    Whalen, B.L.

    1987-01-20

    This patent describes an infinitely variable transmission of inline configuration for interconnecting a primer mover with a load for clutch free operation in a range of speed including hydraulic neutral comprising: a. planetary gear train means having a ring gear, planetary gears supported by a planetary gear carrier, and a sun gear, the sun gear being connected mechanically to the load, output shaft means for joining the sun gear to the load; b. variable torque feedback means comprising (i) a variable displacement hydraulic motor whose rotor shaft is in line with the output shaft means and drivingly connected to the prime mover and the planetary gear carrier during the full range of operation of the transmission, and (ii) a fixed displacement hydraulic pump connected hydraulically to the motor, the rotor shaft of the pump being connected mechanically to the ring gear and being axially displaced from the output shaft means; c. means for adjusting the displacement volume within the hydraulic motor for controlling the torque feedback in the transmission to provide infinitely variable coupling between the prime mover and the load over the full range of the transmission including hydraulic neutral; d. a speed reducer between the primer mover and the motor rotor shaft and a speed multiplier between the sun gear and the load; and e. mechanical transmission assembly means between the speed multiplier and the load in line with the motor rotor shaft and the output shaft means for providing selection of drive, reverse, park, and neutral.

  11. Adaptive and Rational Anticipations in Risk Management Systems and Economy

    NASA Astrophysics Data System (ADS)

    Dubois, Daniel M.; Holmberg, Stig C.

    2010-11-01

    The global financial crisis of year 2009 is explained as a result of uncoordinated risk management decisions in business firms and economic organisations. The underlying reason for this can be found in the current financial system. As the financial market has lost much of its direct coupling to the concrete economy it provides misleading information to economic decision makers at all levels. Hence, the financial system has moved from a state of moderate and slow cyclical fluctuations into a state of fast and chaotic ones. Those misleading decisions can further be described, but not explained, by help of adaptive and rational expectations from macroeconomic theory. In this context, AE, the Adaptive Expectations are related to weak passive Exo-anticipation, and RE, the Rational expectations can be related to a strong, active and design oriented anticipation. The shortcomings of conventional cures, which builds on a reactive paradigm, have already been demonstrated in economic literature and are here further underlined by help of Ashby's "Law of Requisite Variety", Weaver's distinction between systems of "Disorganized Complexity" and those of "Organized Complexity", and Klir's "Reconstructability Analysis". Anticipatory decision-making is hence here proposed as a replacement to current expectation based and passive risk management. An anticipatory model of the business cycle is presented for supporting that proposition. The model, which is an extension of the Kaldor-Kalecki model, includes both retardation and anticipation. While cybernetics with the feedback process in control system deals with an explicit goal or purpose given to a system, the anticipatory system discussed here deals with a behaviour for which the future state of the system is built by the system itself, without explicit goal. A system with weak anticipation is based on a predictive model of the system, while a system with strong anticipation builds its own future by itself. Numerical simulations on

  12. Effects of different feedback types on information integration in repeated monetary gambles

    PubMed Central

    Haffke, Peter; Hübner, Ronald

    2015-01-01

    Most models of risky decision making assume that all relevant information is taken into account (e.g., von Neumann and Morgenstern, 1944; Kahneman and Tversky, 1979). However, there are also some models supposing that only part of the information is considered (e.g., Brandstätter et al., 2006; Gigerenzer and Gaissmaier, 2011). To further investigate the amount of information that is usually used for decision making, and how the use depends on feedback, we conducted a series of three experiments in which participants choose between two lotteries and where no feedback, outcome feedback, and error feedback was provided, respectively. The results show that without feedback participants mostly chose the lottery with the higher winning probability, and largely ignored the potential gains. The same results occurred when the outcome of each decision was fed back. Only after presenting error feedback (i.e., signaling whether a choice was optimal or not), participants considered probabilities as well as gains, resulting in more optimal choices. We propose that outcome feedback was ineffective, because of its probabilistic and ambiguous nature. Participants improve information integration only if provided with a consistent and deterministic signal such as error feedback. PMID:25667576

  13. Effects of different feedback types on information integration in repeated monetary gambles.

    PubMed

    Haffke, Peter; Hübner, Ronald

    2014-01-01

    Most models of risky decision making assume that all relevant information is taken into account (e.g., von Neumann and Morgenstern, 1944; Kahneman and Tversky, 1979). However, there are also some models supposing that only part of the information is considered (e.g., Brandstätter et al., 2006; Gigerenzer and Gaissmaier, 2011). To further investigate the amount of information that is usually used for decision making, and how the use depends on feedback, we conducted a series of three experiments in which participants choose between two lotteries and where no feedback, outcome feedback, and error feedback was provided, respectively. The results show that without feedback participants mostly chose the lottery with the higher winning probability, and largely ignored the potential gains. The same results occurred when the outcome of each decision was fed back. Only after presenting error feedback (i.e., signaling whether a choice was optimal or not), participants considered probabilities as well as gains, resulting in more optimal choices. We propose that outcome feedback was ineffective, because of its probabilistic and ambiguous nature. Participants improve information integration only if provided with a consistent and deterministic signal such as error feedback.

  14. Feedback control of waiting times

    NASA Astrophysics Data System (ADS)

    Brandes, Tobias; Emary, Clive

    2016-04-01

    Feedback loops are known as a versatile tool for controlling transport in small systems, which usually have large intrinsic fluctuations. Here we investigate the control of a temporal correlation function, the waiting-time distribution, under active and passive feedback conditions. We develop a general formalism and then specify to the simple unidirectional transport model, where we compare costs of open-loop and feedback control and use methods from optimal control theory to optimize waiting-time distributions.

  15. Fast feedback for linear colliders

    SciTech Connect

    Hendrickson, L.; Adolphsen, C.; Allison, S.; Gromme, T.; Grossberg, P.; Himel, T.; Krauter, K.; MacKenzie, R.; Minty, M.; Sass, R.

    1995-05-01

    A fast feedback system provides beam stabilization for the SLC. As the SLC is in some sense a prototype for future linear colliders, this system may be a prototype for future feedbacks. The SLC provides a good base of experience for feedback requirements and capabilities as well as a testing ground for performance characteristics. The feedback system controls a wide variety of machine parameters throughout the SLC and associated experiments, including regulation of beam position, angle, energy, intensity and timing parameters. The design and applications of the system are described, in addition to results of recent performance studies.

  16. Learning Rate Updating Methods Applied to Adaptive Fuzzy Equalizers for Broadband Power Line Communications

    NASA Astrophysics Data System (ADS)

    Ribeiro, Moisés V.

    2004-12-01

    This paper introduces adaptive fuzzy equalizers with variable step size for broadband power line (PL) communications. Based on delta-bar-delta and local Lipschitz estimation updating rules, feedforward, and decision feedback approaches, we propose singleton and nonsingleton fuzzy equalizers with variable step size to cope with the intersymbol interference (ISI) effects of PL channels and the hardness of the impulse noises generated by appliances and nonlinear loads connected to low-voltage power grids. The computed results show that the convergence rates of the proposed equalizers are higher than the ones attained by the traditional adaptive fuzzy equalizers introduced by J. M. Mendel and his students. Additionally, some interesting BER curves reveal that the proposed techniques are efficient for mitigating the above-mentioned impairments.

  17. Technical Adequacy of Response to Intervention Decisions

    ERIC Educational Resources Information Center

    VanDerHeyden, Amanda M.

    2011-01-01

    Perhaps the greatest value of response to intervention (RTI) as a decision framework is that it brings attention to variables (e.g., mastery of prerequisite skills, frequency of instructional corrective feedback, reinforcement schedules for correct responding) that if changed might make a meaningful difference for students (e.g., child rate of…

  18. What Drives Farmers to Make Top-Down or Bottom-Up Adaptation to Climate Change and Fluctuations? A Comparative Study on 3 Cases of Apple Farming in Japan and South Africa

    PubMed Central

    Fujisawa, Mariko; Kobayashi, Kazuhiko; Johnston, Peter; New, Mark

    2015-01-01

    Agriculture is one of the most vulnerable sectors to climate change. Farmers have been exposed to multiple stressors including climate change, and they have managed to adapt to those risks. The adaptation actions undertaken by farmers and their decision making are, however, only poorly understood. By studying adaptation practices undertaken by apple farmers in three regions: Nagano and Kazuno in Japan and Elgin in South Africa, we categorize the adaptation actions into two types: farmer initiated bottom-up adaptation and institution led top-down adaptation. We found that the driver which differentiates the type of adaptation likely adopted was strongly related to the farmers’ characteristics, particularly their dependence on the institutions, e.g. the farmers’ cooperative, in selling their products. The farmers who rely on the farmers’ cooperative for their sales are likely to adopt the institution-led adaptation, whereas the farmers who have established their own sales channels tend to start innovative actions by bottom-up. We further argue that even though the two types have contrasting features, the combinations of the both types of adaptations could lead to more successful adaptation particularly in agriculture. This study also emphasizes that more farm-level studies for various crops and regions are warranted to provide substantial feedbacks to adaptation policy. PMID:25822534

  19. What drives farmers to make top-down or bottom-up adaptation to climate change and fluctuations? A comparative study on 3 cases of apple farming in Japan and South Africa.

    PubMed

    Fujisawa, Mariko; Kobayashi, Kazuhiko; Johnston, Peter; New, Mark

    2015-01-01

    Agriculture is one of the most vulnerable sectors to climate change. Farmers have been exposed to multiple stressors including climate change, and they have managed to adapt to those risks. The adaptation actions undertaken by farmers and their decision making are, however, only poorly understood. By studying adaptation practices undertaken by apple farmers in three regions: Nagano and Kazuno in Japan and Elgin in South Africa, we categorize the adaptation actions into two types: farmer initiated bottom-up adaptation and institution led top-down adaptation. We found that the driver which differentiates the type of adaptation likely adopted was strongly related to the farmers' characteristics, particularly their dependence on the institutions, e.g. the farmers' cooperative, in selling their products. The farmers who rely on the farmers' cooperative for their sales are likely to adopt the institution-led adaptation, whereas the farmers who have established their own sales channels tend to start innovative actions by bottom-up. We further argue that even though the two types have contrasting features, the combinations of the both types of adaptations could lead to more successful adaptation particularly in agriculture. This study also emphasizes that more farm-level studies for various crops and regions are warranted to provide substantial feedbacks to adaptation policy.

  20. Distributed feedback lasers

    NASA Technical Reports Server (NTRS)

    Ladany, I.; Andrews, J. T.; Evans, G. A.

    1988-01-01

    A ridge waveguide distributed feedback laser was developed in InGaAsP. These devices have demonstrated CW output powers over 7 mW with threshold currents as low as 60 mA at 25 C. Measurements of the frequency response of these devices show a 3 dB bandwidth of about 2 GHz, which may be limited by the mount. The best devices have a single mode spectra over the entire temperature range tested with a side mode suppression of about 20 dB in both CW and pulsed modes. The design of this device, including detailed modeling of the ridge guide structure, effective index calculations, and a discussion of the grating configuration are presented. Also, the fabrication of the devices is presented in some detail, especially the fabrication of and subsequent growth over the grating. In addition, a high frequency fiber pigtailed package was designed and tested, which is a suitable prototype for a commercial package.