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  1. 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.

  2. Peircean Decision Aid

    Energy Science and Technology Software Center (ESTSC)

    2008-08-14

    The Peircean decision aid (PDA) is a decision support architecture and embedded functionality that supports a decision maker in very complex environments dealing with massive amounts of disparate data, information and knowledge. The solution generated is a hybrid system solution employing a number of technologies that are based on Peircean reasoning, modal logic, and formal concept analysis. The system convolves data/information with knowledge to create a virtual belief state that is passed to a decisionmore » maker for consideration. The system can capture categorized knowledge or it can inductively learn or acquire new knowledge from suites of observations. Captured knowledge is used to abductively generate hypotheses that are potential explanations to observations or collected data. The zero order modal logic architecture is designed to augment knowledge update and belief revision and can be extended to include disjunctive screening of collected data. While intended to be a library for integration into a decision support architecture it possesses a basic stand-alone GUI for use as an analysis support tool.« less

  3. 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.

  4. Decision-level adaptation in motion perception.

    PubMed

    Mather, George; Sharman, Rebecca J

    2015-12-01

    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

  5. 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

  6. 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

  7. 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.

  8. 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

  9. 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…

  10. 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…

  11. Adaptable history biases in human perceptual decisions.

    PubMed

    Abrahamyan, Arman; Silva, Laura Luz; Dakin, Steven C; Carandini, Matteo; Gardner, Justin L

    2016-06-21

    When making choices under conditions of perceptual uncertainty, past experience can play a vital role. However, it can also lead to biases that worsen decisions. Consistent with previous observations, we found that human choices are influenced by the success or failure of past choices even in a standard two-alternative detection task, where choice history is irrelevant. The typical bias was one that made the subject switch choices after a failure. These choice history biases led to poorer performance and were similar for observers in different countries. They were well captured by a simple logistic regression model that had been previously applied to describe psychophysical performance in mice. Such irrational biases seem at odds with the principles of reinforcement learning, which would predict exquisite adaptability to choice history. We therefore asked whether subjects could adapt their irrational biases following changes in trial order statistics. Adaptability was strong in the direction that confirmed a subject's default biases, but weaker in the opposite direction, so that existing biases could not be eradicated. We conclude that humans can adapt choice history biases, but cannot easily overcome existing biases even if irrational in the current context: adaptation is more sensitive to confirmatory than contradictory statistics. PMID:27330086

  12. Adaptive Decision Modeling in Wisconsin River Islands

    NASA Astrophysics Data System (ADS)

    Gyawali, R.; Greb, S. R.; Watkins, D. W., Jr.; Block, P.

    2014-12-01

    River islands in Wisconsin are of high ecological significance. Understanding of climate change impacts and appropriate management alternatives in these islands are of great interest to all stakeholders, including the State of Wisconsin and Bureau of Land Management (BLM) who have jurisdiction of these islands in WI. We use historical areal imagery to describe island dynamics and river morphometry, such as changes in island shape and size. Relationships of related changes are explored with concurrent changes in river flow regimes. In an effort to integrate climate change uncertainties into decision making, we demonstrate an application of a multistage adaptive decision making framework to Wisconsin River islands, with a particular emphasis on flood management and planning. The framework is comprised of hydro-climatic ensemble projections generated from CMIP5 climate model outputs and multiple hydrologic models, including statistical and physically based approaches.

  13. 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.

  14. 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.

  15. Maximal adaptive-decision speedups in quantum-state readout

    NASA Astrophysics Data System (ADS)

    D'Anjou, Benjamin; Kuret, Loutfi; Childress, Lilian; Coish, William A.

    The average time T required for high-fidelity readout of quantum states can be significantly reduced via a real-time adaptive decision rule. An adaptive decision rule stops the readout as soon as a desired level of confidence has been achieved, as opposed to setting a fixed readout time tf. The performance of the adaptive decision is characterized by the ``adaptive-decision speedup'', tf / T . In this work, we reformulate this readout problem in terms of the first-passage time of a particle undergoing stochastic motion. This formalism allows us to theoretically establish the maximum achievable adaptive-decision speedups for several physical two-state readout implementations. We show that for two common readout schemes (the Gaussian latching readout and a readout relying on state-dependent decay), the speedup is bounded by 4 and 2, respectively, in the limit of high single-shot readout fidelity. We experimentally study the achievable speedup in a real-world scenario by applying the adaptive decision rule to a readout of the nitrogen-vacancy-center (NV-center) charge state. We find a speedup of ~ 2 with our experimental parameters. Our results should lead to immediate improvements in nano-scale magnetometry based on spin-to-charge conversion of the NV-center spin. We acknowledge support from NSERC, INTRIQ, CIFAR and the Walter C. Sumner Foundation.

  16. 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…

  17. 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

  18. 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. PMID:26656389

  19. The Computer as Adaptive Instructional Decision Maker.

    ERIC Educational Resources Information Center

    Kopstein, Felix F.; Seidel, Robert J.

    The computer's potential for education, and most particularly for instruction, is contingent on the development of a class of instructional decision models (formal instructional strategies) that interact with the student through appropriate peripheral equipment (man-machine interfaces). Computer hardware and software by themselves should not be…

  20. 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

  1. 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

  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. Maximal Adaptive-Decision Speedups in Quantum-State Readout

    NASA Astrophysics Data System (ADS)

    D'Anjou, B.; Kuret, L.; Childress, L.; Coish, W. A.

    2016-01-01

    The average time T required for high-fidelity readout of quantum states can be significantly reduced via a real-time adaptive decision rule. An adaptive decision rule stops the readout as soon as a desired level of confidence has been achieved, as opposed to setting a fixed readout time tf . The performance of the adaptive decision is characterized by the "adaptive-decision speedup," tf/T . In this work, we reformulate this readout problem in terms of the first-passage time of a particle undergoing stochastic motion. This formalism allows us to theoretically establish the maximum achievable adaptive-decision speedups for several physical two-state readout implementations. We show that for two common readout schemes (the Gaussian latching readout and a readout relying on state-dependent decay), the speedup is bounded by 4 and 2, respectively, in the limit of high single-shot readout fidelity. We experimentally study the achievable speedup in a real-world scenario by applying the adaptive decision rule to a readout of the nitrogen-vacancy-center (NV-center) charge state. We find a speedup of ≈2 with our experimental parameters. In addition, we propose a simple readout scheme for which the speedup can, in principle, be increased without bound as the fidelity is increased. Our results should lead to immediate improvements in nanoscale magnetometry based on spin-to-charge conversion of the NV-center spin, and provide a theoretical framework for further optimization of the bandwidth of quantum measurements.

  4. Addressing the need for adaptable decision processes within healthcare software.

    PubMed

    Miseldine, P; Taleb-Bendiab, A; England, D; Randles, M

    2007-03-01

    In the healthcare sector, where the decisions made by software aid in the direct treatment of patients, software requires high levels of assurance to ensure the correct interpretation of the tasks it is automating. This paper argues that introducing adaptable decision processes within eHealthcare initiatives can reduce software-maintenance complexity and, due to the instantaneous, distributed deployment of decision models, allow for quicker updates of current best practice, thereby improving patient care. The paper provides a description of a collection of technologies and tools that can be used to provide the required adaptation in a decision process. These tools are evaluated against two case studies that individually highlight different requirements in eHealthcare: a breast-cancer decision-support system, in partnership with several of the UK's leading cancer hospitals, and a dental triage in partnership with the Royal Liverpool Hospital which both show how the complete process flow of software can be abstracted and adapted, and the benefits that arise as a result. PMID:17365643

  5. 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.

  6. Adaptive leadership: a novel approach for family decision making.

    PubMed

    Adams, Judith; Bailey, Donald E; Anderson, Ruth A; Galanos, Anthony N

    2013-03-01

    Family members of intensive care unit (ICU) patients want to be involved in decision making, but they may not be best served by being placed in the position of having to solve problems for which they lack knowledge and skills. This case report presents an exemplar family meeting in the ICU led by a palliative care specialist, with discussion about the strategies used to improve the capacity of the family to make a decision consistent with the patient's goals. These strategies are presented through the lens of Adaptive Leadership. PMID:22663140

  7. 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.

  8. An adaptive algorithm for modifying hyperellipsoidal decision surfaces

    SciTech Connect

    Kelly, P.M.; Hush, D.R.; White, J.M.

    1992-05-01

    The LVQ algorithm is a common method which allows a set of reference vectors for a distance classifier to adapt to a given training set. We have developed a similar learning algorithm, LVQ-MM, which manipulates hyperellipsoidal cluster boundaries as opposed to reference vectors. Regions of the input feature space are first enclosed by ellipsoidal decision boundaries, and then these boundaries are iteratively modified to reduce classification error. Results obtained by classifying the Iris data set are provided.

  9. An adaptive algorithm for modifying hyperellipsoidal decision surfaces

    SciTech Connect

    Kelly, P.M.; Hush, D.R. . Dept. of Electrical and Computer Engineering); White, J.M. )

    1992-01-01

    The LVQ algorithm is a common method which allows a set of reference vectors for a distance classifier to adapt to a given training set. We have developed a similar learning algorithm, LVQ-MM, which manipulates hyperellipsoidal cluster boundaries as opposed to reference vectors. Regions of the input feature space are first enclosed by ellipsoidal decision boundaries, and then these boundaries are iteratively modified to reduce classification error. Results obtained by classifying the Iris data set are provided.

  10. 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

  11. 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

  12. Dynamic adaptive learning for decision-making supporting systems

    NASA Astrophysics Data System (ADS)

    He, Haibo; Cao, Yuan; Chen, Sheng; Desai, Sachi; Hohil, Myron E.

    2008-03-01

    This paper proposes a novel adaptive learning method for data mining in support of decision-making systems. Due to the inherent characteristics of information ambiguity/uncertainty, high dimensionality and noisy in many homeland security and defense applications, such as surveillances, monitoring, net-centric battlefield, and others, it is critical to develop autonomous learning methods to efficiently learn useful information from raw data to help the decision making process. The proposed method is based on a dynamic learning principle in the feature spaces. Generally speaking, conventional approaches of learning from high dimensional data sets include various feature extraction (principal component analysis, wavelet transform, and others) and feature selection (embedded approach, wrapper approach, filter approach, and others) methods. However, very limited understandings of adaptive learning from different feature spaces have been achieved. We propose an integrative approach that takes advantages of feature selection and hypothesis ensemble techniques to achieve our goal. Based on the training data distributions, a feature score function is used to provide a measurement of the importance of different features for learning purpose. Then multiple hypotheses are iteratively developed in different feature spaces according to their learning capabilities. Unlike the pre-set iteration steps in many of the existing ensemble learning approaches, such as adaptive boosting (AdaBoost) method, the iterative learning process will automatically stop when the intelligent system can not provide a better understanding than a random guess in that particular subset of feature spaces. Finally, a voting algorithm is used to combine all the decisions from different hypotheses to provide the final prediction results. Simulation analyses of the proposed method on classification of different US military aircraft databases show the effectiveness of this method.

  13. 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

  14. 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

  15. Bayesian Decision Theory for Multi-Category Adaptive Testing

    NASA Astrophysics Data System (ADS)

    Marinagi, Catherine C.; Kaburlasos, Vassilis G.

    2008-09-01

    This work presents a method for item selection in adaptive tests based on Bayesian Decision Theory (BDT). Multiple categories of examinee's competence level are assumed. The method determines the probability an examinee belongs to each category using Bayesian statistics. Before starting a test, prior probabilities of an examinee are assumed. Then, each time an examinee responds to a single item, a new competence level is estimated "a-posteriori" using item response and prior probabilities values. A customized focus-of-attention vector of probabilities is estimated, which is used to draw the next item from the Item Bank. The latter vector considers both Personalized Cost and content balancing percentages of items.

  16. What Does It Take to Produce Interpretation? Informational, Peircean, and Code-Semiotic Views on Biosemiotics

    SciTech Connect

    Brier, Soren; Joslyn, Cliff A.

    2013-04-01

    This paper presents a critical analysis of code-semiotics, which we see as the latest attempt to create paradigmatic foundation for solving the question of the emergence of life and consciousness. We view code semiotics as a an attempt to revise the empirical scientific Darwinian paradigm, and to go beyond the complex systems, emergence, self-organization, and informational paradigms, and also the selfish gene theory of Dawkins and the Peircean pragmaticist semiotic theory built on the simultaneous types of evolution. As such it is a new and bold attempt to use semiotics to solve the problems created by the evolutionary paradigm’s commitment to produce a theory of how to connect the two sides of the Cartesian dualistic view of physical reality and consciousness in a consistent way.

  17. 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

  18. 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

  19. 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.

  20. 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

  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. Automated mechanical ventilation: adapting decision making to different disease states.

    PubMed

    Lozano-Zahonero, S; Gottlieb, D; Haberthür, C; Guttmann, J; Möller, K

    2011-03-01

    The purpose of the present study is to introduce a novel methodology for adapting and upgrading decision-making strategies concerning mechanical ventilation with respect to different disease states into our fuzzy-based expert system, AUTOPILOT-BT. The special features are: (1) Extraction of clinical knowledge in analogy to the daily routine. (2) An automated process to obtain the required information and to create fuzzy sets. (3) The controller employs the derived fuzzy rules to achieve the desired ventilation status. For demonstration this study focuses exclusively on the control of arterial CO(2) partial pressure (p(a)CO(2)). Clinical knowledge from 61 anesthesiologists was acquired using a questionnaire from which different disease-specific fuzzy sets were generated to control p(a)CO(2). For both, patients with healthy lung and with acute respiratory distress syndrome (ARDS) the fuzzy sets show different shapes. The fuzzy set "normal", i.e., "target p(a)CO(2) area", ranges from 35 to 39 mmHg for healthy lungs and from 39 to 43 mmHg for ARDS lungs. With the new fuzzy sets our AUTOPILOT-BT reaches the target p(a)CO(2) within maximal three consecutive changes of ventilator settings. Thus, clinical knowledge can be extended, updated, and the resulting mechanical ventilation therapies can be individually adapted, analyzed, and evaluated. PMID:21069471

  3. A decision-making framework for adaptive pain management.

    PubMed

    Lin, Ching-Feng; LeBoulluec, Aera Kim; Zeng, Li; Chen, Victoria C P; Gatchel, Robert J

    2014-09-01

    Pain management is a critical international health issue. The Eugene McDermott Center for Pain Management at The University of Texas Southwestern Medical Center conducted a two-stage interdisciplinary pain management program that considers a wide variety of treatments. Prior to treatment (beginning of Stage 1), an evaluation records the patient's pain characteristics, medical history and related health parameters. A treatment regime is then determined. At the midpoint of the program (beginning of Stage 2), an evaluation is conducted to determine if an adjustment in the treatment should be made. A final evaluation is conducted at the end of the program to assess final outcomes. We structure this decision-making process using dynamic programming (DP) to generate adaptive treatment strategies for this two-stage program. An approximate DP solution method is employed in which state transition models are constructed empirically based on data from the pain management program, and the future value function is approximated using state space discretization based on a Latin hypercube design and artificial neural networks. The optimization seeks for treatment plans that minimize treatment dosage and pain levels simultaneously. PMID:23974825

  4. 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…

  5. An MPEG-21-driven multimedia adaptation decision-taking engine based on constraint satisfaction problem

    NASA Astrophysics Data System (ADS)

    Feng, Xiao; Tang, Rui-chun; Zhai, Yi-li; Feng, Yu-qing; Hong, Bo-hai

    2013-07-01

    Multimedia adaptation decision-taking techniques based on context are considered. Constraint satisfaction problem-Based Content Adaptation Algorithm (CBCAA) is proposed. First the algorithm obtains and classifies context information using MPEG-21; then it builds the constraint model according to different types of context information, constraint satisfaction method is used to acquire Media Description Decision Set (MDDS); finally a bit-stream adaptation engine performs the multimedia transcoding. Simulation results prove that the presented algorithm offers an efficient solution for personalized multimedia adaptation in heterogeneous environments.

  6. 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...

  7. Conservation program participation and adaptive rangeland decision-making

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper analyzes rancher participation in conservation programs in the context of a social-ecological framework for adaptive rangeland management. We argue that conservation programs are best understood as one of many strategies of adaptively managing rangelands in ways that sustain livelihoods a...

  8. Confidence in Pass/Fail Decisions for Computer Adaptive and Paper and Pencil Examinations.

    ERIC Educational Resources Information Center

    Bergstrom, Betty A.; Lunz, Mary E.

    The level of confidence in pass/fail decisions obtained with computer adaptive tests (CATs) was compared to decisions based on paper-and-pencil tests. Subjects included 645 medical technology students from 238 educational programs across the country. The tests used in this study constituted part of the subjects' review for the certification…

  9. 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

  10. Toolbox or adjustable spanner? A critical comparison of two metaphors for adaptive decision making.

    PubMed

    Söllner, Anke; Bröder, Arndt

    2016-02-01

    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 uniform mechanism is employed but is adapted to the environmental change (adjustable spanner metaphor). Despite recent claims that the frameworks are hard to disentangle empirically, both metaphors make distinct predictions concerning the information acquisition behavior, namely, that search is terminated according to the selected strategy (MSMs) or that information is acquired until an evidence threshold is passed (EAMs). In 3 experiments, we contrasted these predictions by providing participants with different degrees of evidence in a half-open/half-closed information board. For the majority of participants, we find that their stopping behavior is well captured by the notion of an evidence threshold that is either undercut or passed by the given evidence. PMID:26375785

  11. Medical alert management: a real-time adaptive decision support tool to reduce alert fatigue.

    PubMed

    Lee, Eva K; Wu, Tsung-Lin; Senior, Tal; Jose, James

    2014-01-01

    With the adoption of electronic medical records (EMRs), drug safety alerts are increasingly recognized as valuable tools for reducing adverse drug events and improving patient safety. However, even with proper tuning of the EMR alert parameters, the volume of unfiltered alerts can be overwhelming to users. In this paper, we design an adaptive decision support tool in which past cognitive overriding decisions of users are learned, adapted and used for filtering actions to be performed on current alerts. The filters are designed and learned based on a moving time window, number of alerts, overriding rates, and monthly overriding fluctuations. Using alerts from two separate years to derive filters and test performance, predictive accuracy rates of 91.3%-100% are achieved. The moving time window works better than a static training approach. It allows continuous learning and capturing of the most recent decision characteristics and seasonal variations in drug usage. The decision support system facilitates filtering of non-essential alerts and adaptively learns critical alerts and highlights them prominently to catch providers' attention. The tool can be plugged into an existing EMR system as an add-on, allowing real-time decision support to users without interfering with existing EMR functionalities. By automatically filtering the alerts, the decision support tool mitigates alert fatigue and allows users to focus resources on potentially vital alerts, thus reducing the occurrence of adverse drug events. PMID:25954391

  12. 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.

  13. 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…

  14. Reversible and Noisy Progression towards a Commitment Point Enables Adaptable and Reliable Cellular Decision-Making

    PubMed Central

    Garcia-Ojalvo, Jordi; Süel, Gürol M.

    2011-01-01

    Cells must make reliable decisions under fluctuating extracellular conditions, but also be flexible enough to adapt to such changes. How cells reconcile these seemingly contradictory requirements through the dynamics of cellular decision-making is poorly understood. To study this issue we quantitatively measured gene expression and protein localization in single cells of the model organism Bacillus subtilis during the progression to spore formation. We found that sporulation proceeded through noisy and reversible steps towards an irreversible, all-or-none commitment point. Specifically, we observed cell-autonomous and spontaneous bursts of gene expression and transient protein localization events during sporulation. Based on these measurements we developed mathematical population models to investigate how the degree of reversibility affects cellular decision-making. In particular, we evaluated the effect of reversibility on the 1) reliability in the progression to sporulation, and 2) adaptability under changing extracellular stress conditions. Results show that reversible progression allows cells to remain responsive to long-term environmental fluctuations. In contrast, the irreversible commitment point supports reliable execution of cell fate choice that is robust against short-term reductions in stress. This combination of opposite dynamic behaviors (reversible and irreversible) thus maximizes both adaptable and reliable decision-making over a broad range of changes in environmental conditions. These results suggest that decision-making systems might employ a general hybrid strategy to cope with unpredictably fluctuating environmental conditions. PMID:22102806

  15. 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.

  16. 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…

  17. 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

  18. 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

  19. Demosaicing: heterogeneity-projection hard-decision adaptive interpolation using spectral-spatial correlation

    NASA Astrophysics Data System (ADS)

    Tsai, Chi-Yi; Song, Kai-Tai

    2006-02-01

    A novel heterogeneity-projection hard-decision adaptive interpolation (HPHD-AI) algorithm is proposed in this paper for color reproduction from Bayer mosaic images. The proposed algorithm aims to estimate the optimal interpolation direction and perform hard-decision interpolation, in which the decision is made before interpolation. To do so, a new heterogeneity-projection scheme based on spectral-spatial correlation is proposed to decide the best interpolation direction from the original mosaic image directly. Exploiting the proposed heterogeneity-projection scheme, a hard-decision rule can be designed easily to perform the interpolation. We have compared this technique with three recently proposed demosaicing techniques: Lu's, Gunturk's and Li's methods, by utilizing twenty-five natural images from Kodak PhotoCD. The experimental results show that HPHD-AI outperforms all of them in both PSNR values and S-CIELab ▵Ε* ab measures.

  20. [Decision making satisfaction in health scale: instrument adapted and validated to Portuguese].

    PubMed

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

    2014-01-01

    Decision making is an area of health research that has gained importance both for the partnership models of care that give prominence to the patient and family, either by growing concern about quality and customer satisfaction with the care provided. So we decided to make the cultural adaptation and to evaluate the psychometric properties of the Portuguese version "The Satisfaction with Decision Scale" de Holmes-Rovner (1996), which aims to assess satisfaction with the decisions taken in health. The sample consisted of 521 nursing students the School of Nursing of Porto. The results of reliability tests show good internal consistency for the total items (Alpha Cronbach = 0.88). The psychometric study allows us to state that the Portuguese version of "The Satisfaction with Decision Scale", we call "Escala da Satisfação com a Decisão em Saúde", is an instrument comparable with the original in terms of validity and reliability. PMID:25590878

  1. A Bayesian decision-theoretic sequential response-adaptive randomization design.

    PubMed

    Jiang, Fei; Jack Lee, J; Müller, Peter

    2013-05-30

    We propose a class of phase II clinical trial designs with sequential stopping and adaptive treatment allocation to evaluate treatment efficacy. Our work is based on two-arm (control and experimental treatment) designs with binary endpoints. Our overall goal is to construct more efficient and ethical randomized phase II trials by reducing the average sample sizes and increasing the percentage of patients assigned to the better treatment arms of the trials. The designs combine the Bayesian decision-theoretic sequential approach with adaptive randomization procedures in order to achieve simultaneous goals of improved efficiency and ethics. The design parameters represent the costs of different decisions, for example, the decisions for stopping or continuing the trials. The parameters enable us to incorporate the actual costs of the decisions in practice. The proposed designs allow the clinical trials to stop early for either efficacy or futility. Furthermore, the designs assign more patients to better treatment arms by applying adaptive randomization procedures. We develop an algorithm based on the constrained backward induction and forward simulation to implement the designs. The algorithm overcomes the computational difficulty of the backward induction method, thereby making our approach practicable. The designs result in trials with desirable operating characteristics under the simulated settings. Moreover, the designs are robust with respect to the response rate of the control group. PMID:23315678

  2. CREB1 Genotype Modulates Adaptive Reward-Based Decisions in Humans.

    PubMed

    Wolf, Claudia; Mohr, Holger; Diekhof, Esther K; Vieker, Henning; Goya-Maldonado, Roberto; Trost, Sarah; Krämer, Bernd; Keil, Maria; Binder, Elisabeth B; Gruber, Oliver

    2016-07-01

    Cyclic AMP response element-binding protein (CREB) contributes to adaptation of mesocorticolimbic networks by modulating activity-regulated transcription and plasticity in neurons. Activity or expression changes of CREB in the nucleus accumbens (NAc) and orbital frontal cortex (OFC) interact with behavioral changes during reward-motivated learning. However, these findings from animal models have not been evaluated in humans. We tested whether CREB1 genotypes affect reward-motivated decisions and related brain activation, using BOLD fMRI in 224 young and healthy participants. More specifically, participants needed to adapt their decision to either pursue or resist immediate rewards to optimize the reward outcome. We found significant CREB1 genotype effects on choices to pursue increases of the reward outcome and on BOLD signal in the NAc, OFC, insula cortex, cingulate gyrus, hippocampus, amygdala, and precuneus during these decisions in comparison with those decisions avoiding total reward loss. Our results suggest that CREB1 genotype effects in these regions could contribute to individual differences in reward- and associative memory-based decision-making. PMID:26045569

  3. 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

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

    PubMed Central

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

    2015-01-01

    Control engineering offers a systematic and efficient method to optimize the effectiveness of individually tailored treatment and prevention policies known as adaptive or “just-in-time” behavioral interventions. The nature of these interventions requires assigning dosages at categorical levels, which has been addressed in prior work using Mixed Logical Dynamical (MLD)-based hybrid model predictive control (HMPC) schemes. However, certain requirements of adaptive behavioral interventions that involve sequential decision making have not been comprehensively explored in the literature. This paper presents an extension of the traditional MLD framework for HMPC by representing the requirements of sequential decision policies as mixed-integer linear constraints. This is accomplished with user-specified dosage sequence tables, manipulation of one input at a time, and a switching time strategy for assigning dosages at time intervals less frequent than the measurement sampling interval. A model developed for a gestational weight gain (GWG) intervention is used to illustrate the generation of these sequential decision policies and their effectiveness for implementing adaptive behavioral interventions involving multiple components. PMID:25635157

  5. Enhanced adaptive management: integrating decision analysis, scenario analysis and environmental modeling for the Everglades.

    PubMed

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

    2013-01-01

    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. PMID:24113217

  6. 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.

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

    PubMed Central

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

    2013-01-01

    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. PMID:24113217

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. Mice and rats achieve similar levels of performance in an adaptive decision-making task

    PubMed Central

    Jaramillo, Santiago; Zador, Anthony M.

    2014-01-01

    Two opposing constraints exist when choosing a model organism for studying the neural basis of adaptive decision-making: (1) experimental access and (2) behavioral complexity. Available molecular and genetic approaches for studying neural circuits in the mouse fulfill the first requirement. In contrast, it is still under debate if mice can perform cognitive tasks of sufficient complexity. Here we compare learning and performance of mice and rats, the preferred behavioral rodent model, during an acoustic flexible categorization two-alternative choice task. The task required animals to switch between two categorization definitions several times within a behavioral session. We found that both species achieved similarly high performance levels. On average, rats learned the task faster than mice, although some mice were as fast as the average rat. No major differences in subjective categorization boundaries or the speed of adaptation between the two species were found. Our results demonstrate that mice are an appropriate model for the study of the neural mechanisms underlying adaptive decision-making, and suggest they might be suitable for other cognitive tasks as well. PMID:25278849

  13. 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

  14. 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

  15. Participation in Decision Making as a Property of Complex Adaptive Systems: Developing and Testing a Measure

    PubMed Central

    Anderson, Ruth A.; Hsieh, Pi-Ching; Su, Hui Fang; Landerman, Lawrence R.; McDaniel, Reuben R.

    2013-01-01

    Objectives. To (1) describe participation in decision-making as a systems-level property of complex adaptive systems and (2) present empirical evidence of reliability and validity of a corresponding measure. Method. Study 1 was a mail survey of a single respondent (administrators or directors of nursing) in each of 197 nursing homes. Study 2 was a field study using random, proportionally stratified sampling procedure that included 195 organizations with 3,968 respondents. Analysis. In Study 1, we analyzed the data to reduce the number of scale items and establish initial reliability and validity. In Study 2, we strengthened the psychometric test using a large sample. Results. Results demonstrated validity and reliability of the participation in decision-making instrument (PDMI) while measuring participation of workers in two distinct job categories (RNs and CNAs). We established reliability at the organizational level aggregated items scores. We established validity of the multidimensional properties using convergent and discriminant validity and confirmatory factor analysis. Conclusions. Participation in decision making, when modeled as a systems-level property of organization, has multiple dimensions and is more complex than is being traditionally measured. Managers can use this model to form decision teams that maximize the depth and breadth of expertise needed and to foster connection among them. PMID:24349771

  16. Training complexity is not decisive factor for improving adaptation to visual sensory conflict.

    PubMed

    Yang, Yang; Pu, Fang; Li, Shuyu; Li, Yan; Li, Deyu; Fan, Yubo

    2012-01-01

    Ground-based preflight training utilizing unusual visual stimuli is useful for decreasing the susceptibility to space motion sickness (SMS). The effectiveness of the sensorimotor adaptation training is affected by the training tasks, but what kind of task is more effective remains unknown. Whether the complexity is the decisive factor to consider for designing the training and if other factors are more important need to be analyzed. The results from the analysis can help to optimize the preflight training tasks for astronauts. Twenty right-handed subjects were asked to draw the right path of 45° rotated maze before and after 30 min training. Subjects wore an up-down reversing prism spectacle in test and training sessions. Two training tasks were performed: drawing the right path of the horizontal maze (complex task but with different orientation feature) and drawing the L-shape lines (easy task with same orientation feature). The error rate and the executing time were measured during the test. Paired samples t test was used to compare the effects of the two training tasks. After each training, the error rate and the executing time were significantly decreased. However, the training effectiveness of the easy task was better as the test was finished more quickly and accurately. The complexity is not always the decisive factor for designing the adaptation training task, e.g. the orientation feature is more important in this study. In order to accelerate the adaptation and to counter SMS, the task for astronauts preflight adaptation training could be simple activities with the key features. PMID:23366702

  17. 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

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

    PubMed

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

    2016-06-01

    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

  19. 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

  20. 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

  1. 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.

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

    PubMed Central

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

    2013-01-01

    Purpose Introducing new health technologies, including medical devices, into a local setting in a safe, effective, and transparent manner is a complex process, involving many disciplines and players within an organization. Decision making should be systematic, consistent, and transparent. It should involve translating and integrating scientific evidence, such as health technology assessment (HTA) reports, with context-sensitive evidence to develop recommendations on whether and under what conditions a new technology will be introduced. However, the development of a program to support such decision making can require considerable time and resources. An alternative is to adapt a preexisting program to the new setting. Materials and methods We describe a framework for adapting the Local HTA Decision Support Program, originally developed by the Department of Surgery and Surgical Services (Calgary, AB, Canada), for use by other departments. The framework consists of six steps: 1) development of a program review and adaptation manual, 2) education and readiness assessment of interested departments, 3) evaluation of the program by individual departments, 4) joint evaluation via retreats, 5) synthesis of feedback and program revision, and 6) evaluation of the adaptation process. Results Nine departments revised the Local HTA Decision Support Program and expressed strong satisfaction with the adaptation process. Key elements for success were identified. Conclusion Adaptation of a preexisting program may reduce duplication of effort, save resources, raise the health care providers’ awareness of HTA, and foster constructive stakeholder engagement, which enhances the legitimacy of evidence-informed recommendations for introducing new health technologies. We encourage others to use this framework for program adaptation and to report their experiences. PMID:24273415

  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. PMID:15843735

  4. 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…

  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. 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

  7. Assessment of regional climate change and development of climate adaptation decision aids in the Southwestern US

    NASA Astrophysics Data System (ADS)

    Darmenova, K.; Higgins, G.; Kiley, H.; Apling, D.

    2010-12-01

    Current General Circulation Models (GCMs) provide a valuable estimate of both natural and anthropogenic climate changes and variability on global scales. At the same time, future climate projections calculated with GCMs are not of sufficient spatial resolution to address regional needs. Many climate impact models require information at scales of 50 km or less, so dynamical downscaling is often used to estimate the smaller-scale information based on larger scale GCM output. To address current deficiencies in local planning and decision making with respect to regional climate change, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model and developing decision aids that translate the regional climate data into actionable information for users. Our methodology involves development of climatological indices of extreme weather and heating/cooling degree days based on WRF ensemble runs initialized with the NCEP-NCAR reanalysis and the European Center/Hamburg Model (ECHAM5). Results indicate that the downscale simulations provide the necessary detailed output required by state and local governments and the private sector to develop climate adaptation plans. In addition we evaluated the WRF performance in long-term climate simulations over the Southwestern US and validated against observational datasets.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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 ...

  13. 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

  14. 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.

  15. 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

  16. Adaptive Flexibility and Maladaptive Routines in Selecting Fast and Frugal Decision Strategies

    ERIC Educational Resources Information Center

    Broder, Arndt; Schiffer, Stefanie

    2006-01-01

    Decision routines unburden the cognitive capacity of the decision maker. In changing environments, however, routines may become maladaptive. In 2 experiments with a hypothetical stock market game (n = 241), the authors tested whether decision routines tend to persist at the level of decision strategies rather than at the level of options in…

  17. 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. PMID:24468187

  18. Event-based knowledge elicitation of operating room management decision-making using scenarios adapted from information systems data

    PubMed Central

    2011-01-01

    Background No systematic process has previously been described for a needs assessment that identifies the operating room (OR) management decisions made by the anesthesiologists and nurse managers at a facility that do not maximize the efficiency of use of OR time. We evaluated whether event-based knowledge elicitation can be used practically for rapid assessment of OR management decision-making at facilities, whether scenarios can be adapted automatically from information systems data, and the usefulness of the approach. Methods A process of event-based knowledge elicitation was developed to assess OR management decision-making that may reduce the efficiency of use of OR time. Hypothetical scenarios addressing every OR management decision influencing OR efficiency were created from published examples. Scenarios are adapted, so that cues about conditions are accurate and appropriate for each facility (e.g., if OR 1 is used as an example in a scenario, the listed procedure is a type of procedure performed at the facility in OR 1). Adaptation is performed automatically using the facility's OR information system or anesthesia information management system (AIMS) data for most scenarios (43 of 45). Performing the needs assessment takes approximately 1 hour of local managers' time while they decide if their decisions are consistent with the described scenarios. A table of contents of the indexed scenarios is created automatically, providing a simple version of problem solving using case-based reasoning. For example, a new OR manager wanting to know the best way to decide whether to move a case can look in the chapter on "Moving Cases on the Day of Surgery" to find a scenario that describes the situation being encountered. Results Scenarios have been adapted and used at 22 hospitals. Few changes in decisions were needed to increase the efficiency of use of OR time. The few changes were heterogeneous among hospitals, showing the usefulness of individualized assessments

  19. 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

  20. 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

  1. 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

  2. Evidence-based decision-making in healthcare: exploring the issues though the lens of complex, adaptive systems theory.

    PubMed

    Lindstrom, Ronald R

    2003-01-01

    Browman, Snider and Ellis have articulated several reasons as to why and how managers should address the implementation of evidence-based decision-making (EBDM) in healthcare. While their observations are acknowledged to be from the unique perspective of an oncology setting, this is a timely and welcome lead article with significance in other settings. The authors invite opinions on transferability, thus forming the basis of this commentary. In response, this commentary offers a number of supportive and differing views. Complex, adaptive systems (CAS) theory is first addressed as an appropriate lens to reframe our conceptualization of the health system. Then, in contrast to negotiation, dialogue through participatory planning and decision-making is introduced. Evidence-based decision-making (EBDM) and knowledge translation (KT) are expanded upon in the context of CAS and participatory environments. Finally, concrete suggestions are offered on how to structure multiple-stakeholder involvement in the decision-making process, including the growing role of consumers in the new complex, adaptive systems reality of healthcare. PMID:12811085

  3. 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

  4. 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

  5. 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.

  6. 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

  7. 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…

  8. A novel clinical decision support system using improved adaptive genetic algorithm for the assessment of fetal well-being.

    PubMed

    Ravindran, Sindhu; Jambek, Asral Bahari; Muthusamy, Hariharan; 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

  9. 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

  10. 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

  11. 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

  12. 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.

  13. 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. PMID:24328496

  14. 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.

  15. 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…

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

    NASA Astrophysics Data System (ADS)

    Chang, Hsien-cheng; Kopaska-Merkel, David C.; Chen, Hui-Chuan; Durrans, S. Rocky

    2000-06-01

    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 categorical 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%.

  17. 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.

  18. 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

  19. Adaptation.

    PubMed

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  20. 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

  1. Supervised domain adaptation of decision forests: Transfer of models trained in vitro for in vivo intravascular ultrasound tissue characterization.

    PubMed

    Conjeti, Sailesh; Katouzian, Amin; Roy, Abhijit Guha; Peter, Loïc; Sheet, Debdoot; Carlier, Stéphane; Laine, Andrew; Navab, Nassir

    2016-08-01

    In this paper, we propose a supervised domain adaptation (DA) framework for adapting decision forests in the presence of distribution shift between training (source) and testing (target) domains, given few labeled examples. We introduce a novel method for DA through an error-correcting hierarchical transfer relaxation scheme with domain alignment, feature normalization, and leaf posterior reweighting to correct for the distribution shift between the domains. For the first time we apply DA to the challenging problem of extending in vitro trained forests (source domain) for in vivo applications (target domain). The proof-of-concept is provided for in vivo characterization of atherosclerotic tissues using intravascular ultrasound signals, where presence of flowing blood is a source of distribution shift between the two domains. This potentially leads to misclassification upon direct deployment of in vitro trained classifier, thus motivating the need for DA as obtaining reliable in vivo training labels is often challenging if not infeasible. Exhaustive validations and parameter sensitivity analysis substantiate the reliability of the proposed DA framework and demonstrates improved tissue characterization performance for scenarios where adaptation is conducted in presence of only a few examples. The proposed method can thus be leveraged to reduce annotation costs and improve computational efficiency over conventional retraining approaches. PMID:27035487

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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

  7. 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

  8. The evolution of error: error management, cognitive constraints, and adaptive decision-making biases.

    PubMed

    Johnson, Dominic D P; Blumstein, Daniel T; Fowler, James H; Haselton, Martie G

    2013-08-01

    Counterintuitively, biases in behavior or cognition can improve decision making. Under conditions of uncertainty and asymmetric costs of 'false-positive' and 'false-negative' errors, biases can lead to mistakes in one direction but - in so doing - steer us away from more costly mistakes in the other direction. For example, we sometimes think sticks are snakes (which is harmless), but rarely that snakes are sticks (which can be deadly). We suggest that 'error management' biases: (i) have been independently identified by multiple interdisciplinary studies, suggesting the phenomenon is robust across domains, disciplines, and methodologies; (ii) represent a general feature of life, with common sources of variation; and (iii) offer an explanation, in error management theory (EMT), for the evolution of cognitive biases as the best way to manage errors under cognitive and evolutionary constraints. PMID:23787087

  9. 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.

  10. 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.

  11. 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.

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

    PubMed

    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 (12-16years) 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

  13. 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

  14. 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.

  15. Decision making as community adaptation: a case study of emergency managers in Oklahoma.

    PubMed

    Donner, William R

    2008-06-01

    This paper explores how emergency managers make judgments regarding long-term policy and offers a sociological account of organisational decision making within an ecological context. Discussions with emergency managers focusing on the relative merits of rainfall estimation and tornado detection served as data with which to address these issues. Among the 39 interviewees, a consensus emerged favouring tornado detection over rainfall estimation. From these findings, the paper attempts to understand why emergency managers prefer tornado detection to rainfall estimation and to develop theoretical generalisations explaining trends in these preferences. When developing long-term policy, analysis of transcripts revealed emergency managers to be most concerned with the relative uncertainty of hazards, the capabilities of technology in hazard mitigation, and how the public perceives environmental threats. Given the environmental, technological, and social concerns reflected in this reasoning, there appears to be a strong ecological context driving the need for tornado detection among emergency managers. Implications and concerns are presented in the final section. PMID:18380856

  16. Distributed leadership and adaptive decision-making in the ant Tetramorium caespitum.

    PubMed

    Collignon, B; Detrain, C

    2010-04-22

    In the ant species Tetramorium caespitum, communication and foraging patterns rely on group-mass recruitment. Scouts having discovered food recruit nestmates and behave as leaders by guiding groups of recruits to the food location. After a while, a mass recruitment takes place in which foragers follow a chemical trail. Since group recruitment is crucial to the whole foraging process, we investigated whether food characteristics induce a tuning of recruiting stimuli by leaders that act upon the dynamics and size of recruited groups. High sucrose concentration triggers the exit of a higher number of groups that contain twice as many ants and reach the food source twice as fast than towards a weakly concentrated one. Similar trends were found depending on food accessibility: for a cut mealworm, accessibility to haemolymph results in a faster formation of larger groups than for an entire mealworm. These data provide the background for developing a stochastic model accounting for exploitation patterns by group-mass recruiting species. This model demonstrates how the modulations performed by leaders drive the colony to select the most profitable food source among several ones. Our results highlight how a minority of individuals can influence collective decisions in societies based on a distributed leadership. PMID:20031990

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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. PMID:20971546

  3. A reevaluation of achromatic spatio-temporal vision: Nonoriented filters are monocular, they adapt, and can be used for decision making at high flicker speeds

    PubMed Central

    Meese, Tim S; Baker, Daniel H

    2011-01-01

    Masking, adaptation, and summation paradigms have been used to investigate the characteristics of early spatio-temporal vision. Each has been taken to provide evidence for (i) oriented and (ii) nonoriented spatial-filtering mechanisms. However, subsequent findings suggest that the evidence for nonoriented mechanisms has been misinterpreted: those experiments might have revealed the characteristics of suppression (eg, gain control), not excitation, or merely the isotropic subunits of the oriented detecting mechanisms. To shed light on this, we used all three paradigms to focus on the ‘high-speed’ corner of spatio-temporal vision (low spatial frequency, high temporal frequency), where cross-oriented achromatic effects are greatest. We used flickering Gabor patches as targets and a 2IFC procedure for monocular, binocular, and dichoptic stimulus presentations. To account for our results, we devised a simple model involving an isotropic monocular filter-stage feeding orientation-tuned binocular filters. Both filter stages are adaptable, and their outputs are available to the decision stage following nonlinear contrast transduction. However, the monocular isotropic filters (i) adapt only to high-speed stimuli—consistent with a magnocellular subcortical substrate—and (ii) benefit decision making only for high-speed stimuli (ie, isotropic monocular outputs are available only for high-speed stimuli). According to this model, the visual processes revealed by masking, adaptation, and summation are related but not identical. PMID:23145234

  4. 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

  5. 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.

  6. 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

  7. A decision-theoretic approach in the design of an adaptive upper-limb stroke rehabilitation robot.

    PubMed

    Huq, Rajibul; Kan, Patricia; Goetschalckx, Robby; Hébert, Debbie; Hoey, Jesse; Mihailidis, Alex

    2011-01-01

    This paper presents an automated system for a rehabilitation robotic device that guides stroke patients through an upper-limb reaching task. The system uses a partially observable Markov decision process (POMDP) as its primary engine for decision-making. The POMDP allows the system to automatically modify exercise parameters to account for the specific needs and abilities of different individuals, and to use these parameters to take appropriate decisions about stroke rehabilitation exercises. The performance of the system was evaluated through various simulations and by comparing the decisions made by the system with those of a human therapist for a single patient. In general, the simulations showed promising results and the therapist thought the system decisions were believable. PMID:22275621

  8. 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. PMID:26003915

  9. 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. PMID:26321531

  10. 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

  11. The ASLOTS concept: An interactive, adaptive decision support concept for Final Approach Spacing of Aircraft (FASA). FAA-NASA Joint University Program

    NASA Technical Reports Server (NTRS)

    Simpson, Robert W.

    1993-01-01

    This presentation outlines a concept for an adaptive, interactive decision support system to assist controllers at a busy airport in achieving efficient use of multiple runways. The concept is being implemented as a computer code called FASA (Final Approach Spacing for Aircraft), and will be tested and demonstrated in ATCSIM, a high fidelity simulation of terminal area airspace and airport surface operations. Objectives are: (1) to provide automated cues to assist controllers in the sequencing and spacing of landing and takeoff aircraft; (2) to provide the controller with a limited ability to modify the sequence and spacings between aircraft, and to insert takeoffs and missed approach aircraft in the landing flows; (3) to increase spacing accuracy using more complex and precise separation criteria while reducing controller workload; and (4) achieve higher operational takeoff and landing rates on multiple runways in poor visibility.

  12. Space-time adaptive decision feedback neural receivers with data selection for high-data-rate users in DS-CDMA systems.

    PubMed

    de Lamare, Rodrigo C; Sampaio-Neto, Raimundo

    2008-11-01

    A space-time adaptive decision feedback (DF) receiver using recurrent neural networks (RNNs) is proposed for joint equalization and interference suppression in direct-sequence code-division multiple-access (DS-CDMA) systems equipped with antenna arrays. The proposed receiver structure employs dynamically driven RNNs in the feedforward section for equalization and multiaccess interference (MAI) suppression and a finite impulse response (FIR) linear filter in the feedback section for performing interference cancellation. A data selective gradient algorithm, based upon the set-membership (SM) design framework, is proposed for the estimation of the coefficients of RNN structures and is applied to the estimation of the parameters of the proposed neural receiver structure. Simulation results show that the proposed techniques achieve significant performance gains over existing schemes. PMID:18990643

  13. 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

  14. 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

  15. Usability testing of Avoiding Diabetes Thru Action Plan Targeting (ADAPT) decision support for integrating care-based counseling of pre-diabetes in an electronic health record

    PubMed Central

    Chrimes, Dillon; Kushniruk, Andre; Kitos, Nicole R.

    2014-01-01

    Purpose Usability testing can be used to evaluate human computer interaction (HCI) and communication in shared decision making (SDM) for patient-provider behavioral change and behavioral contracting. Traditional evaluations of usability using scripted or mock patient scenarios with think-aloud protocol analysis provide a to identify HCI issues. In this paper we describe the application of these methods in the evaluation of the Avoiding Diabetes Thru Action Plan Targeting (ADAPT) tool, and test the usability of the tool to support the ADAPT framework for integrated care counseling of pre-diabetes. The think-aloud protocol analysis typically does not provide an assessment of how patient-provider interactions are effected in “live” clinical workflow or whether a tool is successful. Therefore, “Near-live” clinical simulations involving applied simulation methods were used to compliment the think-aloud results. This complementary usability technique was used to test the end-user HCI and tool performance by more closely mimicking the clinical workflow and capturing interaction sequences along with assessing the functionality of computer module prototypes on clinician workflow. We expected this method to further complement and provide different usability findings as compared to think-aloud analysis. Together, this mixed method evaluation provided comprehensive and realistic feedback for iterative refinement of the ADAPT system prior to implementation. Methods The study employed two phases of testing of a new interactive ADAPT tool that embedded an evidence-based shared goal setting component into primary care workflow for dealing with pre-diabetes counseling within a commercial physician office electronic health record (EHR). Phase I applied usability testing that involved “think-aloud” protocol analysis of 8 primary care providers interacting with several scripted clinical scenarios. Phase II used “near-live” clinical simulations of 5 providers

  16. An Engineered Approach to Stem Cell Culture: Automating the Decision Process for Real-Time Adaptive Subculture of Stem Cells

    PubMed Central

    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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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...

  2. An adaptive incremental approach to constructing ensemble classifiers: Application in an information-theoretic computer-aided decision system for detection of masses in mammograms

    SciTech Connect

    Mazurowski, Maciej A.; Zurada, Jacek M.; Tourassi, Georgia D.

    2009-07-15

    Ensemble classifiers have been shown efficient in multiple applications. In this article, the authors explore the effectiveness of ensemble classifiers in a case-based computer-aided diagnosis system for detection of masses in mammograms. They evaluate two general ways of constructing subclassifiers by resampling of the available development dataset: Random division and random selection. Furthermore, they discuss the problem of selecting the ensemble size and propose two adaptive incremental techniques that automatically select the size for the problem at hand. All the techniques are evaluated with respect to a previously proposed information-theoretic CAD system (IT-CAD). The experimental results show that the examined ensemble techniques provide a statistically significant improvement (AUC=0.905{+-}0.024) in performance as compared to the original IT-CAD system (AUC=0.865{+-}0.029). Some of the techniques allow for a notable reduction in the total number of examples stored in the case base (to 1.3% of the original size), which, in turn, results in lower storage requirements and a shorter response time of the system. Among the methods examined in this article, the two proposed adaptive techniques are by far the most effective for this purpose. Furthermore, the authors provide some discussion and guidance for choosing the ensemble parameters.

  3. 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

  4. 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

  5. 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

  6. 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...

  7. 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.

  8. Career Adaptability in Childhood

    ERIC Educational Resources Information Center

    Hartung, Paul J.; Porfeli, Erik J.; Vondracek, Fred W.

    2008-01-01

    Childhood marks the dawn of vocational development, involving developmental tasks, transitions, and change. Children must acquire the rudiments of career adaptability to envision a future, make educational and vocational decisions, explore self and occupations, and problem solve. The authors situate child vocational development within human life…

  9. 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…

  10. 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

  11. 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

  12. 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…

  13. Hydropower, adaptive management, and Biodiversity

    NASA Astrophysics Data System (ADS)

    Wieringa, Mark J.; Morton, Anthony G.

    1996-11-01

    Adaptive management is a policy framework within which an iterative process of decision making is followed based on the observed responses to and effectiveness of previous decisions. The use of adaptive management allows science-based research and monitoring of natural resource and ecological community responses, in conjunction with societal values and goals, to guide decisions concerning man's activities. The adaptive management process has been proposed for application to hydropower operations at Glen Canyon Dam on the Colorado River, a situation that requires complex balancing of natural resources requirements and competing human uses. This example is representative of the general increase in public interest in the operation of hydropower facilities and possible effects on downstream natural resources and of the growing conflicts between uses and users of river-based resources. This paper describes the adaptive management process, using the Glen Canyon Dam example, and discusses ways to make the process work effectively in managing downstream natural resources and biodiversity.

  14. A local coastal adaptation pathway

    NASA Astrophysics Data System (ADS)

    Barnett, J.; Graham, S.; Mortreux, C.; Fincher, R.; Waters, E.; Hurlimann, A.

    2014-12-01

    Local governments are not adapting to sea-level rise because it is difficult to build consensus on the need for change and the best way to implement it. In theory, adaptation pathways can resolve this impasse. Adaptation pathways are a sequence of linked strategies that are triggered by a change in environmental conditions, and in which initial decisions can have low regrets and preserve options for future generations. We report on a project that sought to empirically test the relevance and feasibility of a local pathway for adapting to sea-level rise. We find that triggers of change that have social impacts are salient to local people, and developing a local adaptation pathway helps build consensus among diverse constituencies. Our results show that adaptation pathways are feasible at the local scale, offering a low-risk, low-cost way to begin the long process of adaptation to sea-level rise.

  15. Adaptive Management

    EPA Science Inventory

    Adaptive management is an approach to natural resource management that emphasizes learning through management where knowledge is incomplete, and when, despite inherent uncertainty, managers and policymakers must act. Unlike a traditional trial and error approach, adaptive managem...

  16. Single-photon decision maker.

    PubMed

    Naruse, Makoto; Berthel, Martin; Drezet, Aurélien; Huant, Serge; Aono, Masashi; Hori, Hirokazu; Kim, Song-Ju

    2015-01-01

    Decision making is critical in our daily lives and for society in general and is finding evermore practical applications in information and communication technologies. Herein, we demonstrate experimentally that single photons can be used to make decisions in uncertain, dynamically changing environments. Using a nitrogen-vacancy in a nanodiamond as a single-photon source, we demonstrate the decision-making capability by solving the multi-armed bandit problem. This capability is directly and immediately associated with single-photon detection in the proposed architecture, leading to adequate and adaptive autonomous decision making. This study makes it possible to create systems that benefit from the quantum nature of light to perform practical and vital intelligent functions. PMID:26278007

  17. Single-photon decision maker

    PubMed Central

    Naruse, Makoto; Berthel, Martin; Drezet, Aurélien; Huant, Serge; Aono, Masashi; Hori, Hirokazu; Kim, Song-Ju

    2015-01-01

    Decision making is critical in our daily lives and for society in general and is finding evermore practical applications in information and communication technologies. Herein, we demonstrate experimentally that single photons can be used to make decisions in uncertain, dynamically changing environments. Using a nitrogen-vacancy in a nanodiamond as a single-photon source, we demonstrate the decision-making capability by solving the multi-armed bandit problem. This capability is directly and immediately associated with single-photon detection in the proposed architecture, leading to adequate and adaptive autonomous decision making. This study makes it possible to create systems that benefit from the quantum nature of light to perform practical and vital intelligent functions. PMID:26278007

  18. Single-photon decision maker

    NASA Astrophysics Data System (ADS)

    Naruse, Makoto; Berthel, Martin; Drezet, Aurélien; Huant, Serge; Aono, Masashi; Hori, Hirokazu; Kim, Song-Ju

    2015-08-01

    Decision making is critical in our daily lives and for society in general and is finding evermore practical applications in information and communication technologies. Herein, we demonstrate experimentally that single photons can be used to make decisions in uncertain, dynamically changing environments. Using a nitrogen-vacancy in a nanodiamond as a single-photon source, we demonstrate the decision-making capability by solving the multi-armed bandit problem. This capability is directly and immediately associated with single-photon detection in the proposed architecture, leading to adequate and adaptive autonomous decision making. This study makes it possible to create systems that benefit from the quantum nature of light to perform practical and vital intelligent functions.

  19. The Robust Beauty of Majority Rules in Group Decisions

    ERIC Educational Resources Information Center

    Hastie, Reid; Kameda, Tatsuya

    2005-01-01

    How should groups make decisions? The authors provide an original evaluation of 9 group decision rules based on their adaptive success in a simulated test bed environment. When the adaptive success standard is applied, the majority and plurality rules fare quite well, performing at levels comparable to much more resource-demanding rules such as an…

  20. Learning and Teaching Critical Thinking: From a Peircean Perspective

    ERIC Educational Resources Information Center

    Wells, Kelley

    2009-01-01

    The article will argue that Charles Sanders Peirce's concepts of the "Dynamics of Belief and Doubt", the "Fixation of Belief" as well as "habits of belief" taken together comprise a theory of learning. The "dynamics of belief and doubt" are Peirce's explanation for the process of changing from one belief to another. Teaching, then, would be an…

  1. Mathematical Epistemology from a Peircean Semiotic Point of View

    ERIC Educational Resources Information Center

    Otte, Michael

    2006-01-01

    Learning is better than knowing, generalization is more illuminating than abstract generality or universality because we perceive and thus become conscious of change or development only. Signs and representations establish the dialectic of fixation on the one hand and transformation on the other, which is so essential to learning and cognition.…

  2. Evolution, Learning, and Semiotics from a Peircean Point of View

    ERIC Educational Resources Information Center

    Otte, Michael Friedrich

    2011-01-01

    One of the most salient arguments in favor of a semiotic approach, put forward on various occasions among others by Luis Radford, claims that semiotics is most appropriate to treat the interaction between socio-cultural and objective aspects of knowledge problems. But if we want to take such claims seriously, we have to undertake revisions of our…

  3. Developmental decisions

    PubMed Central

    Tobin, David V.; Saito, Richard Mako

    2012-01-01

    The small nematode C. elegans is characterized by developing through a highly coordinated, reproducible cell lineage that serves as the basis of many studies focusing on the development of multi-lineage organisms. Indeed, the reproducible cell lineage enables discovery of developmental defects that occur in even a single cell. Only recently has attention been focused on how these animals modify their genetically programmed cell lineages to adapt to altered environments. Here, we summarize the current understanding of how C. elegans responds to food deprivation by adapting their developmental program in order to conserve energy. In particular, we highlight the AMPK-mediated and insulin-like growth factor signaling pathways that are the principal regulators of induced cell cycle quiescence. PMID:22510569

  4. Adaptive SPECT

    PubMed Central

    Barrett, Harrison H.; Furenlid, Lars R.; Freed, Melanie; Hesterman, Jacob Y.; Kupinski, Matthew A.; Clarkson, Eric; Whitaker, Meredith K.

    2008-01-01

    Adaptive imaging systems alter their data-acquisition configuration or protocol in response to the image information received. An adaptive pinhole single-photon emission computed tomography (SPECT) system might acquire an initial scout image to obtain preliminary information about the radiotracer distribution and then adjust the configuration or sizes of the pinholes, the magnifications, or the projection angles in order to improve performance. This paper briefly describes two small-animal SPECT systems that allow this flexibility and then presents a framework for evaluating adaptive systems in general, and adaptive SPECT systems in particular. The evaluation is in terms of the performance of linear observers on detection or estimation tasks. Expressions are derived for the ideal linear (Hotelling) observer and the ideal linear (Wiener) estimator with adaptive imaging. Detailed expressions for the performance figures of merit are given, and possible adaptation rules are discussed. PMID:18541485

  5. Making Career Decisions--A Sequential Elimination Approach.

    ERIC Educational Resources Information Center

    Gati, Itamar

    1986-01-01

    Presents a model for career decision making based on the sequential elimination of occupational alternatives, an adaptation for career decisions of Tversky's (1972) elimination-by-aspects theory of choice. The expected utility approach is reviewed as a representative compensatory model for career decisions. Advantages, disadvantages, and…

  6. Classifying climate change adaptation frameworks

    NASA Astrophysics Data System (ADS)

    Armstrong, Jennifer

    2014-05-01

    Complex socio-ecological demographics are factors that must be considered when addressing adaptation to the potential effects of climate change. As such, a suite of deployable climate change adaptation frameworks is necessary. Multiple frameworks that are required to communicate the risks of climate change and facilitate adaptation. Three principal adaptation frameworks have emerged from the literature; Scenario - Led (SL), Vulnerability - Led (VL) and Decision - Centric (DC). This study aims to identify to what extent these adaptation frameworks; either, planned or deployed are used in a neighbourhood vulnerable to climate change. This work presents a criterion that may be used as a tool for identifying the hallmarks of adaptation frameworks and thus enabling categorisation of projects. The study focussed on the coastal zone surrounding the Sizewell nuclear power plant in Suffolk in the UK. An online survey was conducted identifying climate change adaptation projects operating in the study area. This inventory was analysed to identify the hallmarks of each adaptation project; Levels of dependency on climate model information, Metrics/units of analysis utilised, Level of demographic knowledge, Level of stakeholder engagement, Adaptation implementation strategies and Scale of adaptation implementation. The study found that climate change adaptation projects could be categorised, based on the hallmarks identified, in accordance with the published literature. As such, the criterion may be used to establish the matrix of adaptation frameworks present in a given area. A comprehensive summary of the nature of adaptation frameworks in operation in a locality provides a platform for further comparative analysis. Such analysis, enabled by the criterion, may aid the selection of appropriate frameworks enhancing the efficacy of climate change adaptation.

  7. Making Sustainable Decisions Using the KONVERGENCE Framework

    SciTech Connect

    Piet, Steven James; Gibson, Patrick Lavern; Joe, Jeffrey Clark; Kerr, Thomas A; Nitschke, Robert Leon; Dakins, Maxine Ellen

    2003-02-01

    Hundreds of contaminated facilities and sites must be cleaned up. “Cleanup” includes decommissioning, environmental restoration, and waste management. Cleanup can be complex, expensive, risky, and time-consuming. Decisions are often controversial, can stall or be blocked, and are sometimes re-done - some before implementation, some decades later. Making and keeping decisions with long time horizons involves special difficulties and requires new approaches, including: • New ways (mental model) to analyze and visualize the problem, • Awareness of the option to shift strategy or reframe from a single decision to an adaptable network of decisions, and • Improved tactical processes that account for several challenges. These include the following: • Stakeholder values are a more fundamental basis for decision making and keeping than “meeting regulations.” • Late-entry players and future generations will question decisions. • People may resist making “irreversible” decisions. • People need “compelling reasons” to take action in the face of uncertainties. Our project goal is to make cleanup decisions easier to make, implement, keep, and sustain. By sustainability, we mean decisions that work better over the entire time-period—from when a decision is made, through implementation, to its end point. That is, alternatives that can be kept “as is” or adapted as circumstances change. Increased attention to sustainability and adaptability may decrease resistance to making and implementing decisions. Our KONVERGENCE framework addresses these challenges. The framework is based on a mental model that states: where Knowledge, Values, and Resources converge (the K, V, R in KONVERGENCE), you will find a sustainable decision. We define these areas or universes as follows: • Knowledge: what is known about the problem and possible solutions? • Values: what is important to those affected by the decision? • Resources: what is available to implement

  8. Ignorance- versus Evidence-Based Decision Making: A Decision Time Analysis of the Recognition Heuristic

    ERIC Educational Resources Information Center

    Hilbig, Benjamin E.; Pohl, Rudiger F.

    2009-01-01

    According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments--and its duration--is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of…

  9. Making Sustainable Decisions Using The KONVERGENCE Framework

    SciTech Connect

    Piet, S. J.; Gibson, P. L.; Joe, J. C.; Kerr, T. A.; Nitschke, R. L.; Dakins, M. E.

    2003-02-25

    Hundreds of contaminated facilities and sites must be cleaned up. ''Cleanup'' includes decommissioning, environmental restoration, and waste management. Cleanup can be complex, expensive, risky, and time-consuming. Decisions are often controversial, can stall or be blocked, and are sometimes re-done--some before implementation, some decades later. Making and keeping decisions with long time horizons involves special difficulties and requires new approaches. Our project goal is to make cleanup decisions easier to make, implement, keep, and sustain. By sustainability, we mean decisions that work better over the entire time-period-from when a decision is made, through implementation, to its end point. That is, alternatives that can be kept ''as is'' or adapted as circumstances change. Increased attention to sustainability and adaptability may decrease resistance to making and implementing decisions. Our KONVERGENCE framework addresses these challenges. The framework is based on a mental model that states: where Knowledge, Values, and Resources converge (the K, V, R in KONVERGENCE), you will find a sustainable decision. We define these areas or universes as follows: (1) Knowledge: what is known about the problem and possible solutions? (2) Values: what is important to those affected by the decision? (3) Resources: what is available to implement possible solutions or improve knowledge? This mental model helps analyze and visualize what is happening as decisions are made and kept. Why is there disagreement? Is there movement toward konvergence? Is a past decision drifting out of konvergence? The framework includes strategic improvements, i.e., expand the spectrum of alternatives to include adaptable alternatives and decision networks. It includes tactical process improvements derived from experience, values, and relevant literature. This paper includes diagnosis and medication (suggested path forward) for intractable cases.

  10. Adaptive management of natural resources-framework and issues

    USGS Publications Warehouse

    Williams, B.K.

    2011-01-01

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

  11. Adaptive sensor fusion

    NASA Astrophysics Data System (ADS)

    Kadar, Ivan

    1995-07-01

    A perceptual reasoning system adaptively extracting, associating, and fusing information from multiple sources, at various levels of abstraction, is considered as the building block for the next generation of surveillance systems. A system architecture is presented which makes use of both centralized and distributed predetection fusion combined with intelligent monitor and control coupling both on-platform and off-board track and decision level fusion results. The goal of this system is to create a `gestalt fused sensor system' whose information product is greater than the sum of the information products from the individual sensors and has performance superior to either individual or a sub-group of combined sensors. The application of this architectural concept to the law enforcement arena (e.g. drug interdiction) utilizing multiple spatially and temporally diverse surveillance platforms and/or information sources, is used to illustrate the benefits of the adaptive perceptual reasoning system concept.

  12. Investigations in adaptive processing of multispectral data

    NASA Technical Reports Server (NTRS)

    Kriegler, F. J.; Horwitz, H. M.

    1973-01-01

    Adaptive data processing procedures are applied to the problem of classifying objects in a scene scanned by multispectral sensor. These procedures show a performance improvement over standard nonadaptive techniques. Some sources of error in classification are identified and those correctable by adaptive processing are discussed. Experiments in adaptation of signature means by decision-directed methods are described. Some of these methods assume correlation between the trajectories of different signature means; for others this assumption is not made.

  13. Adaptive gain control during human perceptual choice

    PubMed Central

    Cheadle, Samuel; Wyart, Valentin; Tsetsos, Konstantinos; Myers, Nicholas; de Gardelle, Vincent; Castañón, Santiago Herce; Summerfield, Christopher

    2015-01-01

    Neural systems adapt to background levels of stimulation. Adaptive gain control has been extensively studied in sensory systems, but overlooked in decision-theoretic models. Here, we describe evidence for adaptive gain control during the serial integration of decision-relevant information. Human observers judged the average information provided by a rapid stream of visual events (samples). The impact that each sample wielded over choices depended on its consistency with the previous sample, with more consistent or expected samples wielding the greatest influence over choice. This bias was also visible in the encoding of decision information in pupillometric signals, and in cortical responses measured with functional neuroimaging. These data can be accounted for with a new serial sampling model in which the gain of information processing adapts rapidly to reflect the average of the available evidence. PMID:24656259

  14. Incorporating geodiversity into conservation decisions.

    PubMed

    Comer, Patrick J; Pressey, Robert L; Hunter, Malcolm L; Schloss, Carrie A; Buttrick, Steven C; Heller, Nicole E; Tirpak, John M; Faith, Daniel P; Cross, Molly S; Shaffer, Mark L

    2015-06-01

    In a rapidly changing climate, conservation practitioners could better use geodiversity in a broad range of conservation decisions. We explored selected avenues through which this integration might improve decision making and organized them within the adaptive management cycle of assessment, planning, implementation, and monitoring. Geodiversity is seldom referenced in predominant environmental law and policy. With most natural resource agencies mandated to conserve certain categories of species, agency personnel are challenged to find ways to practically implement new directives aimed at coping with climate change while retaining their species-centered mandate. Ecoregions and ecological classifications provide clear mechanisms to consider geodiversity in plans or decisions, the inclusion of which will help foster the resilience of conservation to climate change. Methods for biodiversity assessment, such as gap analysis, climate change vulnerability analysis, and ecological process modeling, can readily accommodate inclusion of a geophysical component. We adapted others' approaches for characterizing landscapes along a continuum of climate change vulnerability for the biota they support from resistant, to resilient, to susceptible, and to sensitive and then summarized options for integrating geodiversity into planning in each landscape type. In landscapes that are relatively resistant to climate change, options exist to fully represent geodiversity while ensuring that dynamic ecological processes can change over time. In more susceptible landscapes, strategies aiming to maintain or restore ecosystem resilience and connectivity are paramount. Implementing actions on the ground requires understanding of geophysical constraints on species and an increasingly nimble approach to establishing management and restoration goals. Because decisions that are implemented today will be revisited and amended into the future, increasingly sophisticated forms of monitoring and

  15. Hydropower, adaptive management, and biodiversity

    SciTech Connect

    Wieringa, M.J.; Morton, A.G.

    1996-11-01

    Adaptive management is a policy framework within which an iterative process of decision making is allowed based on the observed responses to and effectiveness of previous decisions. The use of adaptive management allows science-based research and monitoring of natural resource and ecological community responses, in conjunction with societal values and goals, to guide decisions concerning man`s activities. The adaptive management process has been proposed for application to hydropower operations at Glen Canyon Dam on the Colorado River, a situation that requires complex balancing of natural resources requirements and competing human uses. This example is representative of the general increase in public interest in the operation of hydropower facilities and possible effects on downstream natural resources and of the growing conflicts between uses and users of river-based resources. This paper describes the adaptive management process, using the Glen Canyon Dam example, and discusses ways to make the process work effectively in managing downstream natural resources and biodiversity. 10 refs., 2 figs.

  16. Adaptive Development

    NASA Technical Reports Server (NTRS)

    2005-01-01

    The goal of this research is to develop and demonstrate innovative adaptive seal technologies that can lead to dramatic improvements in engine performance, life, range, and emissions, and enhance operability for next generation gas turbine engines. This work is concentrated on the development of self-adaptive clearance control systems for gas turbine engines. Researchers have targeted the high-pressure turbine (HPT) blade tip seal location for following reasons: Current active clearance control (ACC) systems (e.g., thermal case-cooling schemes) cannot respond to blade tip clearance changes due to mechanical, thermal, and aerodynamic loads. As such they are prone to wear due to the required tight running clearances during operation. Blade tip seal wear (increased clearances) reduces engine efficiency, performance, and service life. Adaptive sealing technology research has inherent impact on all envisioned 21st century propulsion systems (e.g. distributed vectored, hybrid and electric drive propulsion concepts).

  17. A Common Mechanism Underlying Food Choice and Social Decisions.

    PubMed

    Krajbich, Ian; Hare, Todd; Bartling, Björn; Morishima, Yosuke; Fehr, Ernst

    2015-10-01

    People make numerous decisions every day including perceptual decisions such as walking through a crowd, decisions over primary rewards such as what to eat, and social decisions that require balancing own and others' benefits. The unifying principles behind choices in various domains are, however, still not well understood. Mathematical models that describe choice behavior in specific contexts have provided important insights into the computations that may underlie decision making in the brain. However, a critical and largely unanswered question is whether these models generalize from one choice context to another. Here we show that a model adapted from the perceptual decision-making domain and estimated on choices over food rewards accurately predicts choices and reaction times in four independent sets of subjects making social decisions. The robustness of the model across domains provides behavioral evidence for a common decision-making process in perceptual, primary reward, and social decision making. PMID:26460812

  18. A control-theory model for human decision-making

    NASA Technical Reports Server (NTRS)

    Levison, W. H.; Tanner, R. B.

    1971-01-01

    A model for human decision making is an adaptation of an optimal control model for pilot/vehicle systems. The models for decision and control both contain concepts of time delay, observation noise, optimal prediction, and optimal estimation. The decision making model was intended for situations in which the human bases his decision on his estimate of the state of a linear plant. Experiments are described for the following task situations: (a) single decision tasks, (b) two-decision tasks, and (c) simultaneous manual control and decision making. Using fixed values for model parameters, single-task and two-task decision performance can be predicted to within an accuracy of 10 percent. Agreement is less good for the simultaneous decision and control situation.

  19. A Common Mechanism Underlying Food Choice and Social Decisions

    PubMed Central

    Krajbich, Ian; Hare, Todd; Bartling, Björn; Morishima, Yosuke; Fehr, Ernst

    2015-01-01

    People make numerous decisions every day including perceptual decisions such as walking through a crowd, decisions over primary rewards such as what to eat, and social decisions that require balancing own and others’ benefits. The unifying principles behind choices in various domains are, however, still not well understood. Mathematical models that describe choice behavior in specific contexts have provided important insights into the computations that may underlie decision making in the brain. However, a critical and largely unanswered question is whether these models generalize from one choice context to another. Here we show that a model adapted from the perceptual decision-making domain and estimated on choices over food rewards accurately predicts choices and reaction times in four independent sets of subjects making social decisions. The robustness of the model across domains provides behavioral evidence for a common decision-making process in perceptual, primary reward, and social decision making. PMID:26460812

  20. Counseling for Decisions

    ERIC Educational Resources Information Center

    Smaby, Marlowe H.; Tamminen, Armas W.

    1978-01-01

    This article presents a model for training counselors to help counselees in the process of making decisions. An effective decision-helping approach that includes processing decisions, relating values to process, and relating actions to beliefs is presented. (Author)

  1. Adapting Animals.

    ERIC Educational Resources Information Center

    Wedman, John; Wedman, Judy

    1985-01-01

    The "Animals" program found on the Apple II and IIe system master disk can be adapted for use in the mathematics classroom. Instructions for making the necessary changes and suggestions for using it in lessons related to geometric shapes are provided. (JN)

  2. Adaptive homeostasis.

    PubMed

    Davies, Kelvin J A

    2016-06-01

    Homeostasis is a central pillar of modern Physiology. The term homeostasis was invented by Walter Bradford Cannon in an attempt to extend and codify the principle of 'milieu intérieur,' or a constant interior bodily environment, that had previously been postulated by Claude Bernard. Clearly, 'milieu intérieur' and homeostasis have served us well for over a century. Nevertheless, research on signal transduction systems that regulate gene expression, or that cause biochemical alterations to existing enzymes, in response to external and internal stimuli, makes it clear that biological systems are continuously making short-term adaptations both to set-points, and to the range of 'normal' capacity. These transient adaptations typically occur in response to relatively mild changes in conditions, to programs of exercise training, or to sub-toxic, non-damaging levels of chemical agents; thus, the terms hormesis, heterostasis, and allostasis are not accurate descriptors. Therefore, an operational adjustment to our understanding of homeostasis suggests that the modified term, Adaptive Homeostasis, may be useful especially in studies of stress, toxicology, disease, and aging. Adaptive Homeostasis may be defined as follows: 'The transient expansion or contraction of the homeostatic range in response to exposure to sub-toxic, non-damaging, signaling molecules or events, or the removal or cessation of such molecules or events.' PMID:27112802

  3. Adaptive Thresholds

    SciTech Connect

    Bremer, P. -T.

    2014-08-26

    ADAPT is a topological analysis code that allow to compute local threshold, in particular relevance based thresholds for features defined in scalar fields. The initial target application is vortex detection but the software is more generally applicable to all threshold based feature definitions.

  4. Reducing uncertainty about objective functions in adaptive management

    USGS Publications Warehouse

    Williams, B.K.

    2012-01-01

    This paper extends the uncertainty framework of adaptive management to include uncertainty about the objectives to be used in guiding decisions. Adaptive decision making typically assumes explicit and agreed-upon objectives for management, but allows for uncertainty as to the structure of the decision process that generates change through time. Yet it is not unusual for there to be uncertainty (or disagreement) about objectives, with different stakeholders expressing different views not only about resource responses to management but also about the appropriate management objectives. In this paper I extend the treatment of uncertainty in adaptive management, and describe a stochastic structure for the joint occurrence of uncertainty about objectives as well as models, and show how adaptive decision making and the assessment of post-decision monitoring data can be used to reduce uncertainties of both kinds. Different degrees of association between model and objective uncertainty lead to different patterns of learning about objectives. ?? 2011.

  5. Group performance and decision making.

    PubMed

    Kerr, Norbert L; Tindale, R Scott

    2004-01-01

    Theory and research on small group performance and decision making is reviewed. Recent trends in group performance research have found that process gains as well as losses are possible, and both are frequently explained by situational and procedural contexts that differentially affect motivation and resource coordination. Research has continued on classic topics (e.g., brainstorming, group goal setting, stress, and group performance) and relatively new areas (e.g., collective induction). Group decision making research has focused on preference combination for continuous response distributions and group information processing. New approaches (e.g., group-level signal detection) and traditional topics (e.g., groupthink) are discussed. New directions, such as nonlinear dynamic systems, evolutionary adaptation, and technological advances, should keep small group research vigorous well into the future. PMID:14744229

  6. Connector adapter

    NASA Technical Reports Server (NTRS)

    Hacker, Scott C. (Inventor); Dean, Richard J. (Inventor); Burge, Scott W. (Inventor); Dartez, Toby W. (Inventor)

    2007-01-01

    An adapter for installing a connector to a terminal post, wherein the connector is attached to a cable, is presented. In an embodiment, the adapter is comprised of an elongated collet member having a longitudinal axis comprised of a first collet member end, a second collet member end, an outer collet member surface, and an inner collet member surface. The inner collet member surface at the first collet member end is used to engage the connector. The outer collet member surface at the first collet member end is tapered for a predetermined first length at a predetermined taper angle. The collet includes a longitudinal slot that extends along the longitudinal axis initiating at the first collet member end for a predetermined second length. The first collet member end is formed of a predetermined number of sections segregated by a predetermined number of channels and the longitudinal slot.

  7. Adaptive sampler

    DOEpatents

    Watson, Bobby L.; Aeby, Ian

    1982-01-01

    An adaptive data compression device for compressing data having variable frequency content, including a plurality of digital filters for analyzing the content of the data over a plurality of frequency regions, a memory, and a control logic circuit for generating a variable rate memory clock corresponding to the analyzed frequency content of the data in the frequency region and for clocking the data into the memory in response to the variable rate memory clock.

  8. Adaptive sampler

    DOEpatents

    Watson, B.L.; Aeby, I.

    1980-08-26

    An adaptive data compression device for compressing data is described. The device has a frequency content, including a plurality of digital filters for analyzing the content of the data over a plurality of frequency regions, a memory, and a control logic circuit for generating a variable rate memory clock corresponding to the analyzed frequency content of the data in the frequency region and for clocking the data into the memory in response to the variable rate memory clock.

  9. Adaptive antennas

    NASA Astrophysics Data System (ADS)

    Barton, P.

    1987-04-01

    The basic principles of adaptive antennas are outlined in terms of the Wiener-Hopf expression for maximizing signal to noise ratio in an arbitrary noise environment; the analogy with generalized matched filter theory provides a useful aid to understanding. For many applications, there is insufficient information to achieve the above solution and thus non-optimum constrained null steering algorithms are also described, together with a summary of methods for preventing wanted signals being nulled by the adaptive system. The three generic approaches to adaptive weight control are discussed; correlation steepest descent, weight perturbation and direct solutions based on sample matrix conversion. The tradeoffs between hardware complexity and performance in terms of null depth and convergence rate are outlined. The sidelobe cancellor technique is described. Performance variation with jammer power and angular distribution is summarized and the key performance limitations identified. The configuration and performance characteristics of both multiple beam and phase scan array antennas are covered, with a brief discussion of performance factors.

  10. Passive and active adaptive management: Approaches and an example

    USGS Publications Warehouse

    Williams, B.K.

    2011-01-01

    Adaptive management is a framework for resource conservation that promotes iterative learning-based decision making. Yet there remains considerable confusion about what adaptive management entails, and how to actually make resource decisions adaptively. A key but somewhat ambiguous distinction in adaptive management is between active and passive forms of adaptive decision making. The objective of this paper is to illustrate some approaches to active and passive adaptive management with a simple example involving the drawdown of water impoundments on a wildlife refuge. The approaches are illustrated for the drawdown example, and contrasted in terms of objectives, costs, and potential learning rates. Some key challenges to the actual practice of AM are discussed, and tradeoffs between implementation costs and long-term benefits are highlighted. ?? 2010 Elsevier Ltd.

  11. Game theory and neural basis of social decision making

    PubMed Central

    Lee, Daeyeol

    2008-01-01

    Decision making in a social group displays two unique features. First, humans and other animals routinely alter their behaviors in response to changes in their physical and social environment. As a result, the outcomes of decisions that depend on the behaviors of multiple decision makers are difficult to predict, and this requires highly adaptive decision-making strategies. Second, decision makers may have other-regarding preferences and therefore choose their actions to improve or reduce the well-beings of others. Recently, many neurobiological studies have exploited game theory to probe the neural basis of decision making, and found that these unique features of social decision making might be reflected in the functions of brain areas involved in reward evaluation and reinforcement learning. Molecular genetic studies have also begun to identify genetic mechanisms for personal traits related to reinforcement learning and complex social decision making, further illuminating the biological basis of social behavior. PMID:18368047

  12. Promoting Metacognitive Decision-Making in Teacher Education

    ERIC Educational Resources Information Center

    Griffith, Robin; Bauml, Michelle; Quebec-Fuentes, Sarah

    2016-01-01

    Effective teachers are characterized by their abilities to make thoughtful, deliberate, and informed adaptations while teaching (Hoffman & Pearson, 2000). These in-the-moment teaching decisions are guided by a complex web of teacher knowledge. Raising teachers' awareness of the decisions they make on a moment-by-moment basis may aid in…

  13. Adapting agriculture to climate change

    PubMed Central

    Howden, S. Mark; Soussana, Jean-François; Tubiello, Francesco N.; Chhetri, Netra; Dunlop, Michael; Meinke, Holger

    2007-01-01

    The strong trends in climate change already evident, the likelihood of further changes occurring, and the increasing scale of potential climate impacts give urgency to addressing agricultural adaptation more coherently. There are many potential adaptation options available for marginal change of existing agricultural systems, often variations of existing climate risk management. We show that implementation of these options is likely to have substantial benefits under moderate climate change for some cropping systems. However, there are limits to their effectiveness under more severe climate changes. Hence, more systemic changes in resource allocation need to be considered, such as targeted diversification of production systems and livelihoods. We argue that achieving increased adaptation action will necessitate integration of climate change-related issues with other risk factors, such as climate variability and market risk, and with other policy domains, such as sustainable development. Dealing with the many barriers to effective adaptation will require a comprehensive and dynamic policy approach covering a range of scales and issues, for example, from the understanding by farmers of change in risk profiles to the establishment of efficient markets that facilitate response strategies. Science, too, has to adapt. Multidisciplinary problems require multidisciplinary solutions, i.e., a focus on integrated rather than disciplinary science and a strengthening of the interface with decision makers. A crucial component of this approach is the implementation of adaptation assessment frameworks that are relevant, robust, and easily operated by all stakeholders, practitioners, policymakers, and scientists. PMID:18077402

  14. 36 CFR 220.7 - Environmental assessment and decision notice.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... AGRICULTURE NATIONAL ENVIRONMENTAL POLICY ACT (NEPA) COMPLIANCE § 220.7 Environmental assessment and decision... incorporated by reference in accord with 40 CFR 1502.21. (iv) The proposed action and one or more alternatives to the proposed action may include adaptive management. An adaptive management proposal...

  15. A holistic strategy for adaptive land management

    USGS Publications Warehouse

    Herrick, Jeffrey E.; Duniway, Michael C.; Pyke, David A.; Bestelmeyer, Brandon T.; Wills, Skye A.; Brown, Joel R.; Karl, Jason W.; Havstad, Kris M.

    2012-01-01

    Adaptive management is widely applied to natural resources management (Holling 1973; Walters and Holling 1990). 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 adaptation of management until desired results are achieved (Brown and MacLeod 1996; Savory and Butterfield 1999). However, adaptive management is often criticized because very few projects ever complete more than one cycle, resulting in little adaptation and little knowledge gain (Lee 1999; Walters 2007). One significant criticism is that adaptive management is often used as a justification for undertaking actions with uncertain outcomes or as a surrogate for the development of specific, measurable indicators and monitoring programs (Lee 1999; Ruhl 2007).

  16. Precipitation Variability and Projection Uncertainties in Climate Change Adaptation: Go Local!

    EPA Science Inventory

    Presentations agenda includes: Regional and local climate change effects: The relevance; Variability and uncertainty in decision- making and adaptation approaches; Adaptation attributes for the U.S. Southwest: Water availability, storage capacity, and related; EPA research...

  17. Automation: Decision Aid or Decision Maker?

    NASA Technical Reports Server (NTRS)

    Skitka, Linda J.

    1998-01-01

    This study clarified that automation bias is something unique to automated decision making contexts, and is not the result of a general tendency toward complacency. By comparing performance on exactly the same events on the same tasks with and without an automated decision aid, we were able to determine that at least the omission error part of automation bias is due to the unique context created by having an automated decision aid, and is not a phenomena that would occur even if people were not in an automated context. However, this study also revealed that having an automated decision aid did lead to modestly improved performance across all non-error events. Participants in the non- automated condition responded with 83.68% accuracy, whereas participants in the automated condition responded with 88.67% accuracy, across all events. Automated decision aids clearly led to better overall performance when they were accurate. People performed almost exactly at the level of reliability as the automation (which across events was 88% reliable). However, also clear, is that the presence of less than 100% accurate automated decision aids creates a context in which new kinds of errors in decision making can occur. Participants in the non-automated condition responded with 97% accuracy on the six "error" events, whereas participants in the automated condition had only a 65% accuracy rate when confronted with those same six events. In short, the presence of an AMA can lead to vigilance decrements that can lead to errors in decision making.

  18. Adaptive sensor fusion using genetic algorithms

    SciTech Connect

    Fitzgerald, D.S.; Adams, D.G.

    1994-08-01

    Past attempts at sensor fusion have used some form of Boolean logic to combine the sensor information. As an alteniative, an adaptive ``fuzzy`` sensor fusion technique is described in this paper. This technique exploits the robust capabilities of fuzzy logic in the decision process as well as the optimization features of the genetic algorithm. This paper presents a brief background on fuzzy logic and genetic algorithms and how they are used in an online implementation of adaptive sensor fusion.

  19. NASA Risk-Informed Decision Making Handbook

    NASA Technical Reports Server (NTRS)

    Dezfuli, Homayoon; Stamatelatos, Michael; Maggio, Gaspare; Everett, Christopher; Youngblood, Robert; Rutledge, Peter; Benjamin, Allan; Williams, Rodney; Smith, Curtis; Guarro, Sergio

    2010-01-01

    This handbook provides guidance for conducting risk-informed decision making in the context of NASA risk management (RM), with a focus on the types of direction-setting key decisions that are characteristic of the NASA program and project life cycles, and which produce derived requirements in accordance with existing systems engineering practices that flow down through the NASA organizational hierarchy. The guidance in this handbook is not meant to be prescriptive. Instead, it is meant to be general enough, and contain a sufficient diversity of examples, to enable the reader to adapt the methods as needed to the particular decision problems that he or she faces. The handbook highlights major issues to consider when making decisions in the presence of potentially significant uncertainty, so that the user is better able to recognize and avoid pitfalls that might otherwise be experienced.

  20. Bayesian Adaptive Exploration

    NASA Astrophysics Data System (ADS)

    Loredo, Thomas J.

    2004-04-01

    I describe a framework for adaptive scientific exploration based on iterating an Observation-Inference-Design cycle that allows adjustment of hypotheses and observing protocols in response to the results of observation on-the-fly, as data are gathered. The framework uses a unified Bayesian methodology for the inference and design stages: Bayesian inference to quantify what we have learned from the available data and predict future data, and Bayesian decision theory to identify which new observations would teach us the most. When the goal of the experiment is simply to make inferences, the framework identifies a computationally efficient iterative ``maximum entropy sampling'' strategy as the optimal strategy in settings where the noise statistics are independent of signal properties. Results of applying the method to two ``toy'' problems with simulated data-measuring the orbit of an extrasolar planet, and locating a hidden one-dimensional object-show the approach can significantly improve observational efficiency in settings that have well-defined nonlinear models. I conclude with a list of open issues that must be addressed to make Bayesian adaptive exploration a practical and reliable tool for optimizing scientific exploration.

  1. Adaptation Challenges and Emerging Efforts in Adaptation Planning in California

    NASA Astrophysics Data System (ADS)

    Moser, S. C.

    2008-12-01

    Following Governor Schwarzenegger's Executive Order (S-03-05) of 2005, numerous researchers have been engaged in an ongoing assessment effort to support the state's mitigation and adaptation efforts. Under the sponsorship and coordination of the California Energy Commission's Public Interest Energy Research (PIER) Program, a wide range of climate change impacts and adaptation studies are being conducted and summarized on a biannual basis to assess the latest climate change science, potential impacts on critical sectors, and the state's efforts to manage its climate change risks. In the past, adaptation needs assessments in the state have primarily used a hazards-based (i.e., climate scenario-driven, top-down) approach, while vulnerability-based, bottom-up studies are only now emerging. They are increasingly viewed as complementary and necessary to adequately inform adaptation strategies. This paper briefly highlights this assessment history and then focuses on the planning efforts currently underway to prepare California's first state-wide adaptation plan. As the science and policy/management evolve in tandem, this paper will suggest future policy- or use-inspired research areas, and offer recommendations on how to improve interaction between researchers and practitioners at the science-policy interface, in order to build the state's decision support capacity in the face of a rapidly changing climate.

  2. Categorization = Decision Making + Generalization

    PubMed Central

    Seger, Carol A; Peterson, Erik J.

    2013-01-01

    We rarely, if ever, repeatedly encounter exactly the same situation. This makes generalization crucial for real world decision making. We argue that categorization, the study of generalizable representations, is a type of decision making, and that categorization learning research would benefit from approaches developed to study the neuroscience of decision making. Similarly, methods developed to examine generalization and learning within the field of categorization may enhance decision making research. We first discuss perceptual information processing and integration, with an emphasis on accumulator models. We then examine learning the value of different decision making choices via experience, emphasizing reinforcement learning modeling approaches. Next we discuss how value is combined with other factors in decision making, emphasizing the effects of uncertainty. Finally, we describe how a final decision is selected via thresholding processes implemented by the basal ganglia and related regions. We also consider how memory related functions in the hippocampus may be integrated with decision making mechanisms and contribute to categorization. PMID:23548891

  3. Reinventing Decision Making.

    ERIC Educational Resources Information Center

    Klempen, Robert A.

    2003-01-01

    Describes how three Wisconsin school superintendents used the process of situation appraisal and decision analysis to improve their problem-solving and decision-making capabilities and those of their leadership teams. Provides several examples. (PKP)

  4. Shared decision making

    MedlinePlus

    Shared decision making is when health care providers and patients work together to decide the best way to test ... you. The two of you will make a decision based on your provider's expertise and your values ...

  5. Building Capacity for Collaborative Decisions, Resilient Ecosystems, and Sustainable Practices: Water, Land, Communtiy and People in Estuarine Watersheds

    EPA Science Inventory

    Population growth, urban expansion, and the warming climate have and will continue to stress our coastal ecosystems. Decisions on how and when to respond with stewardship, adaptation, and mitigation are made by individuals, municipalities, states, and agencies. These decisions ...

  6. Quorum responses and consensus decision making

    PubMed Central

    Sumpter, David J.T.; Pratt, Stephen C.

    2008-01-01

    Animal groups are said to make consensus decisions when group members come to agree on the same option. Consensus decisions are taxonomically widespread and potentially offer three key benefits: maintenance of group cohesion, enhancement of decision accuracy compared with lone individuals and improvement in decision speed. In the absence of centralized control, arriving at a consensus depends on local interactions in which each individual's likelihood of choosing an option increases with the number of others already committed to that option. The resulting positive feedback can effectively direct most or all group members to the best available choice. In this paper, we examine the functional form of the individual response to others' behaviour that lies at the heart of this process. We review recent theoretical and empirical work on consensus decisions, and we develop a simple mathematical model to show the central importance to speedy and accurate decisions of quorum responses, in which an animal's probability of exhibiting a behaviour is a sharply nonlinear function of the number of other individuals already performing this behaviour. We argue that systems relying on such quorum rules can achieve cohesive choice of the best option while also permitting adaptive tuning of the trade-off between decision speed and accuracy. PMID:19073480

  7. Deciding about Decision Making.

    ERIC Educational Resources Information Center

    Hewitson, Mal

    Educational administrators have the power to determine the nature of decision-making structures and processes within their institutions and the extent to which decisions are implemented. This paper reviews assumptions underlying decision-making structures and processes established by school administrators; examines potential individual motives…

  8. Sustainability Based Decision Making

    EPA Science Inventory

    With sustainability as the “true north” for EPA research, a premium is placed on the ability to make decisions under highly complex and uncertain conditions. The primary challenge is reconciling disparate criteria toward credible and defensible decisions. Making decisions on on...

  9. Novice high school science teachers: Lesson plan adaptations

    NASA Astrophysics Data System (ADS)

    Scharon, Aracelis Janelle

    The Next Generation Science Standards (NRC, 2013) positions teachers as responsible for necessary decision making about how their intended science lesson plan content supports continuous student science learning. Teachers interact with their instructional lesson plans in dynamic and constructive ways. Adapting lesson plans is complex. This process of adapting lesson plans may play an important role in affording and constraining teachers' actions and students' learning (Brown, 2009). This study explored how five novice chemistry teachers (under 4 years of total teaching experience) at five Midwestern high schools adapted or retained their honors chemistry instructional lesson plans, and what associated contextual factors influenced their decisions. Using a case study design, this study was conducted during the fall semester of 2013 when teachers were focusing on introductory chemistry topics. Three frameworks (pedagogical content knowledge (PCK), teacher decision making, and pedagogical discontentment and self-efficacy) were used to investigate the relationships between teacher adaptations, contextual factors and decision making. The outcome of this study was the identification of 15 types of adaptations and 17 relevant contextual factors. Contextual factors were categorized by factors that relate to students or the teacher. Adaptations were categorized into three overarching types of adaptations: adapting the activity presented during the lesson, adapting the levels of support to assist students with the lesson plan content, and adapting the lesson plan to create another iteration of the same lesson plan that supports the next class. Lesson plan adaptations and contextual factors are discussed in the context of research on teacher decision making and lesson plan adaptations.

  10. Central Adaptation following Brachial Plexus Injury.

    PubMed

    Simon, Neil G; Franz, Colin K; Gupta, Nalin; Alden, Tord; Kliot, Michel

    2016-01-01

    Brachial plexus trauma (BPT) often affects young patients and may result in lasting functional deficits. Standard care following BPT involves monitoring for clinical and electrophysiological evidence of muscle reinnervation, with surgical treatment decisions based on the presence or absence of spontaneous recovery. Data are emerging to suggest that central and peripheral adaptation may play a role in recovery following BPT. The present review highlights adaptive and maladaptive mechanisms of central and peripheral nervous system changes following BPT that may contribute to functional outcomes. Rehabilitation and other treatment strategies that harness or modulate these intrinsic adaptive mechanisms may improve functional outcomes following BPT. PMID:26409073

  11. 76 FR 58807 - An Assessment of Decision-Making Processes: Evaluation of Where Land Protection Planning Can...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-09-22

    ... decision making. As part of a portfolio of adaptation strategies, land protection may become more important... climate change mitigation and adaptation. Dated: September 9, 2011. Darrell A. Winner, Acting...

  12. Decision Maker based on Nanoscale Photo-excitation Transfer

    NASA Astrophysics Data System (ADS)

    Kim, Song-Ju; Naruse, Makoto; Aono, Masashi; Ohtsu, Motoichi; Hara, Masahiko

    2013-08-01

    Decision-making is one of the most important intellectual abilities of the human brain. Here we propose an efficient decision-making system which uses optical energy transfer between quantum dots (QDs) mediated by optical near-field interactions occurring at scales far below the wavelength of light. The simulation results indicate that our system outperforms the softmax rule, which is known as the best-fitting algorithm for human decision-making behaviour. This suggests that we can produce a nano-system which makes decisions efficiently and adaptively by exploiting the intrinsic spatiotemporal dynamics involving QDs mediated by optical near-field interactions.

  13. Decision Maker based on Nanoscale Photo-excitation Transfer

    PubMed Central

    Kim, Song-Ju; Naruse, Makoto; Aono, Masashi; Ohtsu, Motoichi; Hara, Masahiko

    2013-01-01

    Decision-making is one of the most important intellectual abilities of the human brain. Here we propose an efficient decision-making system which uses optical energy transfer between quantum dots (QDs) mediated by optical near-field interactions occurring at scales far below the wavelength of light. The simulation results indicate that our system outperforms the softmax rule, which is known as the best-fitting algorithm for human decision-making behaviour. This suggests that we can produce a nano-system which makes decisions efficiently and adaptively by exploiting the intrinsic spatiotemporal dynamics involving QDs mediated by optical near-field interactions. PMID:23928655

  14. [Statins in primary prevention: how to share the decision?].

    PubMed

    Nanchen, David; Vonnez, Jean-Luc; Selby, Kevin; Auer, Reto; Cornuz, Jacques

    2015-11-25

    Long-term treatment of hypercholesterolemia with statins diminishes the risk of cardiovascular events. Statins are recommended in secondary prevention of cardiovascular disease. In the absence of preexisting cardiovascular disease, the decision to start a statin or not is most often made by the general practitioner and his patient. An interactive decision aid, developed by the Mayo Clinic, has just been translated in French and adapted to the Swiss epidemiology of cardiovascular risk factors, with the aim of promoting shared decision-making. This paper reviews the conditions and potential benefits of shared decision-making about statin therapy in primary prevention. PMID:26742352

  15. Make better decisions.

    PubMed

    Davenport, Thomas H

    2009-11-01

    Traditionally, decision making in organizations has rarely been the focus of systematic analysis. That may account for the astounding number of recent poor calls, such as decisions to invest in and securitize subprime mortgage loans or to hedge risk with credit default swaps. Business books are rich with insights about the decision process, but organizations have been slow to adopt their recommendations. It's time to focus on decision making, Davenport says, and he proposes four steps: (1) List and prioritize the decisions that must be made; (2) assess the factors that go into each, such as who plays what role, how often the decision must be made, and what information is available to support it; (3) design the roles, processes, systems, and behaviors your organization needs; and (4) institutionalize decision tools and assistance. The Educational Testing Service and The Stanley Works, among others, have succeeded in improving their decisions. ETS established a centralized deliberative body to make evidence-based decisions about new-product offerings, and Stanley has a Pricing Center of Excellence with internal consultants dedicated to its various business units. Leaders should bring multiple perspectives to their decision making, beware of analytical models that managers don't understand, be clear about their assumptions, practice "model management," and--because only people can revise decision criteria over time--cultivate human backups. PMID:19891389

  16. Demographics of reintroduced populations: estimation, modeling, and decision analysis

    USGS Publications Warehouse

    Converse, Sarah J.; Moore, Clinton T.; Armstrong, Doug P.

    2013-01-01

    Reintroduction can be necessary for recovering populations of threatened species. However, the success of reintroduction efforts has been poorer than many biologists and managers would hope. To increase the benefits gained from reintroduction, management decision making should be couched within formal decision-analytic frameworks. Decision analysis is a structured process for informing decision making that recognizes that all decisions have a set of components—objectives, alternative management actions, predictive models, and optimization methods—that can be decomposed, analyzed, and recomposed to facilitate optimal, transparent decisions. Because the outcome of interest in reintroduction efforts is typically population viability or related metrics, models used in decision analysis efforts for reintroductions will need to include population models. In this special section of the Journal of Wildlife Management, we highlight examples of the construction and use of models for informing management decisions in reintroduced populations. In this introductory contribution, we review concepts in decision analysis, population modeling for analysis of decisions in reintroduction settings, and future directions. Increased use of formal decision analysis, including adaptive management, has great potential to inform reintroduction efforts. Adopting these practices will require close collaboration among managers, decision analysts, population modelers, and field biologists.

  17. Distributed decision-making for space operations

    NASA Technical Reports Server (NTRS)

    Hornstein, Rhoda Shaller; Gardner, J. A.; Willoughby, J. K.

    1990-01-01

    A programmatic and technical perspective in the context of future space applications is presented, that includes some of the management challenges that arise as the decision-making process becomes increasingly more decentralized. Three challenges are discussed: (1) the degree to which the planners must communicate with each other and with those who are seeking space operations resources, (2) the collection, management, employment and dissemination of the information needed to make decisions, and (3) the challenges connected with schedule integration. The technical perspective presented leads to recommended adaptations to the normal scheduling algorithms that retain the 'degrees of freedom' in the planning result. It is shown that these adaptations are specific technical responses to the programmatic challenges discussed.

  18. Adaptive Management for Urban Watersheds: The Slavic Village Pilot Project

    EPA Science Inventory

    Adaptive management is an environmental management strategy that uses an iterative process of decision-making to reduce the uncertainty in environmental management via system monitoring. A central tenet of adaptive management is that management involves a learning process that ca...

  19. Development and Standardization of the Diagnostic Adaptive Behavior Scale: Application of Item Response Theory to the Assessment of Adaptive Behavior

    ERIC Educational Resources Information Center

    Tassé, Marc J.; Schalock, Robert L.; Thissen, David; Balboni, Giulia; Bersani, Henry, Jr.; Borthwick-Duffy, Sharon A.; Spreat, Scott; Widaman, Keith F.; Zhang, Dalun; Navas, Patricia

    2016-01-01

    The Diagnostic Adaptive Behavior Scale (DABS) was developed using item response theory (IRT) methods and was constructed to provide the most precise and valid adaptive behavior information at or near the cutoff point of making a decision regarding a diagnosis of intellectual disability. The DABS initial item pool consisted of 260 items. Using IRT…

  20. ADAPTATION AND ADAPTABILITY, THE BELLEFAIRE FOLLOWUP STUDY.

    ERIC Educational Resources Information Center

    ALLERHAND, MELVIN E.; AND OTHERS

    A RESEARCH TEAM STUDIED INFLUENCES, ADAPTATION, AND ADAPTABILITY IN 50 POORLY ADAPTING BOYS AT BELLEFAIRE, A REGIONAL CHILD CARE CENTER FOR EMOTIONALLY DISTURBED CHILDREN. THE TEAM ATTEMPTED TO GAUGE THE SUCCESS OF THE RESIDENTIAL TREATMENT CENTER IN TERMS OF THE PSYCHOLOGICAL PATTERNS AND ROLE PERFORMANCES OF THE BOYS DURING INDIVIDUAL CASEWORK…

  1. Decision Making: from Neuroscience to Psychiatry

    PubMed Central

    Lee, Daeyeol

    2013-01-01

    Adaptive behaviors increase the likelihood of survival and reproduction and improve the quality of life. However, it is often difficult to identify optimal behaviors in real life due to the complexity of the decision maker’s environment and social dynamics. As a result, although many different brain areas and circuits are involved in decision making, evolutionary and learning solutions adopted by individual decision makers sometimes produce suboptimal outcomes. Although these problems are exacerbated in numerous neurological and psychiatric disorders, their underlying neurobiological causes remain incompletely understood. In this review, theoretical frameworks in economics and machine learning and their applications in recent behavioral and neurobiological studies are summarized. Examples of such applications in clinical domains are also discussed for substance abuse, Parkinson’s disease, attention-deficit/hyperactivity disorder, schizophrenia, mood disorders, and autism. Findings from these studies have begun to lay the foundations necessary to improve diagnostics and treatment for various neurological and psychiatric disorders. PMID:23622061

  2. Correlates of risky decision-making.

    PubMed

    Plax, T G; Rosenfeld, L B

    1976-08-01

    The purpose of this investigation was to develop a personality pattern which could be used for both the explication and prediction of risky behavior in a variety of decision-making situations. Two months after the completion of a battery of psychological examinations, 240 randomly selected subjects responded to three problems adapted from the Kogan and Wallach Choice Dilemma Problems. Analyses of the data (correlational, factor analytic, and stepwise multiple regression) revealed a stable personality index representative of individuals exhibiting riskiness in decision-making. Variables contributing to this pattern characterized a dynamic task oriented individual. The results of this study should prove useful to future decision-making research by providing a framework for prediction. PMID:957088

  3. Depression: a decision-theoretic analysis.

    PubMed

    Huys, Quentin J M; Daw, Nathaniel D; Dayan, Peter

    2015-07-01

    The manifold symptoms of depression are common and often transient features of healthy life that are likely to be adaptive in difficult circumstances. It is when these symptoms enter a seemingly self-propelling spiral that the maladaptive features of a disorder emerge. We examine this malignant transformation from the perspective of the computational neuroscience of decision making, investigating how dysfunction of the brain's mechanisms of evaluation might lie at its heart. We start by considering the behavioral implications of pessimistic evaluations of decision variables. We then provide a selective review of work suggesting how such pessimism might arise via specific failures of the mechanisms of evaluation or state estimation. Finally, we analyze ways that miscalibration between the subject and environment may be self-perpetuating. We employ the formal framework of Bayesian decision theory as a foundation for this study, showing how most of the problems arise from one of its broad algorithmic facets, namely model-based reasoning. PMID:25705929

  4. Decision Making in Action

    NASA Technical Reports Server (NTRS)

    Orasanu, Judith; Statler, Irving C. (Technical Monitor)

    1994-01-01

    The importance of decision-making to safety in complex, dynamic environments like mission control centers and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. A similar observation has been made in nuclear power plants. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multidimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication

  5. Inertia and Decision Making.

    PubMed

    Alós-Ferrer, Carlos; Hügelschäfer, Sabine; Li, Jiahui

    2016-01-01

    Decision inertia is the tendency to repeat previous choices independently of the outcome, which can give rise to perseveration in suboptimal choices. We investigate this tendency in probability-updating tasks. Study 1 shows that, whenever decision inertia conflicts with normatively optimal behavior (Bayesian updating), error rates are larger and decisions are slower. This is consistent with a dual-process view of decision inertia as an automatic process conflicting with a more rational, controlled one. We find evidence of decision inertia in both required and autonomous decisions, but the effect of inertia is more clear in the latter. Study 2 considers more complex decision situations where further conflict arises due to reinforcement processes. We find the same effects of decision inertia when reinforcement is aligned with Bayesian updating, but if the two latter processes conflict, the effects are limited to autonomous choices. Additionally, both studies show that the tendency to rely on decision inertia is positively associated with preference for consistency. PMID:26909061

  6. Inertia and Decision Making

    PubMed Central

    Alós-Ferrer, Carlos; Hügelschäfer, Sabine; Li, Jiahui

    2016-01-01

    Decision inertia is the tendency to repeat previous choices independently of the outcome, which can give rise to perseveration in suboptimal choices. We investigate this tendency in probability-updating tasks. Study 1 shows that, whenever decision inertia conflicts with normatively optimal behavior (Bayesian updating), error rates are larger and decisions are slower. This is consistent with a dual-process view of decision inertia as an automatic process conflicting with a more rational, controlled one. We find evidence of decision inertia in both required and autonomous decisions, but the effect of inertia is more clear in the latter. Study 2 considers more complex decision situations where further conflict arises due to reinforcement processes. We find the same effects of decision inertia when reinforcement is aligned with Bayesian updating, but if the two latter processes conflict, the effects are limited to autonomous choices. Additionally, both studies show that the tendency to rely on decision inertia is positively associated with preference for consistency. PMID:26909061

  7. Adaptive Image Denoising by Mixture Adaptation.

    PubMed

    Luo, Enming; Chan, Stanley H; Nguyen, Truong Q

    2016-10-01

    We propose an adaptive learning procedure to learn patch-based image priors for image denoising. The new algorithm, called the expectation-maximization (EM) adaptation, takes a generic prior learned from a generic external database and adapts it to the noisy image to generate a specific prior. Different from existing methods that combine internal and external statistics in ad hoc ways, the proposed algorithm is rigorously derived from a Bayesian hyper-prior perspective. There are two contributions of this paper. First, we provide full derivation of the EM adaptation algorithm and demonstrate methods to improve the computational complexity. Second, in the absence of the latent clean image, we show how EM adaptation can be modified based on pre-filtering. The experimental results show that the proposed adaptation algorithm yields consistently better denoising results than the one without adaptation and is superior to several state-of-the-art algorithms. PMID:27416593

  8. Decisions about Drug Use. Adolescent Decisions Curriculum.

    ERIC Educational Resources Information Center

    Brion-Meisels, Steven; And Others

    This teacher's manual for drug abuse education is one volume of a six volume curriculum for the secondary level, designed to provide a systematic, group-oriented approach to decision-making in areas crucial to adolescent development: drug (substance) use and abuse, sexuality and social relationships, juvenile law, work and people and government.…

  9. Development and initial evaluation of a treatment decision dashboard

    PubMed Central

    2013-01-01

    Background For many healthcare decisions, multiple alternatives are available with different combinations of advantages and disadvantages across several important dimensions. The complexity of current healthcare decisions thus presents a significant barrier to informed decision making, a key element of patient-centered care. Interactive decision dashboards were developed to facilitate decision making in Management, a field marked by similarly complicated choices. These dashboards utilize data visualization techniques to reduce the cognitive effort needed to evaluate decision alternatives and a non-linear flow of information that enables users to review information in a self-directed fashion. Theoretically, both of these features should facilitate informed decision making by increasing user engagement with and understanding of the decision at hand. We sought to determine if the interactive decision dashboard format can be successfully adapted to create a clinically realistic prototype patient decision aid suitable for further evaluation and refinement. Methods We created a computerized, interactive clinical decision dashboard and performed a pilot test of its clinical feasibility and acceptability using a multi-method analysis. The dashboard summarized information about the effectiveness, risks of side effects and drug-drug interactions, out-of-pocket costs, and ease of use of nine analgesic treatment options for knee osteoarthritis. Outcome evaluations included observations of how study participants utilized the dashboard, questionnaires to assess usability, acceptability, and decisional conflict, and an open-ended qualitative analysis. Results The study sample consisted of 25 volunteers - 7 men and 18 women - with an average age of 51 years. The mean time spent interacting with the dashboard was 4.6 minutes. Mean evaluation scores on scales ranging from 1 (low) to 7 (high) were: mechanical ease of use 6.1, cognitive ease of use 6.2, emotional difficulty 2

  10. Decision Making and Cancer

    PubMed Central

    Reyna, Valerie F.; Nelson, Wendy L.; Han, Paul K.; Pignone, Michael P.

    2014-01-01

    We review decision-making along the cancer continuum in the contemporary context of informed and shared decision making, in which patients are encouraged to take a more active role in their health care. We discuss challenges to achieving informed and shared decision making, including cognitive limitations and emotional factors, but argue that understanding the mechanisms of decision making offers hope for improving decision support. Theoretical approaches to decision making that explain cognition, emotion, and their interaction are described, including classical psychophysical approaches, dual-process approaches that focus on conflicts between emotion versus cognition (or reason), and modern integrative approaches such as fuzzy-trace theory. In contrast to the earlier emphasis on rote use of numerical detail, modern approaches emphasize understanding the bottom-line gist of options (which encompasses emotion and other influences on meaning) and retrieving relevant social and moral values to apply to those gist representations. Finally, research on interventions to support better decision making in clinical settings is reviewed, drawing out implications for future research on decision making and cancer. PMID:25730718