Science.gov

Sample records for decision analysis based

  1. Climate policy decisions require policy-based lifecycle analysis.

    PubMed

    Bento, Antonio M; Klotz, Richard

    2014-05-20

    Lifecycle analysis (LCA) metrics of greenhouse gas emissions are increasingly being used to select technologies supported by climate policy. However, LCAs typically evaluate the emissions associated with a technology or product, not the impacts of policies. Here, we show that policies supporting the same technology can lead to dramatically different emissions impacts per unit of technology added, due to multimarket responses to the policy. Using a policy-based consequential LCA, we find that the lifecycle emissions impacts of four US biofuel policies range from a reduction of 16.1 gCO2e to an increase of 24.0 gCO2e per MJ corn ethanol added by the policy. The differences between these results and representative technology-based LCA measures, which do not account for the policy instrument driving the expansion in the technology, illustrate the need for policy-based LCA measures when informing policy decision making.

  2. A distance-based uncertainty analysis approach to multi-criteria decision analysis for water resource decision making.

    PubMed

    Hyde, K M; Maier, H R; Colby, C B

    2005-12-01

    The choice among alternative water supply sources is generally based on the fundamental objective of maximising the ratio of benefits to costs. There is, however, a need to consider sustainability, the environment and social implications in regional water resources planning, in addition to economics. In order to achieve this, multi-criteria decision analysis (MCDA) techniques can be used. Various sources of uncertainty exist in the application of MCDA methods, including the selection of the MCDA method, elicitation of criteria weights and assignment of criteria performance values. The focus of this paper is on the uncertainty in the criteria weights. Sensitivity analysis can be used to analyse the effects of uncertainties associated with the criteria weights. Two existing sensitivity methods are described in this paper and a new distance-based approach is proposed which overcomes limitations of these methods. The benefits of the proposed approach are the concurrent alteration of the criteria weights, the applicability of the method to a range of MCDA techniques and the identification of the most critical criteria weights. The existing and proposed methods are applied to three case studies and the results indicate that simultaneous consideration of the uncertainty in the criteria weights should be an integral part of the decision making process.

  3. Decision trees for symbolic knowledge based on contingency table analysis

    NASA Astrophysics Data System (ADS)

    Rauber, Thomas W.; Steiger-Garcao, A. S.

    1993-09-01

    In this paper we point out an alternative basis for splitting a node of a decision tree. We use exactly the same framework of the tree generation as ID3 does, in order to be able to compare the results properly. The splitting of the sample set is also done locally at a tree node, without considering earlier decisions about the partition of the samples. Only one attribute is used to split the samples. We point out different splitting criteria. Contingency tables are a technique in nonparametric statistics to analyze categorical (symbolic) populations. Among other useful applications of contingency tables, dependence tests between rows and columns of the table can be performed. A sample set is inserted into a contingency table with classes as columns and all values of an attribute as rows. A variety of measurements of dependence can then be derived. Results in respect to the two most important qualities of decision trees, the error rate and tree complexity, are presented. For a set of selected benchmark examples the performance of ID3 and the contingency table approach are compared. It is shown that in many cases the contingency table method exhibits lower estimated error rates or has less nodes for the generated decision tree.

  4. 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…

  5. Decision Aid Tool and Ontology-Based Reasoning for Critical Infrastructure Vulnerabilities and Threats Analysis

    NASA Astrophysics Data System (ADS)

    Choraś, Michał; Flizikowski, Adam; Kozik, Rafał; Hołubowicz, Witold

    In this paper, a decision aid tool (DAT) for Critical Infrastructure threats analysis and ranking is presented. We propose the ontology-based approach that provides classification, relationships and reasoning about vulnerabilities and threats of the critical infrastructures. Our approach is a part of research within INSPIRE project for increasing security and protection through infrastructure resilience.

  6. The basics of decision analysis.

    PubMed

    Kent, D L

    1992-12-01

    Historically, decision analysis (DA) arose from economics, psychology, and statistics. Medical and dental applications have developed over the past two decades. While decision psychology explores how people make their decisions, the DA process involves construction of a model and development of insights into the strengths and uncertainties about recommendations derived from analysis of model outputs. Uncertainties are represented as probabilities and values are assigned to desirable or adverse outcomes according to preferences expressed by the decision maker. The model unifies probabilities and values by calculation of the expected value for each decision choice. The decision maker can improve his or her insight into uncertainties in the model by conducting sensitivity analyses, and can take action based on this improved insight. The DA process is illustrated using the decision to take or skip influenza vaccination. People's decision making behavior for this problem has also been analyzed using methods from decision psychology. Distinctions between clinical DA and cost-effectiveness analysis are given, as are caveats about especially complicated subtopics in decision analysis for medical problems. In closing, opportunities for further study of decision analysis are presented. PMID:1487581

  7. Optimization-based multicriteria decision analysis for identification of desired petroleum-contaminated groundwater remediation strategies.

    PubMed

    Lu, Hongwei; Feng, Mao; He, Li; Ren, Lixia

    2015-06-01

    The conventional multicriteria decision analysis (MCDA) methods used for pollution control generally depend on the data currently available. This could limit their real-world applications, especially where the input data (e.g., the most cost-effective remediation cost and eventual contaminant concentration) might vary by scenario. This study proposes an optimization-based MCDA (OMCDA) framework to address such a challenge. It is capable of (1) capturing various preferences of decision-makers, (2) screening and analyzing the performance of various optimized remediation strategies under changeable scenarios, and (3) compromising incongruous decision analysis results. A real-world case study is employed for demonstration, where four scenarios are considered with each one corresponding to a set of weights representative of the preference of the decision-makers. Four criteria are selected, i.e., optimal total pumping rate, remediation cost, contaminant concentration, and fitting error. Their values are determined through running optimization and optimization-based simulation procedures. Four sets of the most desired groundwater remediation strategies are identified, implying specific pumping rates under varied scenarios. Results indicate that the best action lies in groups 32 and 16 for the 5-year, groups 49 and 36 for the 10-year, groups 26 and 13 for the 15-year, and groups 47 and 13 for the 20-year remediation.

  8. INEEL Subsurface Disposal Area CERCLA-based Decision Analysis for Technology Screening and Remedial Alternative Evaluation

    SciTech Connect

    Parnell, G. S.; Kloeber, Jr. J.; Westphal, D; Fung, V.; Richardson, John Grant

    2000-03-01

    A CERCLA-based decision analysis methodology for alternative evaluation and technology screening has been developed for application at the Idaho National Engineering and Environmental Laboratory WAG 7 OU13/14 Subsurface Disposal Area (SDA). Quantitative value functions derived from CERCLA balancing criteria in cooperation with State and Federal regulators are presented. A weighted criteria hierarchy is also summarized that relates individual value function numerical values to an overall score for a specific technology alternative.

  9. Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

    PubMed Central

    2010-01-01

    Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This paper presents Eb

  10. GIS Based Multi-Criteria Decision Analysis For Cement Plant Site Selection For Cuddalore District

    NASA Astrophysics Data System (ADS)

    Chhabra, A.

    2015-12-01

    India's cement industry is a vital part of its economy, providing employment to more than a million people. On the back of growing demands, due to increased construction and infrastructural activities cement market in India is expected to grow at a compound annual growth rate (CAGR) of 8.96 percent during the period 2014-2019. In this study, GIS-based spatial Multi Criteria Decision Analysis (MCDA) is used to determine the optimum and alternative sites to setup a cement plant. This technique contains a set of evaluation criteria which are quantifiable indicators of the extent to which decision objectives are realized. In intersection with available GIS (Geographical Information System) and local ancillary data, the outputs of image analysis serves as input for the multi-criteria decision making system. Moreover, the following steps were performed so as to represent the criteria in GIS layers, which underwent the GIS analysis in order to get several potential sites. Satellite imagery from LANDSAT 8 and ASTER DEM were used for the analysis. Cuddalore District in Tamil Nadu was selected as the study site as limestone mining is already being carried out in that region which meets the criteria of raw material for cement production. Several other criteria considered were land use land cover (LULC) classification (built-up area, river, forest cover, wet land, barren land, harvest land and agriculture land), slope, proximity to road, railway and drainage networks.

  11. Decision Analysis Using Spreadsheets.

    ERIC Educational Resources Information Center

    Sounderpandian, Jayavel

    1989-01-01

    Discussion of decision analysis and its importance in a business curriculum focuses on the use of spreadsheets instead of commercial software packages for computer assisted instruction. A hypothetical example is given of a company drilling for oil, and suggestions are provided for classroom exercises using spreadsheets. (seven references) (LRW)

  12. 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.

  13. Decision Support Framework Implementation Of The Web-Based Environmental Decision Analysis DASEES: Decision Analysis For A Sustainable Environment, Economy, And Society

    EPA Science Inventory

    Solutions to pervasive environmental problems often are not amenable to a straightforward application of science-based actions. These problems encompass large-scale environmental policy questions where environmental concerns, economic constraints, and societal values conflict ca...

  14. Risk-based economic decision analysis of remediation options at a PCE-contaminated site.

    PubMed

    Lemming, Gitte; Friis-Hansen, Peter; Bjerg, Poul L

    2010-05-01

    Remediation methods for contaminated sites cover a wide range of technical solutions with different remedial efficiencies and costs. Additionally, they may vary in their secondary impacts on the environment i.e. the potential impacts generated due to emissions and resource use caused by the remediation activities. More attention is increasingly being given to these secondary environmental impacts when evaluating remediation options. This paper presents a methodology for an integrated economic decision analysis which combines assessments of remediation costs, health risk costs and potential environmental costs. The health risks costs are associated with the residual contamination left at the site and its migration to groundwater used for drinking water. A probabilistic exposure model using first- and second-order reliability methods (FORM/SORM) is used to estimate the contaminant concentrations at a downstream groundwater well. Potential environmental impacts on the local, regional and global scales due to the site remediation activities are evaluated using life cycle assessments (LCA). The potential impacts on health and environment are converted to monetary units using a simplified cost model. A case study based upon the developed methodology is presented in which the following remediation scenarios are analyzed and compared: (a) no action, (b) excavation and off-site treatment of soil, (c) soil vapor extraction and (d) thermally enhanced soil vapor extraction by electrical heating of the soil. Ultimately, the developed methodology facilitates societal cost estimations of remediation scenarios which can be used for internal ranking of the analyzed options. Despite the inherent uncertainties of placing a value on health and environmental impacts, the presented methodology is believed to be valuable in supporting decisions on remedial interventions.

  15. GIS-based Landing-Site Analysis and Passive Decision Support

    NASA Astrophysics Data System (ADS)

    van Gasselt, Stephan; Nass, Andrea

    2016-04-01

    The increase of surface coverage and the availability and accessibility of planetary data allow researchers and engineers to remotely perform detailed studies on surface processes and properties, in particular on objects such as Mars and the Moon for which Terabytes of multi-temporal data at multiple spatial resolution levels have become available during the last 15 years. Orbiters, rovers and landers have been returning information and insights into the surface evolution of the terrestrial planets in unprecedented detail. While rover- and lander-based analyses are one major research aim to obtain ground truth, resource exploration or even potential establishment of bases using autonomous platforms are others and they require detailed investigation of settings in order to identify spots on the surface that are suitable for spacecraft to land and operate safely and over a long period of time. What has been done using hardcopy material in the past is today being carried by using either in-house developments or off-the-shelf spatial information system technology which allows to manage, integrate and analyse data as well as visualize and create user-defined reports for performing assessments. Usually, such analyses can be broken down (manually) by considering scientific wishes, engineering boundary conditions, potential hazards and various tertiary constraints. We here (1) review standard tasks of landing site analyses, (2) discuss issues inherently related to the analysis using integrated spatial analysis systems and (3) demonstrate a modular analysis framework for integration of data and for the evaluation of results from individual tasks in order to support decisions for landing-site selection.

  16. Risk-Based Prioritization of Research for Aviation Security Using Logic-Evolved Decision Analysis

    NASA Technical Reports Server (NTRS)

    Eisenhawer, S. W.; Bott, T. F.; Sorokach, M. R.; Jones, F. P.; Foggia, J. R.

    2004-01-01

    The National Aeronautics and Space Administration is developing advanced technologies to reduce terrorist risk for the air transportation system. Decision support tools are needed to help allocate assets to the most promising research. An approach to rank ordering technologies (using logic-evolved decision analysis), with risk reduction as the metric, is presented. The development of a spanning set of scenarios using a logic-gate tree is described. Baseline risk for these scenarios is evaluated with an approximate reasoning model. Illustrative risk and risk reduction results are presented.

  17. How accurate are interpretations of curriculum-based measurement progress monitoring data? Visual analysis versus decision rules.

    PubMed

    Van Norman, Ethan R; Christ, Theodore J

    2016-10-01

    Curriculum based measurement of oral reading (CBM-R) is used to monitor the effects of academic interventions for individual students. Decisions to continue, modify, or terminate these interventions are made by interpreting time series CBM-R data. Such interpretation is founded upon visual analysis or the application of decision rules. The purpose of this study was to compare the accuracy of visual analysis and decision rules. Visual analysts interpreted 108 CBM-R progress monitoring graphs one of three ways: (a) without graphic aids, (b) with a goal line, or (c) with a goal line and a trend line. Graphs differed along three dimensions, including trend magnitude, variability of observations, and duration of data collection. Automated trend line and data point decision rules were also applied to each graph. Inferential analyses permitted the estimation of the probability of a correct decision (i.e., the student is improving - continue the intervention, or the student is not improving - discontinue the intervention) for each evaluation method as a function of trend magnitude, variability of observations, and duration of data collection. All evaluation methods performed better when students made adequate progress. Visual analysis and decision rules performed similarly when observations were less variable. Results suggest that educators should collect data for more than six weeks, take steps to control measurement error, and visually analyze graphs when data are variable. Implications for practice and research are discussed. PMID:27586069

  18. How accurate are interpretations of curriculum-based measurement progress monitoring data? Visual analysis versus decision rules.

    PubMed

    Van Norman, Ethan R; Christ, Theodore J

    2016-10-01

    Curriculum based measurement of oral reading (CBM-R) is used to monitor the effects of academic interventions for individual students. Decisions to continue, modify, or terminate these interventions are made by interpreting time series CBM-R data. Such interpretation is founded upon visual analysis or the application of decision rules. The purpose of this study was to compare the accuracy of visual analysis and decision rules. Visual analysts interpreted 108 CBM-R progress monitoring graphs one of three ways: (a) without graphic aids, (b) with a goal line, or (c) with a goal line and a trend line. Graphs differed along three dimensions, including trend magnitude, variability of observations, and duration of data collection. Automated trend line and data point decision rules were also applied to each graph. Inferential analyses permitted the estimation of the probability of a correct decision (i.e., the student is improving - continue the intervention, or the student is not improving - discontinue the intervention) for each evaluation method as a function of trend magnitude, variability of observations, and duration of data collection. All evaluation methods performed better when students made adequate progress. Visual analysis and decision rules performed similarly when observations were less variable. Results suggest that educators should collect data for more than six weeks, take steps to control measurement error, and visually analyze graphs when data are variable. Implications for practice and research are discussed.

  19. Applicability of risk-based management and the need for risk-based economic decision analysis at hazardous waste contaminated sites.

    PubMed

    Khadam, Ibrahim; Kaluarachchi, Jagath J

    2003-07-01

    Decision analysis in subsurface contamination management is generally carried out through a traditional engineering economic viewpoint. However, new advances in human health risk assessment, namely, the probabilistic risk assessment, and the growing awareness of the importance of soft data in the decision-making process, require decision analysis methodologies that are capable of accommodating non-technical and politically biased qualitative information. In this work, we discuss the major limitations of the currently practiced decision analysis framework, which evolves around the definition of risk and cost of risk, and its poor ability to communicate risk-related information. A demonstration using a numerical example was conducted to provide insight on these limitations of the current decision analysis framework. The results from this simple ground water contamination and remediation scenario were identical to those obtained from studies carried out on existing Superfund sites, which suggests serious flaws in the current risk management framework. In order to provide a perspective on how these limitations may be avoided in future formulation of the management framework, more matured and well-accepted approaches to decision analysis in dam safety and the utility industry, where public health and public investment are of great concern, are presented and their applicability in subsurface remediation management is discussed. Finally, in light of the success of the application of risk-based decision analysis in dam safety and the utility industry, potential options for decision analysis in subsurface contamination management are discussed.

  20. Analysis of Phase Transition in Traffic Flow based on a New Model of Driving Decision

    NASA Astrophysics Data System (ADS)

    Peng, Yu; Shang, Hua-Yan; Lu, Hua-Pu

    2011-07-01

    Different driving decisions will cause different processes of phase transition in traffic flow. To reveal the inner mechanism, this paper built a new cellular automaton (CA) model, based on the driving decision (DD). In the DD model, a driver's decision is divided into three stages: decision-making, action, and result. The acceleration is taken as a decision variable and three core factors, i.e. distance between adjacent vehicles, their own velocity, and the preceding vehicle's velocity, are considered. Simulation results show that the DD model can simulate the synchronized flow effectively and describe the phase transition in traffic flow well. Further analyses illustrate that various density will cause the phase transition and the random probability will impact the process. Compared with the traditional NaSch model, the DD model considered the preceding vehicle's velocity, the deceleration limitation, and a safe distance, so it can depict closer to the driver preferences on pursuing safety, stability and fuel-saving and has strong theoretical innovation for future studies.

  1. Model-based decision analysis of remedial alternatives using info-gap theory and Agent-Based Analysis of Global Uncertainty and Sensitivity (ABAGUS)

    NASA Astrophysics Data System (ADS)

    Harp, D.; Vesselinov, V. V.

    2011-12-01

    A newly developed methodology to model-based decision analysis is presented. The methodology incorporates a sampling approach, referred to as Agent-Based Analysis of Global Uncertainty and Sensitivity (ABAGUS; Harp & Vesselinov; 2011), that efficiently collects sets of acceptable solutions (i.e. acceptable model parameter sets) for different levels of a model performance metric representing the consistency of model predictions to observations. In this case, the performance metric is based on model residuals (i.e. discrepancies between observations and simulations). ABAGUS collects acceptable solutions from a discretized parameter space and stores them in a KD-tree for efficient retrieval. The parameter space domain (parameter minimum/maximum ranges) and discretization are predefined. On subsequent visits to collected locations, agents are provided with a modified value of the performance metric, and the model solution is not recalculated. The modified values of the performance metric sculpt the response surface (convexities become concavities), repulsing agents from collected regions. This promotes global exploration of the parameter space and discourages reinvestigation of regions of previously collected acceptable solutions. The resulting sets of acceptable solutions are formulated into a decision analysis using concepts from info-gap theory (Ben-Haim, 2006). Using info-gap theory, the decision robustness and opportuneness are quantified, providing measures of the immunity to failure and windfall, respectively, of alternative decisions. The approach is intended for cases where the information is extremely limited, resulting in non-probabilistic uncertainties concerning model properties such as boundary and initial conditions, model parameters, conceptual model elements, etc. The information provided by this analysis is weaker than the information provided by probabilistic decision analyses (i.e. posterior parameter distributions are not produced), however, this

  2. 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...

  3. Environmental condition assessment of US military installations using GIS based spatial multi-criteria decision analysis.

    PubMed

    Singer, Steve; Wang, Guangxing; Howard, Heidi; Anderson, Alan

    2012-08-01

    Environment functions in various aspects including soil and water conservation, biodiversity and habitats, and landscape aesthetics. Comprehensive assessment of environmental condition is thus a great challenge. The issues include how to assess individual environmental components such as landscape aesthetics and integrate them into an indicator that can comprehensively quantify environmental condition. In this study, a geographic information systems based spatial multi-criteria decision analysis was used to integrate environmental variables and create the indicator. This approach was applied to Fort Riley Military installation in which land condition and its dynamics due to military training activities were assessed. The indicator was derived by integrating soil erosion, water quality, landscape fragmentation, landscape aesthetics, and noise based on the weights from the experts by assessing and ranking the environmental variables in terms of their importance. The results showed that landscape level indicator well quantified the overall environmental condition and its dynamics, while the indicator at level of patch that is defined as a homogeneous area that is different from its surroundings detailed the spatiotemporal variability of environmental condition. The environmental condition was mostly determined by soil erosion, then landscape fragmentation, water quality, landscape aesthetics, and noise. Overall, environmental condition at both landscape and patch levels greatly varied depending on the degree of ground and canopy disturbance and their spatial patterns due to military training activities and being related to slope. It was also determined the environment itself could be recovered quickly once military training was halt or reduced. Thus, this study provided an effective tool for the army land managers to monitor environmental dynamics and plan military training activities. Its limitation lies at that the obtained values of the indicator vary and are

  4. Risk-based decision analysis of atmospheric emission alternatives to reduce ground water degradation on the European scale

    SciTech Connect

    Wladis, D.; Rosen, L.; Kros, H.

    1999-12-01

    Environmental degradation due to emissions of sulfur dioxide, nitrate oxides, and ammonia from diffuse sources amounts to substantial costs to society and so do the alternatives to protect and restore the environment. Damage to ground water includes acidification, aluminum leaching, elevated concentrations of nitrate, and eutrophication. Monetary risk-based decision analysis (on a national scale) is applied to compare alternative actions designed to protect ground water from further degradation. This decision analysis uses simulations of nitrate and aluminum concentrations over a 15 year period with two reduction scenarios for sulfur dioxide, nitrate oxides, and ammonia, and results in estimates of economic uncertainty. For each alternative, an objective function is estimated including the implementation costs, the economic risk associated with failure according to the selected decision criteria, and the economic benefits related to the implementation. The decision criteria are based on the European Community drinking water quality standards for nitrate and aluminum. The study aims at incorporating the hydrogeologic uncertainty resulting from the propagation of errors from data input to model out put. A range of economic values has been applied to the ground water resource to study the sensitivity of the decision analysis to valuing ground water. The results indicate that higher reduction rates of the studied pollutants reduce the economic uncertainty but also lead to larger total costs. The study also indicates that the economic uncertainty may be equal to the total cost provided by the objective function. The contamination level of nitrate is much more responsive to the reduction scenarios than the aluminum concentration. For high, but not unrealistic, ground water valuing, the economic uncertainty makes the decision between the studied alternatives unclear.

  5. Application of risk-based multiple criteria decision analysis for selection of the best agricultural scenario for effective watershed management.

    PubMed

    Javidi Sabbaghian, Reza; Zarghami, Mahdi; Nejadhashemi, A Pouyan; Sharifi, Mohammad Bagher; Herman, Matthew R; Daneshvar, Fariborz

    2016-03-01

    Effective watershed management requires the evaluation of agricultural best management practice (BMP) scenarios which carefully consider the relevant environmental, economic, and social criteria involved. In the Multiple Criteria Decision-Making (MCDM) process, scenarios are first evaluated and then ranked to determine the most desirable outcome for the particular watershed. The main challenge of this process is the accurate identification of the best solution for the watershed in question, despite the various risk attitudes presented by the associated decision-makers (DMs). This paper introduces a novel approach for implementation of the MCDM process based on a comparative neutral risk/risk-based decision analysis, which results in the selection of the most desirable scenario for use in the entire watershed. At the sub-basin level, each scenario includes multiple BMPs with scores that have been calculated using the criteria derived from two cases of neutral risk and risk-based decision-making. The simple additive weighting (SAW) operator is applied for use in neutral risk decision-making, while the ordered weighted averaging (OWA) and induced OWA (IOWA) operators are effective for risk-based decision-making. At the watershed level, the BMP scores of the sub-basins are aggregated to calculate each scenarios' combined goodness measurements; the most desirable scenario for the entire watershed is then selected based on the combined goodness measurements. Our final results illustrate the type of operator and risk attitudes needed to satisfy the relevant criteria within the number of sub-basins, and how they ultimately affect the final ranking of the given scenarios. The methodology proposed here has been successfully applied to the Honeyoey Creek-Pine Creek watershed in Michigan, USA to evaluate various BMP scenarios and determine the best solution for both the stakeholders and the overall stream health.

  6. Decision Envelopment Analysis of space and terrestrially-based large scale commercial power systems for earth

    NASA Astrophysics Data System (ADS)

    Criswell, David R.; Thompson, Russell G.

    1992-08-01

    Decision Envelopment Analysis (DEA), the detailed quantitative comparison of alternative economic systems, is used to compare the technical efficiency of the large-scale power systems needed to meet the growing energy needs of terrestrial society. The Lunar Power System (LPS) captures sunlight on the moon, converts it to microwaves and beams the power to receivers on earth that output electricity. In terms of benefits versus costs, normalized to the range of 0 to 1, DEA reveals that LPS is at least ten times more efficient than conventional terrestrial solar-thermal and -photovoltaic, fossil, and nuclear systems. LPS is also environmentally benign compared to the conventional systems.

  7. Risk-based analysis and decision making in multi-disciplinary environments

    NASA Technical Reports Server (NTRS)

    Feather, Martin S.; Cornford, Steven L.; Moran, Kelly

    2003-01-01

    A risk-based decision-making process conceived of and developed at JPL and NASA, has been used to help plan and guide novel technology applications for use on spacecraft. These applications exemplify key challenges inherent in multi-disciplinary design of novel technologies deployed in mission-critical settings. 1) Cross-disciplinary concerns are numerous (e.g., spacecraft involve navigation, propulsion, telecommunications). These concems are cross-coupled and interact in multiple ways (e.g., electromagnetic interference, heat transfer). 2) Time and budget pressures constrain development, operational resources constrain the resulting system (e.g., mass, volume, power). 3) Spacecraft are critical systems that must operate correctly the first time in only partially understood environments, with no chance for repair. 4) Past experience provides only a partial guide: New mission concepts are enhanced and enabled by new technologies, for which past experience is lacking. The decision-making process rests on quantitative assessments of the relationships between three classes of information - objectives (the things the system is to accomplish and constraints on its operation and development), risks (whose occurrence detracts from objectives), and mitigations (options for reducing the likelihood and or severity of risks). The process successfully guides experts to pool their knowledge, using custom-built software to support information gathering and decision-making.

  8. Use of social science-based analysis in bureaucratic decision making: regulatory analysis in the Environmental Protection Agency

    SciTech Connect

    Mogee, M.E.

    1983-01-01

    This dissertation studies the use of regulatory analysis (a form of cost-benefit analysis) in Environmental Protection Agency (EPA) decision making. It addresses the questions of how the analysis was used, what influence it had on the regulations, and what the major factors were that affected its use. Case studies were conducted of six EPA rule makings during the period 1978 to 1980, including: Premanufacture Notification under TSCA Section 5; the Carbon Monoxide National Ambient Air Quality Standard; Visibility Protection; Light-Duty Truck gaseous emissions; effluent guidelines for Timber Products industries; and Motorcycle Noise standards. Data for the cases came from official documents and interviews with EPA participants. Regulatory analysis was used in EPA regulation development in six ways: in decision making, to support or legitimate, in intra-agency partisan negotiations, to review or exercise quality control, to describe or educate, and in external relations. The influence of the analysis on the regulations in these cases varied from almost none to moderately high. Even in those cases where the analysis was used in decision making and had relatively high influence, however, it was only one of many factors affecting the regulation. The major factors found to affect the use of regulatory analysis, in addition to the overall context set by EPA's regulation development process, were: the statute; program considerations; the existence of a tradition of economic analysis; the structure and quality of the analysis itself; the timing of the analysis with respect to the rule making; and scientific, technical, and implementation uncertainties.

  9. Integrating multi-criteria decision analysis for a GIS-based hazardous waste landfill sitting in Kurdistan Province, western Iran

    SciTech Connect

    Sharifi, Mozafar Hadidi, Mosslem Vessali, Elahe Mosstafakhani, Parasto Taheri, Kamal Shahoie, Saber Khodamoradpour, Mehran

    2009-10-15

    The evaluation of a hazardous waste disposal site is a complicated process because it requires data from diverse social and environmental fields. These data often involve processing of a significant amount of spatial information which can be used by GIS as an important tool for land use suitability analysis. This paper presents a multi-criteria decision analysis alongside with a geospatial analysis for the selection of hazardous waste landfill sites in Kurdistan Province, western Iran. The study employs a two-stage analysis to provide a spatial decision support system for hazardous waste management in a typically under developed region. The purpose of GIS was to perform an initial screening process to eliminate unsuitable land followed by utilization of a multi-criteria decision analysis (MCDA) to identify the most suitable sites using the information provided by the regional experts with reference to new chosen criteria. Using 21 exclusionary criteria, as input layers, masked maps were prepared. Creating various intermediate or analysis map layers a final overlay map was obtained representing areas for hazardous waste landfill sites. In order to evaluate different landfill sites produced by the overlaying a landfill suitability index system was developed representing cumulative effects of relative importance (weights) and suitability values of 14 non-exclusionary criteria including several criteria resulting from field observation. Using this suitability index 15 different sites were visited and based on the numerical evaluation provided by MCDA most suitable sites were determined.

  10. Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations

    PubMed Central

    Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

    2015-01-01

    Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions. PMID:26089862

  11. Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations.

    PubMed

    Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

    2015-01-01

    Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions.

  12. The Neural Substrate of Prior Information in Perceptual Decision Making: A Model-Based Analysis

    PubMed Central

    Forstmann, Birte U.; Brown, Scott; Dutilh, Gilles; Neumann, Jane; Wagenmakers, Eric-Jan

    2010-01-01

    Prior information biases the decision process: actions consistent with prior information are executed swiftly, whereas actions inconsistent with prior information are executed slowly. How is this bias implemented in the brain? To address this question we conducted an experiment in which people had to decide quickly whether a cloud of dots moved coherently to the left or to the right. Cues provided probabilistic information about the upcoming stimulus. Behavioral data were analyzed with the linear ballistic accumulator (LBA) model, confirming that people used the cue to bias their decisions. The functional magnetic resonance imaging (fMRI) data showed that presentation of the cue differentially activated orbitofrontal cortex, hippocampus, and the putamen. Directional cues selectively activated the contralateral putamen. The fMRI analysis yielded results only when the LBA bias parameter was included as a covariate, highlighting the practical benefits of formal modeling. Our results suggest that the human brain uses prior information by increasing cortico-striatal activation to selectively disinhibit preferred responses. PMID:20577592

  13. Material degradation analysis and maintenance decisions based on material condition monitoring during in-service inspections

    SciTech Connect

    Yacout, A.M.; Orechwa, Y.

    1996-03-01

    The degradation of the material in critical components is shown to be an effective measure which can be used to compute the risk adjusted economic penalty associated with different maintenance decisions. The approach of estimating the probability, with confidence interval, of the time that a prescribed degradation level is exceeded is shown to be practical, as demonstrated in the analysis of irradiated fuel cladding. The methodology for the estimation of the probability is predicated on the existence of a parsimonious and robust mixed-effects model of the evolution of the degradation. This model, in general, relates measured surrogates of the degradation level to computed or measured variables, which characterize the environment during the operating history of the component. We propose and demonstrate the efficacy of using an artificial neural network, constructed via a genetic supervisor, as an aid in developing the requisite mixed-effects model and testing its continued validity as new data are obtained.

  14. Screening for Chlamydia trachomatis in adolescent males: a cost-based decision analysis.

    PubMed Central

    Randolph, A G; Washington, A E

    1990-01-01

    To evaluate the cost and benefits of screening tests for Chlamydia trachomatis in adolescent males, we developed a decision analysis model and compared the leukocyte esterase urine dipstick test with culture, with direct-smear fluorescent antibody (DFA), and with the option of no screening (no treatment). The leukocyte esterase test has the lowest average cost-per-cure ($51) compared with direct-smear fluorescent antibody ($192) and culture ($414). Compared with the DFA, we estimate that the leukocyte esterase test saves over $9,727 per cohort of 1,000 sexually active adolescent males screened. Sensitivity analyses show the leukocyte esterase test results in a lower cost-per-cure and lower overall costs (per cohort) than culture and direct-smear fluorescent antibody at any prevalence of C. trachomatis infection, and lower overall costs (per cohort) than no screening at prevalences above 21 percent. PMID:2109544

  15. Decisions Based on Science.

    ERIC Educational Resources Information Center

    Campbell, Vincent; Lofstrom, Jocelyn; Jerome, Brian

    This guide makes the case for a decision-making focus in the science curriculum as a response to concern over preparing scientifically literate students. The student activities are organized by guided activities and independent exercises. Themes of the guided activities include xenotransplants, immunizations, household cleaning products, ozone,…

  16. The conscious mind and its emergent properties; an analysis based on decision theory.

    PubMed

    Morris, James A

    2011-08-01

    The process of conscious and unconscious decision making is analyzed using decision theory. An essential part of an optimum decision strategy is the assessment of values and costs associated with correct and incorrect decisions. In the case of unconscious decisions this involves an automatic process akin to computation using numerical values. But for conscious decisions the conscious mind must experience the outcome of the decision as pleasure or pain. It is suggested that the rules of behavior are programmed in our genes but modified by experience of the society in which we are reared. Our unconscious then uses the rules to reward or punish our conscious mind for the decisions it makes. This is relevant to concepts of altruism and religion in society. It is consistent with the observation that we prefer beauty to utility. The decision theory equations also explain the paradox that a single index of happiness can be applied in society. The symptoms of mental illness can be due to appropriate or inappropriate action by the unconscious. The former indicates a psychological conflict between conscious and unconscious decision making. Inappropriate action indicates that a pathological process has switched on genetic networks that should be switched off.

  17. Diagnosis of pulmonary hypertension from magnetic resonance imaging-based computational models and decision tree analysis.

    PubMed

    Lungu, Angela; Swift, Andrew J; Capener, David; Kiely, David; Hose, Rod; Wild, Jim M

    2016-06-01

    Accurately identifying patients with pulmonary hypertension (PH) using noninvasive methods is challenging, and right heart catheterization (RHC) is the gold standard. Magnetic resonance imaging (MRI) has been proposed as an alternative to echocardiography and RHC in the assessment of cardiac function and pulmonary hemodynamics in patients with suspected PH. The aim of this study was to assess whether machine learning using computational modeling techniques and image-based metrics of PH can improve the diagnostic accuracy of MRI in PH. Seventy-two patients with suspected PH attending a referral center underwent RHC and MRI within 48 hours. Fifty-seven patients were diagnosed with PH, and 15 had no PH. A number of functional and structural cardiac and cardiovascular markers derived from 2 mathematical models and also solely from MRI of the main pulmonary artery and heart were integrated into a classification algorithm to investigate the diagnostic utility of the combination of the individual markers. A physiological marker based on the quantification of wave reflection in the pulmonary artery was shown to perform best individually, but optimal diagnostic performance was found by the combination of several image-based markers. Classifier results, validated using leave-one-out cross validation, demonstrated that combining computation-derived metrics reflecting hemodynamic changes in the pulmonary vasculature with measurement of right ventricular morphology and function, in a decision support algorithm, provides a method to noninvasively diagnose PH with high accuracy (92%). The high diagnostic accuracy of these MRI-based model parameters may reduce the need for RHC in patients with suspected PH. PMID:27252844

  18. Diagnosis of pulmonary hypertension from magnetic resonance imaging-based computational models and decision tree analysis.

    PubMed

    Lungu, Angela; Swift, Andrew J; Capener, David; Kiely, David; Hose, Rod; Wild, Jim M

    2016-06-01

    Accurately identifying patients with pulmonary hypertension (PH) using noninvasive methods is challenging, and right heart catheterization (RHC) is the gold standard. Magnetic resonance imaging (MRI) has been proposed as an alternative to echocardiography and RHC in the assessment of cardiac function and pulmonary hemodynamics in patients with suspected PH. The aim of this study was to assess whether machine learning using computational modeling techniques and image-based metrics of PH can improve the diagnostic accuracy of MRI in PH. Seventy-two patients with suspected PH attending a referral center underwent RHC and MRI within 48 hours. Fifty-seven patients were diagnosed with PH, and 15 had no PH. A number of functional and structural cardiac and cardiovascular markers derived from 2 mathematical models and also solely from MRI of the main pulmonary artery and heart were integrated into a classification algorithm to investigate the diagnostic utility of the combination of the individual markers. A physiological marker based on the quantification of wave reflection in the pulmonary artery was shown to perform best individually, but optimal diagnostic performance was found by the combination of several image-based markers. Classifier results, validated using leave-one-out cross validation, demonstrated that combining computation-derived metrics reflecting hemodynamic changes in the pulmonary vasculature with measurement of right ventricular morphology and function, in a decision support algorithm, provides a method to noninvasively diagnose PH with high accuracy (92%). The high diagnostic accuracy of these MRI-based model parameters may reduce the need for RHC in patients with suspected PH.

  19. Diagnosis of pulmonary hypertension from magnetic resonance imaging–based computational models and decision tree analysis

    PubMed Central

    Swift, Andrew J.; Capener, David; Kiely, David; Hose, Rod; Wild, Jim M.

    2016-01-01

    Abstract Accurately identifying patients with pulmonary hypertension (PH) using noninvasive methods is challenging, and right heart catheterization (RHC) is the gold standard. Magnetic resonance imaging (MRI) has been proposed as an alternative to echocardiography and RHC in the assessment of cardiac function and pulmonary hemodynamics in patients with suspected PH. The aim of this study was to assess whether machine learning using computational modeling techniques and image-based metrics of PH can improve the diagnostic accuracy of MRI in PH. Seventy-two patients with suspected PH attending a referral center underwent RHC and MRI within 48 hours. Fifty-seven patients were diagnosed with PH, and 15 had no PH. A number of functional and structural cardiac and cardiovascular markers derived from 2 mathematical models and also solely from MRI of the main pulmonary artery and heart were integrated into a classification algorithm to investigate the diagnostic utility of the combination of the individual markers. A physiological marker based on the quantification of wave reflection in the pulmonary artery was shown to perform best individually, but optimal diagnostic performance was found by the combination of several image-based markers. Classifier results, validated using leave-one-out cross validation, demonstrated that combining computation-derived metrics reflecting hemodynamic changes in the pulmonary vasculature with measurement of right ventricular morphology and function, in a decision support algorithm, provides a method to noninvasively diagnose PH with high accuracy (92%). The high diagnostic accuracy of these MRI-based model parameters may reduce the need for RHC in patients with suspected PH. PMID:27252844

  20. Student Portfolio Analysis by Data Cube Technology for Decision Support of Web-based Classroom Teacher.

    ERIC Educational Resources Information Center

    Chang, Chih-Kai; Chen, Gwo-Dong; Ou, Kou-Liang

    1998-01-01

    Proposes a Web-based model as the infrastructure to store learning logs for analysis in distance education. Describes the method of using query language to retrieve information from a database to construct the data cube. Illustrates data-cube implementation with a group-discussion example. Shows how data-cube technology can solve the recording and…

  1. The Research of Spatial-Temporal Analysis and Decision-Making Assistant System for Disabled Person Affairs Based on Mapworld

    NASA Astrophysics Data System (ADS)

    Zhang, J. H.; Yang, J.; Sun, Y. S.

    2015-06-01

    This system combines the Mapworld platform and informationization of disabled person affairs, uses the basic information of disabled person as center frame. Based on the disabled person population database, the affairs management system and the statistical account system, the data were effectively integrated and the united information resource database was built. Though the data analysis and mining, the system provides powerful data support to the decision making, the affairs managing and the public serving. It finally realizes the rationalization, normalization and scientization of disabled person affairs management. It also makes significant contributions to the great-leap-forward development of the informationization of China Disabled Person's Federation.

  2. Latent effects decision analysis

    DOEpatents

    Cooper, J. Arlin; Werner, Paul W.

    2004-08-24

    Latent effects on a system are broken down into components ranging from those far removed in time from the system under study (latent) to those which closely effect changes in the system. Each component is provided with weighted inputs either by a user or from outputs of other components. A non-linear mathematical process known as `soft aggregation` is performed on the inputs to each component to provide information relating to the component. This information is combined in decreasing order of latency to the system to provide a quantifiable measure of an attribute of a system (e.g., safety) or to test hypotheses (e.g., for forensic deduction or decisions about various system design options).

  3. Multicriteria decision analysis in oncology

    PubMed Central

    Adunlin, Georges; Diaby, Vakaramoko; Montero, Alberto J.; Xiao, Hong

    2015-01-01

    Background There has been a growing interest in the development and application of alternative decision-making frameworks within health care, including multicriteria decision analysis (MCDA). Even though the literature includes several reviews on MCDA methods, applications of MCDA in oncology are lacking. Aim The aim of this paper is to discuss a rationale for the use of MCDA in oncology. In this context, the following research question emerged: How can MCDA be used to develop a clinical decision support tool in oncology? Methods In this paper, a brief background on decision making is presented, followed by an overview of MCDA methods and process. The paper discusses some applications of MCDA, proposes research opportunities in the context of oncology and presents an illustrative example of how MCDA can be applied to oncology. Findings Decisions in oncology involve trade-offs between possible benefits and harms. MCDA can help analyse trade-off preferences. A wide range of MCDA methods exist. Each method has its strengths and weaknesses. Choosing the appropriate method varies depending on the source and nature of information used to inform decision making. The literature review identified eight studies. The analytical hierarchy process (AHP) was the most often used method in the identified studies. Conclusion Overall, MCDA appears to be a promising tool that can be used to assist clinical decision making in oncology. Nonetheless, field testing is desirable before MCDA becomes an established decision-making tool in this field. PMID:24635949

  4. Staged decision making based on probabilistic forecasting

    NASA Astrophysics Data System (ADS)

    Booister, Nikéh; Verkade, Jan; Werner, Micha; Cranston, Michael; Cumiskey, Lydia; Zevenbergen, Chris

    2016-04-01

    Flood forecasting systems reduce, but cannot eliminate uncertainty about the future. Probabilistic forecasts explicitly show that uncertainty remains. However, as - compared to deterministic forecasts - a dimension is added ('probability' or 'likelihood'), with this added dimension decision making is made slightly more complicated. A technique of decision support is the cost-loss approach, which defines whether or not to issue a warning or implement mitigation measures (risk-based method). With the cost-loss method a warning will be issued when the ratio of the response costs to the damage reduction is less than or equal to the probability of the possible flood event. This cost-loss method is not widely used, because it motivates based on only economic values and is a technique that is relatively static (no reasoning, yes/no decision). Nevertheless it has high potential to improve risk-based decision making based on probabilistic flood forecasting because there are no other methods known that deal with probabilities in decision making. The main aim of this research was to explore the ways of making decision making based on probabilities with the cost-loss method better applicable in practice. The exploration began by identifying other situations in which decisions were taken based on uncertain forecasts or predictions. These cases spanned a range of degrees of uncertainty: from known uncertainty to deep uncertainty. Based on the types of uncertainties, concepts of dealing with situations and responses were analysed and possible applicable concepts where chosen. Out of this analysis the concepts of flexibility and robustness appeared to be fitting to the existing method. Instead of taking big decisions with bigger consequences at once, the idea is that actions and decisions are cut-up into smaller pieces and finally the decision to implement is made based on economic costs of decisions and measures and the reduced effect of flooding. The more lead-time there is in

  5. Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials.

    PubMed

    Hristozov, Danail; Zabeo, Alex; Alstrup Jensen, Keld; Gottardo, Stefania; Isigonis, Panagiotis; Maccalman, Laura; Critto, Andrea; Marcomini, Antonio

    2016-11-01

    Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.

  6. Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials.

    PubMed

    Hristozov, Danail; Zabeo, Alex; Alstrup Jensen, Keld; Gottardo, Stefania; Isigonis, Panagiotis; Maccalman, Laura; Critto, Andrea; Marcomini, Antonio

    2016-11-01

    Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables. PMID:26853193

  7. Initial Decision and Risk Analysis

    SciTech Connect

    Engel, David W.

    2012-02-29

    Decision and Risk Analysis capabilities will be developed for industry consideration and possible adoption within Year 1. These tools will provide a methodology for merging qualitative ranking of technology maturity and acknowledged risk contributors with quantitative metrics that drive investment decision processes. Methods and tools will be initially introduced as applications to the A650.1 case study, but modular spreadsheets and analysis routines will be offered to industry collaborators as soon as possible to stimulate user feedback and co-development opportunities.

  8. Decision analysis applications and the CERCLA process

    SciTech Connect

    Purucker, S.T.; Lyon, B.F. |

    1994-06-01

    Quantitative decision methods can be developed during environmental restoration projects that incorporate stakeholder input and can complement current efforts that are undertaken for data collection and alternatives evaluation during the CERCLA process. These decision-making tools can supplement current EPA guidance as well as focus on problems that arise as attempts are made to make informed decisions regarding remedial alternative selection. In examining the use of such applications, the authors discuss the use of decision analysis tools and their impact on collecting data and making environmental decisions from a risk-based perspective. They will look at the construction of objective functions for quantifying different risk-based perspective. They will look at the construction of objective functions for quantifying different risk-based decision rules that incorporate stakeholder concerns. This represents a quantitative method for implementing the Data Quality Objective (DQO) process. These objective functions can be expressed using a variety of indices to analyze problems that currently arise in the environmental field. Examples include cost, magnitude of risk, efficiency, and probability of success or failure. Based on such defined objective functions, a project can evaluate the impact of different risk and decision selection strategies on data worth and alternative selection.

  9. A decision class analysis of critical care life-support decision-making.

    PubMed

    Seiver, A

    1993-02-01

    Decision analysis is a powerful methodology that can help clinicians make good decisions. Because it is not practical to place a decision analyst at the bedside in critical care units, the application of this methodology will require leveraging the analyst through computer-based systems. A decision class analysis is a collective analysis of a group of decisions that provides the high-level specification for such a computer system. This paper presents a decision class analysis of critical care life-support decisions. Key elements of this analysis are: the simplification of an otherwise extremely complex multistage sequential decision problem by using a sequence of two-stage models, and the use of six generic knowledge maps that capture the extremely complex relevant medical knowledge. PMID:8326214

  10. Evidence-based decision-making 2: Systematic reviews and meta-analysis.

    PubMed

    Bello, Aminu; Wiebe, Natasha; Garg, Amit; Tonelli, Marcello

    2015-01-01

    The number of studies published in the biomedical literature has dramatically increased over the last few decades. This massive proliferation of literature makes clinical medicine increasingly complex, and information from multiple studies is often needed to inform a particular clinical decision. However, available studies often vary in their design, methodological quality, populations studied and may define the research question of interest quite differently, which can make it challenging to synthesize their conclusions. In addition, since even highly cited trials may be challenged over time, clinical decision-making requires ongoing reconciliation of studies which provide different answers to the same question. Because it is often impractical for readers to track down and review all the primary studies, systematic reviews and meta-analyses are an important source of evidence on the diagnosis, prognosis, and treatment of any given disease. This chapter summarizes methods for conducting and reading systematic reviews and meta-analyses, as well as describing potential advantages and disadvantages of these publications.

  11. An approach for automated fault diagnosis based on a fuzzy decision tree and boundary analysis of a reconstructed phase space.

    PubMed

    Aydin, Ilhan; Karakose, Mehmet; Akin, Erhan

    2014-03-01

    Although reconstructed phase space is one of the most powerful methods for analyzing a time series, it can fail in fault diagnosis of an induction motor when the appropriate pre-processing is not performed. Therefore, boundary analysis based a new feature extraction method in phase space is proposed for diagnosis of induction motor faults. The proposed approach requires the measurement of one phase current signal to construct the phase space representation. Each phase space is converted into an image, and the boundary of each image is extracted by a boundary detection algorithm. A fuzzy decision tree has been designed to detect broken rotor bars and broken connector faults. The results indicate that the proposed approach has a higher recognition rate than other methods on the same dataset. PMID:24296116

  12. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis☆

    PubMed Central

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-01-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster–Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty–sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights. PMID:25843987

  13. The Risky Shift in Policy Decision Making: A Comparative Analysis

    ERIC Educational Resources Information Center

    Wilpert, B.; And Others

    1976-01-01

    Based on analysis of data on 432 decision-makers from around the world, this study examines the decision-making phenomenon that individuals tend to move toward riskier decisions after group discussion. Findings of the analysis contradicted earlier studies, showing a consistent shift toward greater risk avoidance. Available from Elsevier Scientific…

  14. Decision-problem state analysis methodology

    NASA Technical Reports Server (NTRS)

    Dieterly, D. L.

    1980-01-01

    A methodology for analyzing a decision-problem state is presented. The methodology is based on the analysis of an incident in terms of the set of decision-problem conditions encountered. By decomposing the events that preceded an unwanted outcome, such as an accident, into the set of decision-problem conditions that were resolved, a more comprehensive understanding is possible. All human-error accidents are not caused by faulty decision-problem resolutions, but it appears to be one of the major areas of accidents cited in the literature. A three-phase methodology is presented which accommodates a wide spectrum of events. It allows for a systems content analysis of the available data to establish: (1) the resolutions made, (2) alternatives not considered, (3) resolutions missed, and (4) possible conditions not considered. The product is a map of the decision-problem conditions that were encountered as well as a projected, assumed set of conditions that should have been considered. The application of this methodology introduces a systematic approach to decomposing the events that transpired prior to the accident. The initial emphasis is on decision and problem resolution. The technique allows for a standardized method of accident into a scenario which may used for review or the development of a training simulation.

  15. Pelagic Habitat Analysis Module (PHAM) for GIS Based Fisheries Decision Support

    NASA Technical Reports Server (NTRS)

    Kiefer, D. A.; Armstrong, Edward M.; Harrison, D. P.; Hinton, M. G.; Kohin, S.; Snyder, S.; O'Brien, F. J.

    2011-01-01

    We have assembled a system that integrates satellite and model output with fisheries data We have developed tools that allow analysis of the interaction between species and key environmental variables Demonstrated the capacity to accurately map habitat of Thresher Sharks Alopias vulpinus & pelagicus. Their seasonal migration along the California Current is at least partly driven by the seasonal migration of sardine, key prey of the sharks.We have assembled a system that integrates satellite and model output with fisheries data We have developed tools that allow analysis of the interaction between species and key environmental variables Demonstrated the capacity to accurately map habitat of Thresher Sharks Alopias vulpinus nd pelagicus. Their seasonal migration along the California Current is at least partly driven by the seasonal migration of sardine, key prey of the sharks.

  16. A Multi-Criteria Decision Analysis based methodology for quantitatively scoring the reliability and relevance of ecotoxicological data.

    PubMed

    Isigonis, Panagiotis; Ciffroy, Philippe; Zabeo, Alex; Semenzin, Elena; Critto, Andrea; Giove, Silvio; Marcomini, Antonio

    2015-12-15

    Ecotoxicological data are highly important for risk assessment processes and are used for deriving environmental quality criteria, which are enacted for assuring the good quality of waters, soils or sediments and achieving desirable environmental quality objectives. Therefore, it is of significant importance the evaluation of the reliability of available data for analysing their possible use in the aforementioned processes. The thorough analysis of currently available frameworks for the assessment of ecotoxicological data has led to the identification of significant flaws but at the same time various opportunities for improvement. In this context, a new methodology, based on Multi-Criteria Decision Analysis (MCDA) techniques, has been developed with the aim of analysing the reliability and relevance of ecotoxicological data (which are produced through laboratory biotests for individual effects), in a transparent quantitative way, through the use of expert knowledge, multiple criteria and fuzzy logic. The proposed methodology can be used for the production of weighted Species Sensitivity Weighted Distributions (SSWD), as a component of the ecological risk assessment of chemicals in aquatic systems. The MCDA aggregation methodology is described in detail and demonstrated through examples in the article and the hierarchically structured framework that is used for the evaluation and classification of ecotoxicological data is shortly discussed. The methodology is demonstrated for the aquatic compartment but it can be easily tailored to other environmental compartments (soil, air, sediments).

  17. Measuring Land Uses Accessibility by Using Fuzzy Majority Gis-Based Multicriteria Decision Analysis Case Study: Malayer City

    NASA Astrophysics Data System (ADS)

    Taravat, A.; Yari, A.; Rajaei, M.; Mousavian, R.

    2014-10-01

    Public spaces accessibility has become one of the important factors in urban planning. Therefore, considerable attention has been given to measure accessibility to public spaces on the UK, US and Canada, but there are few studies outside the anglophone world especially in developing countries such as Iran. In this study an attempt has been made to measure objective accessibility to public spaces (parks, school, library and administrative) using fuzzy majority GIS-based multicriteria decision analysis. This method is for defining the priority for distribution of urban facilities and utilities as the first step towards elimination of social justice. In order to test and demonstrate the presented model, the comprehensive plan of Malayer city has been considered for ranking in three objectives and properties in view of index per capital (Green space, sport facilities and major cultural centers like library and access index). The results can be used to inform the local planning process and the GIS approach can be expanded into other local authority domains. The results shows that the distribution of facilities in Malayer city has followed on the base of cost benefit law and the human aspect of resource allocation programming of facilities (from centre to suburbs of the city).

  18. "Junior Doctor Decision Making: Isn't that an Oxymoron?" A Qualitative Analysis of Junior Doctors' Ward-Based Decision-Making

    ERIC Educational Resources Information Center

    Bull, Stephanie; Mattick, Karen; Postlethwaite, Keith

    2013-01-01

    Unacceptable levels of adverse healthcare events, combined with changes to training, have put the spotlight on junior doctor decision-making. This study aimed to describe the decisions made by junior doctors and the contextual factors influencing how decisions were made and justified. Stimulated recall interviews with 20 junior doctors across five…

  19. Monte Carlo-based interval transformation analysis for multi-criteria decision analysis of groundwater management strategies under uncertain naphthalene concentrations and health risks

    NASA Astrophysics Data System (ADS)

    Ren, Lixia; He, Li; Lu, Hongwei; Chen, Yizhong

    2016-08-01

    A new Monte Carlo-based interval transformation analysis (MCITA) is used in this study for multi-criteria decision analysis (MCDA) of naphthalene-contaminated groundwater management strategies. The analysis can be conducted when input data such as total cost, contaminant concentration and health risk are represented as intervals. Compared to traditional MCDA methods, MCITA-MCDA has the advantages of (1) dealing with inexactness of input data represented as intervals, (2) mitigating computational time due to the introduction of Monte Carlo sampling method, (3) identifying the most desirable management strategies under data uncertainty. A real-world case study is employed to demonstrate the performance of this method. A set of inexact management alternatives are considered in each duration on the basis of four criteria. Results indicated that the most desirable management strategy lied in action 15 for the 5-year, action 8 for the 10-year, action 12 for the 15-year, and action 2 for the 20-year management.

  20. Application of portfolio theory in decision tree analysis.

    PubMed

    Galligan, D T; Ramberg, C; Curtis, C; Ferguson, J; Fetrow, J

    1991-07-01

    A general application of portfolio analysis for herd decision tree analysis is described. In the herd environment, this methodology offers a means of employing population-based decision strategies that can help the producer control economic variation in expected return from a given set of decision options. An economic decision tree model regarding the use of prostaglandin in dairy cows with undetected estrus was used to determine the expected return of the decisions to use prostaglandin and breed on a timed basis, use prostaglandin and then breed on sign of estrus, or breed on signs of estrus. The risk attributes of these decision alternatives were calculated from the decision tree, and portfolio theory was used to find the efficient decision combinations (portfolios with the highest return for a given variance). The resulting combinations of decisions could be used to control return variation.

  1. Decision making based on analysis of benefit versus costs of preventive retrofit versus costs of repair after earthquake hazards

    NASA Astrophysics Data System (ADS)

    Bostenaru Dan, M.

    2012-04-01

    In this presentation interventions on seismically vulnerable early reinforced concrete skeleton buildings, from the interwar time, at different performance levels, from avoiding collapse up to assuring immediate post-earthquake functionality are considered. Between these two poles there are degrees of damage depending on the performance aim set. The costs of the retrofit and post-earthquake repair differ depending on the targeted performance. Not only an earthquake has impact on a heritage building, but also the retrofit measure, for example on its appearance or its functional layout. This way criteria of the structural engineer, the investor, the architect/conservator/urban planner and the owner/inhabitants from the neighbourhood are considered for taking a benefit-cost decision. Benefit-cost analysis based decision is an element in a risk management process. A solution must be found on how much change to accept for retrofit and how much repairable damage to take into account. There are two impact studies. Numerical simulation was run for the building typology considered for successive earthquakes, selected in a deterministic way (1977, 1986 and two for 1991 from Vrancea, Romania and respectively 1978 Thessaloniki, Greece), considering also the case when retrofit is done between two earthquakes. The typology of buildings itself was studied not only for Greece and Romania, but for numerous European countries, including Italy. The typology was compared to earlier reinforced concrete buildings, with Hennebique system, in order to see to which amount these can belong to structural heritage and to shape the criteria of the architect/conservator. Based on the typology study two model buildings were designed, and for one of these different retrofit measures (side walls, structural walls, steel braces, steel jacketing) were considered, while for the other one of these retrofit techniques (diagonal braces, which permits adding also active measures such as energy

  2. A multi-attribute utility decision analysis for treatment alternatives for the DOE/SR aluminum-based spent nuclear fuel

    SciTech Connect

    DAVIS,FREDDIE J.; WEINER,RUTH FLEISCHMAN; WHEELER,TIMOTHY A.; SORENSON,KEN B.; KUZIO,KENNETH A.

    2000-05-24

    A multi-attribute utility analysis is applied to a decision process to select a treatment method for the management of aluminum-based spent nuclear fuel (Al-SNF) owned by the US Department of Energy (DOE). DOE will receive, treat, and temporarily store Al-SNF, most of which is composed of highly enriched uranium, at its Savannah River Site in South Carolina. DOE intends ultimately to send the treated Al-SNF to a geologic repository for permanent disposal. DOE initially considered ten treatment alternatives for the management of Al-SNF, and has narrowed the choice to two of these: the direct disposal and melt and dilute alternatives. The decision analysis presented in this document focuses on a formal decision process used to evaluate these two remaining alternatives.

  3. Value-Based Assessment of New Medical Technologies: Towards a Robust Methodological Framework for the Application of Multiple Criteria Decision Analysis in the Context of Health Technology Assessment.

    PubMed

    Angelis, Aris; Kanavos, Panos

    2016-05-01

    In recent years, multiple criteria decision analysis (MCDA) has emerged as a likely alternative to address shortcomings in health technology assessment (HTA) by offering a more holistic perspective to value assessment and acting as an alternative priority setting tool. In this paper, we argue that MCDA needs to subscribe to robust methodological processes related to the selection of objectives, criteria and attributes in order to be meaningful in the context of healthcare decision making and fulfil its role in value-based assessment (VBA). We propose a methodological process, based on multi-attribute value theory (MAVT) methods comprising five distinct phases, outline the stages involved in each phase and discuss their relevance in the HTA process. Importantly, criteria and attributes need to satisfy a set of desired properties, otherwise the outcome of the analysis can produce spurious results and misleading recommendations. Assuming the methodological process we propose is adhered to, the application of MCDA presents three very distinct advantages to decision makers in the context of HTA and VBA: first, it acts as an instrument for eliciting preferences on the performance of alternative options across a wider set of explicit criteria, leading to a more complete assessment of value; second, it allows the elicitation of preferences across the criteria themselves to reflect differences in their relative importance; and, third, the entire process of preference elicitation can be informed by direct stakeholder engagement, and can therefore reflect their own preferences. All features are fully transparent and facilitate decision making.

  4. Value-Based Assessment of New Medical Technologies: Towards a Robust Methodological Framework for the Application of Multiple Criteria Decision Analysis in the Context of Health Technology Assessment.

    PubMed

    Angelis, Aris; Kanavos, Panos

    2016-05-01

    In recent years, multiple criteria decision analysis (MCDA) has emerged as a likely alternative to address shortcomings in health technology assessment (HTA) by offering a more holistic perspective to value assessment and acting as an alternative priority setting tool. In this paper, we argue that MCDA needs to subscribe to robust methodological processes related to the selection of objectives, criteria and attributes in order to be meaningful in the context of healthcare decision making and fulfil its role in value-based assessment (VBA). We propose a methodological process, based on multi-attribute value theory (MAVT) methods comprising five distinct phases, outline the stages involved in each phase and discuss their relevance in the HTA process. Importantly, criteria and attributes need to satisfy a set of desired properties, otherwise the outcome of the analysis can produce spurious results and misleading recommendations. Assuming the methodological process we propose is adhered to, the application of MCDA presents three very distinct advantages to decision makers in the context of HTA and VBA: first, it acts as an instrument for eliciting preferences on the performance of alternative options across a wider set of explicit criteria, leading to a more complete assessment of value; second, it allows the elicitation of preferences across the criteria themselves to reflect differences in their relative importance; and, third, the entire process of preference elicitation can be informed by direct stakeholder engagement, and can therefore reflect their own preferences. All features are fully transparent and facilitate decision making. PMID:26739955

  5. SADA: Ecological Risk Based Decision Support System for Selective Remediation

    EPA Science Inventory

    Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

  6. Understanding The Decision Context: DPSIR, Decision Landscape, And Social Network Analysis

    EPA Science Inventory

    Establishing the decision context for a management problem is the critical first step for effective decision analysis. Understanding the decision context allow stakeholders and decision-makers to integrate the societal, environmental, and economic considerations that must be con...

  7. [HEALTH ECONOMIC ANALYSIS AND FAIR DECISION MAKING].

    PubMed

    Jeantet, Marine; Lopez, Alain

    2015-09-01

    Health technology assessment consists in evaluating the incremental cost-benefit ratio of a medicine, a medical device, a vaccine, a health strategy, in comparison to alternative health technologies. This form of socio-eoonomic evaluation aims at optimizing resource allocation within the health system. By setting the terms of valid alternatives, it is useful to highlight public choices, but it cannot in itself make the decision as regards the public funding of patient's access to the considered technology. The decision to include such technology in the basket of health goods and sercices covered, the levels and conditions of the coverage, also result from budget constraints, from economic situation and from a political vision about health policy, social protection and public expenditure. Accordingly, health economic analysis must be implemented on specific and targeted topics. The decision making process, with its health, economic and ethical stakes, calls for a public procedure and debate, based on shared information and argument. Otherwise, health system regulation, confronted with radical and costly innovations in the coming years, will become harder to handle. This requires the development of health economic research teams able to contribute to this assessment exercise. PMID:26619723

  8. 2D Hydrodynamic Based Logic Modeling Tool for River Restoration Decision Analysis: A Quantitative Approach to Project Prioritization

    NASA Astrophysics Data System (ADS)

    Bandrowski, D.; Lai, Y.; Bradley, N.; Gaeuman, D. A.; Murauskas, J.; Som, N. A.; Martin, A.; Goodman, D.; Alvarez, J.

    2014-12-01

    In the field of river restoration sciences there is a growing need for analytical modeling tools and quantitative processes to help identify and prioritize project sites. 2D hydraulic models have become more common in recent years and with the availability of robust data sets and computing technology, it is now possible to evaluate large river systems at the reach scale. The Trinity River Restoration Program is now analyzing a 40 mile segment of the Trinity River to determine priority and implementation sequencing for its Phase II rehabilitation projects. A comprehensive approach and quantitative tool has recently been developed to analyze this complex river system referred to as: 2D-Hydrodynamic Based Logic Modeling (2D-HBLM). This tool utilizes various hydraulic output parameters combined with biological, ecological, and physical metrics at user-defined spatial scales. These metrics and their associated algorithms are the underpinnings of the 2D-HBLM habitat module used to evaluate geomorphic characteristics, riverine processes, and habitat complexity. The habitat metrics are further integrated into a comprehensive Logic Model framework to perform statistical analyses to assess project prioritization. The Logic Model will analyze various potential project sites by evaluating connectivity using principal component methods. The 2D-HBLM tool will help inform management and decision makers by using a quantitative process to optimize desired response variables with balancing important limiting factors in determining the highest priority locations within the river corridor to implement restoration projects. Effective river restoration prioritization starts with well-crafted goals that identify the biological objectives, address underlying causes of habitat change, and recognizes that social, economic, and land use limiting factors may constrain restoration options (Bechie et. al. 2008). Applying natural resources management actions, like restoration prioritization, is

  9. A regret theory approach to decision curve analysis: A novel method for eliciting decision makers' preferences and decision-making

    PubMed Central

    2010-01-01

    Background Decision curve analysis (DCA) has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1), and analytical, deliberative process (system 2), thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. We use the cognitive emotion of regret to serve as a link between systems 1 and 2 and to reformulate DCA. Methods First, we analysed a classic decision tree describing three decision alternatives: treat, do not treat, and treat or no treat based on a predictive model. We then computed the expected regret for each of these alternatives as the difference between the utility of the action taken and the utility of the action that, in retrospect, should have been taken. For any pair of strategies, we measure the difference in net expected regret. Finally, we employ the concept of acceptable regret to identify the circumstances under which a potentially wrong strategy is tolerable to a decision-maker. Results We developed a novel dual visual analog scale to describe the relationship between regret associated with "omissions" (e.g. failure to treat) vs. "commissions" (e.g. treating unnecessary) and decision maker's preferences as expressed in terms of threshold probability. We then proved that the Net Expected Regret Difference, first presented in this paper, is equivalent to net benefits as described in the original DCA. Based on the concept of acceptable regret we identified the circumstances under which a decision maker tolerates a potentially wrong decision and expressed it in terms of probability of disease. Conclusions We present a novel method for eliciting decision maker's preferences and an alternative derivation of DCA based on regret theory. Our approach may be intuitively more

  10. An analysis of pathology knowledge and decision making for the development of artificial intelligence-based consulting systems.

    PubMed

    Smeulders, A W; van Ginneken, A M

    1989-06-01

    This paper partly addresses the question "What artificial intelligence (AI) tools are appropriate for which parts of pathology?" by analyzing the structure and components of knowledge in pathology (e.g., observations plus archival and reference data) and which aspects of that knowledge should be expressible in an AI consulting system. The different aspects of uncertainty (observational, prevalence and validity) play an important role in both human and computer-based decision-making processes, as do relationships between the components of knowledge. The design of an AI consultant system is discussed in terms of the way uncertainty is expressed and in how many parameters, the way uncertainty is propagated (Bayes, certainty factors, Dempster-Schafer, logic or Pathfinder heuristic methods), whether the system reasons from data to a conclusion or vice versa and what the aim of the system is. The suitability of an AI tool is determined by the knowable facts of the pathology subfield, by the match with its knowledge structure and by its requirements. While the success of an AI tool will partly depend on an appropriate definition of its scope, the appropriate combinatoric also depends on the expertise of the user.

  11. The relative importance of perceived doctor’s attitude on the decision to consult for symptomatic osteoarthritis: a choice-based conjoint analysis study

    PubMed Central

    Coxon, Domenica; Frisher, Martin; Jinks, Clare; Jordan, Kelvin; Paskins, Zoe; Peat, George

    2015-01-01

    Objectives Some patients spend years with painful osteoarthritis without consulting for it, including times when they are experiencing persistent severe pain and disability. Beliefs about osteoarthritis and what primary care has to offer may influence the decision to consult but their relative importance has seldom been quantified. We sought to investigate the relative importance of perceived service-related and clinical need attributes in the decision to consult a primary care physician for painful osteoarthritis. Design Partial-profile choice-based conjoint analysis study, using a self-complete questionnaire containing 10 choice tasks, each presenting two scenarios based on a combination of three out of six selected attributes. Setting General population. Participants Adults aged 50 years and over with hip, knee or hand pain registered with four UK general practices. Outcome measures Relative importance of pain characteristics, level of disruption to everyday life, extent of comorbidity, assessment, management, perceived general practitioner (GP) attitude. Results 863 (74%) people responded (55% female; mean age 70 years, range: 58–93). The most important determinants of the patient's decision to consult the GP for joint pain were the extent to which pain disrupted everyday life (‘most’ vs ‘none’: relative importance 31%) and perceived GP attitude (‘legitimate problem, requires treatment’ vs ‘part of the normal ageing process that one just has to accept’: 24%). Thoroughness of assessment (14%), management options offered (13%), comorbidity (13%) and pain characteristics (5%) were less strongly associated with the decision to consult. Conclusions Anticipating that the GP will regard joint pain as ‘part of the normal ageing process that one just has to accept’ is a strong disincentive to seeking help, potentially outweighing other aspects of quality of care. Alongside the recognition and management of disrupted function, an important goal

  12. Decisions, decisions: analysis of age, cohort, and time of testing on framing of risky decision options.

    PubMed

    Mayhorn, Christopher B; Fisk, Arthur D; Whittle, Justin D

    2002-01-01

    Decision making in uncertain environments is a daily challenge faced by adults of all ages. Framing decision options as either gains or losses is a common method of altering decision-making behavior. In the experiment reported here, benchmark decision-making data collected in the 1970s by Tversky and Kahneman (1981, 1988) were compared with data collected from current samples of young and older adults to determine whether behavior was consistent across time. Although differences did emerge between the benchmark and the present samples, the effect of framing on decision behavior was relatively stable. The present findings suggest that adults of all ages are susceptible to framing effects. Results also indicated that apparent age differences might be better explained by an analysis of cohort and time-of-testing effects. Actual or potential applications of this research include an understanding of how framing might influence the decision-making behavior of people of all ages in a number of applied contexts, such as product warning interactions and medical decision scenarios.

  13. Cost/Effort Drivers and Decision Analysis

    NASA Technical Reports Server (NTRS)

    Seidel, Jonathan

    2010-01-01

    Engineering trade study analyses demand consideration of performance, cost and schedule impacts across the spectrum of alternative concepts and in direct reference to product requirements. Prior to detailed design, requirements are too often ill-defined (only goals ) and prone to creep, extending well beyond the Systems Requirements Review. Though lack of engineering design and definitive requirements inhibit the ability to perform detailed cost analyses, affordability trades still comprise the foundation of these future product decisions and must evolve in concert. This presentation excerpts results of the recent NASA subsonic Engine Concept Study for an Advanced Single Aisle Transport to demonstrate an affordability evaluation of performance characteristics and the subsequent impacts on engine architecture decisions. Applying the Process Based Economic Analysis Tool (PBEAT), development cost, production cost, as well as operation and support costs were considered in a traditional weighted ranking of the following system-level figures of merit: mission fuel burn, take-off noise, NOx emissions, and cruise speed. Weighting factors were varied to ascertain the architecture ranking sensitivities to these performance figures of merit with companion cost considerations. A more detailed examination of supersonic variable cycle engine cost is also briefly presented, with observations and recommendations for further refinements.

  14. Thinking styles and decision making: A meta-analysis.

    PubMed

    Phillips, Wendy J; Fletcher, Jennifer M; Marks, Anthony D G; Hine, Donald W

    2016-03-01

    This meta-analysis examined whether tendencies to use reflective and intuitive thinking styles predicted decision performance (normatively correct responding) and decision experience (e.g., speed, enjoyment) on a range of decision-making tasks. A pooled sample of 17,704 participants (Mage = 25 years) from 89 samples produced small but significant weighted average effects for reflection on performance (r = .11) and experience (r = .14). Intuition was negatively associated with performance (r = -.09) but positively associated with experience (r = .06). Moderation analyses using 499 effect sizes revealed heterogeneity across task-theory match/mismatch, task type, description-based versus experience-based decisions, time pressure, age, and measure type. Effects of both thinking styles were strongest when the task matched the theoretical strengths of the thinking style (up to r = .29). Specific tasks that produced the largest thinking style effects (up to r = .35) were also consistent with system characteristics. Time pressure weakened the effects of reflection, but not intuition, on performance. Effect sizes for reflection on performance were largest for individuals aged either 12 to 18 years or 25+ (up to r = .18), and the effects of both reflection and intuition on experience were largest for adults aged 25+ (up to r = .27). Overall, our results indicate that associations between thinking styles and decision outcomes are context dependent. To improve decision performance and experience, decision architects and educators should carefully consider both individual differences in the decision maker and the nature of the decision task.

  15. School Principals' Personal Constructs Regarding Technology: An Analysis Based on Decision-Making Grid Technique

    ERIC Educational Resources Information Center

    Bektas, Fatih

    2014-01-01

    This study aims to determine the similarities and differences between existing school principals' personal constructs of "ideal principal qualities" in terms of technology by means of the decision-making grid technique. The study has a phenomenological design, and the study group consists of 17 principals who have been serving at…

  16. Decision Support and Knowledge-Based Systems.

    ERIC Educational Resources Information Center

    Konsynski, Benn R.; And Others

    1988-01-01

    A series of articles addresses issues concerning decision support and knowledge based systems. Topics covered include knowledge-based systems for information centers; object oriented systems; strategic information systems case studies; user perception; manipulation of certainty factors by individuals and expert systems; spreadsheet program use;…

  17. CURRICULUM DECISIONS--FURTHER EXPLORATION OF BASES.

    ERIC Educational Resources Information Center

    1966

    A FIRST STEP IN DEVELOPING CURRICULUM PLANS IS TO CONSIDER THE BASES OF THE CURRICULUM DECISIONS IN TERMS OF THEIR IMPLICATIONS FOR OBJECTIVES, LEARNING EXPERIENCES, TEACHING AIDS, AND EVALUATION. THESE BASES INCLUDE BELIEFS ABOUT HOME ECONOMICS AND EDUCATION, SOCIOECONOMIC CONDITIONS, LEGISLATION AFFECTING EDUCATION AND FAMILIES, NEEDS OF…

  18. Decision Analysis for Equipment Selection

    ERIC Educational Resources Information Center

    Cilliers, J. J.

    2005-01-01

    Equipment selection during process design is a critical aspect of chemical engineering and requires engineering judgment and subjective analysis. When educating chemical engineering students in the selection of proprietary equipment during design, the focus is often on the types of equipment available and their operating characteristics. The…

  19. Sediment Analysis Network for Decision Support (SANDS)

    NASA Astrophysics Data System (ADS)

    Hardin, D. M.; Keiser, K.; Graves, S. J.; Conover, H.; Ebersole, S.

    2009-12-01

    Since the year 2000, Eastern Louisiana, coastal Mississippi, Alabama, and the western Florida panhandle have been affected by 28 tropical storms, seven of which were hurricanes. These tropical cyclones have significantly altered normal coastal processes and characteristics in the Gulf region through sediment disturbance. Although tides, seasonality, and agricultural development influence suspended sediment and sediment deposition over periods of time, tropical storm activity has the capability of moving the largest sediment loads in the shortest periods of time for coastal areas. The importance of sediments upon water quality, coastal erosion, habitats and nutrients has made their study and monitoring vital to decision makers in the region. Currently agencies such as United States Army Corps of Engineers (USACE), NASA, and Geological Survey of Alabama (GSA) are employing a variety of in-situ and airborne based measurements to assess and monitor sediment loading and deposition. These methods provide highly accurate information but are limited in geographic range, are not continuous over a region and, in the case of airborne LIDAR are expensive and do not recur on a regular basis. Multi-temporal and multi-spectral satellite imagery that shows tropical-storm-induced suspended sediment and storm-surge sediment deposits can provide decision makers with immediate and long-term information about the impacts of tropical storms and hurricanes. It can also be valuable for those conducting research and for projects related to coastal issues such as recovery, planning, management, and mitigation. The recently awarded Sediment Analysis Network for Decision Support will generate decision support products using NASA satellite observations from MODIS, Landsat and SeaWiFS instruments to support resource management, planning, and decision making activities in the Gulf of Mexico. Specifically, SANDS will generate decision support products that address the impacts of tropical storms

  20. Monitoring Natural World Heritage Sites: optimization of the monitoring system in Bogda with GIS-based multi-criteria decision analysis.

    PubMed

    Wang, Zhaoguo; Du, Xishihui

    2016-07-01

    Natural World Heritage Sites (NWHSs) are invaluable treasure due to the uniqueness of each site. Proper monitoring and management can guarantee their protection from multiple threats. In this study, geographic information system (GIS)-based multi-criteria decision analysis (GIS-MCDA) was used to assess criteria layers acquired from the data available in the literature. A conceptual model for determining the priority area for monitoring in Bogda, China, was created based on outstanding universal values (OUV) and expert knowledge. Weights were assigned to each layer using the analytic hierarchy process (AHP) based on group decisions, encompassing three experts: one being a heritage site expert, another a forest ranger, and the other a heritage site manager. Subsequently, evaluation layers and constraint layers were used to generate a priority map and to determine the feasibility of monitoring in Bogda. Finally, a monitoring suitability map of Bogda was obtained by referencing priority and feasibility maps.The high-priority monitoring area is located in the montane forest belt, which exhibits high biodiversity and is the main tourist area of Bogda. The northern buffer zone of Bogda comprises the concentrated feasible monitoring areas, and the area closest to roads and monitoring facilities is highly feasible for NWHS monitoring. The suitability of an area in terms of monitoring is largely determined by the monitoring priority in that particular area. The majority of planned monitoring facilities are well distributed in both suitable and less suitable areas. Analysis results indicate that the protection of Bogda will be more scientifically based due to its effective and all-around planned monitoring system proposed by the declaration text of Xinjiang Tianshan, which is the essential file submitted to World Heritage Centre to inscribe as a NWHS.

  1. Monitoring Natural World Heritage Sites: optimization of the monitoring system in Bogda with GIS-based multi-criteria decision analysis.

    PubMed

    Wang, Zhaoguo; Du, Xishihui

    2016-07-01

    Natural World Heritage Sites (NWHSs) are invaluable treasure due to the uniqueness of each site. Proper monitoring and management can guarantee their protection from multiple threats. In this study, geographic information system (GIS)-based multi-criteria decision analysis (GIS-MCDA) was used to assess criteria layers acquired from the data available in the literature. A conceptual model for determining the priority area for monitoring in Bogda, China, was created based on outstanding universal values (OUV) and expert knowledge. Weights were assigned to each layer using the analytic hierarchy process (AHP) based on group decisions, encompassing three experts: one being a heritage site expert, another a forest ranger, and the other a heritage site manager. Subsequently, evaluation layers and constraint layers were used to generate a priority map and to determine the feasibility of monitoring in Bogda. Finally, a monitoring suitability map of Bogda was obtained by referencing priority and feasibility maps.The high-priority monitoring area is located in the montane forest belt, which exhibits high biodiversity and is the main tourist area of Bogda. The northern buffer zone of Bogda comprises the concentrated feasible monitoring areas, and the area closest to roads and monitoring facilities is highly feasible for NWHS monitoring. The suitability of an area in terms of monitoring is largely determined by the monitoring priority in that particular area. The majority of planned monitoring facilities are well distributed in both suitable and less suitable areas. Analysis results indicate that the protection of Bogda will be more scientifically based due to its effective and all-around planned monitoring system proposed by the declaration text of Xinjiang Tianshan, which is the essential file submitted to World Heritage Centre to inscribe as a NWHS. PMID:27251219

  2. GIS-based suitability modeling and multi-criteria decision analysis for utility scale solar plants in four states in the Southeast U.S

    NASA Astrophysics Data System (ADS)

    Tisza, Kata

    Photovoltaic (PV) development shows significantly smaller growth in the Southeast U.S., than in the Southwest; which is mainly due to the low cost of fossil-fuel based energy production in the region and the lack of solar incentives. However, the Southeast has appropriate insolation conditions (4.0-6.0 KWh/m2/day) for photovoltaic deployment and in the past decade the region has experienced the highest population growth for the entire country. These factors, combined with new renewable energy portfolio policies, could create an opportunity for PV to provide some of the energy that will be required to sustain this growth. The goal of the study was to investigate the potential for PV generation in the Southeast region by identifying suitable areas for a utility-scale solar power plant deployment. Four states with currently low solar penetration were studied: Georgia, North Carolina, South Carolina and Tennessee. Feasible areas were assessed with Geographic Information Systems (GIS) software using solar, land use and population growth criteria combined with proximity to transmission lines and roads. After the GIS-based assessment of the areas, technological potential was calculated for each state. Multi-decision analysis model (MCDA) was used to simulate the decision making method for a strategic PV installation. The model accounted for all criteria necessary to consider in case of a PV development and also included economic and policy criteria, which is thought to be a strong influence on the PV market. Three different scenarios were established, representing decision makers' theoretical preferences. Map layers created in the first part were used as basis for the MCDA and additional technical, economic and political/market criteria were added. A sensitivity analysis was conducted to test the model's robustness. Finally, weighted criteria were assigned to the GIS map layers, so that the different preference systems could be visualized. As a result, lands suitable for

  3. Feature Extraction Based on Decision Boundaries

    NASA Technical Reports Server (NTRS)

    Lee, Chulhee; Landgrebe, David A.

    1993-01-01

    In this paper, a novel approach to feature extraction for classification is proposed based directly on the decision boundaries. We note that feature extraction is equivalent to retaining informative features or eliminating redundant features; thus, the terms 'discriminantly information feature' and 'discriminantly redundant feature' are first defined relative to feature extraction for classification. Next, it is shown how discriminantly redundant features and discriminantly informative features are related to decision boundaries. A novel characteristic of the proposed method arises by noting that usually only a portion of the decision boundary is effective in discriminating between classes, and the concept of the effective decision boundary is therefore introduced. Next, a procedure to extract discriminantly informative features based on a decision boundary is proposed. The proposed feature extraction algorithm has several desirable properties: (1) It predicts the minimum number of features necessary to achieve the same classification accuracy as in the original space for a given pattern recognition problem; and (2) it finds the necessary feature vectors. The proposed algorithm does not deteriorate under the circumstances of equal class means or equal class covariances as some previous algorithms do. Experiments show that the performance of the proposed algorithm compares favorably with those of previous algorithms.

  4. Finding Sales Promotion and Making Decision for New Product Based on Group Analysis of Edge-Enhanced Product Networks

    NASA Astrophysics Data System (ADS)

    Huang, Yi; Tan, Jianbin; Wu, Bin

    A novel method is proposed in this paper to find the promotive relationship of products from a network point of view. Firstly, a product network is built based on the dataset of handsets’ sale information collected from all outlets of a telecom operator of one province of China, with a period from Jan. 2006 to Jul. 2008. Then the edge enhanced model is applied on product network to divide all the products into several groups, according to which each outlet is assigned to class A or class B for a certain handset. Class A is defined as the outlet which sell the certain handset and contains all of handsets of its group, while other situation for class B which sell the certain handset too. It’s shown from the result of analysis on these two kinds of outlets that many handsets are sold better in outlets of class A than that of class B, even though the sales revenue of all these outlets in the time period is close. That is to say the handsets within a group would promote the sale for each other. Furthermore, a method proposed in this paper gives a way to find out the important attributes of the handsets which lead them to br divided into the same group, and it also explains how to add a new handset to an existing group and where would the new handset be sold best.

  5. Data-Based Decision Making in Education: Challenges and Opportunities

    ERIC Educational Resources Information Center

    Schildkamp, Kim, Ed.; Lai, Mei Kuin, Ed.; Earl, Lorna, Ed.

    2013-01-01

    In a context where schools are held more and more accountable for the education they provide, data-based decision making has become increasingly important. This book brings together scholars from several countries to examine data-based decision making. Data-based decision making in this book refers to making decisions based on a broad range of…

  6. Estimating Decision Indices Based on Composite Scores

    ERIC Educational Resources Information Center

    Knupp, Tawnya Lee

    2009-01-01

    The purpose of this study was to develop an IRT model that would enable the estimation of decision indices based on composite scores. The composite scores, defined as a combination of unidimensional test scores, were either a total raw score or an average scale score. Additionally, estimation methods for the normal and compound multinomial models…

  7. EEG feature selection method based on decision tree.

    PubMed

    Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

    2015-01-01

    This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

  8. Evidence-based process for decision-making in the analysis of legal demands for medicines in Brazil.

    PubMed

    Figueiredo, Tatiana Aragão; Osorio-de-Castro, Claudia Garcia Serpa; Pepe, Vera Lúcia Edais

    2013-11-01

    Legal actions have been playing a significant role as an alternative pathway to access to medicines in Brazil. These lawsuits demand medicines used in Primary Health Care as well as medicines that are still in clinical research and have not been market approved by the Brazilian National Agency for Sanitary Surveillance (ANVISA). The goal was to analyze medicines demanded through lawsuits brought to the judicial district which includes the city of Rio de Janeiro, Brazil, from July/2007 to June/2008. The medicines in 281 lawsuits were examined for their respective indications, classified according to their presence in publicly-funded lists, market approval by ANVISA, compliance with national clinical guidelines, existence of alternative therapies in lists and support of indication by scientific evidence. Six different categories were described, which are deemed useful to managers and the Judiciary in decision-making. The support of evidence is of utmost importance for medicines that are not included in public funding lists and also for those with no available therapeutic alternatives.

  9. Evidence-based process for decision-making in the analysis of legal demands for medicines in Brazil.

    PubMed

    Figueiredo, Tatiana Aragão; Osorio-de-Castro, Claudia Garcia Serpa; Pepe, Vera Lúcia Edais

    2013-11-01

    Legal actions have been playing a significant role as an alternative pathway to access to medicines in Brazil. These lawsuits demand medicines used in Primary Health Care as well as medicines that are still in clinical research and have not been market approved by the Brazilian National Agency for Sanitary Surveillance (ANVISA). The goal was to analyze medicines demanded through lawsuits brought to the judicial district which includes the city of Rio de Janeiro, Brazil, from July/2007 to June/2008. The medicines in 281 lawsuits were examined for their respective indications, classified according to their presence in publicly-funded lists, market approval by ANVISA, compliance with national clinical guidelines, existence of alternative therapies in lists and support of indication by scientific evidence. Six different categories were described, which are deemed useful to managers and the Judiciary in decision-making. The support of evidence is of utmost importance for medicines that are not included in public funding lists and also for those with no available therapeutic alternatives. PMID:25402244

  10. 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

  11. 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.

  12. Venture Capital Investment Selection Decision-making Base on Fuzzy Theory

    NASA Astrophysics Data System (ADS)

    Zhang, Xubo

    Venture capital investment decision-making is the most important issue in venture capital investment selection. There are higher uncertainty and complexity in venture capital investment decision-making process. This paper analysis these uncertain risk in venture capital investment decision-making base the previous studies. Attributed the venture capital candidate firms' select to fuzzy optimal decision-making. Build a risk-weight fuzzy optimal return model to avoid the decision-making risk. Get the optimal solution set.

  13. Improving Intelligence Analysis With Decision Science.

    PubMed

    Dhami, Mandeep K; Mandel, David R; Mellers, Barbara A; Tetlock, Philip E

    2015-11-01

    Intelligence analysis plays a vital role in policy decision making. Key functions of intelligence analysis include accurately forecasting significant events, appropriately characterizing the uncertainties inherent in such forecasts, and effectively communicating those probabilistic forecasts to stakeholders. We review decision research on probabilistic forecasting and uncertainty communication, drawing attention to findings that could be used to reform intelligence processes and contribute to more effective intelligence oversight. We recommend that the intelligence community (IC) regularly and quantitatively monitor its forecasting accuracy to better understand how well it is achieving its functions. We also recommend that the IC use decision science to improve these functions (namely, forecasting and communication of intelligence estimates made under conditions of uncertainty). In the case of forecasting, decision research offers suggestions for improvement that involve interventions on data (e.g., transforming forecasts to debias them) and behavior (e.g., via selection, training, and effective team structuring). In the case of uncertainty communication, the literature suggests that current intelligence procedures, which emphasize the use of verbal probabilities, are ineffective. The IC should, therefore, leverage research that points to ways in which verbal probability use may be improved as well as exploring the use of numerical probabilities wherever feasible.

  14. Automated Vectorization of Decision-Based Algorithms

    NASA Technical Reports Server (NTRS)

    James, Mark

    2006-01-01

    Virtually all existing vectorization algorithms are designed to only analyze the numeric properties of an algorithm and distribute those elements across multiple processors. This advances the state of the practice because it is the only known system, at the time of this reporting, that takes high-level statements and analyzes them for their decision properties and converts them to a form that allows them to automatically be executed in parallel. The software takes a high-level source program that describes a complex decision- based condition and rewrites it as a disjunctive set of component Boolean relations that can then be executed in parallel. This is important because parallel architectures are becoming more commonplace in conventional systems and they have always been present in NASA flight systems. This technology allows one to take existing condition-based code and automatically vectorize it so it naturally decomposes across parallel architectures.

  15. Map-based decision aids for fire support

    NASA Astrophysics Data System (ADS)

    Yarosh, Victor

    1996-06-01

    The Fire Control Division at ARDEC is developing prototype decision aid tools to enable fire support echelons to rapidly respond to requests for fire support. Decision aids on fire support platforms can assist in route planning, site selection, and develop mobility overlays to enable the shooter to rapidly move into position and prepare for the fire mission. The Decision Aid system utilizes an integrated design approach which has each module interacting with the others by sharing data bases and common algorithms to provide recommended courses of action for route planning and generation, position selection, self defense, logistics estimates, situational awareness and fire mission planning aids such as tactical assessment, tactical planning, sustainment, etc. The Decision Aid system will use expert system artificial intelligence which will be developed from knowledge bases utilizing object oriented design. The modules currently reason on Defense Mapping Agency Interim Terrain Data and Digital Terrain Elevation Data and collect mission, intelligence, and sensor data from the digitized battlefield information distribution system to provide the crew or mission planners with intelligent recommendations. The system can provide a trade off analysis of time vs. safety, enable commanders to rapidly respond to fire support request, automatically generate OpOrders, and create overlays which depict mobility corridors, NBC areas, friendly units, overhead concealment, communications, and threat areas. The Decision Aids system can provide a vastly improved mobility, situational awareness, and decision cycle capabilities which can be utilized to increase the tempo of battle.

  16. Forecasting for energy and chemical decision analysis

    SciTech Connect

    Cazalet, E.G.

    1984-08-01

    This paper focuses on uncertainty and bias in forecasts used for major energy and chemical investment decisions. Probability methods for characterizing uncertainty in the forecast are reviewed. Sources of forecasting bias are classified based on the results of relevant psychology research. Examples are drawn from the energy and chemical industry to illustrate the value of explicit characterization of uncertainty and reduction of bias in forecasts.

  17. Campgrounds Suitability Evaluation Using GIS-based Multiple Criteria Decision Analysis: A Case Study of Kuerdening, China

    NASA Astrophysics Data System (ADS)

    Cuirong, Wang; Zhaoping, Yang; Huaxian, Liu; Fang, Han; Wenjin, Xia

    2016-04-01

    The main objective of this study was to evaluate the suitability and select the most appropriate areas for building campgrounds in Kuerdening, China. To achieve this aim, AHP and GIS-based weighted overlay methods were adopted. AHP was used to determine the weights of the indexes, and ArcGIS 10 was used to calculate and map the campground suitability. In pursuit of minimum environmental effects and sustainable development, this paper identifies four factors to evaluate the suitability of areas for building campgrounds: natural environment condition, landscape condition, safety condition and infrastructure condition. The final outcome of this studywas the suitability map for building campgrounds. This research not only provides a theoretical guide for the construction of campgrounds in this area but also provides a scientific and efficientworkflow to evaluate the appropriateness of other areas. The result is reasonable and operable for camping facilities development and also useful for managers and planners working in local governments as well as investors.

  18. Dopamine and Effort-Based Decision Making

    PubMed Central

    Kurniawan, Irma Triasih; Guitart-Masip, Marc; Dolan, Ray J.

    2011-01-01

    Motivational theories of choice focus on the influence of goal values and strength of reinforcement to explain behavior. By contrast relatively little is known concerning how the cost of an action, such as effort expended, contributes to a decision to act. Effort-based decision making addresses how we make an action choice based on an integration of action and goal values. Here we review behavioral and neurobiological data regarding the representation of effort as action cost, and how this impacts on decision making. Although organisms expend effort to obtain a desired reward there is a striking sensitivity to the amount of effort required, such that the net preference for an action decreases as effort cost increases. We discuss the contribution of the neurotransmitter dopamine (DA) toward overcoming response costs and in enhancing an animal's motivation toward effortful actions. We also consider the contribution of brain structures, including the basal ganglia and anterior cingulate cortex, in the internal generation of action involving a translation of reward expectation into effortful action. PMID:21734862

  19. Decision analysis for INEL hazardous waste storage

    SciTech Connect

    Page, L.A.; Roach, J.A.

    1994-01-01

    In mid-November 1993, the Idaho National Engineering Laboratory (INEL) Waste Reduction Operations Complex (WROC) Manager requested that the INEL Hazardous Waste Type Manager perform a decision analysis to determine whether or not a new Hazardous Waste Storage Facility (HWSF) was needed to store INEL hazardous waste (HW). In response to this request, a team was formed to perform a decision analysis for recommending the best configuration for storage of INEL HW. Personnel who participated in the decision analysis are listed in Appendix B. The results of the analysis indicate that the existing HWSF is not the best configuration for storage of INEL HW. The analysis detailed in Appendix C concludes that the best HW storage configuration would be to modify and use a portion of the Waste Experimental Reduction Facility (WERF) Waste Storage Building (WWSB), PBF-623 (Alternative 3). This facility was constructed in 1991 to serve as a waste staging facility for WERF incineration. The modifications include an extension of the current Room 105 across the south end of the WWSB and installing heating, ventilation, and bay curbing, which would provide approximately 1,600 ft{sup 2} of isolated HW storage area. Negotiations with the State to discuss aisle space requirements along with modifications to WWSB operating procedures are also necessary. The process to begin utilizing the WWSB for HW storage includes planned closure of the HWSF, modification to the WWSB, and relocation of the HW inventory. The cost to modify the WWSB can be funded by a reallocation of funding currently identified to correct HWSF deficiencies.

  20. Decision Analysis of Dynamic Spectrum Access Rules

    SciTech Connect

    Juan D. Deaton; Luiz A. DaSilva; Christian Wernz

    2011-12-01

    A current trend in spectrum regulation is to incorporate spectrum sharing through the design of spectrum access rules that support Dynamic Spectrum Access (DSA). This paper develops a decision-theoretic framework for regulators to assess the impacts of different decision rules on both primary and secondary operators. We analyze access rules based on sensing and exclusion areas, which in practice can be enforced through geolocation databases. Our results show that receiver-only sensing provides insufficient protection for primary and co-existing secondary users and overall low social welfare. On the other hand, using sensing information between the transmitter and receiver of a communication link, provides dramatic increases in system performance. The performance of using these link end points is relatively close to that of using many cooperative sensing nodes associated to the same access point and large link exclusion areas. These results are useful to regulators and network developers in understanding in developing rules for future DSA regulation.

  1. Risk Analysis and Decision Making FY 2013 Milestone Report

    SciTech Connect

    Engel, David W.; Dalton, Angela C.; Dale, Crystal; Jones, Edward; Thompson, J.

    2013-06-01

    Risk analysis and decision making is one of the critical objectives of CCSI, which seeks to use information from science-based models with quantified uncertainty to inform decision makers who are making large capital investments. The goal of this task is to develop tools and capabilities to facilitate the development of risk models tailored for carbon capture technologies, quantify the uncertainty of model predictions, and estimate the technical and financial risks associated with the system. This effort aims to reduce costs by identifying smarter demonstrations, which could accelerate development and deployment of the technology by several years.

  2. Decerns: A framework for multi-criteria decision analysis

    DOE PAGES

    Yatsalo, Boris; Didenko, Vladimir; Gritsyuk, Sergey; Sullivan, Terry

    2015-02-27

    A new framework, Decerns, for multicriteria decision analysis (MCDA) of a wide range of practical problems on risk management is introduced. Decerns framework contains a library of modules that are the basis for two scalable systems: DecernsMCDA for analysis of multicriteria problems, and DecernsSDSS for multicriteria analysis of spatial options. DecernsMCDA includes well known MCDA methods and original methods for uncertainty treatment based on probabilistic approaches and fuzzy numbers. As a result, these MCDA methods are described along with a case study on analysis of multicriteria location problem.

  3. Decision-theoretic refinement planning: a new method for clinical decision analysis.

    PubMed Central

    Doan, A.; Haddawy, P.; Kahn, C. E.

    1995-01-01

    Clinical decision analysis seeks to identify the optimal management strategy by modelling the uncertainty and risks entailed in the diagnosis, natural history, and treatment of a particular problem or disorder. Decision trees are the most frequently used model in clinical decision analysis, but can be tedious to construct, cumbersome to use, and computationally prohibitive, especially with large, complex decision problems. We present a new method for clinical decision analysis that combines the techniques of decision theory and artificial intelligence. Our model uses a modular representation of knowledge that simplifies model building and enables more fully automated decision making. Moreover, the model exploits problem structures to yield better computational efficiency. As an example we apply our techniques to the problem of management of acute deep venous thrombosis. PMID:8563289

  4. Reliability analysis framework for computer-assisted medical decision systems

    SciTech Connect

    Habas, Piotr A.; Zurada, Jacek M.; Elmaghraby, Adel S.; Tourassi, Georgia D.

    2007-02-15

    We present a technique that enhances computer-assisted decision (CAD) systems with the ability to assess the reliability of each individual decision they make. Reliability assessment is achieved by measuring the accuracy of a CAD system with known cases similar to the one in question. The proposed technique analyzes the feature space neighborhood of the query case to dynamically select an input-dependent set of known cases relevant to the query. This set is used to assess the local (query-specific) accuracy of the CAD system. The estimated local accuracy is utilized as a reliability measure of the CAD response to the query case. The underlying hypothesis of the study is that CAD decisions with higher reliability are more accurate. The above hypothesis was tested using a mammographic database of 1337 regions of interest (ROIs) with biopsy-proven ground truth (681 with masses, 656 with normal parenchyma). Three types of decision models, (i) a back-propagation neural network (BPNN), (ii) a generalized regression neural network (GRNN), and (iii) a support vector machine (SVM), were developed to detect masses based on eight morphological features automatically extracted from each ROI. The performance of all decision models was evaluated using the Receiver Operating Characteristic (ROC) analysis. The study showed that the proposed reliability measure is a strong predictor of the CAD system's case-specific accuracy. Specifically, the ROC area index for CAD predictions with high reliability was significantly better than for those with low reliability values. This result was consistent across all decision models investigated in the study. The proposed case-specific reliability analysis technique could be used to alert the CAD user when an opinion that is unlikely to be reliable is offered. The technique can be easily deployed in the clinical environment because it is applicable with a wide range of classifiers regardless of their structure and it requires neither additional

  5. ISHM Decision Analysis Tool: Operations Concept

    NASA Technical Reports Server (NTRS)

    2006-01-01

    The state-of-the-practice Shuttle caution and warning system warns the crew of conditions that may create a hazard to orbiter operations and/or crew. Depending on the severity of the alarm, the crew is alerted with a combination of sirens, tones, annunciator lights, or fault messages. The combination of anomalies (and hence alarms) indicates the problem. Even with much training, determining what problem a particular combination represents is not trivial. In many situations, an automated diagnosis system can help the crew more easily determine an underlying root cause. Due to limitations of diagnosis systems,however, it is not always possible to explain a set of alarms with a single root cause. Rather, the system generates a set of hypotheses that the crew can select from. The ISHM Decision Analysis Tool (IDAT) assists with this task. It presents the crew relevant information that could help them resolve the ambiguity of multiple root causes and determine a method for mitigating the problem. IDAT follows graphical user interface design guidelines and incorporates a decision analysis system. I describe both of these aspects.

  6. Exposure models for the prior distribution in bayesian decision analysis for occupational hygiene decision making.

    PubMed

    Lee, Eun Gyung; Kim, Seung Won; Feigley, Charles E; Harper, Martin

    2013-01-01

    This study introduces two semi-quantitative methods, Structured Subjective Assessment (SSA) and Control of Substances Hazardous to Health (COSHH) Essentials, in conjunction with two-dimensional Monte Carlo simulations for determining prior probabilities. Prior distribution using expert judgment was included for comparison. Practical applications of the proposed methods were demonstrated using personal exposure measurements of isoamyl acetate in an electronics manufacturing facility and of isopropanol in a printing shop. Applicability of these methods in real workplaces was discussed based on the advantages and disadvantages of each method. Although these methods could not be completely independent of expert judgments, this study demonstrated a methodological improvement in the estimation of the prior distribution for the Bayesian decision analysis tool. The proposed methods provide a logical basis for the decision process by considering determinants of worker exposure. PMID:23252451

  7. Exposure models for the prior distribution in bayesian decision analysis for occupational hygiene decision making.

    PubMed

    Lee, Eun Gyung; Kim, Seung Won; Feigley, Charles E; Harper, Martin

    2013-01-01

    This study introduces two semi-quantitative methods, Structured Subjective Assessment (SSA) and Control of Substances Hazardous to Health (COSHH) Essentials, in conjunction with two-dimensional Monte Carlo simulations for determining prior probabilities. Prior distribution using expert judgment was included for comparison. Practical applications of the proposed methods were demonstrated using personal exposure measurements of isoamyl acetate in an electronics manufacturing facility and of isopropanol in a printing shop. Applicability of these methods in real workplaces was discussed based on the advantages and disadvantages of each method. Although these methods could not be completely independent of expert judgments, this study demonstrated a methodological improvement in the estimation of the prior distribution for the Bayesian decision analysis tool. The proposed methods provide a logical basis for the decision process by considering determinants of worker exposure.

  8. 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.

  9. Optimal policy for value-based decision-making

    PubMed Central

    Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

    2016-01-01

    For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down. PMID:27535638

  10. Cloud Service Selection Using Multicriteria Decision Analysis

    PubMed Central

    Anuar, Nor Badrul; Shiraz, Muhammad; Haque, Israat Tanzeena

    2014-01-01

    Cloud computing (CC) has recently been receiving tremendous attention from the IT industry and academic researchers. CC leverages its unique services to cloud customers in a pay-as-you-go, anytime, anywhere manner. Cloud services provide dynamically scalable services through the Internet on demand. Therefore, service provisioning plays a key role in CC. The cloud customer must be able to select appropriate services according to his or her needs. Several approaches have been proposed to solve the service selection problem, including multicriteria decision analysis (MCDA). MCDA enables the user to choose from among a number of available choices. In this paper, we analyze the application of MCDA to service selection in CC. We identify and synthesize several MCDA techniques and provide a comprehensive analysis of this technology for general readers. In addition, we present a taxonomy derived from a survey of the current literature. Finally, we highlight several state-of-the-art practical aspects of MCDA implementation in cloud computing service selection. The contributions of this study are four-fold: (a) focusing on the state-of-the-art MCDA techniques, (b) highlighting the comparative analysis and suitability of several MCDA methods, (c) presenting a taxonomy through extensive literature review, and (d) analyzing and summarizing the cloud computing service selections in different scenarios. PMID:24696645

  11. Cloud service selection using multicriteria decision analysis.

    PubMed

    Whaiduzzaman, Md; Gani, Abdullah; Anuar, Nor Badrul; Shiraz, Muhammad; Haque, Mohammad Nazmul; Haque, Israat Tanzeena

    2014-01-01

    Cloud computing (CC) has recently been receiving tremendous attention from the IT industry and academic researchers. CC leverages its unique services to cloud customers in a pay-as-you-go, anytime, anywhere manner. Cloud services provide dynamically scalable services through the Internet on demand. Therefore, service provisioning plays a key role in CC. The cloud customer must be able to select appropriate services according to his or her needs. Several approaches have been proposed to solve the service selection problem, including multicriteria decision analysis (MCDA). MCDA enables the user to choose from among a number of available choices. In this paper, we analyze the application of MCDA to service selection in CC. We identify and synthesize several MCDA techniques and provide a comprehensive analysis of this technology for general readers. In addition, we present a taxonomy derived from a survey of the current literature. Finally, we highlight several state-of-the-art practical aspects of MCDA implementation in cloud computing service selection. The contributions of this study are four-fold: (a) focusing on the state-of-the-art MCDA techniques, (b) highlighting the comparative analysis and suitability of several MCDA methods, (c) presenting a taxonomy through extensive literature review, and (d) analyzing and summarizing the cloud computing service selections in different scenarios.

  12. Practical risk-based decision making: Good decisions made efficiently

    SciTech Connect

    Haire, M.J.; Guthrie, V.; Walker, D.; Singer, R.

    1995-12-01

    The Robotics and Process Systems Division of the Oak Ridge National Laboratory and the Westinghouse Savannah River Company have teamed with JBF Associates, Inc. to address risk-based robotic planning. The objective of the project is to provide systematic, risk-based relative comparisons of competing alternatives for solving clean-up problems at DOE facilities. This paper presents the methodology developed, describes the software developed to efficiently apply the methodology, and discusses the results of initial applications for DOE. The paper also addresses current work in applying the approach to problems in other industries (including an example from the hydrocarbon processing industry).

  13. DECISION ANALYSIS OF INCINERATION COSTS IN SUPERFUND SITE REMEDIATION

    EPA Science Inventory

    This study examines the decision-making process of the remedial design (RD) phase of on-site incineration projects conducted at Superfund sites. Decisions made during RD affect the cost and schedule of remedial action (RA). Decision analysis techniques are used to determine the...

  14. The xeroderma pigmentosum pathway: decision tree analysis of DNA quality.

    PubMed

    Naegeli, Hanspeter; Sugasawa, Kaoru

    2011-07-15

    The nucleotide excision repair (NER) system is a fundamental cellular stress response that uses only a handful of DNA binding factors, mutated in the cancer-prone syndrome xeroderma pigmentosum (XP), to detect an astounding diversity of bulky base lesions, including those induced by ultraviolet light, electrophilic chemicals, oxygen radicals and further genetic insults. Several of these XP proteins are characterized by a mediocre preference for damaged substrates over the native double helix but, intriguingly, none of them recognizes injured bases with sufficient selectivity to account for the very high precision of bulky lesion excision. Instead, substrate versatility as well as damage specificity and strand selectivity are achieved by a multistage quality control strategy whereby different subunits of the XP pathway, in succession, interrogate the DNA double helix for a distinct abnormality in its structural or dynamic parameters. Through this step-by-step filtering procedure, the XP proteins operate like a systematic decision making tool, generally known as decision tree analysis, to sort out rare damaged bases embedded in a vast excess of native DNA. The present review is focused on the mechanisms by which multiple XP subunits of the NER pathway contribute to the proposed decision tree analysis of DNA quality in eukaryotic cells. PMID:21684221

  15. An Application of Decision Tree Based on ID3

    NASA Astrophysics Data System (ADS)

    Xiaohu, Wang; Lele, Wang; Nianfeng, Li

    This article deals with the application of classical decision tree ID3 of the data mining in a certain site data. It constitutes a decision tree based on information gain and thus produces some useful purchasing behavior rules. It also proves that the decision tree has a wide applicable future in the sale field on site.

  16. DISPLA: decision information system for procurement and logistics analysis

    NASA Astrophysics Data System (ADS)

    Calvo, Alberto B.; Danish, Alexander J.; Lamonakis, Gregory G.

    2002-08-01

    This paper describes an information-exchange system for Display systems acquisition and logistics support. DISPLA (Decision Information System for Procurement and Logistics Analysis) is an Internet-based system concept for bringing sellers (display system and component suppliers) and buyers (Government Program Offices and System Integrators) together in an electronic exchange to improve the acquisition and logistics analysis support of Flat Panel Displays for the military. A proof-of-concept demonstration is presented in this paper using sample data from vendor Web sites and Government data sources.

  17. Case-based reasoning in Intelligent Health Decision Support Systems.

    PubMed

    González, Carolina; López, Diego M; Blobel, Bernd

    2013-01-01

    Decision-making is a crucial task for decision makers in healthcare, especially because decisions have to be made quickly, accurately and under uncertainty. Taking into account the importance of providing quality decisions, offering assistance in this complex process has been one of the main challenges of Artificial Intelligence throughout history. Decision Support Systems (DSS) have gained popularity in the medical field for their efficacy to assist decision-making. In this sense, many DSS have been developed, but only few of them consider processing and analysis of information contained in electronic health records, in order to identify individual or population health risk factors. This paper deals with Intelligent Decision Support Systems that are integrated into Electronic Health Records Systems (EHRS) or Public Health Information Systems (PHIS). It provides comprehensive support for a wide range of decisions with the purpose of improving quality of care delivered to patients or public health planning, respectively.

  18. Decision analysis of polluted sites -- A fuzzy set approach

    SciTech Connect

    Mohamed, A.M.O.; Cote, K.

    1999-07-01

    A decision analysis based model (DAPS 1.0, Decision Analysis of Polluted Sites) has been developed to evaluate risks that polluted sites might pose to human health. Pollutants present in soils and sediments can potentially migrate from source to receptor(s), via different pathways. in the developed model, pathways are simulated via transport models (i.e., groundwater transport model, runoff-erosion model, air diffusion model, and sediment diffusion, and resuspension model in water bodies). Humans can be affected by pollutant migration through land and water use. health risks can arise from ingestion of and dermal contact with polluted water and soil, as well as through inhalation of polluted air. Quantitative estimates of risks are calculated for both carcinogenic and non-carcinogenic pollutants. Being very heterogeneous, soil and sediment systems are characterized by uncertain parameters. Concepts of fuzzy set theory have been adopted to account for uncertainty in the input parameters which are represented by fuzzy numbers. An inference model using fuzzy logic has been constructed for reasoning in the decision analysis.

  19. Decision analysis of treatment choices in the osteochondroses.

    PubMed

    Bunch, W H

    1981-01-01

    Physicians tend to decry the lack of data on which they can make decisions. This is commendable, and all should encourage the pursuit of better data and more precise analysis. But decisions must be made, and each physician must deal with what data are available and evaluate them against all the general uncertainties. Equally important are the values that we place on the outcome of treatment. Much of the disagreement among physicians about treatment protocols involves a difference in values. While this is not necessarily bad, it points to the need to consider explicitly the value we place on a result or the morbidity possibly accompanying that result. In the osteochondroses, consideration of values will protect patients from overzealous treatment. Finally, the formality of a decision process should not necessarily modify a plan of treatment based on fundamentally sound principles, intuition, and anecdotal experience. Regardless of which factors represent the basis for an individual surgeon's selection of a particular approach, evaluation of both desirable and undesirable aspects of each alternative prevents impulsive acceptance of the most recently described, often unproven operation. Salter's aphorism: "The decision is more important than the incision," is particularly applicable in treatment of the osteochondroses.

  20. DAUBERT DECISION APPLIED TO GEOSPATIAL ANALYSIS

    EPA Science Inventory

    Protection of the environment is, in part, dependent on the quality of data used in decision making. Whether the decisions are part of the scientific process or relate to application of the laws governing people and their living conditions, good quality data are required/needed ...

  1. Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets

    PubMed Central

    Doubravsky, Karel; Dohnal, Mirko

    2015-01-01

    Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details. PMID:26158662

  2. [Decision making: biological bases and limitations].

    PubMed

    Portera Sánchez, A

    2000-01-01

    In the human brain, simple molecules and complex circuits are constantly making decisions which are indispensable for our survival and also to accomplish a variety of daily activities such as walking, memorizing, conversing, composing music, painting or poetry.... All are the result of the integration of many neural systems that perceive many and simultaneous visual, tactile, auditory and/or mental stimuli. Once synthetized, they are immediately transmitted to the corresponding executive systems, thus completing the fascinating functional loop of decision-making: a) perception of stimuli or information which originate in the environment, b) selection and elaboration of the decision which is considered more appropriate or attractive according to personal experience or intuition and c) execution. If these neural nets have been damaged or haven failed to develop the mechanisms of facilitation or inhibition that govern them become unbalanced. If inhibition is reduced, excessive and violent behaviour is expressed as in patients suffering from manic phases. Conversely, if inhibition is excessive, decision making mechanisms are not operative. In either case, behaviour is not "reasonable" and does not follow prototypical patterns. All these processes must be the consequence of a constant molecular activity full of micro-decisions whose effectiveness depends on the histological and biochemical integrity of the neurons. This microenvironment is responsible for all types of decisions of all forms of life and represents one of the fundamental successes of evolution.

  3. ALTERNATIVE FUTURES ANALYSIS: A FRAMEWORK FOR COMMUNITY DECISION-MAKING

    EPA Science Inventory

    Alternative futures analysis is an assessment approach designed to inform community decisions about land and water use. We conducted an alternative futures analysis in Oregon's Willamette River Basin. Three alternative future landscapes for the year 2050 were depicted and compare...

  4. A Decision Support Framework For Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

    EPA Science Inventory

    We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environ...

  5. Data-Based Decision Making 2.0

    ERIC Educational Resources Information Center

    Protheroe, Nancy

    2011-01-01

    The phrase "data-based decision making" has been used so often in discussions about school improvement efforts that it has become almost a mantra. However, it's "how" data is used that really provides the critical link between practice and school improvement. "Data-Based Decision Making 2.0" is designed to help principals take on the role of…

  6. School-Based Decision Making (SBDM) Guidance, 2004.

    ERIC Educational Resources Information Center

    Kentucky Department of Education, 2004

    2004-01-01

    This report provides guidance on implementation of Kentucky's school-based decision making law. It contains the text of the current School-Based Decision Making (SBDM) statute, KRS 160.345. The actual text of the law is located in the gray blocks throughout the Chapter, divided and briefly explained section by section. Statutory requirements are…

  7. Multi-criteria decision analysis with probabilistic risk assessment for the management of contaminated ground water

    SciTech Connect

    Khadam, Ibrahim M.; Kaluarachchi, Jagath J

    2003-10-01

    Traditionally, environmental decision analysis in subsurface contamination scenarios is performed using cost-benefit analysis. In this paper, we discuss some of the limitations associated with cost-benefit analysis, especially its definition of risk, its definition of cost of risk, and its poor ability to communicate risk-related information. This paper presents an integrated approach for management of contaminated ground water resources using health risk assessment and economic analysis through a multi-criteria decision analysis framework. The methodology introduces several important concepts and definitions in decision analysis related to subsurface contamination. These are the trade-off between population risk and individual risk, the trade-off between the residual risk and the cost of risk reduction, and cost-effectiveness as a justification for remediation. The proposed decision analysis framework integrates probabilistic health risk assessment into a comprehensive, yet simple, cost-based multi-criteria decision analysis framework. The methodology focuses on developing decision criteria that provide insight into the common questions of the decision-maker that involve a number of remedial alternatives. The paper then explores three potential approaches for alternative ranking, a structured explicit decision analysis, a heuristic approach of importance of the order of criteria, and a fuzzy logic approach based on fuzzy dominance and similarity analysis. Using formal alternative ranking procedures, the methodology seeks to present a structured decision analysis framework that can be applied consistently across many different and complex remediation settings. A simple numerical example is presented to demonstrate the proposed methodology. The results showed the importance of using an integrated approach for decision-making considering both costs and risks. Future work should focus on the application of the methodology to a variety of complex field conditions to

  8. An information theory analysis of spatial decisions in cognitive development

    PubMed Central

    Scott, Nicole M.; Sera, Maria D.; Georgopoulos, Apostolos P.

    2015-01-01

    Performance in a cognitive task can be considered as the outcome of a decision-making process operating across various knowledge domains or aspects of a single domain. Therefore, an analysis of these decisions in various tasks can shed light on the interplay and integration of these domains (or elements within a single domain) as they are associated with specific task characteristics. In this study, we applied an information theoretic approach to assess quantitatively the gain of knowledge across various elements of the cognitive domain of spatial, relational knowledge, as a function of development. Specifically, we examined changing spatial relational knowledge from ages 5 to 10 years. Our analyses consisted of a two-step process. First, we performed a hierarchical clustering analysis on the decisions made in 16 different tasks of spatial relational knowledge to determine which tasks were performed similarly at each age group as well as to discover how the tasks clustered together. We next used two measures of entropy to capture the gradual emergence of order in the development of relational knowledge. These measures of “cognitive entropy” were defined based on two independent aspects of chunking, namely (1) the number of clusters formed at each age group, and (2) the distribution of tasks across the clusters. We found that both measures of entropy decreased with age in a quadratic fashion and were positively and linearly correlated. The decrease in entropy and, therefore, gain of information during development was accompanied by improved performance. These results document, for the first time, the orderly and progressively structured “chunking” of decisions across the development of spatial relational reasoning and quantify this gain within a formal information-theoretic framework. PMID:25698915

  9. An information theory analysis of spatial decisions in cognitive development.

    PubMed

    Scott, Nicole M; Sera, Maria D; Georgopoulos, Apostolos P

    2015-01-01

    Performance in a cognitive task can be considered as the outcome of a decision-making process operating across various knowledge domains or aspects of a single domain. Therefore, an analysis of these decisions in various tasks can shed light on the interplay and integration of these domains (or elements within a single domain) as they are associated with specific task characteristics. In this study, we applied an information theoretic approach to assess quantitatively the gain of knowledge across various elements of the cognitive domain of spatial, relational knowledge, as a function of development. Specifically, we examined changing spatial relational knowledge from ages 5 to 10 years. Our analyses consisted of a two-step process. First, we performed a hierarchical clustering analysis on the decisions made in 16 different tasks of spatial relational knowledge to determine which tasks were performed similarly at each age group as well as to discover how the tasks clustered together. We next used two measures of entropy to capture the gradual emergence of order in the development of relational knowledge. These measures of "cognitive entropy" were defined based on two independent aspects of chunking, namely (1) the number of clusters formed at each age group, and (2) the distribution of tasks across the clusters. We found that both measures of entropy decreased with age in a quadratic fashion and were positively and linearly correlated. The decrease in entropy and, therefore, gain of information during development was accompanied by improved performance. These results document, for the first time, the orderly and progressively structured "chunking" of decisions across the development of spatial relational reasoning and quantify this gain within a formal information-theoretic framework.

  10. Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

    PubMed

    Dolan, James G

    2010-01-01

    Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

  11. Prioritizing groundwater remediation policies: a fuzzy compatibility analysis decision aid.

    PubMed

    Nasiri, Fuzhan; Huang, Gordon; Fuller, Norma

    2007-01-01

    The implementation of groundwater remediation strategies in contaminated areas includes not only a cost-benefit analysis and an environmental risk assessment but also another type of study called compatibility analysis. A compatibility analysis targets the interactions between remediation technologies and site characteristics, such as the types of active contaminants and their concentrations, soil composition and geological features, etc. The purpose of this analysis is to identify the most compatible remediation plan for the contaminated site. In this paper, we introduce a decision support system for the prioritization of remediation plans based on their estimated compatibility index. As this model receives data in terms of linguistic judgments and experts' opinions, we use fuzzy sets theory to deal with these uncertainties. First, we break down the concept of compatibility into the measurable factors. Then by using a multiple-attribute decision-making (MADM) outline, we compute a factorial, regional and overall compatibility indicator for each plan. Finally, by comparing these generated indicators, we rank the remediation policies.

  12. Parallel constraint satisfaction in memory-based decisions.

    PubMed

    Glöckner, Andreas; Hodges, Sara D

    2011-01-01

    Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

  13. Robust Decision Making and Scenario Based Engineering Hazard Analysis Regarding the Potential Abrupt Sea-Level Rise from a Collapse of the West Antarctic Ice Sheet: An Overview Paper

    NASA Astrophysics Data System (ADS)

    Berner, D. E.

    2012-12-01

    Recently scientific researchers have made significant advances in better understanding the risks of abrupt sea-level rise, SLR, but they have not adequately conveyed this understanding to decision makers who need to have sufficient information to decide what actions to take. The state-of-the-art in SLR projection is currently not sufficient to provide fully probabilistic risk functions to decision makers. Nevertheless, using the tools of Robust Decision Making, RDM, and Scenario Based Engineering Hazard Analysis, SBEHA, this article will present sufficient information to characterize a Maximum Credible Event, MCE, for abrupt SLR this century to allow decision makers to better understand the risks and timing that they are facing from the potential collapse of the West Antarctic Ice Sheet, WAIS, coupled together with other concurrent dynamic ice mass loss events. The article presents an overview of published research related topics including: paleo-evidence regarding abrupt SLR; radiative forcing scenarios; both RDM and SBEHA methodologies; and direct cause and effect evidence of an MCE scenario for the potential partial, or full, collapse of the WAIS the century. Findings of the article are presented in the form of summary graphs of projected relative sea-level rise, RSLR, and probability density functions, PDFs, for California.

  14. Beliefs Underlying the Decision to Eat Breakfast: The Role of Theory-based Behavioral Analysis in the Development of Policy, Communication and Educational Interventions for Healthy Eating.

    PubMed

    Middlestadt, Susan E; Stevenson, Laurel D; Hung, Chia-Ling; Roditis, Maria Leia; Fly, Alyce D; Sheats, Jylana L

    2011-01-01

    Policy, communication, and education efforts to influence any social or health outcome are more effective if based on an understanding of the underlying behaviors and their determinants. This conceptual paper outlines how behavioral theory can help design interventions for one healthy eating behavior, eating breakfast. More specifically, the paper illustrates how a prominent health behavior theory, the Reasoned Action Approach, can be used to guide formative research to identify factors underlying people's decisions. Select findings are presented from three studies of beliefs underlying eating breakfast: online surveys with 1185 undergraduates from a large university in Indiana; in-depth interviews with 61 adults from four Indiana worksites; and 63 in-depth interviews with students from three middle schools in rural Indiana. Analyses of data from the undergraduates demonstrated the role of self-efficacy. Analyses of data from the working adults revealed the importance of normative beliefs about what employers believed. Analyses comparing consequences perceived by adults with those perceived by middle school students found that both groups believed that eating breakfast would provide energy but only middle school students believed that eating breakfast would improve alertness. For each finding, the theory is presented, the finding is described, implications for interventions are suggested, and the need for additional research is outlined. In sum, theory-based behavioral research can help develop interventions at intrapersonal, interpersonal, and environmental levels that are warranted to encourage healthy eating. PMID:24089658

  15. Beliefs Underlying the Decision to Eat Breakfast: The Role of Theory-based Behavioral Analysis in the Development of Policy, Communication and Educational Interventions for Healthy Eating.

    PubMed

    Middlestadt, Susan E; Stevenson, Laurel D; Hung, Chia-Ling; Roditis, Maria Leia; Fly, Alyce D; Sheats, Jylana L

    2011-01-01

    Policy, communication, and education efforts to influence any social or health outcome are more effective if based on an understanding of the underlying behaviors and their determinants. This conceptual paper outlines how behavioral theory can help design interventions for one healthy eating behavior, eating breakfast. More specifically, the paper illustrates how a prominent health behavior theory, the Reasoned Action Approach, can be used to guide formative research to identify factors underlying people's decisions. Select findings are presented from three studies of beliefs underlying eating breakfast: online surveys with 1185 undergraduates from a large university in Indiana; in-depth interviews with 61 adults from four Indiana worksites; and 63 in-depth interviews with students from three middle schools in rural Indiana. Analyses of data from the undergraduates demonstrated the role of self-efficacy. Analyses of data from the working adults revealed the importance of normative beliefs about what employers believed. Analyses comparing consequences perceived by adults with those perceived by middle school students found that both groups believed that eating breakfast would provide energy but only middle school students believed that eating breakfast would improve alertness. For each finding, the theory is presented, the finding is described, implications for interventions are suggested, and the need for additional research is outlined. In sum, theory-based behavioral research can help develop interventions at intrapersonal, interpersonal, and environmental levels that are warranted to encourage healthy eating.

  16. [What should medical decision be based on?].

    PubMed

    Grenier, B

    1997-01-01

    Medical decision making is basically related to three criteria: 1) estimated effectiveness in terms of objective and subjective results: 2) equity related to the concept of justice in the societal context; 3) legitimacy according to the willingness to pay of the society, its resource availability and the fraction of its income that is allowed to be spent for health care. A worsening dilemma is unescapable between a utilitarian medical project, and the traditional hippocratic rule of rescue no matter what the cost may be. Every care taker should be involved to give a clear account of medical decision in order to generate and adopt some acceptable view for a reliable implementation with respect to equity and justice.

  17. Analysis of obstetricians' decision making on CTG recordings.

    PubMed

    Spilka, Jiří; Chudáček, Václav; Janků, Petr; Hruban, Lukáš; Burša, Miroslav; Huptych, Michal; Zach, Lukáš; Lhotská, Lenka

    2014-10-01

    Interpretation of cardiotocogram (CTG) is a difficult task since its evaluation is complicated by a great inter- and intra-individual variability. Previous studies have predominantly analyzed clinicians' agreement on CTG evaluation based on quantitative measures (e.g. kappa coefficient) that do not offer any insight into clinical decision making. In this paper we aim to examine the agreement on evaluation in detail and provide data-driven analysis of clinical evaluation. For this study, nine obstetricians provided clinical evaluation of 634 CTG recordings (each ca. 60min long). We studied the agreement on evaluation and its dependence on the increasing number of clinicians involved in the final decision. We showed that despite of large number of clinicians the agreement on CTG evaluations is difficult to reach. The main reason is inherent inter- and intra-observer variability of CTG evaluation. Latent class model provides better and more natural way to aggregate the CTG evaluation than the majority voting especially for larger number of clinicians. Significant improvement was reached in particular for the pathological evaluation - giving a new insight into the process of CTG evaluation. Further, the analysis of latent class model revealed that clinicians unconsciously use four classes when evaluating CTG recordings, despite the fact that the clinical evaluation was based on FIGO guidelines where three classes are defined.

  18. Initial Risk Analysis and Decision Making Framework

    SciTech Connect

    Engel, David W.

    2012-02-01

    Commercialization of new carbon capture simulation initiative (CCSI) technology will include two key elements of risk management, namely, technical risk (will process and plant performance be effective, safe, and reliable) and enterprise risk (can project losses and costs be controlled within the constraints of market demand to maintain profitability and investor confidence). Both of these elements of risk are incorporated into the risk analysis subtask of Task 7. Thus far, this subtask has developed a prototype demonstration tool that quantifies risk based on the expected profitability of expenditures when retrofitting carbon capture technology on a stylized 650 MW pulverized coal electric power generator. The prototype is based on the selection of specific technical and financial factors believed to be important determinants of the expected profitability of carbon capture, subject to uncertainty. The uncertainty surrounding the technical performance and financial variables selected thus far is propagated in a model that calculates the expected profitability of investments in carbon capture and measures risk in terms of variability in expected net returns from these investments. Given the preliminary nature of the results of this prototype, additional work is required to expand the scope of the model to include additional risk factors, additional information on extant and proposed risk factors, the results of a qualitative risk factor elicitation process, and feedback from utilities and other interested parties involved in the carbon capture project. Additional information on proposed distributions of these risk factors will be integrated into a commercial implementation framework for the purpose of a comparative technology investment analysis.

  19. CUDT: A CUDA Based Decision Tree Algorithm

    PubMed Central

    Sheu, Ruey-Kai; Chiu, Chun-Chieh

    2014-01-01

    Decision tree is one of the famous classification methods in data mining. Many researches have been proposed, which were focusing on improving the performance of decision tree. However, those algorithms are developed and run on traditional distributed systems. Obviously the latency could not be improved while processing huge data generated by ubiquitous sensing node in the era without new technology help. In order to improve data processing latency in huge data mining, in this paper, we design and implement a new parallelized decision tree algorithm on a CUDA (compute unified device architecture), which is a GPGPU solution provided by NVIDIA. In the proposed system, CPU is responsible for flow control while the GPU is responsible for computation. We have conducted many experiments to evaluate system performance of CUDT and made a comparison with traditional CPU version. The results show that CUDT is 5∼55 times faster than Weka-j48 and is 18 times speedup than SPRINT for large data set. PMID:25140346

  20. Organizing for Evidence-Based Decision Making and Improvement

    ERIC Educational Resources Information Center

    Leimer, Christina

    2012-01-01

    In today's accountability climate, regional accrediting bodies are requiring colleges and universities to develop and sustain a culture of evidence-based decision making and improvement. But two-thirds of college presidents in a 2011 "Inside Higher Ed" survey said their institutions are not particularly strong at using data for making decisions.…

  1. Practitioner Expertise in Evidence-Based Practice Decision Making

    ERIC Educational Resources Information Center

    McCracken, Stanley G.; Marsh, Jeanne C.

    2008-01-01

    Evidence-based practice (EBP) is an orientation to practice that values evidence as a resource for clinical decision making while recognizing that evidence alone is never sufficient to make a clinical decision. Critics of EBP typically ignore, negate, or misrepresent the role of practitioner thinking processes and expertise in clinical settings.…

  2. A benefit–risk assessment model for statins using multicriteria decision analysis based on a discrete choice experiment in Korean patients

    PubMed Central

    Byun, Ji-Hye; Kwon, Sun-Hong; Ha, Ji-Hye; Lee, Eui-Kyung

    2016-01-01

    Purpose The benefit–risk balance for drugs can alter post approval owing to additional data on efficacy or adverse events. This study developed a quantitative benefit–risk assessment (BRA) model for statins using multicriteria decision analysis with discrete choice experiments and compared a recent BRA with that at the time of approval. Patients and methods Following a systematic review of the literature, the benefit criteria within the statin BRA model were defined as a reduction in the plasma low-density lipoprotein cholesterol level and a reduction in myocardial infarction incidence; the risk criteria were hepatotoxicity (Liv) and fatal rhabdomyolysis (Rha). The scores for these criteria were estimated using mixed treatment comparison methods. Weighting was calculated from a discrete choice experiment involving 203 Korean patients. The scores and weights were integrated to produce an overall value representing the benefit–risk balance, and sensitivity analyses were conducted. Results In this BRA model, low-density lipoprotein (relative importance [RI]: 37.50%) was found to be a more important benefit criterion than myocardial infarction (RI: 35.43%), and Liv (RI: 16.28%) was a more important risk criterion than Rha (RI: 10.79%). Patients preferred atorvastatin, and the preference ranking of cerivastatin and simvastatin was switched post approval because of the emergence of additional risk information related to cerivastatin. Conclusion A quantitative statin BRA model confirmed that the preference ranking of statins changed post approval because of the identification of additional benefits or risks. PMID:27358567

  3. Developing Cost Accounting and Decision Support Software for Comprehensive Community-Based Support Systems: An Analysis of Needs, Interest, and Readiness in the Field.

    ERIC Educational Resources Information Center

    Harrington, Robert; Jenkins, Peter; Marzke, Carolyn; Cohen, Carol

    Prominent among the new models of social service delivery are organizations providing comprehensive, community-based supports and services (CCBSS) to children and their families. A needs analysis explored CCBSS sites' interest in and readiness to use a software tool designed to help them make more effective internal resource allocation decisions…

  4. Fuzzy Multicriteria Decision Analysis for Adaptive Watershed Management

    NASA Astrophysics Data System (ADS)

    Chang, N.

    2006-12-01

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

  5. A Decision Support Framework for Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

    NASA Astrophysics Data System (ADS)

    Rehr, Amanda P.; Small, Mitchell J.; Bradley, Patricia; Fisher, William S.; Vega, Ann; Black, Kelly; Stockton, Tom

    2012-12-01

    We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.

  6. Using Cluster Analysis to Examine Husband-Wife Decision Making

    ERIC Educational Resources Information Center

    Bonds-Raacke, Jennifer M.

    2006-01-01

    Cluster analysis has a rich history in many disciplines and although cluster analysis has been used in clinical psychology to identify types of disorders, its use in other areas of psychology has been less popular. The purpose of the current experiments was to use cluster analysis to investigate husband-wife decision making. Cluster analysis was…

  7. Forest fire autonomous decision system based on fuzzy logic

    NASA Astrophysics Data System (ADS)

    Lei, Z.; Lu, Jianhua

    2010-11-01

    The proposed system integrates GPS / pseudolite / IMU and thermal camera in order to autonomously process the graphs by identification, extraction, tracking of forest fire or hot spots. The airborne detection platform, the graph-based algorithms and the signal processing frame are analyzed detailed; especially the rules of the decision function are expressed in terms of fuzzy logic, which is an appropriate method to express imprecise knowledge. The membership function and weights of the rules are fixed through a supervised learning process. The perception system in this paper is based on a network of sensorial stations and central stations. The sensorial stations collect data including infrared and visual images and meteorological information. The central stations exchange data to perform distributed analysis. The experiment results show that working procedure of detection system is reasonable and can accurately output the detection alarm and the computation of infrared oscillations.

  8. Forest fire autonomous decision system based on fuzzy logic

    NASA Astrophysics Data System (ADS)

    Lei, Z.; Lu, Jianhua

    2009-09-01

    The proposed system integrates GPS / pseudolite / IMU and thermal camera in order to autonomously process the graphs by identification, extraction, tracking of forest fire or hot spots. The airborne detection platform, the graph-based algorithms and the signal processing frame are analyzed detailed; especially the rules of the decision function are expressed in terms of fuzzy logic, which is an appropriate method to express imprecise knowledge. The membership function and weights of the rules are fixed through a supervised learning process. The perception system in this paper is based on a network of sensorial stations and central stations. The sensorial stations collect data including infrared and visual images and meteorological information. The central stations exchange data to perform distributed analysis. The experiment results show that working procedure of detection system is reasonable and can accurately output the detection alarm and the computation of infrared oscillations.

  9. Cost-effectiveness v patient preference in the choice of treatment for distal ureteral calculi: a literature-based decision analysis.

    PubMed

    Wolf, J S; Carroll, P R; Stoller, M L

    1995-06-01

    Ureteroscopy (URS) and extracorporeal shockwave lithotripsy (SWL) battle for supremacy in the management distal ureteral calculi. In order to clarify issues surrounding this controversy, we created a decision tree modeling URS or SWL with literature-based probabilities and used as endpoints both cost and patient preferences. Ureteroscopy was more successful than single-session or multiple-session SWL, 92.1% v 74.3% or 84.5%, and had a lower retreatment/complication rate. Although initial SWL was only slightly more expensive than URS, $4,420 v $4,337, the difference increased when the additional costs of complications and retreatment were calculated, $6,745 v $5,555. Using values for an "average" patient, SWL was preferred to URS in terms of patient satisfaction. The most important factors distinguishing between URS and SWL were the success of treatment, the cost of initial therapy, and patient attitudes toward unplanned ancillary procedures and retreatment. Although no alteration of success rates and cost figures within reasonable ranges made URS less cost-effective than SWL, individual differences in patients' aversion for complications allowed URS to be preferred to SWL in some situations. Therefore, SWL is less cost-effective than URS and is not necessarily preferred by patients. The physician should be aware of the principal determinants of the choice between URS and SWL treatment of distal ureteral calculi.

  10. SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA) TRAINING COURSE

    EPA Science Inventory

    Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

  11. Analyses of S-Box in Image Encryption Applications Based on Fuzzy Decision Making Criterion

    NASA Astrophysics Data System (ADS)

    Rehman, Inayatur; Shah, Tariq; Hussain, Iqtadar

    2014-06-01

    In this manuscript, we put forward a standard based on fuzzy decision making criterion to examine the current substitution boxes and study their strengths and weaknesses in order to decide their appropriateness in image encryption applications. The proposed standard utilizes the results of correlation analysis, entropy analysis, contrast analysis, homogeneity analysis, energy analysis, and mean of absolute deviation analysis. These analyses are applied to well-known substitution boxes. The outcome of these analyses are additional observed and a fuzzy soft set decision making criterion is used to decide the suitability of an S-box to image encryption applications.

  12. How to use multi-criteria decision analysis methods for reimbursement decision-making in healthcare: a step-by-step guide.

    PubMed

    Diaby, Vakaramoko; Goeree, Ron

    2014-02-01

    In recent years, the quest for more comprehensiveness, structure and transparency in reimbursement decision-making in healthcare has prompted the research into alternative decision-making frameworks. In this environment, multi-criteria decision analysis (MCDA) is arising as a valuable tool to support healthcare decision-making. In this paper, we present the main MCDA decision support methods (elementary methods, value-based measurement models, goal programming models and outranking models) using a case study approach. For each family of methods, an example of how an MCDA model would operate in a real decision-making context is presented from a critical perspective, highlighting the parameters setting, the selection of the appropriate evaluation model as well as the role of sensitivity and robustness analyses. This study aims to provide a step-by-step guide on how to use MCDA methods for reimbursement decision-making in healthcare.

  13. Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

    NASA Astrophysics Data System (ADS)

    Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

    2014-05-01

    Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in

  14. Reliable binary cell-fate decisions based on oscillations

    NASA Astrophysics Data System (ADS)

    Pfeuty, B.; Kaneko, K.

    2014-02-01

    Biological systems have often to perform binary decisions under highly dynamic and noisy environments, such as during cell-fate determination. These decisions can be implemented by two main bifurcation mechanisms based on the transitions from either monostability or oscillation to bistability. We compare these two mechanisms by using stochastic models with time-varying fields and by establishing asymptotic formulas for the choice probabilities. Different scaling laws for decision sensitivity with respect to noise strength and signal timescale are obtained, supporting a role for oscillatory dynamics in performing noise-robust and temporally tunable binary decision-making. This result provides a rationale for recent experimental evidences showing that oscillatory expression of proteins often precedes binary cell-fate decisions.

  15. Beyond Bioethics: A Child Rights-Based Approach to Complex Medical Decision-Making.

    PubMed

    Wade, Katherine; Melamed, Irene; Goldhagen, Jeffrey

    2016-01-01

    This analysis adopts a child rights approach-based on the principles, standards, and norms of child rights and the U.N. Convention on the Rights of the Child (CRC)-to explore how decisions could be made with regard to treatment of a severely impaired infant (Baby G). While a child rights approach does not provide neat answers to ethically complex issues, it does provide a framework for decision-making in which the infant is viewed as an independent rights-holder. The state has obligations to develop the capacity of those who make decisions for infants in such situations to meet their obligations to respect, protect, and fulfill their rights as delineated in the CRC. Furthermore, a child rights approach requires procedural clarity and transparency in decision-making processes. As all rights in the CRC are interdependent and indivisible, all must be considered in the process of ethical decision-making, and the reasons for decisions must be delineated by reference to how these rights were considered. It is also important that decisions that are made in this context be monitored and reviewed to ensure consistency. A rights-based framework ensures decision-making is child-centered and that there are transparent criteria and legitimate procedures for making decisions regarding the child's most basic human right: the right to life, survival, and development. PMID:27157351

  16. A Conditional Model of Evidence-Based Decision Making

    PubMed Central

    Falzer, Paul R.; Garman, D. Melissa

    2009-01-01

    Rationale Efforts to describe how individual treatment decisions are informed by systematic knowledge have been hindered by a standard that gauges the quality of clinical decisions by their adherence to guidelines and evidence-based practices. This paper tests a new contextual standard that gauges the incorporation of knowledge into practice and develops a model of evidence-based decision making. Aims and objectives Previous work found that the forecasted outcome of a treatment guideline exerts a highly significant influence on how it is used in making decisions. This study proposed that forecasted outcomes affect the recognition of a treatment scenario, and this recognition triggers distinct contextual decision strategies. Method N=21 volunteers from a psychiatric residency program responded to 64 case vignettes, 16 in each of four treatment scenarios. The vignettes represented a fully balanced within-subjects design that included guideline switching criteria and patient-specific factors. For each vignette, participants indicated whether they endorsed the guideline’s recommendation. Results Clinicians employed consistent contextual decision strategies in responding to clearly positive or negative forecasts. When forecasts were more ambiguous or risky, their strategies became complex and relatively inconsistent. Conclusion The results support a three step model of evidence-based decision making, in which clinicians recognize a decision scenario, apply a simple contextual strategy, then if necessary engage a more complex strategy to resolve discrepancies between general guidelines and specific cases. The paper concludes by noting study limitations and discussing implications of the model for future research in clinical and shared decision making, training, and guideline development. PMID:20367718

  17. Life cycle cost based program decisions

    NASA Technical Reports Server (NTRS)

    Dick, James S.

    1991-01-01

    The following subject areas are covered: background (space propulsion facility assessment team final report); changes (Advanced Launch System, National Aerospace Plane, and space exploration initiative); life cycle cost analysis rationale; and recommendation to panel.

  18. Decision Analysis System for Selection of Appropriate Decontamination Technologies

    SciTech Connect

    Ebadian, M.A.; Boudreaux, J.F.; Chinta, S.; Zanakis, S.H.

    1998-01-01

    The principal objective for designing Decision Analysis System for Decontamination (DASD) is to support DOE-EM's endeavor to employ the most efficient and effective technologies for treating radiologically contaminated surfaces while minimizing personnel and environmental risks. DASD will provide a tool for environmental decision makers to improve the quality, consistency, and efficacy of their technology selection decisions. The system will facilitate methodical comparisons between innovative and baseline decontamination technologies and aid in identifying the most suitable technologies for performing surface decontamination at DOE environmental restoration sites.

  19. A Speedy Cardiovascular Diseases Classifier Using Multiple Criteria Decision Analysis

    PubMed Central

    Lee, Wah Ching; Hung, Faan Hei; Tsang, Kim Fung; Tung, Hoi Ching; Lau, Wing Hong; Rakocevic, Veselin; Lai, Loi Lei

    2015-01-01

    Each year, some 30 percent of global deaths are caused by cardiovascular diseases. This figure is worsening due to both the increasing elderly population and severe shortages of medical personnel. The development of a cardiovascular diseases classifier (CDC) for auto-diagnosis will help address solve the problem. Former CDCs did not achieve quick evaluation of cardiovascular diseases. In this letter, a new CDC to achieve speedy detection is investigated. This investigation incorporates the analytic hierarchy process (AHP)-based multiple criteria decision analysis (MCDA) to develop feature vectors using a Support Vector Machine. The MCDA facilitates the efficient assignment of appropriate weightings to potential patients, thus scaling down the number of features. Since the new CDC will only adopt the most meaningful features for discrimination between healthy persons versus cardiovascular disease patients, a speedy detection of cardiovascular diseases has been successfully implemented. PMID:25587978

  20. Text Classification Using ESC-Based Stochastic Decision Lists.

    ERIC Educational Resources Information Center

    Li, Hang; Yamanishi, Kenji

    2002-01-01

    Proposes a new method of text classification using stochastic decision lists, ordered sequences of IF-THEN-ELSE rules. The method can be viewed as a rule-based method for text classification having advantages of readability and refinability of acquired knowledge. Advantages of rule-based methods over non-rule-based ones are empirically verified.…

  1. Decision making under uncertainty: a neural model based on partially observable markov decision processes.

    PubMed

    Rao, Rajesh P N

    2010-01-01

    A fundamental problem faced by animals is learning to select actions based on noisy sensory information and incomplete knowledge of the world. It has been suggested that the brain engages in Bayesian inference during perception but how such probabilistic representations are used to select actions has remained unclear. Here we propose a neural model of action selection and decision making based on the theory of partially observable Markov decision processes (POMDPs). Actions are selected based not on a single "optimal" estimate of state but on the posterior distribution over states (the "belief" state). We show how such a model provides a unified framework for explaining experimental results in decision making that involve both information gathering and overt actions. The model utilizes temporal difference (TD) learning for maximizing expected reward. The resulting neural architecture posits an active role for the neocortex in belief computation while ascribing a role to the basal ganglia in belief representation, value computation, and action selection. When applied to the random dots motion discrimination task, model neurons representing belief exhibit responses similar to those of LIP neurons in primate neocortex. The appropriate threshold for switching from information gathering to overt actions emerges naturally during reward maximization. Additionally, the time course of reward prediction error in the model shares similarities with dopaminergic responses in the basal ganglia during the random dots task. For tasks with a deadline, the model learns a decision making strategy that changes with elapsed time, predicting a collapsing decision threshold consistent with some experimental studies. The model provides a new framework for understanding neural decision making and suggests an important role for interactions between the neocortex and the basal ganglia in learning the mapping between probabilistic sensory representations and actions that maximize rewards.

  2. Decentralisation of Health Services in Fiji: A Decision Space Analysis

    PubMed Central

    Mohammed, Jalal; North, Nicola; Ashton, Toni

    2016-01-01

    Background: Decentralisation aims to bring services closer to the community and has been advocated in the health sector to improve quality, access and equity, and to empower local agencies, increase innovation and efficiency and bring healthcare and decision-making as close as possible to where people live and work. Fiji has attempted two approaches to decentralisation. The current approach reflects a model of deconcentration of outpatient services from the tertiary level hospital to the peripheral health centres in the Suva subdivision. Methods: Using a modified decision space approach developed by Bossert, this study measures decision space created in five broad categories (finance, service organisation, human resources, access rules, and governance rules) within the decentralised services. Results: Fiji’s centrally managed historical-based allocation of financial resources and management of human resources resulted in no decision space for decentralised agents. Narrow decision space was created in the service organisation category where, with limited decision space created over access rules, Fiji has seen greater usage of its decentralised health centres. There remains limited decision space in governance. Conclusion: The current wave of decentralisation reveals that, whilst the workload has shifted from the tertiary hospital to the peripheral health centres, it has been accompanied by limited transfer of administrative authority, suggesting that Fiji’s deconcentration reflects the transfer of workload only with decision-making in the five functional areas remaining largely centralised. As such, the benefits of decentralisation for users and providers are likely to be limited. PMID:26927588

  3. Towards a controlled sensitivity analysis of model development decisions

    NASA Astrophysics Data System (ADS)

    Clark, Martyn; Nijssen, Bart

    2016-04-01

    The current generation of hydrologic models have followed a myriad of different development paths, making it difficult for the community to test underlying hypotheses and identify a clear path to model improvement. Model comparison studies have been undertaken to explore model differences, but these studies have not been able to meaningfully attribute inter-model differences in predictive ability to individual model components because there are often too many structural and implementation differences among the models considered. As a consequence, model comparison studies to date have provided limited insight into the causes of differences in model behavior, and model development has often relied on the inspiration and experience of individual modelers rather than a systematic analysis of model shortcomings. This presentation will discuss a unified approach to process-based hydrologic modeling to enable controlled and systematic analysis of multiple model representations (hypotheses) of hydrologic processes and scaling behavior. Our approach, which we term the Structure for Unifying Multiple Modeling Alternatives (SUMMA), formulates a general set of conservation equations, providing the flexibility to experiment with different spatial representations, different flux parameterizations, different model parameter values, and different time stepping schemes. We will discuss the use of SUMMA to systematically analyze different model development decisions, focusing on both analysis of simulations for intensively instrumented research watersheds as well as simulations across a global dataset of FLUXNET sites. The intent of the presentation is to demonstrate how the systematic analysis of model shortcomings can help identify model weaknesses and inform future model development priorities.

  4. Evidence-Based Medicine in judicial decisions concerning right to healthcare

    PubMed Central

    Dias, Eduardo Rocha; da Silva, Geraldo Bezerra

    2016-01-01

    ABSTRACT Objective To analyze, from the examination of decisions issued by Brazilian courts, how Evidence-Based Medicine was applied and if it led to well-founded decisions, searching the best scientific knowledge. Methods The decisions made by the Federal Courts were searched, with no time limits, at the website of the Federal Court Council, using the expression “Evidence-Based Medicine”. With regard to decisions issued by the court of the State of São Paulo, the search was done at the webpage and applying the same terms and criterion as to time. Next, a qualitative analysis of the decisions was conducted for each action, to verify if the patient/plaintiff’s situation, as well as the efficacy or inefficacy of treatments or drugs addressed in existing protocols were considered before the court granted the provision claimed by the plaintiff. Results In less than one-third of the decisions there was an appropriate discussion about efficacy of the procedure sought in court, in comparison to other procedures available in clinical guidelines adopted by the Brazilian Unified Health System (Sistema Único de Saúde) or by private health insurance plans, considering the individual situation. The majority of the decisions involved private health insurance plans (n=13, 68%). Conclusion The number of decisions that did consider scientific evidence and the peculiarities of each patient was a concern. Further discussion on Evidence-Based Medicine in judgments involving public healthcare are required. PMID:27074226

  5. Reduced model-based decision-making in schizophrenia.

    PubMed

    Culbreth, Adam J; Westbrook, Andrew; Daw, Nathaniel D; Botvinick, Matthew; Barch, Deanna M

    2016-08-01

    Individuals with schizophrenia have a diminished ability to use reward history to adaptively guide behavior. However, tasks traditionally used to assess such deficits often rely on multiple cognitive and neural processes, leaving etiology unresolved. In the current study, we adopted recent computational formalisms of reinforcement learning to distinguish between model-based and model-free decision-making in hopes of specifying mechanisms associated with reinforcement-learning dysfunction in schizophrenia. Under this framework, decision-making is model-free to the extent that it relies solely on prior reward history, and model-based if it relies on prospective information such as motivational state, future consequences, and the likelihood of obtaining various outcomes. Model-based and model-free decision-making was assessed in 33 schizophrenia patients and 30 controls using a 2-stage 2-alternative forced choice task previously demonstrated to discern individual differences in reliance on the 2 forms of reinforcement-learning. We show that, compared with controls, schizophrenia patients demonstrate decreased reliance on model-based decision-making. Further, parameter estimates of model-based behavior correlate positively with IQ and working memory measures, suggesting that model-based deficits seen in schizophrenia may be partially explained by higher-order cognitive deficits. These findings demonstrate specific reinforcement-learning and decision-making deficits and thereby provide valuable insights for understanding disordered behavior in schizophrenia. (PsycINFO Database Record

  6. Making Good Decisions in Healthcare with Multi-Criteria Decision Analysis: The Use, Current Research and Future Development of MCDA.

    PubMed

    Mühlbacher, Axel C; Kaczynski, Anika

    2016-02-01

    Healthcare decision making is usually characterized by a low degree of transparency. The demand for transparent decision processes can be fulfilled only when assessment, appraisal and decisions about health technologies are performed under a systematic construct of benefit assessment. The benefit of an intervention is often multidimensional and, thus, must be represented by several decision criteria. Complex decision problems require an assessment and appraisal of various criteria; therefore, a decision process that systematically identifies the best available alternative and enables an optimal and transparent decision is needed. For that reason, decision criteria must be weighted and goal achievement must be scored for all alternatives. Methods of multi-criteria decision analysis (MCDA) are available to analyse and appraise multiple clinical endpoints and structure complex decision problems in healthcare decision making. By means of MCDA, value judgments, priorities and preferences of patients, insurees and experts can be integrated systematically and transparently into the decision-making process. This article describes the MCDA framework and identifies potential areas where MCDA can be of use (e.g. approval, guidelines and reimbursement/pricing of health technologies). A literature search was performed to identify current research in healthcare. The results showed that healthcare decision making is addressing the problem of multiple decision criteria and is focusing on the future development and use of techniques to weight and score different decision criteria. This article emphasizes the use and future benefit of MCDA.

  7. SIDEKICK: Genomic data driven analysis and decision-making framework

    PubMed Central

    2010-01-01

    Background Scientists striving to unlock mysteries within complex biological systems face myriad barriers in effectively integrating available information to enhance their understanding. While experimental techniques and available data sources are rapidly evolving, useful information is dispersed across a variety of sources, and sources of the same information often do not use the same format or nomenclature. To harness these expanding resources, scientists need tools that bridge nomenclature differences and allow them to integrate, organize, and evaluate the quality of information without extensive computation. Results Sidekick, a genomic data driven analysis and decision making framework, is a web-based tool that provides a user-friendly intuitive solution to the problem of information inaccessibility. Sidekick enables scientists without training in computation and data management to pursue answers to research questions like "What are the mechanisms for disease X" or "Does the set of genes associated with disease X also influence other diseases." Sidekick enables the process of combining heterogeneous data, finding and maintaining the most up-to-date data, evaluating data sources, quantifying confidence in results based on evidence, and managing the multi-step research tasks needed to answer these questions. We demonstrate Sidekick's effectiveness by showing how to accomplish a complex published analysis in a fraction of the original time with no computational effort using Sidekick. Conclusions Sidekick is an easy-to-use web-based tool that organizes and facilitates complex genomic research, allowing scientists to explore genomic relationships and formulate hypotheses without computational effort. Possible analysis steps include gene list discovery, gene-pair list discovery, various enrichments for both types of lists, and convenient list manipulation. Further, Sidekick's ability to characterize pairs of genes offers new ways to approach genomic analysis that

  8. Using explicit decision rules to manage issues of justice, risk, and ethics in decision analysis: when is it not rational to maximize expected utility?

    PubMed

    Deber, R B; Goel, V

    1990-01-01

    Concepts of justice, risk, and ethics can be merged with decision analysis by requiring the analyst to specify explicity a decision rule or sequence of rules. Decision rules are categorized by whether they consider: 1) aspects of outcome distributions beyond central tendencies; 2) probabilities as well as utilities of outcomes; and 3) means as well as ends. This formulation suggests that distribution-based decision rules could address both risk (for an individual) and justice (for the population). Rational choice under risk if choices are one-time only (vs. repeated events) or if one branch contains unlikely but disastrous outcomes might ignore probability information. Incorporating risk attitude into decision rules rather than utilities could facilitate use of multiattribute approaches to measuring outcomes. Certain ethical concerns could be addressed by prior specification of rules for allowing particular branches. Examples, including selection of polio vaccine strategies, are discussed, and theoretical and practical implications of a decision rule approach noted. PMID:2196412

  9. Enabling computer decisions based on EEG input

    NASA Technical Reports Server (NTRS)

    Culpepper, Benjamin J.; Keller, Robert M.

    2003-01-01

    Multilayer neural networks were successfully trained to classify segments of 12-channel electroencephalogram (EEG) data into one of five classes corresponding to five cognitive tasks performed by a subject. Independent component analysis (ICA) was used to segregate obvious artifact EEG components from other sources, and a frequency-band representation was used to represent the sources computed by ICA. Examples of results include an 85% accuracy rate on differentiation between two tasks, using a segment of EEG only 0.05 s long and a 95% accuracy rate using a 0.5-s-long segment.

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

    PubMed

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

    2016-05-01

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

  11. Closed-Loop Analysis of Soft Decisions for Serial Links

    NASA Technical Reports Server (NTRS)

    Lansdowne, Chatwin A.; Steele, Glen F.; Zucha, Joan P.; Schlesinger, Adam M.

    2013-01-01

    We describe the benefit of using closed-loop measurements for a radio receiver paired with a counterpart transmitter. We show that real-time analysis of the soft decision output of a receiver can provide rich and relevant insight far beyond the traditional hard-decision bit error rate (BER) test statistic. We describe a Soft Decision Analyzer (SDA) implementation for closed-loop measurements on single- or dual- (orthogonal) channel serial data communication links. The analyzer has been used to identify, quantify, and prioritize contributors to implementation loss in live-time during the development of software defined radios. This test technique gains importance as modern receivers are providing soft decision symbol synchronization as radio links are challenged to push more data and more protocol overhead through noisier channels, and software-defined radios (SDRs) use error-correction codes that approach Shannon's theoretical limit of performance.

  12. Use of multicriteria decision analysis to address conservation conflicts.

    PubMed

    Davies, A L; Bryce, R; Redpath, S M

    2013-10-01

    Conservation conflicts are increasing on a global scale and instruments for reconciling competing interests are urgently needed. Multicriteria decision analysis (MCDA) is a structured, decision-support process that can facilitate dialogue between groups with differing interests and incorporate human and environmental dimensions of conflict. MCDA is a structured and transparent method of breaking down complex problems and incorporating multiple objectives. The value of this process for addressing major challenges in conservation conflict management is that MCDA helps in setting realistic goals; entails a transparent decision-making process; and addresses mistrust, differing world views, cross-scale issues, patchy or contested information, and inflexible legislative tools. Overall we believe MCDA provides a valuable decision-support tool, particularly for increasing awareness of the effects of particular values and choices for working toward negotiated compromise, although an awareness of the effect of methodological choices and the limitations of the method is vital before applying it in conflict situations.

  13. Employing Conjoint Analysis in Making Compensation Decisions.

    ERIC Educational Resources Information Center

    Kienast, Philip; And Others

    1983-01-01

    Describes a method employing conjoint analysis that generates utility/cost ratios for various elements of the compensation package. Its superiority to simple preference surveys is examined. Results of a study of the use of this method in fringe benefit planning in a large financial institution are reported. (Author/JAC)

  14. A Web-Based Decision Support Tool for Academic Advising

    ERIC Educational Resources Information Center

    Feghali, Tony; Zbib, Imad; Hallal, Sophia

    2011-01-01

    Student advising is an important and time-consuming effort in academic life. This paper attempts to solve a technology-based "last mile" problem by developing and evaluating a web-based decision support tool (the Online Advisor) that helps advisors and students make better use of an already present university student information system. Two…

  15. The application of decision analysis to life support research and technology development

    NASA Technical Reports Server (NTRS)

    Ballin, Mark G.

    1994-01-01

    Applied research and technology development is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Decision making regarding which technologies to advance and what resources to devote to them is a challenging but essential task. In the application of life support technology to future manned space flight, new technology concepts typically are characterized by nonexistent data and rough approximations of technology performance, uncertain future flight program needs, and a complex, time-intensive process to develop technology to a flight-ready status. Decision analysis is a quantitative, logic-based discipline that imposes formalism and structure to complex problems. It also accounts for the limits of knowledge that may be available at the time a decision is needed. The utility of decision analysis to life support technology R & D was evaluated by applying it to two case studies. The methodology was found to provide insight that is not possible from more traditional analysis approaches.

  16. 78 FR 44102 - Record of Decision for F35A Training Basing Final Environmental Impact Statement

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-07-23

    ... Department of the Air Force Record of Decision for F35A Training Basing Final Environmental Impact Statement... second ROD for the F-35A Training Basing Final Environmental Impact Statement (FEIS). The ROD states the... (42 U.S.C. 4321, et seq.) and the Air Force's Environmental Impact Analysis Process (EIAP) (32...

  17. Use of a pro-fibrogenic mechanism-based predictive toxicological approach for tiered testing and decision analysis of carbonaceous nanomaterials.

    PubMed

    Wang, Xiang; Duch, Matthew C; Mansukhani, Nikhita; Ji, Zhaoxia; Liao, Yu-Pei; Wang, Meiying; Zhang, Haiyuan; Sun, Bingbing; Chang, Chong Hyun; Li, Ruibin; Lin, Sijie; Meng, Huan; Xia, Tian; Hersam, Mark C; Nel, André E

    2015-03-24

    Engineered carbonaceous nanomaterials (ECNs), including single-wall carbon nanotubes (SWCNTs), multiwall carbon nanotubes (MWCNTs), graphene, and graphene oxide (GO), are potentially hazardous to the lung. With incremental experience in the use of predictive toxicological approaches, seeking to relate ECN physicochemical properties to adverse outcome pathways (AOPs), it is logical to explore the existence of a common AOP that allows comparative analysis of broad ECN categories. We established an ECN library comprising three different types of SWCNTs, graphene, and graphene oxide (two sizes) for comparative analysis according to a cell-based AOP that also plays a role in the pathogenesis of pulmonary fibrosis. SWCNTs synthesized by Hipco, arc discharge and Co-Mo catalyst (CoMoCAT) methods were obtained in their as-prepared (AP) state, following which they were further purified (PD) or coated with Pluronic F108 (PF108) or bovine serum albumin (BSA) to improve dispersal and colloidal stability. GO was prepared as two sizes, GO-small (S) and GO-large (L), while the graphene samples were coated with BSA and PF108 to enable dispersion in aqueous solution. In vitro screening showed that AP- and PD-SWCNTs, irrespective of the method of synthesis, as well as graphene (BSA) and GO (S and L) could trigger interleukin-1β (IL-1β) and transforming growth factor-β1 (TGF-β1) production in myeloid (THP-1) and epithelial (BEAS-2B) cell lines, respectively. Oropharyngeal aspiration in mice confirmed that AP-Hipco tubes, graphene (BSA-dispersed), GO-S and GO-L could induce IL-1β and TGF-β1 production in the lung in parallel with lung fibrosis. Notably, GO-L was the most pro-fibrogenic material based on rapid kinetics of pulmonary injury. In contrast, PF108-dispersed SWCNTs and -graphene failed to exert fibrogenic effects. Collectively, these data indicate that the dispersal state and surface reactivity of ECNs play key roles in triggering a pro-fibrogenic AOP, which could prove

  18. Neuroeconomics: The neurobiology of value-based decision-making

    PubMed Central

    Rangel, Antonio; Camerer, Colin; Montague, P. Read

    2015-01-01

    Neuroeconomics studies the neurobiological and computational basis of value-based decision-making. Its goal is to provide a biologically-based account of human behavior that can be applied in both the natural and the social sciences. In this review we propose a framework for thinking about decision-making that allows us to bring together recent findings in the field, highlight some of the most important outstanding problems, define a common lexicon that bridges the different disciplines that inform neuroeconomics, and point the way to future applications. PMID:18545266

  19. Modulation of Saccade Vigor during Value-Based Decision Making

    PubMed Central

    Lempert, Karolina M.; Glimcher, Paul W.; Shadmehr, Reza

    2015-01-01

    During value-based decision-making, individuals consider the various options and select the one that provides the maximum subjective value. Although the brain integrates abstract information to compute and compare these values, the only behavioral outcome is often the decision itself. However, if the options are visual stimuli, during deliberation the brain moves the eyes from one stimulus to the other. Previous work suggests that saccade vigor, i.e., peak velocity as a function of amplitude, is greater if reward is associated with the visual stimulus. This raises the possibility that vigor during the free viewing of options may be influenced by the valuation of each option. Here, humans chose between a small, immediate monetary reward and a larger but delayed reward. As the deliberation began, vigor was similar for the saccades made to the two options but diverged 0.5 s before decision time, becoming greater for the preferred option. This difference in vigor increased as a function of the difference in the subjective values that the participant assigned to the delayed and immediate options. After the decision was made, participants continued to gaze at the options, but with reduced vigor, making it possible to infer timing of the decision from the sudden drop in vigor. Therefore, the subjective value that the brain assigned to a stimulus during decision-making affected the motor system via the vigor with which the eyes moved toward that stimulus. SIGNIFICANCE STATEMENT We find that, as individuals deliberate between two rewarding options and arrive at a decision, the vigor with which they make saccades to each option reflects a real-time evaluation of that option. With deliberation, saccade vigor diverges between the two options, becoming greater for the option that the individual will eventually choose. The results suggest a shared element between the network that assigns value to a stimulus during the process of decision-making and the network that controls

  20. Influence of branding on preference-based decision making.

    PubMed

    Philiastides, Marios G; Ratcliff, Roger

    2013-07-01

    Branding has become one of the most important determinants of consumer choices. Intriguingly, the psychological mechanisms of how branding influences decision making remain elusive. In the research reported here, we used a preference-based decision-making task and computational modeling to identify which internal components of processing are affected by branding. We found that a process of noisy temporal integration of subjective value information can model preference-based choices reliably and that branding biases are explained by changes in the rate of the integration process itself. This result suggests that branding information and subjective preference are integrated into a single source of evidence in the decision-making process, thereby altering choice behavior.

  1. Influence of branding on preference-based decision making.

    PubMed

    Philiastides, Marios G; Ratcliff, Roger

    2013-07-01

    Branding has become one of the most important determinants of consumer choices. Intriguingly, the psychological mechanisms of how branding influences decision making remain elusive. In the research reported here, we used a preference-based decision-making task and computational modeling to identify which internal components of processing are affected by branding. We found that a process of noisy temporal integration of subjective value information can model preference-based choices reliably and that branding biases are explained by changes in the rate of the integration process itself. This result suggests that branding information and subjective preference are integrated into a single source of evidence in the decision-making process, thereby altering choice behavior. PMID:23696199

  2. Spent Nuclear Fuel Alternative Technology Decision Analysis

    SciTech Connect

    Shedrow, C.B.

    1999-11-29

    The Westinghouse Savannah River Company (WSRC) made a FY98 commitment to the Department of Energy (DOE) to recommend a technology for the disposal of aluminum-based spent nuclear fuel (SNF) at the Savannah River Site (SRS). The two technologies being considered, direct co-disposal and melt and dilute, had been previously selected from a group of eleven potential SNF management technologies by the Research Reactor Spent Nuclear Fuel Task Team chartered by the DOE''s Office of Spent Fuel Management. To meet this commitment, WSRC organized the SNF Alternative Technology Program to further develop the direct co-disposal and melt and dilute technologies and ultimately provide a WSRC recommendation to DOE on a preferred SNF alternative management technology.

  3. Recycling decision support system: Design and development of a Web-based DSS. Master thesis

    SciTech Connect

    Tettelbach, C.G.

    1997-03-01

    The explosive growth of the World Wide Web creates new opportunities for the development and deployment of Decision Support Systems. No longer restricted by machine-specific limitations, Web-based Decision Support Systems (DSS) provide global access to widely diversified and geographically dispersed users through sharing of data, models, algorithms, and modeling environments. This thesis examines the design and development processes involved in the creation of a Web-based DSS. The Recycling Decision Support System utilizes a rapid prototype and refinement process to create a Web-based system focusing on supporting ordinary people and industrial users in making good decisions for recycling and disposal of household and industrial waste. Through abstraction of details from the specific Web-based DSS design, a generalized framework for supporting decision-making via the WWW is built which supports functionality in education, queries, and analysis of complex problems. An important aspect of this research is the development of a new architecture which conforms to the complexities specific to Web-based Decision Support Systems. Prompted by the additional interactions required for WWW connectivity, this architecture incorporates agents for negotiating transactions between the functional components of a standard DSS.

  4. Philosophical Foundations for Curriculum Decision: A Reflective Analysis

    ERIC Educational Resources Information Center

    Belbase, Shashidhar

    2011-01-01

    This paper discusses the author's curriculum experiences under different philosophical, epistemological and theoretical backdrops. The analysis of different perspectives bridges epistemological and philosophical/theoretical lenses to my understanding of curriculum and different curricular decisions. This praxeological experience as a student and…

  5. Child Custody Decisions: Content Analysis of a Judicial Survey.

    ERIC Educational Resources Information Center

    Settle, Shirley A; Lowery, Carol R.

    1982-01-01

    Surveyed judges and trial commissioners (N=80) regarding child custody decisions in divorce. The content analysis described the responents' comments which clarified their reasons for attaching greater or lesser importance to a particular consideration or the method using in assessing a particular consideration during a court proceeding. (JAC)

  6. Decision framework for technology choice. Volume 2: decision analysis user's manual. [TCM computer code

    SciTech Connect

    Sicherman, A.; Keeney, R.L.

    1982-03-01

    A computer program was developed to aid decision makers in choosing among alternatives. It facilitiates the implementation of the decision analysis approach to multiobjective decision-making problems. The program's main functions are to store the information and perform all the necessary computations required by the approach. The program is designed so that only a few basic commands need to be understood in order to use it effectively. The style of input can be both batch and interactively oriented. Detailed specification of preferences and alternatives is usually done in batch mode while sensitivity analysis can be performed interactively. The output consists of ranking, preference and alternative information displays. The program is quite general and should be applicable to a wide variety of problems. The code allows for an interface to user supplied models when that is desirable. It is designed to run on most computer systems without or with very minor system-specific modifications. This report presents a user's manual for the program that includes a simple illustrative example.

  7. Age Estimation Based on Children's Voice: A Fuzzy-Based Decision Fusion Strategy

    PubMed Central

    Ting, Hua-Nong

    2014-01-01

    Automatic estimation of a speaker's age is a challenging research topic in the area of speech analysis. In this paper, a novel approach to estimate a speaker's age is presented. The method features a “divide and conquer” strategy wherein the speech data are divided into six groups based on the vowel classes. There are two reasons behind this strategy. First, reduction in the complicated distribution of the processing data improves the classifier's learning performance. Second, different vowel classes contain complementary information for age estimation. Mel-frequency cepstral coefficients are computed for each group and single layer feed-forward neural networks based on self-adaptive extreme learning machine are applied to the features to make a primary decision. Subsequently, fuzzy data fusion is employed to provide an overall decision by aggregating the classifier's outputs. The results are then compared with a number of state-of-the-art age estimation methods. Experiments conducted based on six age groups including children aged between 7 and 12 years revealed that fuzzy fusion of the classifier's outputs resulted in considerable improvement of up to 53.33% in age estimation accuracy. Moreover, the fuzzy fusion of decisions aggregated the complementary information of a speaker's age from various speech sources. PMID:25006595

  8. Locating the Optic Nerve in Retinal Images: Comparing Model-Based and Bayesian Decision Methods

    SciTech Connect

    Karnowski, Thomas Paul; Tobin Jr, Kenneth William; Muthusamy Govindasamy, Vijaya Priya; Chaum, Edward

    2006-01-01

    In this work we compare two methods for automatic optic nerve (ON) localization in retinal imagery. The first method uses a Bayesian decision theory is criminator based on four spatial features of the retina imagery. The second method uses a principal component-based reconstruction to model the ON. We report on an improvement to the model-based technique by incorporating linear discriminant analysis and Bayesian decision theory methods. We explore a method to combine both techniques to produce a composite technique with high accuracy and rapid throughput. Results are shown for a data set of 395 images with 2-fold validation testing.

  9. The Ultimate Sampling Dilemma in Experience-Based Decision Making

    ERIC Educational Resources Information Center

    Fiedler, Klaus

    2008-01-01

    Computer simulations and 2 experiments demonstrate the ultimate sampling dilemma, which constitutes a serious obstacle to inductive inferences in a probabilistic world. Participants were asked to take the role of a manager who is to make purchasing decisions based on positive versus negative feedback about 3 providers in 2 different product…

  10. Integrating Evidence-based Decision Making into Allied Health Curricula.

    ERIC Educational Resources Information Center

    Forrest, Jane L.; Miller, Syrene A.

    2001-01-01

    Evidence-based decision making (EBDM) was incorporated into an institute for 42 dental hygiene, occupational therapy, and physical therapy faculty. The 4-day sessions addressed active teaching techniques, formulation of good questions, critical appraisal of evidence, and application, feedback, and evaluation. Most participants felt prepared to…

  11. Ideology and Decision Making in School-Based Counseling

    ERIC Educational Resources Information Center

    Brenner, Michelle Klein

    2013-01-01

    The present study built on the design and results from the pilot study in an attempt to explore the relationship between psychologists' personal ideologies and the decisions they make in school-based counseling. Of particular interest was whether higher levels of self-reported ideology were related to support of relevant school policies.…

  12. Accommodating complexity and human behaviors in decision analysis.

    SciTech Connect

    Backus, George A.; Siirola, John Daniel; Schoenwald, David Alan; Strip, David R.; Hirsch, Gary B.; Bastian, Mark S.; Braithwaite, Karl R.; Homer, Jack

    2007-11-01

    This is the final report for a LDRD effort to address human behavior in decision support systems. One sister LDRD effort reports the extension of this work to include actual human choices and additional simulation analyses. Another provides the background for this effort and the programmatic directions for future work. This specific effort considered the feasibility of five aspects of model development required for analysis viability. To avoid the use of classified information, healthcare decisions and the system embedding them became the illustrative example for assessment.

  13. Towards an intelligent decision support system for public health surveillance - a qualitative analysis of information needs.

    PubMed

    Mera, Maritza; González, Carolina; López, Diego M

    2014-01-01

    Public health information systems are often implemented considering the functionalities and requirements established by administrative staff or researchers, but sometimes ignoring the particular needs of decision makers. This paper describes a proposal to support the design of a Decision Support System for Public Health Surveillance in Colombia, by conducting a qualitative study to identify the real needs of people involved in decision making processes. Based on the study results, an intelligent computational component that supports Data Analysis Automation, Prediction of future scenarios and the identification of new Behavioral Patterns is proposed. The component will be implemented using the Case Based Reasoning methodology, which will be integrated as a new component of the Open Source DHIS2 Platform, enabling public health decision-making.

  14. Use of multi-criteria decision analysis in regulatory alternatives analysis: a case study of lead free solder.

    PubMed

    Malloy, Timothy F; Sinsheimer, Peter J; Blake, Ann; Linkov, Igor

    2013-10-01

    Regulators are implementing new programs that require manufacturers of products containing certain chemicals of concern to identify, evaluate, and adopt viable, safer alternatives. Such programs raise the difficult question for policymakers and regulated businesses of which alternatives are "viable" and "safer." To address that question, these programs use "alternatives analysis," an emerging methodology that integrates issues of human health and environmental effects with technical feasibility and economic impact. Despite the central role that alternatives analysis plays in these programs, the methodology itself is neither well-developed nor tailored to application in regulatory settings. This study uses the case of Pb-based bar solder and its non-Pb-based alternatives to examine the application of 2 multi-criteria decision analysis (MCDA) methods to alternatives analysis: multi-attribute utility analysis and outranking. The article develops and evaluates an alternatives analysis methodology and supporting decision-analysis software for use in a regulatory context, using weighting of the relevant decision criteria generated from a stakeholder elicitation process. The analysis produced complete rankings of the alternatives, including identification of the relative contribution to the ranking of each of the highest level decision criteria such as human health impacts, technical feasibility, and economic feasibility. It also examined the effect of variation in data conventions, weighting, and decision frameworks on the outcome. The results indicate that MCDA can play a critical role in emerging prevention-based regulatory programs. Multi-criteria decision analysis methods offer a means for transparent, objective, and rigorous analysis of products and processes, providing regulators and stakeholders with a common baseline understanding of the relative performance of alternatives and the trade-offs they present.

  15. Use of multi-criteria decision analysis in regulatory alternatives analysis: a case study of lead free solder.

    PubMed

    Malloy, Timothy F; Sinsheimer, Peter J; Blake, Ann; Linkov, Igor

    2013-10-01

    Regulators are implementing new programs that require manufacturers of products containing certain chemicals of concern to identify, evaluate, and adopt viable, safer alternatives. Such programs raise the difficult question for policymakers and regulated businesses of which alternatives are "viable" and "safer." To address that question, these programs use "alternatives analysis," an emerging methodology that integrates issues of human health and environmental effects with technical feasibility and economic impact. Despite the central role that alternatives analysis plays in these programs, the methodology itself is neither well-developed nor tailored to application in regulatory settings. This study uses the case of Pb-based bar solder and its non-Pb-based alternatives to examine the application of 2 multi-criteria decision analysis (MCDA) methods to alternatives analysis: multi-attribute utility analysis and outranking. The article develops and evaluates an alternatives analysis methodology and supporting decision-analysis software for use in a regulatory context, using weighting of the relevant decision criteria generated from a stakeholder elicitation process. The analysis produced complete rankings of the alternatives, including identification of the relative contribution to the ranking of each of the highest level decision criteria such as human health impacts, technical feasibility, and economic feasibility. It also examined the effect of variation in data conventions, weighting, and decision frameworks on the outcome. The results indicate that MCDA can play a critical role in emerging prevention-based regulatory programs. Multi-criteria decision analysis methods offer a means for transparent, objective, and rigorous analysis of products and processes, providing regulators and stakeholders with a common baseline understanding of the relative performance of alternatives and the trade-offs they present. PMID:23703936

  16. Validation of decision-making models and analysis of decision variables in the rat basal ganglia.

    PubMed

    Ito, Makoto; Doya, Kenji

    2009-08-01

    Reinforcement learning theory plays a key role in understanding the behavioral and neural mechanisms of choice behavior in animals and humans. Especially, intermediate variables of learning models estimated from behavioral data, such as the expectation of reward for each candidate choice (action value), have been used in searches for the neural correlates of computational elements in learning and decision making. The aims of the present study are as follows: (1) to test which computational model best captures the choice learning process in animals and (2) to elucidate how action values are represented in different parts of the corticobasal ganglia circuit. We compared different behavioral learning algorithms to predict the choice sequences generated by rats during a free-choice task and analyzed associated neural activity in the nucleus accumbens (NAc) and ventral pallidum (VP). The major findings of this study were as follows: (1) modified versions of an action-value learning model captured a variety of choice strategies of rats, including win-stay-lose-switch and persevering behavior, and predicted rats' choice sequences better than the best multistep Markov model; and (2) information about action values and future actions was coded in both the NAc and VP, but was less dominant than information about trial types, selected actions, and reward outcome. The results of our model-based analysis suggest that the primary role of the NAc and VP is to monitor information important for updating choice behaviors. Information represented in the NAc and VP might contribute to a choice mechanism that is situated elsewhere.

  17. The potential for meta-analysis to support decision analysis in ecology.

    PubMed

    Mengersen, Kerrie; MacNeil, M Aaron; Caley, M Julian

    2015-06-01

    Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable expectations that benefits would be derived from doing so. Meta-analysis combines information from multiple studies to provide more accurate parameter estimates and to reduce the uncertainty surrounding them. Decision analysis involves selecting among alternative choices using statistical information that helps to shed light on the uncertainties involved. By linking meta-analysis to decision analysis, improved decisions can be made, with quantification of the costs and benefits of alternate decisions supported by a greater density of information. Here, we briefly review concepts of both meta-analysis and decision analysis, illustrating the natural linkage between them and the benefits from explicitly linking one to the other. We discuss some examples in which this linkage has been exploited in the medical arena and how improvements in precision and reduction of structural uncertainty inherent in a meta-analysis can provide substantive improvements to decision analysis outcomes by reducing uncertainty in expected loss and maximising information from across studies. We then argue that these significant benefits could be translated to ecology, in particular to the problem of making optimal ecological decisions in the face of uncertainty.

  18. The Performance Analysis of the Map-Aided Fuzzy Decision Tree Based on the Pedestrian Dead Reckoning Algorithm in an Indoor Environment.

    PubMed

    Chiang, Kai-Wei; Liao, Jhen-Kai; Tsai, Guang-Je; Chang, Hsiu-Wen

    2015-12-28

    Hardware sensors embedded in a smartphone allow the device to become an excellent mobile navigator. A smartphone is ideal for this task because its great international popularity has led to increased phone power and since most of the necessary infrastructure is already in place. However, using a smartphone for indoor pedestrian navigation can be problematic due to the low accuracy of sensors, imprecise predictability of pedestrian motion, and inaccessibility of the Global Navigation Satellite System (GNSS) in some indoor environments. Pedestrian Dead Reckoning (PDR) is one of the most common technologies used for pedestrian navigation, but in its present form, various errors tend to accumulate. This study introduces a fuzzy decision tree (FDT) aided by map information to improve the accuracy and stability of PDR with less dependency on infrastructure. First, the map is quickly surveyed by the Indoor Mobile Mapping System (IMMS). Next, Bluetooth beacons are implemented to enable the initializing of any position. Finally, map-aided FDT can estimate navigation solutions in real time. The experiments were conducted in different fields using a variety of smartphones and users in order to verify stability. The contrast PDR system demonstrates low stability for each case without pre-calibration and post-processing, but the proposed low-complexity FDT algorithm shows good stability and accuracy under the same conditions.

  19. The Performance Analysis of the Map-Aided Fuzzy Decision Tree Based on the Pedestrian Dead Reckoning Algorithm in an Indoor Environment.

    PubMed

    Chiang, Kai-Wei; Liao, Jhen-Kai; Tsai, Guang-Je; Chang, Hsiu-Wen

    2015-01-01

    Hardware sensors embedded in a smartphone allow the device to become an excellent mobile navigator. A smartphone is ideal for this task because its great international popularity has led to increased phone power and since most of the necessary infrastructure is already in place. However, using a smartphone for indoor pedestrian navigation can be problematic due to the low accuracy of sensors, imprecise predictability of pedestrian motion, and inaccessibility of the Global Navigation Satellite System (GNSS) in some indoor environments. Pedestrian Dead Reckoning (PDR) is one of the most common technologies used for pedestrian navigation, but in its present form, various errors tend to accumulate. This study introduces a fuzzy decision tree (FDT) aided by map information to improve the accuracy and stability of PDR with less dependency on infrastructure. First, the map is quickly surveyed by the Indoor Mobile Mapping System (IMMS). Next, Bluetooth beacons are implemented to enable the initializing of any position. Finally, map-aided FDT can estimate navigation solutions in real time. The experiments were conducted in different fields using a variety of smartphones and users in order to verify stability. The contrast PDR system demonstrates low stability for each case without pre-calibration and post-processing, but the proposed low-complexity FDT algorithm shows good stability and accuracy under the same conditions. PMID:26729114

  20. The Performance Analysis of the Map-Aided Fuzzy Decision Tree Based on the Pedestrian Dead Reckoning Algorithm in an Indoor Environment

    PubMed Central

    Chiang, Kai-Wei; Liao, Jhen-Kai; Tsai, Guang-Je; Chang, Hsiu-Wen

    2015-01-01

    Hardware sensors embedded in a smartphone allow the device to become an excellent mobile navigator. A smartphone is ideal for this task because its great international popularity has led to increased phone power and since most of the necessary infrastructure is already in place. However, using a smartphone for indoor pedestrian navigation can be problematic due to the low accuracy of sensors, imprecise predictability of pedestrian motion, and inaccessibility of the Global Navigation Satellite System (GNSS) in some indoor environments. Pedestrian Dead Reckoning (PDR) is one of the most common technologies used for pedestrian navigation, but in its present form, various errors tend to accumulate. This study introduces a fuzzy decision tree (FDT) aided by map information to improve the accuracy and stability of PDR with less dependency on infrastructure. First, the map is quickly surveyed by the Indoor Mobile Mapping System (IMMS). Next, Bluetooth beacons are implemented to enable the initializing of any position. Finally, map-aided FDT can estimate navigation solutions in real time. The experiments were conducted in different fields using a variety of smartphones and users in order to verify stability. The contrast PDR system demonstrates low stability for each case without pre-calibration and post-processing, but the proposed low-complexity FDT algorithm shows good stability and accuracy under the same conditions. PMID:26729114

  1. Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images

    PubMed Central

    Møllersen, Kajsa; Kirchesch, Herbert; Zortea, Maciel; Schopf, Thomas R.; Hindberg, Kristian; Godtliebsen, Fred

    2015-01-01

    Commercially available clinical decision support systems (CDSSs) for skin cancer have been designed for the detection of melanoma only. Correct use of the systems requires expert knowledge, hampering their utility for nonexperts. Furthermore, there are no systems to detect other common skin cancer types, that is, nonmelanoma skin cancer (NMSC). As early diagnosis of skin cancer is essential, there is a need for a CDSS that is applicable to all types of skin lesions and is suitable for nonexperts. Nevus Doctor (ND) is a CDSS being developed by the authors. We here investigate ND's ability to detect both melanoma and NMSC and the opportunities for improvement. An independent test set of dermoscopic images of 870 skin lesions, including 44 melanomas and 101 NMSCs, were analysed by ND. Its sensitivity to melanoma and NMSC was compared to that of Mole Expert (ME), a commercially available CDSS, using the same set of lesions. ND and ME had similar sensitivity to melanoma. For ND at 95% melanoma sensitivity, the NMSC sensitivity was 100%, and the specificity was 12%. The melanomas misclassified by ND at 95% sensitivity were correctly classified by ME, and vice versa. ND is able to detect NMSC without sacrificing melanoma sensitivity. PMID:26693486

  2. What can decision analysis do for invasive species management?

    PubMed

    Maguire, Lynn A

    2004-08-01

    Decisions about management of invasive species are difficult for all the reasons typically addressed by multiattribute decision analysis: uncertain outcomes, multiple and conflicting objectives, and many interested parties with differing views on both facts and values. This article illustrates how the tools of multiattribute analysis can improve management of invasive species, with an emphasis on making explicit the social values and preferences that must inform invasive species management. Risk assessment protocols developed previously for invasive species management typically suffer from two interacting flaws: (1) separating risk assessment from risk management, thus disrupting essential connections between the social values at stake in invasive species decisions and the scientific knowledge necessary to predict the likely impacts of management actions, and (2) relying on expert judgment about risk framed in qualitative and value-laden terms, inadvertently mixing the expert's judgment about what is likely to happen with personal preferences. Using the values structuring and probability-modeling elements of formal decision analysis can remedy these difficulties and make invasive species management responsive to both good science and public values. The management of feral pigs in Hawaiian ecosystems illustrates the need for such an integrated approach.

  3. What can decision analysis do for invasive species management?

    PubMed

    Maguire, Lynn A

    2004-08-01

    Decisions about management of invasive species are difficult for all the reasons typically addressed by multiattribute decision analysis: uncertain outcomes, multiple and conflicting objectives, and many interested parties with differing views on both facts and values. This article illustrates how the tools of multiattribute analysis can improve management of invasive species, with an emphasis on making explicit the social values and preferences that must inform invasive species management. Risk assessment protocols developed previously for invasive species management typically suffer from two interacting flaws: (1) separating risk assessment from risk management, thus disrupting essential connections between the social values at stake in invasive species decisions and the scientific knowledge necessary to predict the likely impacts of management actions, and (2) relying on expert judgment about risk framed in qualitative and value-laden terms, inadvertently mixing the expert's judgment about what is likely to happen with personal preferences. Using the values structuring and probability-modeling elements of formal decision analysis can remedy these difficulties and make invasive species management responsive to both good science and public values. The management of feral pigs in Hawaiian ecosystems illustrates the need for such an integrated approach. PMID:15357805

  4. A safety-based decision making architecture for autonomous systems

    NASA Technical Reports Server (NTRS)

    Musto, Joseph C.; Lauderbaugh, L. K.

    1991-01-01

    Engineering systems designed specifically for space applications often exhibit a high level of autonomy in the control and decision-making architecture. As the level of autonomy increases, more emphasis must be placed on assimilating the safety functions normally executed at the hardware level or by human supervisors into the control architecture of the system. The development of a decision-making structure which utilizes information on system safety is detailed. A quantitative measure of system safety, called the safety self-information, is defined. This measure is analogous to the reliability self-information defined by McInroy and Saridis, but includes weighting of task constraints to provide a measure of both reliability and cost. An example is presented in which the safety self-information is used as a decision criterion in a mobile robot controller. The safety self-information is shown to be consistent with the entropy-based Theory of Intelligent Machines defined by Saridis.

  5. H.264 SVC Complexity Reduction Based on Likelihood Mode Decision

    PubMed Central

    Balaji, L.; Thyagharajan, K. K.

    2015-01-01

    H.264 Advanced Video Coding (AVC) was prolonged to Scalable Video Coding (SVC). SVC executes in different electronics gadgets such as personal computer, HDTV, SDTV, IPTV, and full-HDTV in which user demands various scaling of the same content. The various scaling is resolution, frame rate, quality, heterogeneous networks, bandwidth, and so forth. Scaling consumes more encoding time and computational complexity during mode selection. In this paper, to reduce encoding time and computational complexity, a fast mode decision algorithm based on likelihood mode decision (LMD) is proposed. LMD is evaluated in both temporal and spatial scaling. From the results, we conclude that LMD performs well, when compared to the previous fast mode decision algorithms. The comparison parameters are time, PSNR, and bit rate. LMD achieve time saving of 66.65% with 0.05% detriment in PSNR and 0.17% increment in bit rate compared with the full search method. PMID:26221623

  6. H.264 SVC Complexity Reduction Based on Likelihood Mode Decision.

    PubMed

    Balaji, L; Thyagharajan, K K

    2015-01-01

    H.264 Advanced Video Coding (AVC) was prolonged to Scalable Video Coding (SVC). SVC executes in different electronics gadgets such as personal computer, HDTV, SDTV, IPTV, and full-HDTV in which user demands various scaling of the same content. The various scaling is resolution, frame rate, quality, heterogeneous networks, bandwidth, and so forth. Scaling consumes more encoding time and computational complexity during mode selection. In this paper, to reduce encoding time and computational complexity, a fast mode decision algorithm based on likelihood mode decision (LMD) is proposed. LMD is evaluated in both temporal and spatial scaling. From the results, we conclude that LMD performs well, when compared to the previous fast mode decision algorithms. The comparison parameters are time, PSNR, and bit rate. LMD achieve time saving of 66.65% with 0.05% detriment in PSNR and 0.17% increment in bit rate compared with the full search method.

  7. Counseling Students' Decision Making Regarding Teaching Effectiveness: A Conjoint Analysis

    ERIC Educational Resources Information Center

    Pietrzak, Dale; Duncan, Kelly; Korcuska, James S.

    2008-01-01

    The authors examined the relative importance of 4 attributes of decision making for student evaluation of teaching effectiveness: perceived knowledge base of the professor, professor's delivery style, course organization, and course workload. Participants were 234 counseling graduate students from 6 midwestern universities in the United States.…

  8. Interactive agent based modeling of public health decision-making.

    PubMed

    Parks, Amanda L; Walker, Brett; Pettey, Warren; Benuzillo, Jose; Gesteland, Per; Grant, Juliana; Koopman, James; Drews, Frank; Samore, Matthew

    2009-01-01

    Agent-based models have yielded important insights regarding the transmission dynamics of communicable diseases. To better understand how these models can be used to study decision making of public health officials, we developed a computer program that linked an agent-based model of pertussis with an agent-based model of public health management. The program, which we call the Public Health Interactive Model & simulation (PHIMs) encompassed the reporting of cases to public health, case investigation, and public health response. The user directly interacted with the model in the role of the public health decision-maker. In this paper we describe the design of our model, and present the results of a pilot study to assess its usability and potential for future development. Affinity for specific tools was demonstrated. Participants ranked the program high in usability and considered it useful for training. Our ultimate goal is to achieve better public health decisions and outcomes through use of public health decision support tools. PMID:20351907

  9. An empirical analysis of the corporate call decision

    NASA Astrophysics Data System (ADS)

    Carlson, Murray Dean

    1998-12-01

    In this thesis we provide insights into the behavior of financial managers of utility companies by studying their decisions to redeem callable preferred shares. In particular, we investigate whether or not an option pricing based model of the call decision, with managers who maximize shareholder value, does a better job of explaining callable preferred share prices and call decisions than do other models of the decision. In order to perform these tests, we extend an empirical technique introduced by Rust (1987) to include the use of information from preferred share prices in addition to the call decisions. The model we develop to value the option embedded in a callable preferred share differs from standard models in two ways. First, as suggested in Kraus (1983), we explicitly account for transaction costs associated with a redemption. Second, we account for state variables that are observed by the decision makers but not by the preferred shareholders. We interpret these unobservable state variables as the benefits and costs associated with a change in capital structure that can accompany a call decision. When we add this variable, our empirical model changes from one which predicts exactly when a share should be called to one which predicts the probability of a call as the function of the observable state. These two modifications of the standard model result in predictions of calls, and therefore of callable preferred share prices, that are consistent with several previously unexplained features of the data; we show that the predictive power of the model is improved in a statistical sense by adding these features to the model. The pricing and call probability functions from our model do a good job of describing call decisions and preferred share prices for several utilities. Using data from shares of the Pacific Gas and Electric Co. (PGE) we obtain reasonable estimates for the transaction costs associated with a call. Using a formal empirical test, we are able to

  10. Ensemble-based analysis of Front Range severe convection on 6-7 June 2012: Forecast uncertainty and communication of weather information to Front Range decision-makers

    NASA Astrophysics Data System (ADS)

    Vincente, Vanessa

    -allowing ensemble also showed greater skill in forecasting heavy precipitation amounts in the vicinity of where they were observed during the most active convective period, particularly near urbanized areas. A total of 9 Front Range EMs were interviewed to research how they understood hazardous weather information, and how their perception of forecast uncertainty would influence their decision making following a heavy rain event. Many of the EMs use situational awareness and past experiences with major weather events to guide their emergency planning. They also highly valued their relationship with the National Weather Service to improve their understanding of weather forecasts and ask questions about the uncertainties. Most of the EMs perceived forecast uncertainty in terms of probability and with the understanding that forecasting the weather is an imprecise science. The greater the likelihood of occurrence (implied by a higher probability of precipitation) showed greater confidence in the forecast that an event was likely to happen. Five probabilistic forecast products were generated from the convection-allowing ensemble output to generate a hypothetical warm season heavy rain event scenario. Responses varied between the EMs in which products they found most practical or least useful. Most EMs believed that there was a high probability for flooding, as illustrated by the degree of forecasted precipitation intensity. Most confirmed perceiving uncertainty in the different forecast representations, sharing the idea that there is an inherent uncertainty that follows modeled forecasts. The long-term goal of this research is to develop and add reliable probabilistic forecast products to the "toolbox" of decision-makers to help them better assess hazardous weather information and improve warning notifications and response.

  11. A new tool for analysis of cleanup criteria decisions.

    PubMed

    Klemic, Gladys A; Bailey, Paul; Elcock, Deborah

    2003-08-01

    Radionuclides and other hazardous materials resulting from processes used in nuclear weapons production contaminate soil, groundwater, and buildings around the United States. Cleanup criteria for environmental contaminants are agreed on prior to remediation and underpin the scope and legacy of the cleanup process. Analysis of cleanup criteria can be relevant for future agreements and may also provide insight into a complex decision making process where science and policy issues converge. An Internet accessible database has been established to summarize cleanup criteria and related factors involved in U.S. Department of Energy remediation decisions. This paper reports on a new user interface for the database that is designed to integrate related information into graphic displays and tables with interactive features that allow exploratory data analysis of cleanup criteria. Analysis of 137Cs in surface soil is presented as an example.

  12. A decision-based perspective for the design of methods for systems design

    NASA Technical Reports Server (NTRS)

    Mistree, Farrokh; Muster, Douglas; Shupe, Jon A.; Allen, Janet K.

    1989-01-01

    Organization of material, a definition of decision based design, a hierarchy of decision based design, the decision support problem technique, a conceptual model design that can be manufactured and maintained, meta-design, computer-based design, action learning, and the characteristics of decisions are among the topics covered.

  13. The neural bases underlying social risk perception in purchase decisions.

    PubMed

    Yokoyama, Ryoichi; Nozawa, Takayuki; Sugiura, Motoaki; Yomogida, Yukihito; Takeuchi, Hikaru; Akimoto, Yoritaka; Shibuya, Satoru; Kawashima, Ryuta

    2014-05-01

    Social considerations significantly influence daily purchase decisions, and the perception of social risk (i.e., the anticipated disapproval of others) is crucial in dissuading consumers from making purchases. However, the neural basis for consumers' perception of social risk remains undiscovered, and this novel study clarifies the relevant neural processes. A total of 26 volunteers were scanned while they evaluated purchase intention of products (purchase intention task) and their anticipation of others' disapproval for possessing a product (social risk task), using functional magnetic resonance imaging (fMRI). The fMRI data from the purchase intention task was used to identify the brain region associated with perception of social risk during purchase decision making by using subjective social risk ratings for a parametric modulation analysis. Furthermore, we aimed to explore if there was a difference between participants' purchase decisions and their explicit evaluations of social risk, with reference to the neural activity associated with social risk perception. For this, subjective social risk ratings were used for a parametric modulation analysis on fMRI data from the social risk task. Analysis of the purchase intention task revealed a significant positive correlation between ratings of social risk and activity in the anterior insula, an area of the brain that is known as part of the emotion-related network. Analysis of the social risk task revealed a significant positive correlation between ratings of social risk and activity in the temporal parietal junction and the medial prefrontal cortex, which are known as theory-of-mind regions. Our results suggest that the anterior insula processes consumers' social risk implicitly to prompt consumers not to buy socially unacceptable products, whereas ToM-related regions process such risk explicitly in considering the anticipated disapproval of others. These findings may prove helpful in understanding the mental

  14. The neural bases underlying social risk perception in purchase decisions.

    PubMed

    Yokoyama, Ryoichi; Nozawa, Takayuki; Sugiura, Motoaki; Yomogida, Yukihito; Takeuchi, Hikaru; Akimoto, Yoritaka; Shibuya, Satoru; Kawashima, Ryuta

    2014-05-01

    Social considerations significantly influence daily purchase decisions, and the perception of social risk (i.e., the anticipated disapproval of others) is crucial in dissuading consumers from making purchases. However, the neural basis for consumers' perception of social risk remains undiscovered, and this novel study clarifies the relevant neural processes. A total of 26 volunteers were scanned while they evaluated purchase intention of products (purchase intention task) and their anticipation of others' disapproval for possessing a product (social risk task), using functional magnetic resonance imaging (fMRI). The fMRI data from the purchase intention task was used to identify the brain region associated with perception of social risk during purchase decision making by using subjective social risk ratings for a parametric modulation analysis. Furthermore, we aimed to explore if there was a difference between participants' purchase decisions and their explicit evaluations of social risk, with reference to the neural activity associated with social risk perception. For this, subjective social risk ratings were used for a parametric modulation analysis on fMRI data from the social risk task. Analysis of the purchase intention task revealed a significant positive correlation between ratings of social risk and activity in the anterior insula, an area of the brain that is known as part of the emotion-related network. Analysis of the social risk task revealed a significant positive correlation between ratings of social risk and activity in the temporal parietal junction and the medial prefrontal cortex, which are known as theory-of-mind regions. Our results suggest that the anterior insula processes consumers' social risk implicitly to prompt consumers not to buy socially unacceptable products, whereas ToM-related regions process such risk explicitly in considering the anticipated disapproval of others. These findings may prove helpful in understanding the mental

  15. Core domains of shared decision-making during psychiatric visits: Scientific and preference-based discussions

    PubMed Central

    Fukui, Sadaaki; Matthias, Marianne S.; Salyers, Michelle P.

    2014-01-01

    Shared decision-making (SDM) is imperative to person-centered care, yet little is known about what aspects of SDM are targeted during psychiatric visits. This secondary data analysis (191 psychiatric visits with 11 providers, coded with a validated SDM coding system) revealed two factors (scientific and preference-based discussions) underlying SDM communication. Preference-based discussion occurred less. Both provider and consumer initiation of SDM elements and decision complexity were associated with greater discussions in both factors, but were more strongly associated with scientific discussion. Longer visit length correlated with only scientific discussion. Providers’ understanding of core domains could facilitate engaging consumers in SDM. PMID:24500023

  16. Decision analysis in the clinical neurosciences: a systematic review of the literature.

    PubMed

    Dippel, D W; Habbema, J D

    1995-12-01

    Clinical decision analysis can be a useful scientific tool for individual patient management, for planning of clinical research and for reaching consensus about clinical problems. We systematically reviewed the decision analytic studies in the clinical neurosciences that were published between 1975 and July 1994. All studies were assessed on aspects of clinical applicability: presence of case and context description, completeness of the analysed strategies from a clinical point of view, extendibility of the analyses to different patient profiles, and up-to-date-ness. Fifty-nine decision analyses of twenty-eight different clinical problems were identified. Twenty-eight analyses were based on the theory of subjective expected utility, twelve on cost-effectiveness analysis. Four studies used ROC analysis, and fifteen were risk-, or risk-benefit analyses. At least six studies could have been improved by more elaborately disclosing the context of the clinical problem that was addressed. In eleven studies, the effect of different, yet plausible assumptions was not explored, and in eighteen studies the reader was not informed how to extend the results of the analysis to patients with (slightly) different clinical characterisitics. All studies had, by nature, the potential to promote insight into the clinical problem and focus the discussion on clinically important aspects, and gave clinically useful advice. We conclude that clinical decision analysis, as an explicit, quantitative approach to uncertainty in decision making in the clinical neurosciences will fulfill a growing need in the near future. PMID:24283779

  17. An Integrated Web-based Decision Support System in Disaster Risk Management

    NASA Astrophysics Data System (ADS)

    Aye, Z. C.; Jaboyedoff, M.; Derron, M. H.

    2012-04-01

    Nowadays, web based decision support systems (DSS) play an essential role in disaster risk management because of their supporting abilities which help the decision makers to improve their performances and make better decisions without needing to solve complex problems while reducing human resources and time. Since the decision making process is one of the main factors which highly influence the damages and losses of society, it is extremely important to make right decisions at right time by combining available risk information with advanced web technology of Geographic Information System (GIS) and Decision Support System (DSS). This paper presents an integrated web-based decision support system (DSS) of how to use risk information in risk management efficiently and effectively while highlighting the importance of a decision support system in the field of risk reduction. Beyond the conventional systems, it provides the users to define their own strategies starting from risk identification to the risk reduction, which leads to an integrated approach in risk management. In addition, it also considers the complexity of changing environment from different perspectives and sectors with diverse stakeholders' involvement in the development process. The aim of this platform is to contribute a part towards the natural hazards and geosciences society by developing an open-source web platform where the users can analyze risk profiles and make decisions by performing cost benefit analysis, Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) with the support of others tools and resources provided. There are different access rights to the system depending on the user profiles and their responsibilities. The system is still under development and the current version provides maps viewing, basic GIS functionality, assessment of important infrastructures (e.g. bridge, hospital, etc.) affected by landslides and visualization of the impact

  18. Decision-Making, Information Communication Technology, and Data Analysis by School Leaders about Student Achievement

    ERIC Educational Resources Information Center

    Akoma, Ahunna Margaux

    2012-01-01

    This case study of one school district examined how school leaders use student performance data and technology-based data analysis tools to engage in data-informed decision-making for continuous improvement. School leaders in this context included leaders at the district, school, and classroom levels. An extensive literature review provided the…

  19. Use of stochastic multi-criteria decision analysis to support sustainable management of contaminated sediments.

    PubMed

    Sparrevik, Magnus; Barton, David N; Bates, Mathew E; Linkov, Igor

    2012-02-01

    Sustainable management of contaminated sediments requires careful prioritization of available resources and focuses on efforts to optimize decisions that consider environmental, economic, and societal aspects simultaneously. This may be achieved by combining different analytical approaches such as risk analysis (RA), life cycle analysis (LCA), multicriteria decision analysis (MCDA), and economic valuation methods. We propose the use of stochastic MCDA based on outranking algorithms to implement integrative sustainability strategies for sediment management. In this paper we use the method to select the best sediment management alternatives for the dibenzo-p-dioxin and -furan (PCDD/F) contaminated Grenland fjord in Norway. In the analysis, the benefits of health risk reductions and socio-economic benefits from removing seafood health advisories are evaluated against the detriments of remedial costs and life cycle environmental impacts. A value-plural based weighing of criteria is compared to criteria weights mimicking traditional cost-effectiveness (CEA) and cost-benefit (CBA) analyses. Capping highly contaminated areas in the inner or outer fjord is identified as the most preferable remediation alternative under all criteria schemes and the results are confirmed by a probabilistic sensitivity analysis. The proposed methodology can serve as a flexible framework for future decision support and can be a step toward more sustainable decision making for contaminated sediment management. It may be applicable to the broader field of ecosystem restoration for trade-off analysis between ecosystem services and restoration costs.

  20. Multi-criteria decision analysis: Limitations, pitfalls, and practical difficulties

    SciTech Connect

    Kujawski, Edouard

    2003-02-01

    The 2002 Winter Olympics women's figure skating competition is used as a case study to illustrate some of the limitations, pitfalls, and practical difficulties of Multi-Criteria Decision Analysis (MCDA). The paper compares several widely used models for synthesizing the multiple attributes into a single aggregate value. The various MCDA models can provide conflicting rankings of the alternatives for a common set of information even under states of certainty. Analysts involved in MCDA need to deal with the following challenging tasks: (1) selecting an appropriate analysis method, and (2) properly interpreting the results. An additional trap is the availability of software tools that implement specific MCDA models that can beguile the user with quantitative scores. These conclusions are independent of the decision domain and they should help foster better MCDA practices in many fields including systems engineering trade studies.

  1. Guide to IDAP, Version 2: an interactive decision analysis procedure

    SciTech Connect

    Jusko, M.J.; Whitfield, R.G.

    1980-11-01

    This document is intended to serve as both a programmer's and user's guide to the current version of the IDAP; and to prompt interested individuals into making suggestions for the future development of IDAP. The majority of the sections pertain to the main IDA program rather than to the IDAIN procedure. A brief discussion is presented of the theory of decision analysis. The aspects of decision analysis that are relevant to the IDAP are discussed. A complete list and description of the commands used in the IDAP program is provided and, including three complete examples. This section may be considered a user's guide to the IDAP. The programmer's guide to the IDAP discusses the various technical aspects of the programs, and may be skipped by users not involved with programming the IDAP. A list of the error messages generated by the IDAP is presented. As the program is developed, error handling and messages will improve.

  2. Ethics-based decision-making and health impact assessment.

    PubMed

    Tannahill, Andrew; Douglas, Margaret J

    2014-03-01

    To compare the use of health impact assessment (HIA) and the decision-making triangle (DMT) framework for evidence-informed, ethics-based decision-making and consider implications for practice. We compared HIA and the DMT approach with reference to: their use of evidence and theory; their application of ethical principles or values; and how they aid decision-making. A good fit between the HIA and DMT approaches was found. Ways in which they could be of benefit to each other were identified. The DMT approach and HIA are highly compatible: they are rooted in largely shared ethical principles or values; both involve appropriate use of evidence and theory; and both are concerned with enhancing the quality of decision-making in the interests of population health. The DMT approach and HIA are of potential value to each other: established HIA methods and tools can be of practical help in using the DMT approach; and the DMT framework provides insights to how HIA methods and processes could be improved and the vision of 'impacts that matter' widened.

  3. A decision analysis approach for risk management of near-earth objects

    NASA Astrophysics Data System (ADS)

    Lee, Robert C.; Jones, Thomas D.; Chapman, Clark R.

    2014-10-01

    Risk management of near-Earth objects (NEOs; e.g., asteroids and comets) that can potentially impact Earth is an important issue that took on added urgency with the Chelyabinsk event of February 2013. Thousands of NEOs large enough to cause substantial damage are known to exist, although only a small fraction of these have the potential to impact Earth in the next few centuries. The probability and location of a NEO impact are subject to complex physics and great uncertainty, and consequences can range from minimal to devastating, depending upon the size of the NEO and location of impact. Deflecting a potential NEO impactor would be complex and expensive, and inter-agency and international cooperation would be necessary. Such deflection campaigns may be risky in themselves, and mission failure may result in unintended consequences. The benefits, risks, and costs of different potential NEO risk management strategies have not been compared in a systematic fashion. We present a decision analysis framework addressing this hazard. Decision analysis is the science of informing difficult decisions. It is inherently multi-disciplinary, especially with regard to managing catastrophic risks. Note that risk analysis clarifies the nature and magnitude of risks, whereas decision analysis guides rational risk management. Decision analysis can be used to inform strategic, policy, or resource allocation decisions. First, a problem is defined, including the decision situation and context. Second, objectives are defined, based upon what the different decision-makers and stakeholders (i.e., participants in the decision) value as important. Third, quantitative measures or scales for the objectives are determined. Fourth, alternative choices or strategies are defined. Fifth, the problem is then quantitatively modeled, including probabilistic risk analysis, and the alternatives are ranked in terms of how well they satisfy the objectives. Sixth, sensitivity analyses are performed in

  4. Stereotactic Body Radiotherapy Versus Surgery for Medically Operable Stage I Non-Small-Cell Lung Cancer: A Markov Model-Based Decision Analysis

    SciTech Connect

    Louie, Alexander V.; Rodrigues, George; Palma, David A.; Cao, Jeffrey Q.; Yaremko, Brian P.; Malthaner, Richard; Mocanu, Joseph D.

    2011-11-15

    Purpose: To compare the quality-adjusted life expectancy and overall survival in patients with Stage I non-small-cell lung cancer (NSCLC) treated with either stereotactic body radiation therapy (SBRT) or surgery. Methods and Materials: We constructed a Markov model to describe health states after either SBRT or lobectomy for Stage I NSCLC for a 5-year time frame. We report various treatment strategy survival outcomes stratified by age, sex, and pack-year history of smoking, and compared these with an external outcome prediction tool (Adjuvant{exclamation_point} Online). Results: Overall survival, cancer-specific survival, and other causes of death as predicted by our model correlated closely with those predicted by the external prediction tool. Overall survival at 5 years as predicted by baseline analysis of our model is in favor of surgery, with a benefit ranging from 2.2% to 3.0% for all cohorts. Mean quality-adjusted life expectancy ranged from 3.28 to 3.78 years after surgery and from 3.35 to 3.87 years for SBRT. The utility threshold for preferring SBRT over surgery was 0.90. Outcomes were sensitive to quality of life, the proportion of local and regional recurrences treated with standard vs. palliative treatments, and the surgery- and SBRT-related mortalities. Conclusions: The role of SBRT in the medically operable patient is yet to be defined. Our model indicates that SBRT may offer comparable overall survival and quality-adjusted life expectancy as compared with surgical resection. Well-powered prospective studies comparing surgery vs. SBRT in early-stage lung cancer are warranted to further investigate the relative survival, quality of life, and cost characteristics of both treatment paradigms.

  5. An analysis of CPR decision-making by elderly patients.

    PubMed Central

    Sayers, G M; Schofield, I; Aziz, M

    1997-01-01

    Traditionally clinicians have determined their patients' resuscitation status without consultation. This has been condemned as morally indefensible in cases where not for resuscitation (NFR) orders are based on quality of life considerations and when the patient's true wishes are not known. Such instances would encompass most resuscitation decisions in elderly patients. Having previously involved patients in CPR decision-making, we chose formally to explore the reasons behind the choices made. Although the patients were not upset, and readily decided at the time of initial consultation, on later analysing the decision-making we found poor understanding of the procedure, poor recall of information given and in some cases evidence of harm. This may be attributed to impaired decision-making capacity of elderly hospitalised patients as previously shown, or to the discomfort precipitated by having to contemplate the apparent immediacy of cardiac arrest by these patients. We propose that subscribing to autonomy as a general principle needs to be balanced against particular cases where distress may be caused by, or result in, diminished competence and limited autonomy. PMID:9279741

  6. Decision Consequence Model (DCM): Integrating environmental data and analysis into real time decision making

    SciTech Connect

    Cimorelli, A.J.; Stahl, C.H.; Chow, A.H.; Fernandez, C.

    1999-07-01

    A critical evaluation of the many environmental issues facing EPA Region 3 has established five major priorities: (1) ozone pollution (and its precursors); (2) impacts of acidification (acid deposition and acid mine drainage); (3) eutrophication of the Chesapeake Bay from atmospheric nitrogen deposition; (4) Cities/Urban Environment (ozone, particulate matter (PM), air toxics are some of the air components); and (5) Climate Change. Recognizing the complex nature of the systems controlling these issues, Region III's Air Protection Division (APD) is developing a decision support tool, i.e., the Decision Consequence Model (DCM), that will integrate and automate the analysis of environmental impacts in a manner that allows them to holistically address these regional priorities. Using this tool the authors intend to consider the interdependency of pollutants and their environmental impacts in order to support real-time decision making. The purpose of this paper is to outline the basic concept of the DCM and to present an example set of environmental indicators to illustrate how the DCM will be used to evaluate environmental impacts. The authors will discuss their process of indicator development, and present an example suite of indicators to provide a concrete example of the concepts presented above and, to illustrate the utility of the DCM to simultaneously evaluate multiple effects of a single pollutant. They will discuss the type of indicators chosen for this example as well as the general criteria the DCM indicators must satisfy. The framework that was developed to construct the indicators is discussed and used to calculate the example indicators. The yearly magnitudes of these example indicators are calculated for various multi-year periods to show their behavior over time.

  7. A decision analysis approach for risk management of near-earth objects

    NASA Astrophysics Data System (ADS)

    Lee, Robert C.; Jones, Thomas D.; Chapman, Clark R.

    2014-10-01

    Risk management of near-Earth objects (NEOs; e.g., asteroids and comets) that can potentially impact Earth is an important issue that took on added urgency with the Chelyabinsk event of February 2013. Thousands of NEOs large enough to cause substantial damage are known to exist, although only a small fraction of these have the potential to impact Earth in the next few centuries. The probability and location of a NEO impact are subject to complex physics and great uncertainty, and consequences can range from minimal to devastating, depending upon the size of the NEO and location of impact. Deflecting a potential NEO impactor would be complex and expensive, and inter-agency and international cooperation would be necessary. Such deflection campaigns may be risky in themselves, and mission failure may result in unintended consequences. The benefits, risks, and costs of different potential NEO risk management strategies have not been compared in a systematic fashion. We present a decision analysis framework addressing this hazard. Decision analysis is the science of informing difficult decisions. It is inherently multi-disciplinary, especially with regard to managing catastrophic risks. Note that risk analysis clarifies the nature and magnitude of risks, whereas decision analysis guides rational risk management. Decision analysis can be used to inform strategic, policy, or resource allocation decisions. First, a problem is defined, including the decision situation and context. Second, objectives are defined, based upon what the different decision-makers and stakeholders (i.e., participants in the decision) value as important. Third, quantitative measures or scales for the objectives are determined. Fourth, alternative choices or strategies are defined. Fifth, the problem is then quantitatively modeled, including probabilistic risk analysis, and the alternatives are ranked in terms of how well they satisfy the objectives. Sixth, sensitivity analyses are performed in

  8. Visualizing and communicating climate change using the ClimateWizard: decision support and education through web-based analysis and mapping

    NASA Astrophysics Data System (ADS)

    Girvetz, E. H.; Zganjar, C.; Raber, G. T.; Maurer, E. P.; Duffy, P.

    2009-12-01

    Virtually all fields of study and parts of society—from ecological science and nature conservation, to global development, multinational corporations, and government bodies—need to know how climate change has and may impact specific locations of interest. Our ability to respond to climate change depends on having convenient tools that make past and projected climate trends available to planners, managers, scientists and the general public, at scales ranging from global to local scales. Web-mapping applications provide an effective platform for communicating climate change impacts in specific geographic areas of interest to the public. Here, we present one such application, the ClimateWizard, that allows users to analyze, visualize and explore climate change maps for specific geographic areas of interest throughout the world (http://ClimateWizard.org). Built on Web 2.0 web-services (SOAP), Google Maps mash-up, and cloud computing technologies, the ClimateWizard analyzes large databases of climate information located on remote servers to create synthesized information and useful products tailored to geographic areas of interest (e.g. maps, graphs, tables, GIS layers). We demonstrate how the ClimateWizard can be used to assess projected changes to temperature and precipitation across all states in the contiguous United States and all countries of the world using statistically downscaled general circulation models from the CMIP3 dataset. We then go on to show how ClimateWizard can be used to analyze changes to other climate related variables, such as moisture stress and water production. Finally, we discuss how this tool can be adapted to develop a wide range of web-based tools that are targeted at informing specific audiences—from scientific research and natural resource management, to K-12 and higher education—about how climate change may affect different aspects of human and natural systems.

  9. Health care priority setting in Norway a multicriteria decision analysis

    PubMed Central

    2012-01-01

    Background Priority setting in population health is increasingly based on explicitly formulated values. The Patients Rights Act of the Norwegian tax-based health service guaranties all citizens health care in case of a severe illness, a proven health benefit, and proportionality between need and treatment. This study compares the values of the country's health policy makers with these three official principles. Methods In total 34 policy makers participated in a discrete choice experiment, weighting the relative value of six policy criteria. We used multi-variate logistic regression with selection as dependent valuable to derive odds ratios for each criterion. Next, we constructed a composite league table - based on the sum score for the probability of selection - to rank potential interventions in five major disease areas. Results The group considered cost effectiveness, large individual benefits and severity of disease as the most important criteria in decision making. Priority interventions are those related to cardiovascular diseases and respiratory diseases. Less attractive interventions rank those related to mental health. Conclusions Norwegian policy makers' values are in agreement with principles formulated in national health laws. Multi-criteria decision approaches may provide a tool to support explicit allocation decisions. PMID:22335815

  10. The Aeronautical Data Link: Decision Framework for Architecture Analysis

    NASA Technical Reports Server (NTRS)

    Morris, A. Terry; Goode, Plesent W.

    2003-01-01

    A decision analytic approach that develops optimal data link architecture configuration and behavior to meet multiple conflicting objectives of concurrent and different airspace operations functions has previously been developed. The approach, premised on a formal taxonomic classification that correlates data link performance with operations requirements, information requirements, and implementing technologies, provides a coherent methodology for data link architectural analysis from top-down and bottom-up perspectives. This paper follows the previous research by providing more specific approaches for mapping and transitioning between the lower levels of the decision framework. The goal of the architectural analysis methodology is to assess the impact of specific architecture configurations and behaviors on the efficiency, capacity, and safety of operations. This necessarily involves understanding the various capabilities, system level performance issues and performance and interface concepts related to the conceptual purpose of the architecture and to the underlying data link technologies. Efficient and goal-directed data link architectural network configuration is conditioned on quantifying the risks and uncertainties associated with complex structural interface decisions. Deterministic and stochastic optimal design approaches will be discussed that maximize the effectiveness of architectural designs.

  11. Risk-based decision support tools: protecting rail-centered transit corridors from cascading effects.

    PubMed

    Greenberg, Michael R; Lowrie, Karen; Mayer, Henry; Altiok, Tayfur

    2011-12-01

    We consider the value of decision support tools for passenger rail system managers. First, we call for models that follow events along main rail lines and then into the surrounding environment where they can cascade onto connected light rail, bus, auto, truck, and other transport modes. Second, we suggest that both probabilistic risk assessment (PRA-based) and agent-based models have a role to play at different scales of analysis and for different kinds of risks. Third, we argue that economic impact tools need more systematic evaluation. Fourth, we note that developers of decision support tools face a challenge of balancing their desire for theoretical elegance and the tendency to focus only on high consequence events against decisionmakers' mistrust of complex tools that they and their staff cannot manage and incorporate into their routine operations, as well as the high costs of developing, updating, and applying decision support tools to transport systems undergoing budget cuts and worker and service reductions.

  12. Informed decision making for in-home use of motion sensor-based monitoring technologies.

    PubMed

    Bruce, Courtenay R

    2012-06-01

    Motion sensor-based monitoring technologies are designed to maintain independence and safety of older individuals living alone. These technologies use motion sensors that are placed throughout older individuals' homes in order to derive information about eating, sleeping, and leaving/returning home habits. Deviations from normal behavioral patterns are detected using statistical analysis of activities of daily living. Sensors are linked to mobile devices and secure Web pages in order to transmit information to designated caregivers who live outside the home. It is difficult to make informed decisions about purchasing new technologies. This article describes elements for making informed decisions about purchasing motion sensor-based monitoring technologies and factors that could be used to evaluate these technologies. Case managers, physicians, nurses, and social workers may be asked to help older individuals and their families make informed purchasing decisions. Recommendations and practical tools are provided to best support these professionals in their dialog with older individuals and their families. PMID:22056959

  13. Database and knowledge base integration in decision support systems.

    PubMed Central

    Johansson, B.; Shahsavar, N.; Ahlfeldt, H.; Wigertz, O.

    1996-01-01

    Since decision support systems (DSS) in medicine often are linked to clinical databases it is important to find methods that facilitate the work for DSS developers to implement database queries in the knowledge base (KB). This paper presents a method for linking clinical databases to a KB with Arden Syntax modules. The method is based on a query meta database including templates for SQL queries. During knowledge module authoring the medical expert only refers to a code in the query meta database. Our method uses standard tools so it can be implemented on different platforms and linked to different clinical databases. PMID:8947666

  14. Decision support system based semantic web for personalized patient care.

    PubMed

    Douali, Nassim; De Roo, Jos; Jaulent, Marie-Christine

    2012-01-01

    Personalized medicine may be considered an extension of traditional approaches to understanding and treating diseases, but with greater precision. A profile of a patient's genetic variation can guide the selection of drugs or treatment protocols that minimize harmful side effects or ensure a more successful outcome. In this paper we describe a decision support system designed to assist physicians for personalized care, and methodology for integration in the clinical workflow. A reasoning method for interacting heterogeneous knowledge and data is a necessity in the context of personalized medicine. Development of clinical decision support based semantic web for personalized patient care is to achieve its potential and improve the quality, safety and efficiency of healthcare.

  15. Toward image analysis and decision support for ultrasound technology.

    PubMed

    Crofts, Gillian; Padman, Rema; Maharaja, Nisha

    2013-01-01

    Ultrasound is a low cost and efficient method of detecting diseases and abnormalities in the body. Yet there is a lack of precision and reliability associated with the technology, partly due to the operator dependent nature of ultrasound scanning. When scanning is performed to an agreed protocol, ultrasound has been shown to be highly reliable. This research aims to minimize these limitations that arise during ultrasound training, scanning and reporting by developing and evaluating an image analysis and decision support system that can aid the decision making process. We hypothesize that this intervention will likely increase the role of ultrasound in diagnosis when compared with other imaging technologies, particularly in low resource settings. PMID:23920862

  16. Levels of Analysis in Mass Media Decision Making: A Taxonomy, Research Strategy, and Illustrative Data Analysis.

    ERIC Educational Resources Information Center

    Dimmick, John; Coit, Philip

    1982-01-01

    Presents a taxonomy of influences on decision making in mass media. Illustrates the use of the taxonomy and research strategy in a quantitative analysis of influences on the decision autonomy of reporters. Results indicate that reporters' experience plays the most important role in explaining their story selection/content autonomy. (PD)

  17. HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS

    EPA Science Inventory

    Decision makers using environmental decision support tools are often confronted with information that predicts a multitude of different human health effects due to environmental stressors. If these health effects need to be contrasted with costs or compared with alternative scena...

  18. [Value-based cancer care. From traditional evidence-based decision making to balanced decision making within frameworks of shared values].

    PubMed

    Palazzo, Salvatore; Filice, Aldo; Mastroianni, Candida; Biamonte, Rosalbino; Conforti, Serafino; Liguori, Virginia; Turano, Salvatore; De Simone, Rosanna; Rovito, Antonio; Manfredi, Caterina; Minardi, Stefano; Vilardo, Emmanuelle; Loizzo, Monica; Oriolo, Carmela

    2016-04-01

    Clinical decision making in oncology is based so far on the evidence of efficacy from high-quality clinical research. Data collection and analysis from experimental studies provide valuable insight into response rates and progression-free or overall survival. Data processing generates valuable information for medical professionals involved in cancer patient care, enabling them to make objective and unbiased choices. The increased attention of many scientific associations toward a more rational resource consumption in clinical decision making is mirrored in the Choosing Wisely campaign against the overuse or misuse of exams and procedures of little or no benefit for the patient. This cultural movement has been actively promoting care solutions based on the concept of "value". As a result, the value-based decision-making process for cancer care should not be dissociated from economic sustainability and from ethics of the affordability, also given the growing average cost of the most recent cancer drugs. In support of this orientation, the National Comprehensive Cancer Network (NCCN) has developed innovative and "complex" guidelines based on values, defined as "evidence blocks", with the aim of assisting the medical community in making overall sustainable choices.

  19. Leadership Style, Decision Context, and the Poliheuristic Theory of Decision Making: An Experimental Analysis

    ERIC Educational Resources Information Center

    Keller, Jonathan W.; Yang, Yi Edward

    2008-01-01

    The poliheuristic (PH) theory of decision making has made important contributions to our understanding of political decision making but remains silent about certain key aspects of the decision process. Specifically, PH theory contends that leaders screen out politically unacceptable options, but it provides no guidance on (1) the crucial threshold…

  20. Cost-Benefit Analysis in Environmental Decision Making.

    ERIC Educational Resources Information Center

    Singer, S. Fred

    1977-01-01

    Discusses how to set the ambient standards for water and air based on cost-benefit analysis. Describes marginal analysis, the basis of cost-benefit analysis and how dynamic cost-benefit analysis is carried out with application to the automobile pollution problem. (HM)

  1. Soft Mathematical Aggregation in Safety Assessment and Decision Analysis

    SciTech Connect

    Cooper, J. Arlin

    1999-06-10

    This paper improves on some of the limitations of conventional safety assessment and decision analysis methods. It develops a top-down mathematical method for expressing imprecise individual metrics as possibilistic or fuzzy numbers and shows how they may be combined (aggregated) into an overall metric, also portraying the inherent uncertainty. Both positively contributing and negatively contributing factors are included. Metrics are weighted according to significance of the attribute and evaluated as to contribution toward the attribute. Aggregation is performed using exponential combination of the metrics, since the accumulating effect of such factors responds less and less to additional factors. This is termed soft mathematical aggregation. Dependence among the contributing factors is accounted for by incorporating subjective metrics on overlap of the factors and by correspondingly reducing the overall contribution of these combinations to the overall aggregation. Decisions corresponding to the meaningfulness of the results are facilitated in several ways. First, the results are compared to a soft threshold provided by a sigmoid function. Second, information is provided on input ''Importance'' and ''Sensitivity,'' in order to know where to place emphasis on controls that may be necessary. Third, trends in inputs and outputs are tracked in order to add important information to the decision process. The methodology has been implemented in software.

  2. Engaging stakeholders for adaptive management using structured decision analysis

    USGS Publications Warehouse

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

    2009-01-01

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

  3. Dynamic sensor action selection with Bayesian decision analysis

    NASA Astrophysics Data System (ADS)

    Kristensen, Steen; Hansen, Volker; Kondak, Konstantin

    1998-10-01

    The aim of this work is to create a framework for the dynamic planning of sensor actions for an autonomous mobile robot. The framework uses Bayesian decision analysis, i.e., a decision-theoretic method, to evaluate possible sensor actions and selecting the most appropriate ones given the available sensors and what is currently known about the state of the world. Since sensing changes the knowledge of the system and since the current state of the robot (task, position, etc.) determines what knowledge is relevant, the evaluation and selection of sensing actions is an on-going process that effectively determines the behavior of the robot. The framework has been implemented on a real mobile robot and has been proven to be able to control in real-time the sensor actions of the system. In current work we are investigating methods to reduce or automatically generate the necessary model information needed by the decision- theoretic method to select the appropriate sensor actions.

  4. Decomposition-Based Decision Making for Aerospace Vehicle Design

    NASA Technical Reports Server (NTRS)

    Borer, Nicholas K.; Mavris, DImitri N.

    2005-01-01

    reader to observe how this technique can be applied to aerospace systems design and compare the results of this so-called Decomposition-Based Decision Making to more traditional design approaches.

  5. Memory-Based Decision-Making with Heuristics: Evidence for a Controlled Activation of Memory Representations

    ERIC Educational Resources Information Center

    Khader, Patrick H.; Pachur, Thorsten; Meier, Stefanie; Bien, Siegfried; Jost, Kerstin; Rosler, Frank

    2011-01-01

    Many of our daily decisions are memory based, that is, the attribute information about the decision alternatives has to be recalled. Behavioral studies suggest that for such decisions we often use simple strategies (heuristics) that rely on controlled and limited information search. It is assumed that these heuristics simplify decision-making by…

  6. Markov Modeling with Soft Aggregation for Safety and Decision Analysis

    SciTech Connect

    COOPER,J. ARLIN

    1999-09-01

    The methodology in this report improves on some of the limitations of many conventional safety assessment and decision analysis methods. A top-down mathematical approach is developed for decomposing systems and for expressing imprecise individual metrics as possibilistic or fuzzy numbers. A ''Markov-like'' model is developed that facilitates combining (aggregating) inputs into overall metrics and decision aids, also portraying the inherent uncertainty. A major goal of Markov modeling is to help convey the top-down system perspective. One of the constituent methodologies allows metrics to be weighted according to significance of the attribute and aggregated nonlinearly as to contribution. This aggregation is performed using exponential combination of the metrics, since the accumulating effect of such factors responds less and less to additional factors. This is termed ''soft'' mathematical aggregation. Dependence among the contributing factors is accounted for by incorporating subjective metrics on ''overlap'' of the factors as well as by correspondingly reducing the overall contribution of these combinations to the overall aggregation. Decisions corresponding to the meaningfulness of the results are facilitated in several ways. First, the results are compared to a soft threshold provided by a sigmoid function. Second, information is provided on input ''Importance'' and ''Sensitivity,'' in order to know where to place emphasis on considering new controls that may be necessary. Third, trends in inputs and outputs are tracked in order to obtain significant information% including cyclic information for the decision process. A practical example from the air transportation industry is used to demonstrate application of the methodology. Illustrations are given for developing a structure (along with recommended inputs and weights) for air transportation oversight at three different levels, for developing and using cycle information, for developing Importance and

  7. Choices, choices: the application of multi-criteria decision analysis to a food safety decision-making problem.

    PubMed

    Fazil, A; Rajic, A; Sanchez, J; McEwen, S

    2008-11-01

    In the food safety arena, the decision-making process can be especially difficult. Decision makers are often faced with social and fiscal pressures when attempting to identify an appropriate balance among several choices. Concurrently, policy and decision makers in microbial food safety are under increasing pressure to demonstrate that their policies and decisions are made using transparent and accountable processes. In this article, we present a multi-criteria decision analysis approach that can be used to address the problem of trying to select a food safety intervention while balancing various criteria. Criteria that are important when selecting an intervention were determined, as a result of an expert consultation, to include effectiveness, cost, weight of evidence, and practicality associated with the interventions. The multi-criteria decision analysis approach we present is able to consider these criteria and arrive at a ranking of interventions. It can also provide a clear justification for the ranking as well as demonstrate to stakeholders, through a scenario analysis approach, how to potentially converge toward common ground. While this article focuses on the problem of selecting food safety interventions, the range of applications in the food safety arena is truly diverse and can be a significant tool in assisting decisions that need to be coherent, transparent, and justifiable. Most importantly, it is a significant contributor when there is a need to strike a fine balance between various potentially competing alternatives and/or stakeholder groups.

  8. Application of decision tree on land suitability analysis

    NASA Astrophysics Data System (ADS)

    Hou, Yajuan; Liu, Yaolin; Ren, Zhouqiao

    2008-12-01

    With increasing volume of data in modern science, there has been a rapid expansion of interests and researches on data mining, which is an increasingly popular tool in data analysis to obtain implicit knowledge. Decision Tree (DT), as one of widespread used classification approaches in data mining, is used successfully in many diverse areas. This paper attempts to show how to apply Decision Tree on land suitability analysis and make some conclusions for its application. Firstly, the approach of application of DT on Land Suitability and the popular learning algorithm is discussed. Then 3 towns' land units in Hainan province are selected as study case to demonstrate our approach by C4.5 implemented using C++ language, and the obtained results are compared to the results in the literature and are checked by random sample investigation. The major conclusion is that DT is suitable for land suitability analysis, by which a high veracity result can be obtained, and the obtained classifying knowledge is readable and can be interpreted well. In some sense, it can adjust knowledge by updated training dataset naturally and avoid the highly dependence with experience.

  9. Using activity-based costing to guide strategic decision making.

    PubMed

    Dowless, R M

    1997-06-01

    Activity-based costing (ABC) is not widely used in the healthcare industry. Some healthcare provider organizations are considering ABC, however, because of its potential to improve resource management and thereby maximize efficiency. ABC supports better pricing practices through more accurate costing and can be used to identify underutilized resources as well as associated costs that can be reduced. ABC can be a useful tool for determining the cost of unused capacity and for making strategic management decisions that will reduce costs. PMID:10167847

  10. Decerns: A framework for multi-criteria decision analysis

    SciTech Connect

    Yatsalo, Boris; Didenko, Vladimir; Gritsyuk, Sergey; Sullivan, Terry

    2015-02-27

    A new framework, Decerns, for multicriteria decision analysis (MCDA) of a wide range of practical problems on risk management is introduced. Decerns framework contains a library of modules that are the basis for two scalable systems: DecernsMCDA for analysis of multicriteria problems, and DecernsSDSS for multicriteria analysis of spatial options. DecernsMCDA includes well known MCDA methods and original methods for uncertainty treatment based on probabilistic approaches and fuzzy numbers. As a result, these MCDA methods are described along with a case study on analysis of multicriteria location problem.

  11. Decision Analysis and Its Application to the Frequency of Containment Integrated Leakage Rate Tests

    SciTech Connect

    Apostolakis, George E.; Koser, John P.; Sato, Gaku

    2004-05-15

    For nuclear utilities to become competitive in a deregulated electricity market, costs must be reduced, safety must be maintained, and interested stakeholders must remain content with the decisions being made. One way to reduce costs is to reduce the frequency of preventive maintenance and testing. However, these changes must be weighed against their impact on safety and stakeholder relations. We present a methodology that allows the evaluation of decision options using a number of objectives that include safety, economics, and stakeholder relations. First, the candidate decision options are screened to make sure that they satisfy the relevant regulatory requirements. The remaining options are evaluated using multiattribute utility theory. The results of the formal analysis include a ranking of the options according to their desirability as well as the major reasons that explain this ranking. These results are submitted to a deliberative process in which the decision makers scrutinize the results to ensure that they are meaningful. During the deliberation, new decision options may be formulated based on the insights that the formal analysis provides, as happened in the case study of this paper. This case study deals with the reduction in frequency of the containment integrated leak rate test of a boiling water reactor.

  12. Knowledge-based decision support for patient monitoring in cardioanesthesia.

    PubMed

    Schecke, T; Langen, M; Popp, H J; Rau, G; Käsmacher, H; Kalff, G

    1992-01-01

    An approach to generating 'intelligent alarms' is presented that aggregates many information items, i.e. measured vital signs, recent medications, etc., into state variables that more directly reflect the patient's physiological state. Based on these state variables the described decision support system AES-2 also provides therapy recommendations. The assessment of the state variables and the generation of therapeutic advice follow a knowledge-based approach. Aspects of uncertainty, e.g. a gradual transition between 'normal' and 'below normal', are considered applying a fuzzy set approach. Special emphasis is laid on the ergonomic design of the user interface, which is based on color graphics and finger touch input on the screen. Certain simulation techniques considerably support the design process of AES-2 as is demonstrated with a typical example from cardioanesthesia. PMID:1402299

  13. Artificial intelligence based decision support for trumpeter swan management

    USGS Publications Warehouse

    Sojda, Richard S.

    2002-01-01

    The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988

  14. Composite tissue allotransplantation of the face: Decision analysis model

    PubMed Central

    Cugno, Sabrina; Sprague, Sheila; Duku, Eric; Thoma, Achilleas

    2007-01-01

    BACKGROUND: Facial composite tissue allotransplantation is a potential reconstructive option for severe facial disfigurement. The purpose of the present investigation was to use decision analysis modelling to ascertain the expected quality-adjusted life years (QALYs) gained with face transplantation (versus remaining in a disfigured state) in an effort to assist surgeons with the decision of whether to adopt this procedure. STUDY DESIGN: The probabilities of potential complications associated with facial allotransplantation were identified by a comprehensive review of kidney and hand transplant literature. A decision analysis tree illustrating possible health states for face allotransplantation was then constructed. Utilities were obtained from 30 participants, using the standard gamble and time trade-off measures. The utilities were then translated into QALYs, and the expected QALYs gained with transplantation were computed. RESULTS: Severe facial deformity was associated with an average of 7.34 QALYs. Allotransplantation of the face imparted an expected gain in QALYs of between 16.2 and 27.3 years. CONCLUSIONS: The current debate within the medical community surrounding facial composite tissue allotransplantation has centred on the issue of inducing a state of immunocompromise in a physically healthy individual for a non-life-saving procedure. However, the latter must be weighed against the potential social and psychological benefits that transplantation would confer. As demonstrated by a gain of 26.9 QALYs, participants’ valuation of quality of life is notably greater for face transplantation with its side effects of immunosuppression than for a state of uncompromised physical health with severe facial disfigurement. PMID:19554146

  15. Developing shape analysis tools to assist complex spatial decision making

    SciTech Connect

    Mackey, H.E.; Ehler, G.B.; Cowen, D.

    1996-05-31

    The objective of this research was to develop and implement a shape identification measure within a geographic information system, specifically one that incorporates analytical modeling for site location planning. The application that was developed incorporated a location model within a raster-based GIS, which helped address critical performance issues for the decision support system. Binary matrices, which approximate the object`s geometrical form, are passed over the grided data structure and allow identification of irregular and regularly shaped objects. Lastly, the issue of shape rotation is addressed and is resolved by constructing unique matrices corresponding to the object`s orientation

  16. Spatially explicit multi-criteria decision analysis for managing vector-borne diseases.

    PubMed

    Hongoh, Valerie; Hoen, Anne Gatewood; Aenishaenslin, Cécile; Waaub, Jean-Philippe; Bélanger, Denise; Michel, Pascal

    2011-12-29

    The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular.

  17. Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

    PubMed Central

    2011-01-01

    The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular

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

    PubMed Central

    Lee, Wen-Chung; Wu, Yun-Chun

    2016-01-01

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

  19. Using multi-criteria decision analysis to assess the vulnerability of drinking water utilities.

    PubMed

    Joerin, Florent; Cool, Geneviève; Rodriguez, Manuel J; Gignac, Marc; Bouchard, Christian

    2010-07-01

    Outbreaks of microbiological waterborne disease have increased governmental concern regarding the importance of drinking water safety. Considering the multi-barrier approach to safe drinking water may improve management decisions to reduce contamination risks. However, the application of this approach must consider numerous and diverse kinds of information simultaneously. This makes it difficult for authorities to apply the approach to decision making. For this reason, multi-criteria decision analysis can be helpful in applying the multi-barrier approach to vulnerability assessment. The goal of this study is to propose an approach based on a multi-criteria analysis method in order to rank drinking water systems (DWUs) based on their vulnerability to microbiological contamination. This approach is illustrated with an application carried out on 28 DWUs supplied by groundwater in the Province of Québec, Canada. The multi-criteria analysis method chosen is measuring attractiveness by a categorical based evaluation technique methodology allowing the assessment of a microbiological vulnerability indicator (MVI) for each DWU. Results are presented on a scale ranking DWUs from less vulnerable to most vulnerable to contamination. MVI results are tested using a sensitivity analysis on barrier weights and they are also compared with historical data on contamination at the utilities. The investigation demonstrates that MVI provides a good representation of the vulnerability of DWUs to microbiological contamination.

  20. Query-handling in MLM-based decision support systems.

    PubMed

    Arkad, K; Gao, X M; Ahlfeldt, H

    1995-01-01

    Arden Syntax for Medical Logic Modules is a standard specification for creation and sharing of knowledge bases. The standard specification focuses on knowledge that can be represented as a set of independent Medical Logic Modules (MLMs) such as rules, formulas and protocols. The basic functions of an MLM are to retrieve patient data, manipulate the data, come to some decision, and possibly perform an action. All connections to the world outside an MLM are collected in the data-slot of the MLM. The institution specific parts of these connections are inside the notation of curly brackets ([]) to facilitate sharing of MLM between institutions. This paper focuses on some of the problems that occur in relation to Arden Syntax and connections to a patient database such as database queries. Problems related to possibilities of moving one or several module(s) are also discussed, with emphasis on database connections. As an example, an MLM based Decision Support System (DSS) developed at Linköping University is described. PMID:8882561

  1. Ontology-based diagnostic decision support in radiology.

    PubMed

    Kahn, Charles E

    2014-01-01

    The Radiology Gamuts Ontology (RGO) is a knowledge model of diseases, interventions, and imaging manifestations. RGO incorporates 16,822 terms with their synonyms and abbreviations and 55,393 relationships between terms. Subsumption defines the relationship between more general and more specific terms; causality relates disorders and their imaging manifestations. We explored the application of the RGO to build an interactive decision support system for radiological diagnosis. The Gamuts DDx system was created to apply the RGO's knowledge: it identifies a list of potential diagnoses in response to one or more user-specified imaging observations. The system also identifies a set of observations that allow one to narrow the diagnosis, and dynamically narrows or expands the list of diagnoses as imaging findings are selected or deselected. The functionality has been implemented as a web-based user interface and as a web service. The current work demonstrates the feasibility of exploiting the RGO's causal knowledge to provide interactive decision support for diagnosis of imaging findings. Ongoing efforts include the further development of the system's knowledge base and evaluation of the system in clinical use. PMID:25160149

  2. Ontology-based diagnostic decision support in radiology.

    PubMed

    Kahn, Charles E

    2014-01-01

    The Radiology Gamuts Ontology (RGO) is a knowledge model of diseases, interventions, and imaging manifestations. RGO incorporates 16,822 terms with their synonyms and abbreviations and 55,393 relationships between terms. Subsumption defines the relationship between more general and more specific terms; causality relates disorders and their imaging manifestations. We explored the application of the RGO to build an interactive decision support system for radiological diagnosis. The Gamuts DDx system was created to apply the RGO's knowledge: it identifies a list of potential diagnoses in response to one or more user-specified imaging observations. The system also identifies a set of observations that allow one to narrow the diagnosis, and dynamically narrows or expands the list of diagnoses as imaging findings are selected or deselected. The functionality has been implemented as a web-based user interface and as a web service. The current work demonstrates the feasibility of exploiting the RGO's causal knowledge to provide interactive decision support for diagnosis of imaging findings. Ongoing efforts include the further development of the system's knowledge base and evaluation of the system in clinical use.

  3. Spaceborne power systems preference analyses. Volume 2: Decision analysis

    NASA Technical Reports Server (NTRS)

    Smith, J. H.; Feinberg, A.; Miles, R. F., Jr.

    1985-01-01

    Sixteen alternative spaceborne nuclear power system concepts were ranked using multiattribute decision analysis. The purpose of the ranking was to identify promising concepts for further technology development and the issues associated with such development. Four groups were interviewed to obtain preference. The four groups were: safety, systems definition and design, technology assessment, and mission analysis. The highest ranked systems were the heat-pipe thermoelectric systems, heat-pipe Stirling, in-core thermionic, and liquid-metal thermoelectric systems. The next group contained the liquid-metal Stirling, heat-pipe Alkali Metal Thermoelectric Converter (AMTEC), heat-pipe Brayton, liquid-metal out-of-core thermionic, and heat-pipe Rankine systems. The least preferred systems were the liquid-metal AMTEC, heat-pipe thermophotovoltaic, liquid-metal Brayton and Rankine, and gas-cooled Brayton. The three nonheat-pipe technologies selected matched the top three nonheat-pipe systems ranked by this study.

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

    NASA Astrophysics Data System (ADS)

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

    2011-07-01

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

  5. Applications of decision analysis and related techniques to industrial engineering problems at KSC

    NASA Technical Reports Server (NTRS)

    Evans, Gerald W.

    1995-01-01

    This report provides: (1) a discussion of the origination of decision analysis problems (well-structured problems) from ill-structured problems; (2) a review of the various methodologies and software packages for decision analysis and related problem areas; (3) a discussion of how the characteristics of a decision analysis problem affect the choice of modeling methodologies, thus providing a guide as to when to choose a particular methodology; and (4) examples of applications of decision analysis to particular problems encountered by the IE Group at KSC. With respect to the specific applications at KSC, particular emphasis is placed on the use of the Demos software package (Lumina Decision Systems, 1993).

  6. Evidence-based decision-making 1: Critical appraisal.

    PubMed

    Twells, Laurie K

    2015-01-01

    This chapter provides an introduction to the concept of Evidence-based Medicine (EBM) including its history, rooted in Canada and its important role in modern medicine. The chapter both defines EBM and explains the process of conducting EBM. It includes a discussion of the hierarchy of evidence that exists with reference to common methods used to assess the levels of quality inherent in study designs. The focus of the chapter is on how to critically appraise the medical literature, as one step in the EBM process. Critical appraisal requires an understanding of the strengths and weaknesses of study design and how these in turn impact the validity and applicability of research findings. Strong critical appraisal skills are critical to evidence-based decision-making.

  7. A Framework for Decision Support Systems Based on Zachman Framework

    NASA Astrophysics Data System (ADS)

    Ostadzadeh, S. Shervin; Habibi, Jafar; Ostadzadeh, S. Arash

    Recent challenges have brought about an inevitable tendency for enterprises to lunge towards organizing their information activities in a comprehensive way. In this respect, Enterprise Architecture (EA) has proven to be the leading option for development and maintenance of information systems. EA clearly provides a thorough outline of the whole information system comprising an enterprise. To establish such an outline, a logical framework needs to be laid upon the entire information system. Zachman framework (ZF) has been widely accepted as a standard scheme for identifying and organizing descriptive representations that have critical roles in enterprise management and system development. In this paper, we propose a framework based on ZF for Decision Support Systems (DSS). Furthermore, a modeling approach based on Model-Driven Architecture (MDA) is utilized to obtain compatible models for all cells in the framework. The efficiency of the proposed framework is examined through a case study.

  8. 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

  9. Visual Cluster Analysis in Support of Clinical Decision Intelligence

    PubMed Central

    Gotz, David; Sun, Jimeng; Cao, Nan; Ebadollahi, Shahram

    2011-01-01

    Electronic health records (EHRs) contain a wealth of information about patients. In addition to providing efficient and accurate records for individual patients, large databases of EHRs contain valuable information about overall patient populations. While statistical insights describing an overall population are beneficial, they are often not specific enough to use as the basis for individualized patient-centric decisions. To address this challenge, we describe an approach based on patient similarity which analyzes an EHR database to extract a cohort of patient records most similar to a specific target patient. Clusters of similar patients are then visualized to allow interactive visual refinement by human experts. Statistics are then extracted from the refined patient clusters and displayed to users. The statistical insights taken from these refined clusters provide personalized guidance for complex decisions. This paper focuses on the cluster refinement stage where an expert user must interactively (a) judge the quality and contents of automatically generated similar patient clusters, and (b) refine the clusters based on his/her expertise. We describe the DICON visualization tool which allows users to interactively view and refine multidimensional similar patient clusters. We also present results from a preliminary evaluation where two medical doctors provided feedback on our approach. PMID:22195102

  10. Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management.

    PubMed

    Convertino, Matteo; Valverde, L James

    2013-01-01

    Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA) framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA) that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the needs of

  11. Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management

    PubMed Central

    Convertino, Matteo; Valverde, L. James

    2013-01-01

    Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA) framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA) that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the needs of

  12. Grey situation group decision-making method based on prospect theory.

    PubMed

    Zhang, Na; Fang, Zhigeng; Liu, Xiaqing

    2014-01-01

    This paper puts forward a grey situation group decision-making method on the basis of prospect theory, in view of the grey situation group decision-making problems that decisions are often made by multiple decision experts and those experts have risk preferences. The method takes the positive and negative ideal situation distance as reference points, defines positive and negative prospect value function, and introduces decision experts' risk preference into grey situation decision-making to make the final decision be more in line with decision experts' psychological behavior. Based on TOPSIS method, this paper determines the weight of each decision expert, sets up comprehensive prospect value matrix for decision experts' evaluation, and finally determines the optimal situation. At last, this paper verifies the effectiveness and feasibility of the method by means of a specific example.

  13. Grey Situation Group Decision-Making Method Based on Prospect Theory

    PubMed Central

    Zhang, Na; Fang, Zhigeng; Liu, Xiaqing

    2014-01-01

    This paper puts forward a grey situation group decision-making method on the basis of prospect theory, in view of the grey situation group decision-making problems that decisions are often made by multiple decision experts and those experts have risk preferences. The method takes the positive and negative ideal situation distance as reference points, defines positive and negative prospect value function, and introduces decision experts' risk preference into grey situation decision-making to make the final decision be more in line with decision experts' psychological behavior. Based on TOPSIS method, this paper determines the weight of each decision expert, sets up comprehensive prospect value matrix for decision experts' evaluation, and finally determines the optimal situation. At last, this paper verifies the effectiveness and feasibility of the method by means of a specific example. PMID:25197706

  14. 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.

  15. Vascular access choice in incident hemodialysis patients: a decision analysis.

    PubMed

    Drew, David A; Lok, Charmaine E; Cohen, Joshua T; Wagner, Martin; Tangri, Navdeep; Weiner, Daniel E

    2015-01-01

    Hemodialysis vascular access recommendations promote arteriovenous (AV) fistulas first; however, it may not be the best approach for all hemodialysis patients, because likelihood of successful fistula placement, procedure-related and subsequent costs, and patient survival modify the optimal access choice. We performed a decision analysis evaluating AV fistula, AV graft, and central venous catheter (CVC) strategies for patients initiating hemodialysis with a CVC, a scenario occurring in over 70% of United States dialysis patients. A decision tree model was constructed to reflect progression from hemodialysis initiation. Patients were classified into one of three vascular access choices: maintain CVC, attempt fistula, or attempt graft. We explicitly modeled probabilities of primary and secondary patency for each access type, with success modified by age, sex, and diabetes. Access-specific mortality was incorporated using preexisting cohort data, including terms for age, sex, and diabetes. Costs were ascertained from the 2010 USRDS report and Medicare for procedure costs. An AV fistula attempt strategy was found to be superior to AV grafts and CVCs in regard to mortality and cost for the majority of patient characteristic combinations, especially younger men without diabetes. Women with diabetes and elderly men with diabetes had similar outcomes, regardless of access type. Overall, the advantages of an AV fistula attempt strategy lessened considerably among older patients, particularly women with diabetes, reflecting the effect of lower AV fistula success rates and lower life expectancy. These results suggest that vascular access-related outcomes may be optimized by considering individual patient characteristics.

  16. Helping patients make choices about breast reconstruction: a decision analysis approach.

    PubMed

    Sun, Clement S; Cantor, Scott B; Reece, Gregory P; Fingeret, Michelle C; Crosby, Melissa A; Markey, Mia K

    2014-10-01

    Decision analysis can help breast reconstruction patients and their surgeons to methodically evaluate clinical alternatives and make hard decisions. The purpose of this article is to help plastic surgeons guide patients in making decisions though a case study in breast reconstruction. By making good decisions, patient outcomes may be improved. This article aims to illustrate decision analysis techniques from the patient perspective, with an emphasis on her values and preferences. The authors introduce normative decision-making through a fictional breast reconstruction patient and systematically build the decision basis to help her make a good decision. The authors broadly identify alternatives of breast reconstruction, propose types of outcomes that the patient should consider, discuss sources of probabilistic information and outcome values, and demonstrate how to make a good decision. The concepts presented here may be extended to other shared decision-making problems in plastic and reconstructive surgery. In addition, the authors discuss how sensitivity analysis may test the robustness of the decision and how to evaluate the quality of decisions. The authors also present tools to help implement these concepts in practice. Finally, the authors examine limitations that hamper adoption of patient decision analysis in reconstructive surgery and health care in general. In particular, the authors emphasize the need for routine collection of quality-of-life information, out-of-pocket expense, and recovery time.

  17. On the origins and development of evidence-based medicine and medical decision making.

    PubMed

    Elstein, A S

    2004-08-01

    The aims of this paper are to identify the issues and forces that were the impetus for two recent developments in academic medicine, evidence-based medicine (EBM) and medical decision making (MDM); to make explicit their underlying similarities and differences; and to relate them to the fates of these innovations. Both developments respond to concerns about practice variation; the rapid growth of medical technology, leading to a proliferation of diagnostic and treatment options; the patient empowerment movement; and psychological research that raised questions about the quality of human judgment and decision making. Their commonalities include: use of Bayesian principles in diagnostic reasoning, and the common structure embedded in an answerable clinical question and a decision tree. Major differences include: emphasis on knowledge or judgment as the fundamental problem; the status of formal models and utility assessment; and the spirit and tone of the innovation. These differences have led to broader acceptance of EBM within academic medicine, while decision analysis, the fundamental tool of MDM, has been less welcomed in clinical circles and has found its place in guideline development, cost-effectiveness analysis, and health policy.

  18. School Board Decision Making: An Analysis of the Process

    ERIC Educational Resources Information Center

    Crum, Karen S.

    2007-01-01

    The goal of this study was to analyze the characteristics in the school board decision-making process and to discover whether school board members are aware of the characteristics surrounding the school board's decision-making process. Specifically, this study examines the decision-making process of a school board in Virginia, and it provides…

  19. An analysis of soil arsenic records of decision.

    PubMed

    Davis, A; Sherwin, D; Ditmars, R; Hoenke, K A

    2001-06-15

    In 1986 the US EPA created the National Priority List (NPL) that now comprises in excess of 2,000 sites nationwide, with arsenic the second most common inorganic constituent. A survey of 69 Records of Decision (RODs) written between 1985 and 1998 for which arsenic was a major driver found that 84% of cleanup goals were risk-driven and 16% were background-driven, with a wide range of soil-arsenic cleanup standards for 10(-6) residential risk goals (2-305 mg/kg). In comparison, the range of background-based cleanup goals was much narrower (8-21 mg/kg). ROD soil arsenic concentrations exhibit no statistically significanttemporal trend, but on a geographic basis, EPA Regions 6, 8, 9, and 10 had some of the higher decisions. The risk assessment process is important in defining cleanup goals; however routine use of site-specific variables (i.e., bioavailability, realistic tenure in both residential and occupational settings, natural attenuation of arsenic in groundwater, etc.) is necessary to ensure an accurate assessment of potential site risks and to preclude over-remediation that may result from the use of default risk variables.

  20. Decision Manifold Approximation for Physics-Based Simulations

    NASA Technical Reports Server (NTRS)

    Wong, Jay Ming; Samareh, Jamshid A.

    2016-01-01

    With the recent surge of success in big-data driven deep learning problems, many of these frameworks focus on the notion of architecture design and utilizing massive databases. However, in some scenarios massive sets of data may be difficult, and in some cases infeasible, to acquire. In this paper we discuss a trajectory-based framework that quickly learns the underlying decision manifold of binary simulation classifications while judiciously selecting exploratory target states to minimize the number of required simulations. Furthermore, we draw particular attention to the simulation prediction application idealized to the case where failures in simulations can be predicted and avoided, providing machine intelligence to novice analysts. We demonstrate this framework in various forms of simulations and discuss its efficacy.

  1. Transmission Bearing Damage Detection Using Decision Fusion Analysis

    NASA Technical Reports Server (NTRS)

    Dempsey, Paula J.; Lewicki, David G.; Decker, Harry J.

    2004-01-01

    A diagnostic tool was developed for detecting fatigue damage to rolling element bearings in an OH-58 main rotor transmission. Two different monitoring technologies, oil debris analysis and vibration, were integrated using data fusion into a health monitoring system for detecting bearing surface fatigue pitting damage. This integrated system showed improved detection and decision-making capabilities as compared to using individual monitoring technologies. This diagnostic tool was evaluated by collecting vibration and oil debris data from tests performed in the NASA Glenn 500 hp Helicopter Transmission Test Stand. Data was collected during experiments performed in this test rig when two unanticipated bearing failures occurred. Results show that combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spiral bevel gears duplex ball bearings and spiral bevel pinion triplex ball bearings in a main rotor transmission.

  2. Spiral Bevel Gear Damage Detection Using Decision Fusion Analysis

    NASA Technical Reports Server (NTRS)

    Dempsey, Paula J.; Handschuh, Robert F.; Afjeh, Abdollah A.

    2002-01-01

    A diagnostic tool for detecting damage to spiral bevel gears was developed. Two different monitoring technologies, oil debris analysis and vibration, were integrated using data fusion into a health monitoring system for detecting surface fatigue pitting damage on gears. This integrated system showed improved detection and decision-making capabilities as compared to using individual monitoring technologies. This diagnostic tool was evaluated by collecting vibration and oil debris data from fatigue tests performed in the NASA Glenn Spiral Bevel Gear Fatigue Rigs. Data was collected during experiments performed in this test rig when pitting damage occurred. Results show that combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spiral bevel gears.

  3. The Potential for Meta-Analysis to Support Decision Analysis in Ecology

    ERIC Educational Resources Information Center

    Mengersen, Kerrie; MacNeil, M. Aaron; Caley, M. Julian

    2015-01-01

    Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable…

  4. [A tooth or an implant--literature based decision making].

    PubMed

    Bar On, H; Sharon, E; Lipovezky-Adler, M; Haramaty, O; Smidt, A

    2014-07-01

    The common use of dental implants in the daily practice led to a profound change in the available treatment strategies. The option of replacing a diagnosed doubtful tooth with an implant has become widely accepted and often used. The prognosis systems in use today are based on the three major disciplines: endodontics, periodontics and prosthodontics. Combining these three may impair and bias the decision making process and increase the tendency to base it on subjective clinical experience and personal preference. Reading and reviewing the relevant literature gives no clear tool for use. Root canal treatment is considered a highly predictable treatment procedure and a treated tooth is affected mainly by the quality and type of the fabricated restoration and the risk of caries. Periodontal treatment followed by a suitable maintenance regimen will likely allow long term tooth survival. When comparing the success rates of natural teeth rehabilitation versus implant supported restorations, it appears that with implants an additional treatment is demanded along the years. This coincides with the fact that to date there is no consensus regarding the extent of perimplantitis and perimucositis that is to be expected around a restored implant. In addition, a peri implant tissue problem or a failure of a dental implant may prove to be more challenging than a failure of a tooth. It is important to remember that a dental implant is made to substitute a missing tooth and it is a treatment modality with known and clear indications for rehabilitation of an edentulous space. The aim of this paper is to review and discuss the various aspects of whether to maintain a compromised or a doubtful tooth or to prefer a treatment modality using dental implants. In conclusion it is advised here, to incorporate the discussed issues in the decision making process towards the most suitable treatment plan. PMID:25219096

  5. A Decision Analytic Approach to Exposure-Based Chemical Prioritization

    PubMed Central

    Mitchell, Jade; Pabon, Nicolas; Collier, Zachary A.; Egeghy, Peter P.; Cohen-Hubal, Elaine; Linkov, Igor; Vallero, Daniel A.

    2013-01-01

    The manufacture of novel synthetic chemicals has increased in volume and variety, but often the environmental and health risks are not fully understood in terms of toxicity and, in particular, exposure. While efforts to assess risks have generally been effective when sufficient data are available, the hazard and exposure data necessary to assess risks adequately are unavailable for the vast majority of chemicals in commerce. The US Environmental Protection Agency has initiated the ExpoCast Program to develop tools for rapid chemical evaluation based on potential for exposure. In this context, a model is presented in which chemicals are evaluated based on inherent chemical properties and behaviorally-based usage characteristics over the chemical’s life cycle. These criteria are assessed and integrated within a decision analytic framework, facilitating rapid assessment and prioritization for future targeted testing and systems modeling. A case study outlines the prioritization process using 51 chemicals. The results show a preliminary relative ranking of chemicals based on exposure potential. The strength of this approach is the ability to integrate relevant statistical and mechanistic data with expert judgment, allowing for an initial tier assessment that can further inform targeted testing and risk management strategies. PMID:23940664

  6. An Agent-Based Model of Farmer Decision Making in Jordan

    NASA Astrophysics Data System (ADS)

    Selby, Philip; Medellin-Azuara, Josue; Harou, Julien; Klassert, Christian; Yoon, Jim

    2016-04-01

    We describe an agent based hydro-economic model of groundwater irrigated agriculture in the Jordan Highlands. The model employs a Multi-Agent-Simulation (MAS) framework and is designed to evaluate direct and indirect outcomes of climate change scenarios and policy interventions on farmer decision making, including annual land use, groundwater use for irrigation, and water sales to a water tanker market. Land use and water use decisions are simulated for groups of farms grouped by location and their behavioural and economic similarities. Decreasing groundwater levels, and the associated increase in pumping costs, are important drivers for change within Jordan'S agricultural sector. We describe how this is considered by coupling of agricultural and groundwater models. The agricultural production model employs Positive Mathematical Programming (PMP), a method for calibrating agricultural production functions to observed planted areas. PMP has successfully been used with disaggregate models for policy analysis. We adapt the PMP approach to allow explicit evaluation of the impact of pumping costs, groundwater purchase fees and a water tanker market. The work demonstrates the applicability of agent-based agricultural decision making assessment in the Jordan Highlands and its integration with agricultural model calibration methods. The proposed approach is designed and implemented with software such that it could be used to evaluate a variety of physical and human influences on decision making in agricultural water management.

  7. Devaluation and sequential decisions: linking goal-directed and model-based behavior.

    PubMed

    Friedel, Eva; Koch, Stefan P; Wendt, Jean; Heinz, Andreas; Deserno, Lorenz; Schlagenhauf, Florian

    2014-01-01

    In experimental psychology different experiments have been developed to assess goal-directed as compared to habitual control over instrumental decisions. Similar to animal studies selective devaluation procedures have been used. More recently sequential decision-making tasks have been designed to assess the degree of goal-directed vs. habitual choice behavior in terms of an influential computational theory of model-based compared to model-free behavioral control. As recently suggested, different measurements are thought to reflect the same construct. Yet, there has been no attempt to directly assess the construct validity of these different measurements. In the present study, we used a devaluation paradigm and a sequential decision-making task to address this question of construct validity in a sample of 18 healthy male human participants. Correlational analysis revealed a positive association between model-based choices during sequential decisions and goal-directed behavior after devaluation suggesting a single framework underlying both operationalizations and speaking in favor of construct validity of both measurement approaches. Up to now, this has been merely assumed but never been directly tested in humans.

  8. Devaluation and sequential decisions: linking goal-directed and model-based behavior.

    PubMed

    Friedel, Eva; Koch, Stefan P; Wendt, Jean; Heinz, Andreas; Deserno, Lorenz; Schlagenhauf, Florian

    2014-01-01

    In experimental psychology different experiments have been developed to assess goal-directed as compared to habitual control over instrumental decisions. Similar to animal studies selective devaluation procedures have been used. More recently sequential decision-making tasks have been designed to assess the degree of goal-directed vs. habitual choice behavior in terms of an influential computational theory of model-based compared to model-free behavioral control. As recently suggested, different measurements are thought to reflect the same construct. Yet, there has been no attempt to directly assess the construct validity of these different measurements. In the present study, we used a devaluation paradigm and a sequential decision-making task to address this question of construct validity in a sample of 18 healthy male human participants. Correlational analysis revealed a positive association between model-based choices during sequential decisions and goal-directed behavior after devaluation suggesting a single framework underlying both operationalizations and speaking in favor of construct validity of both measurement approaches. Up to now, this has been merely assumed but never been directly tested in humans. PMID:25136310

  9. Disease Control through Voluntary Vaccination Decisions Based on the Smoothed Best Response

    PubMed Central

    Xu, Fei; Cressman, Ross

    2014-01-01

    We investigate game-theory based decisions on vaccination uptake and its effects on the spread of an epidemic with nonlinear incidence rate. It is assumed that each individual's decision approximates his/her best response (called smoothed best response) in that this person chooses to take the vaccine based on its cost-benefit analysis. The basic reproduction number of the resultant epidemic model is calculated and used to characterize the existence and stability of the disease-free and endemic equilibria of the model. The effects on the spread and control of the epidemic are revealed in terms of the sensitivity of the response to changes in costs and benefits, in the “cost” of the vaccination, and in the proportion of susceptible individuals who are faced with the decision of whether or not to be vaccinated per unit time. The effects of the best response decision rule are also analyzed and compared to those of the smoothed best response. Our study shows that, when there is a perceived cost to take the vaccine, the smoothed best response is more effective in controlling the epidemic. However, when this cost is 0, the best response is the more efficient control. PMID:24693329

  10. Spatial query for decision support of cross-country movement. [in image-based geographic information system

    NASA Technical Reports Server (NTRS)

    Hepner, George F.; Logan, Thomas L.; Bryant, Nevin A.

    1988-01-01

    The use of a query language processor for decision support of cross-country movement in an image-based geographic information system is evaluated. It is found that query processing yields results which are comparable to those obtained using conventional cross-country movement techniques and analysis. Query processing also provides a flexibility of information extraction, rapid display, and flexible decision support in time-critical, limited data situations.

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

    PubMed

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

    2010-10-15

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

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

    PubMed

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

    2010-10-15

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

  13. Measurement Decision Theory.

    ERIC Educational Resources Information Center

    Rudner, Lawrence M.

    This paper describes and evaluates the use of decision theory as a tool for classifying examinees based on their item response patterns. Decision theory, developed by A. Wald (1947) and now widely used in engineering, agriculture, and computing, provides a simple model for the analysis of categorical data. Measurement decision theory requires only…

  14. An index-based robust decision making framework for watershed management in a changing climate.

    PubMed

    Kim, Yeonjoo; Chung, Eun-Sung

    2014-03-01

    This study developed an index-based robust decision making framework for watershed management dealing with water quantity and quality issues in a changing climate. It consists of two parts of management alternative development and analysis. The first part for alternative development consists of six steps: 1) to understand the watershed components and process using HSPF model, 2) to identify the spatial vulnerability ranking using two indices: potential streamflow depletion (PSD) and potential water quality deterioration (PWQD), 3) to quantify the residents' preferences on water management demands and calculate the watershed evaluation index which is the weighted combinations of PSD and PWQD, 4) to set the quantitative targets for water quantity and quality, 5) to develop a list of feasible alternatives and 6) to eliminate the unacceptable alternatives. The second part for alternative analysis has three steps: 7) to analyze all selected alternatives with a hydrologic simulation model considering various climate change scenarios, 8) to quantify the alternative evaluation index including social and hydrologic criteria with utilizing multi-criteria decision analysis methods and 9) to prioritize all options based on a minimax regret strategy for robust decision. This framework considers the uncertainty inherent in climate models and climate change scenarios with utilizing the minimax regret strategy, a decision making strategy under deep uncertainty and thus this procedure derives the robust prioritization based on the multiple utilities of alternatives from various scenarios. In this study, the proposed procedure was applied to the Korean urban watershed, which has suffered from streamflow depletion and water quality deterioration. Our application shows that the framework provides a useful watershed management tool for incorporating quantitative and qualitative information into the evaluation of various policies with regard to water resource planning and management.

  15. A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.

    PubMed

    Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

    2015-01-01

    Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks. PMID:26610496

  16. A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality

    PubMed Central

    Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

    2015-01-01

    Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks. PMID:26610496

  17. Risk-based decision-making framework for the selection of sediment dredging option.

    PubMed

    Manap, Norpadzlihatun; Voulvoulis, Nikolaos

    2014-10-15

    The aim of this study was to develop a risk-based decision-making framework for the selection of sediment dredging option. Descriptions using case studies of the newly integrated, holistic and staged framework were followed. The first stage utilized the historical dredging monitoring data and the contamination level in media data into Ecological Risk Assessment phases, which have been altered for benefits in cost, time and simplicity. How Multi-Criteria Decision Analysis (MCDA) can be used to analyze and prioritize dredging areas based on environmental, socio-economic and managerial criteria was described for the next stage. The results from MCDA will be integrated into Ecological Risk Assessment to characterize the degree of contamination in the prioritized areas. The last stage was later described using these findings and analyzed using MCDA, in order to identify the best sediment dredging option, accounting for the economic, environmental and technical aspects of dredging, which is beneficial for dredging and sediment management industries.

  18. A decision surface-based taxonomy of detection statistics

    NASA Astrophysics Data System (ADS)

    Bouffard, François

    2012-09-01

    Current and past literature on the topic of detection statistics - in particular those used in hyperspectral target detection - can be intimidating for newcomers, especially given the huge number of detection tests described in the literature. Detection tests for hyperspectral measurements, such as those generated by dispersive or Fourier transform spectrometers used in remote sensing of atmospheric contaminants, are of paramount importance if any level of analysis automation is to be achieved. The detection statistics used in hyperspectral target detection are generally borrowed and adapted from other fields such as radar signal processing or acoustics. Consequently, although remarkable efforts have been made to clarify and categorize the vast number of available detection tests, understanding their differences, similarities, limits and other intricacies is still an exacting journey. Reasons for this state of affairs include heterogeneous nomenclature and mathematical notation, probably due to the multiple origins of hyperspectral target detection formalisms. Attempts at sorting out detection statistics using ambiguously defined properties may also cause more harm than good. Ultimately, a detection statistic is entirely characterized by its decision boundary. Thus, we propose to catalogue detection statistics according to the shape of their decision surfaces, which greatly simplifies this taxonomy exercise. We make a distinction between the topology resulting from the mathematical formulation of the statistic and mere parameters that adjust the boundary's precise shape, position and orientation. Using this simple approach, similarities between various common detection statistics are found, limit cases are reduced to simpler statistics, and a general understanding of the available detection tests and their properties becomes much easier to achieve.

  19. Rationality versus reality: the challenges of evidence-based decision making for health policy makers

    PubMed Central

    2010-01-01

    Background Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. Discussion We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. Summary In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the

  20. System and method for integrating hazard-based decision making tools and processes

    DOEpatents

    Hodgin, C. Reed

    2012-03-20

    A system and method for inputting, analyzing, and disseminating information necessary for identified decision-makers to respond to emergency situations. This system and method provides consistency and integration among multiple groups, and may be used for both initial consequence-based decisions and follow-on consequence-based decisions. The system and method in a preferred embodiment also provides tools for accessing and manipulating information that are appropriate for each decision-maker, in order to achieve more reasoned and timely consequence-based decisions. The invention includes processes for designing and implementing a system or method for responding to emergency situations.

  1. Decision-theoretic analysis of forensic sampling criteria using bayesian decision networks.

    PubMed

    Biedermann, A; Bozza, S; Garbolino, P; Taroni, F

    2012-11-30

    Sampling issues represent a topic of ongoing interest to the forensic science community essentially because of their crucial role in laboratory planning and working protocols. For this purpose, forensic literature described thorough (bayesian) probabilistic sampling approaches. These are now widely implemented in practice. They allow, for instance, to obtain probability statements that parameters of interest (e.g., the proportion of a seizure of items that present particular features, such as an illegal substance) satisfy particular criteria (e.g., a threshold or an otherwise limiting value). Currently, there are many approaches that allow one to derive probability statements relating to a population proportion, but questions on how a forensic decision maker--typically a client of a forensic examination or a scientist acting on behalf of a client--ought actually to decide about a proportion or a sample size, remained largely unexplored to date. The research presented here intends to address methodology from decision theory that may help to cope usefully with the wide range of sampling issues typically encountered in forensic science applications. The procedures explored in this paper enable scientists to address a variety of concepts such as the (net) value of sample information, the (expected) value of sample information or the (expected) decision loss. All of these aspects directly relate to questions that are regularly encountered in casework. Besides probability theory and bayesian inference, the proposed approach requires some additional elements from decision theory that may increase the efforts needed for practical implementation. In view of this challenge, the present paper will emphasise the merits of graphical modelling concepts, such as decision trees and bayesian decision networks. These can support forensic scientists in applying the methodology in practice. How this may be achieved is illustrated with several examples. The graphical devices invoked

  2. Following Human Footsteps: Proposal of a Decision Theory Based on Human Behavior

    NASA Technical Reports Server (NTRS)

    Mahmud, Faisal

    2011-01-01

    Human behavior is a complex nature which depends on circumstances and decisions varying from time to time as well as place to place. The way a decision is made either directly or indirectly related to the availability of the options. These options though appear at random nature, have a solid directional way for decision making. In this paper, a decision theory is proposed which is based on human behavior. The theory is structured with model sets that will show the all possible combinations for making a decision, A virtual and simulated environment is considered to show the results of the proposed decision theory

  3. Contextual and conceptual content analysis in the study of foreign policy decision making

    SciTech Connect

    Schlagheck, D.M.

    1985-01-01

    This dissertation focuses upon two related questions in the study of foreign policy decision making at the individual level: (1) How does a decision maker define the situation he/she confronts. and, (2) How can the research reliably establish that definition. The problem of context and how a decision maker defines it is shown to be a common thread running throughout the foreign policy literature, brought together in a manageable form by the operational code. The operational code is used to guide the application of a new, contextual and conceptual content analysis program in a case study of Henry A. Kissinger's definition of the situations he faced in the Vietnam and arms control negotiations. Kissinger's verbal behavior is examined, including his academic writing; speeches and interviews he gave while in office; his memoirs; and, addresses he has made since leaving public service. The content analysis program (Minnesota Contextural Content Analysis, MCCA) analyzes an individual's understanding of context based on her/his choice of language, and scores verbal behavior in four context categories: pragmatic (rational), analytical, emotional, and traditional. Results of the content analysis of Kissinger's definition of the Vietnam War and arms control talks are analyzed in terms of COPDAB events data to determine whether Kissinger's verbal behavior was events dependent; results are also evaluated in terms of other psycho-biographical and operational studies of Kissinger, as well.

  4. A multicriteria decision analysis model and risk assessment framework for carbon capture and storage.

    PubMed

    Humphries Choptiany, John Michael; Pelot, Ronald

    2014-09-01

    Multicriteria decision analysis (MCDA) has been applied to various energy problems to incorporate a variety of qualitative and quantitative criteria, usually spanning environmental, social, engineering, and economic fields. MCDA and associated methods such as life-cycle assessments and cost-benefit analysis can also include risk analysis to address uncertainties in criteria estimates. One technology now being assessed to help mitigate climate change is carbon capture and storage (CCS). CCS is a new process that captures CO2 emissions from fossil-fueled power plants and injects them into geological reservoirs for storage. It presents a unique challenge to decisionmakers (DMs) due to its technical complexity, range of environmental, social, and economic impacts, variety of stakeholders, and long time spans. The authors have developed a risk assessment model using a MCDA approach for CCS decisions such as selecting between CO2 storage locations and choosing among different mitigation actions for reducing risks. The model includes uncertainty measures for several factors, utility curve representations of all variables, Monte Carlo simulation, and sensitivity analysis. This article uses a CCS scenario example to demonstrate the development and application of the model based on data derived from published articles and publicly available sources. The model allows high-level DMs to better understand project risks and the tradeoffs inherent in modern, complex energy decisions. PMID:24772997

  5. A multicriteria decision analysis model and risk assessment framework for carbon capture and storage.

    PubMed

    Humphries Choptiany, John Michael; Pelot, Ronald

    2014-09-01

    Multicriteria decision analysis (MCDA) has been applied to various energy problems to incorporate a variety of qualitative and quantitative criteria, usually spanning environmental, social, engineering, and economic fields. MCDA and associated methods such as life-cycle assessments and cost-benefit analysis can also include risk analysis to address uncertainties in criteria estimates. One technology now being assessed to help mitigate climate change is carbon capture and storage (CCS). CCS is a new process that captures CO2 emissions from fossil-fueled power plants and injects them into geological reservoirs for storage. It presents a unique challenge to decisionmakers (DMs) due to its technical complexity, range of environmental, social, and economic impacts, variety of stakeholders, and long time spans. The authors have developed a risk assessment model using a MCDA approach for CCS decisions such as selecting between CO2 storage locations and choosing among different mitigation actions for reducing risks. The model includes uncertainty measures for several factors, utility curve representations of all variables, Monte Carlo simulation, and sensitivity analysis. This article uses a CCS scenario example to demonstrate the development and application of the model based on data derived from published articles and publicly available sources. The model allows high-level DMs to better understand project risks and the tradeoffs inherent in modern, complex energy decisions.

  6. 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

  7. Hand-Based Biometric Analysis

    NASA Technical Reports Server (NTRS)

    Bebis, George

    2013-01-01

    Hand-based biometric analysis systems and techniques provide robust hand-based identification and verification. An image of a hand is obtained, which is then segmented into a palm region and separate finger regions. Acquisition of the image is performed without requiring particular orientation or placement restrictions. Segmentation is performed without the use of reference points on the images. Each segment is analyzed by calculating a set of Zernike moment descriptors for the segment. The feature parameters thus obtained are then fused and compared to stored sets of descriptors in enrollment templates to arrive at an identity decision. By using Zernike moments, and through additional manipulation, the biometric analysis is invariant to rotation, scale, or translation or an input image. Additionally, the analysis uses re-use of commonly seen terms in Zernike calculations to achieve additional efficiencies over traditional Zernike moment calculation.

  8. Hand-Based Biometric Analysis

    NASA Technical Reports Server (NTRS)

    Bebis, George (Inventor); Amayeh, Gholamreza (Inventor)

    2015-01-01

    Hand-based biometric analysis systems and techniques are described which provide robust hand-based identification and verification. An image of a hand is obtained, which is then segmented into a palm region and separate finger regions. Acquisition of the image is performed without requiring particular orientation or placement restrictions. Segmentation is performed without the use of reference points on the images. Each segment is analyzed by calculating a set of Zernike moment descriptors for the segment. The feature parameters thus obtained are then fused and compared to stored sets of descriptors in enrollment templates to arrive at an identity decision. By using Zernike moments, and through additional manipulation, the biometric analysis is invariant to rotation, scale, or translation or an in put image. Additionally, the analysis utilizes re-use of commonly-seen terms in Zernike calculations to achieve additional efficiencies over traditional Zernike moment calculation.

  9. Analysis of ETMS Data Quality for Traffic Flow Management Decisions

    NASA Technical Reports Server (NTRS)

    Chatterji, Gano B.; Sridhar, Banavar; Kim, Douglas

    2003-01-01

    The data needed for air traffic flow management decision support tools is provided by the Enhanced Traffic Management System (ETMS). This includes both the tools that are in current use and the ones being developed for future deployment. Since the quality of decision support provided by all these tools will be influenced by the quality of the input ETMS data, an assessment of ETMS data quality is needed. Motivated by this desire, ETMS data quality is examined in this paper in terms of the unavailability of flight plans, deviation from the filed flight plans, departure delays, altitude errors and track data drops. Although many of these data quality issues are not new, little is known about their extent. A goal of this paper is to document the magnitude of data quality issues supported by numerical analysis of ETMS data. Guided by this goal, ETMS data for a 24-hour period were processed to determine the number of aircraft with missing flight plan messages at any given instant of time. Results are presented for aircraft above 18,000 feet altitude and also at all altitudes. Since deviation from filed flight plan is also a major cause of trajectory-modeling errors, statistics of deviations are presented. Errors in proposed departure times and ETMS-generated vertical profiles are also shown. A method for conditioning the vertical profiles for improving demand prediction accuracy is described. Graphs of actual sector counts obtained using these vertical profiles are compared with those obtained using the Host data for sectors in the Fort Worth Center to demonstrate the benefit of preprocessing. Finally, results are presented to quantify the extent of data drops. A method for propagating track positions during ETMS data drops is also described.

  10. Research on web-based decision support system for sports competitions

    NASA Astrophysics Data System (ADS)

    Huo, Hanqiang

    2010-07-01

    This paper describes the system architecture and implementation technology of the decision support system for sports competitions, discusses the design of decision-making modules, management modules and security of the system, and proposes the development idea of building a web-based decision support system for sports competitions.

  11. The value of decision tree analysis in planning anaesthetic care in obstetrics.

    PubMed

    Bamber, J H; Evans, S A

    2016-08-01

    The use of decision tree analysis is discussed in the context of the anaesthetic and obstetric management of a young pregnant woman with joint hypermobility syndrome with a history of insensitivity to local anaesthesia and a previous difficult intubation due to a tongue tumour. The multidisciplinary clinical decision process resulted in the woman being delivered without complication by elective caesarean section under general anaesthesia after an awake fibreoptic intubation. The decision process used is reviewed and compared retrospectively to a decision tree analytical approach. The benefits and limitations of using decision tree analysis are reviewed and its application in obstetric anaesthesia is discussed. PMID:27026589

  12. Multiobjective Integrated Decision Analysis System (MIDAS): Volume 1, Model overview: Final report

    SciTech Connect

    Farber, M.; Brusger, E.; Gerber, M.

    1988-04-01

    MIDAS (Multiobjective Integrated Decision Analysis System) is an innovative utility planning tool that facilitates the analysis of risk. Three features distinguish this framework from other planning models: it incorporates a generalized decision analysis approach; it includes a completely integrated planning model for demand-supply evaluation; and the complete model runs on a microcomputer. 24 figs.

  13. EPA Growing DASEES (Decision Analysis For A Sustainable Environment, Economy & Society) - To Aid In Making Decisions On Complex Environmental Issues

    EPA Science Inventory

    Having a framework and tools to help sort through complicated environmental issues in an objective way would be useful to communities and risk managers, and all the stakeholders affected by these issues. This is one need that DASEES (Decision Analysis for a Sustainable En...

  14. Evidence-based practice: how to perform and use systematic reviews for clinical decision-making.

    PubMed

    Kranke, Peter

    2010-09-01

    One approach to clinical decision-making requires the integration of the best available research evidence with individual clinical expertise and patient values, and is known as evidence-based medicine (EBM). In clinical decision-making with the current best evidence, systematic reviews have an important role. This review article covers the basic principles of systematic reviews and meta-analyses, and their role in the process of evidence-based decision-making. The problems associated with traditional narrative reviews are discussed, as well as the way systematic reviews limit bias associated with the assembly, critical appraisal and synthesis of studies addressing specific clinical questions. The relevant steps in writing a systematic review from the formulation of an initial research question to sensitivity analyses in conjunction with the combined analysis of the pooled data are described. Important issues that need to be considered when appraising a systematic review or meta-analysis are outlined. Some of the terms that are used in the reporting of systematic reviews and meta-analyses, such as relative risk, confidence interval, Forest plot or L'Abbé plot, will be introduced and explained. PMID:20523217

  15. Activity-based analyses lead to better decision making.

    PubMed

    Player, S

    1998-08-01

    Activity-based costing (ABC) and activity-based management (ABM) are cost-management tools that are relatively new to the healthcare industry. ABC is used for strategic decision making. It assesses the costs associated with specific activities and resources and links those costs to specific internal and external customers of the healthcare enterprise (e.g., patients, service lines, and physician groups) to determine the costs associated with each customer. This cost information then can be adjusted to account for anticipated changes and to predict future costs. ABM, on the other hand, supports operations by focusing on the causes of costs and how costs can be reduced. It assesses cost drivers that directly affect the cost of a product or service, and uses performance measures to evaluate the financial or nonfinancial benefit an activity provides. By identifying each cost driver and assessing the value the element adds to the healthcare enterprise, ABM provides a basis for selecting areas that can be changed to reduce costs. PMID:10182280

  16. Rational decision making based on history: adult sore throats.

    PubMed

    Clancy, C M; Centor, R M; Campbell, M S; Dalton, H P

    1988-01-01

    Primary care physicians are often required to make preliminary evaluations based only on the patient's history, especially during telephone encounters about sore throats. The authors studied adults with sore throats to determine whether patients can be stratified into higher and lower risks of strep throat by history alone. They first obtained data from 517 patients seen in an emergency room. Providers graded symptoms on a four-point scale (absent, mild, moderate, or severe). Initial analyses showed that prediction based on history should include three variables: fever, difficulty in swallowing, and cough. For ease of computation, these were consolidated into one score, "history" (= fever history + difficulty in swallowing - cough). This score was used to develop a model that predicts the probability of infection with group A beta-hemolytic streptococcus, and the model's performance was tested in two additional patient groups. The predictive accuracy of the "history" score was confirmed in all patient groups, despite differences in providers and disease prevalences. Primary care physicians may use this model to help them make decisions in situations such as telephone encounters without using additional data.

  17. Recollection- and Familiarity-Based Decisions Reflect Memory Strength

    PubMed Central

    Wiesmann, Martin; Ishai, Alumit

    2008-01-01

    We used event-related fMRI to investigate whether recollection- and familiarity-based memory judgments are modulated by the degree of visual similarity between old and new art paintings. Subjects performed a flower detection task, followed by a Remember/Know/New surprise memory test. The old paintings were randomly presented with new paintings, which were either visually similar or visually different. Consistent with our prediction, subjects were significantly faster and more accurate to reject new, visually different paintings than new, visually similar ones. The proportion of false alarms, namely remember and know responses to new paintings, was significantly reduced with decreased visual similarity. The retrieval task evoked activation in multiple visual, parietal and prefrontal regions, within which remember judgments elicited stronger activation than know judgments. New, visually different paintings evoked weaker activation than new, visually similar items in the intraparietal sulcus. Contrasting recollection with familiarity revealed activation predominantly within the precuneus, where the BOLD response elicited by recollection peaked significantly earlier than the BOLD response evoked by familiarity judgments. These findings suggest that successful memory retrieval of pictures is mediated by activation in a distributed cortical network, where memory strength is manifested by differential hemodynamic profiles. Recollection- and familiarity-based memory decisions may therefore reflect strong memories and weak memories, respectively. PMID:18958245

  18. Demonstration of optical computing logics based on binary decision diagram.

    PubMed

    Lin, Shiyun; Ishikawa, Yasuhiko; Wada, Kazumi

    2012-01-16

    Optical circuits are low power consumption and fast speed alternatives for the current information processing based on transistor circuits. However, because of no transistor function available in optics, the architecture for optical computing should be chosen that optics prefers. One of which is Binary Decision Diagram (BDD), where signal is processed by sending an optical signal from the root through a serial of switching nodes to the leaf (terminal). Speed of optical computing is limited by either transmission time of optical signals from the root to the leaf or switching time of a node. We have designed and experimentally demonstrated 1-bit and 2-bit adders based on the BDD architecture. The switching nodes are silicon ring resonators with a modulation depth of 10 dB and the states are changed by the plasma dispersion effect. The quality, Q of the rings designed is 1500, which allows fast transmission of signal, e.g., 1.3 ps calculated by a photon escaping time. A total processing time is thus analyzed to be ~9 ps for a 2-bit adder and would scales linearly with the number of bit. It is two orders of magnitude faster than the conventional CMOS circuitry, ~ns scale of delay. The presented results show the potential of fast speed optical computing circuits.

  19. A Z-number-based decision making procedure with ranking fuzzy numbers method

    NASA Astrophysics Data System (ADS)

    Mohamad, Daud; Shaharani, Saidatull Akma; Kamis, Nor Hanimah

    2014-12-01

    The theory of fuzzy set has been in the limelight of various applications in decision making problems due to its usefulness in portraying human perception and subjectivity. Generally, the evaluation in the decision making process is represented in the form of linguistic terms and the calculation is performed using fuzzy numbers. In 2011, Zadeh has extended this concept by presenting the idea of Z-number, a 2-tuple fuzzy numbers that describes the restriction and the reliability of the evaluation. The element of reliability in the evaluation is essential as it will affect the final result. Since this concept can still be considered as new, available methods that incorporate reliability for solving decision making problems is still scarce. In this paper, a decision making procedure based on Z-numbers is proposed. Due to the limitation of its basic properties, Z-numbers will be first transformed to fuzzy numbers for simpler calculations. A method of ranking fuzzy number is later used to prioritize the alternatives. A risk analysis problem is presented to illustrate the effectiveness of this proposed procedure.

  20. Computer-Based Support of Organizational Decision Making.

    ERIC Educational Resources Information Center

    Bonczek, Robert H.; And Others

    1979-01-01

    Explores the extent to which computer facilities can be used to support organizational decision-making processes beyond mere performance of information retrieval. Human perceptual and judgmental processes, as they apply to organizational decisions, are examined as a basis for the design of a generalized, intelligent problem processor. (Author/RAO)

  1. Safety Assessment of Dangerous Goods Transport Enterprise Based on the Relative Entropy Aggregation in Group Decision Making Model

    PubMed Central

    Wu, Jun; Li, Chengbing; Huo, Yueying

    2014-01-01

    Safety of dangerous goods transport is directly related to the operation safety of dangerous goods transport enterprise. Aiming at the problem of the high accident rate and large harm in dangerous goods logistics transportation, this paper took the group decision making problem based on integration and coordination thought into a multiagent multiobjective group decision making problem; a secondary decision model was established and applied to the safety assessment of dangerous goods transport enterprise. First of all, we used dynamic multivalue background and entropy theory building the first level multiobjective decision model. Secondly, experts were to empower according to the principle of clustering analysis, and combining with the relative entropy theory to establish a secondary rally optimization model based on relative entropy in group decision making, and discuss the solution of the model. Then, after investigation and analysis, we establish the dangerous goods transport enterprise safety evaluation index system. Finally, case analysis to five dangerous goods transport enterprises in the Inner Mongolia Autonomous Region validates the feasibility and effectiveness of this model for dangerous goods transport enterprise recognition, which provides vital decision making basis for recognizing the dangerous goods transport enterprises. PMID:25477954

  2. Safety assessment of dangerous goods transport enterprise based on the relative entropy aggregation in group decision making model.

    PubMed

    Wu, Jun; Li, Chengbing; Huo, Yueying

    2014-01-01

    Safety of dangerous goods transport is directly related to the operation safety of dangerous goods transport enterprise. Aiming at the problem of the high accident rate and large harm in dangerous goods logistics transportation, this paper took the group decision making problem based on integration and coordination thought into a multiagent multiobjective group decision making problem; a secondary decision model was established and applied to the safety assessment of dangerous goods transport enterprise. First of all, we used dynamic multivalue background and entropy theory building the first level multiobjective decision model. Secondly, experts were to empower according to the principle of clustering analysis, and combining with the relative entropy theory to establish a secondary rally optimization model based on relative entropy in group decision making, and discuss the solution of the model. Then, after investigation and analysis, we establish the dangerous goods transport enterprise safety evaluation index system. Finally, case analysis to five dangerous goods transport enterprises in the Inner Mongolia Autonomous Region validates the feasibility and effectiveness of this model for dangerous goods transport enterprise recognition, which provides vital decision making basis for recognizing the dangerous goods transport enterprises. PMID:25477954

  3. Seismic slope-performance analysis: from hazard map to decision support system

    USGS Publications Warehouse

    Miles, Scott B.; Keefer, David K.; Ho, Carlton L.

    1999-01-01

    In response to the growing recognition of engineers and decision-makers of the regional effects of earthquake-induced landslides, this paper presents a general approach to conducting seismic landslide zonation, based on the popular Newmark's sliding block analogy for modeling coherent landslides. Four existing models based on the sliding block analogy are compared. The comparison shows that the models forecast notably different levels of slope performance. Considering this discrepancy along with the limitations of static maps as a decision tool, a spatial decision support system (SDSS) for seismic landslide analysis is proposed, which will support investigations over multiple scales for any number of earthquake scenarios and input conditions. Most importantly, the SDSS will allow use of any seismic landslide analysis model and zonation approach. Developments associated with the SDSS will produce an object-oriented model for encapsulating spatial data, an object-oriented specification to allow construction of models using modular objects, and a direct-manipulation, dynamic user-interface that adapts to the particular seismic landslide model configuration.

  4. Trustworthy patient decision aids: a qualitative analysis addressing the risk of competing interests

    PubMed Central

    Elwyn, Glyn; Dannenberg, Michelle; Blaine, Arianna; Poddar, Urbashi; Durand, Marie-Anne

    2016-01-01

    Objective Our aim in this study was to examine the competing interest policies and procedures of organisations who develop and maintain patient decision aids. Design Descriptive and thematic analysis of data collected from a cross-sectional survey of patient decision aid developer's competing interest policies and disclosure forms. Results We contacted 25 organisations likely to meet the inclusion criteria. 12 eligible organisations provided data. 11 organisations did not reply and 2 declined to participate. Most patient decision aid developers recognise the need to consider the issue of competing interests. Assessment processes vary widely and, for the most part, are insufficiently robust to minimise the risk of competing interests. Only half of the 12 organisations had competing interest policies. Some considered disclosure to be sufficient, while others imposed differing levels of exclusion. Conclusions Patient decision aid developers do not have a consistent approach to managing competing interests. Some have developed policies and procedures, while others pay no attention to the issue. As is the case for clinical practice guidelines, increasing attention will need to be given to how the competing interests of contributors of evidence-based publications may influence materials, especially if they are designed for patient use. PMID:27612542

  5. Multi-criteria decision analysis for waste management in Saharawi refugee camps.

    PubMed

    Garfì, M; Tondelli, S; Bonoli, A

    2009-10-01

    The aim of this paper is to compare different waste management solutions in Saharawi refugee camps (Algeria) and to test the feasibility of a decision-making method developed to be applied in particular conditions in which environmental and social aspects must be considered. It is based on multi criteria analysis, and in particular on the analytic hierarchy process (AHP), a mathematical technique for multi-criteria decision making (Saaty, T.L., 1980. The Analytic Hierarchy Process. McGraw-Hill, New York, USA; Saaty, T.L., 1990. How to Make a Decision: The Analytic Hierarchy Process. European Journal of Operational Research; Saaty, T.L., 1994. Decision Making for Leaders: The Analytic Hierarchy Process in a Complex World. RWS Publications, Pittsburgh, PA), and on participatory approach, focusing on local community's concerns. The research compares four different waste collection and management alternatives: waste collection by using three tipper trucks, disposal and burning in an open area; waste collection by using seven dumpers and disposal in a landfill; waste collection by using seven dumpers and three tipper trucks and disposal in a landfill; waste collection by using three tipper trucks and disposal in a landfill. The results show that the second and the third solutions provide better scenarios for waste management. Furthermore, the discussion of the results points out the multidisciplinarity of the approach, and the equilibrium between social, environmental and technical impacts. This is a very important aspect in a humanitarian and environmental project, confirming the appropriateness of the chosen method.

  6. Multi-criteria decision analysis for waste management in Saharawi refugee camps

    SciTech Connect

    Garfi, M. Tondelli, S.; Bonoli, A.

    2009-10-15

    The aim of this paper is to compare different waste management solutions in Saharawi refugee camps (Algeria) and to test the feasibility of a decision-making method developed to be applied in particular conditions in which environmental and social aspects must be considered. It is based on multi criteria analysis, and in particular on the analytic hierarchy process (AHP), a mathematical technique for multi-criteria decision making (Saaty, T.L., 1980. The Analytic Hierarchy Process. McGraw-Hill, New York, USA; Saaty, T.L., 1990. How to Make a Decision: The Analytic Hierarchy Process. European Journal of Operational Research; Saaty, T.L., 1994. Decision Making for Leaders: The Analytic Hierarchy Process in a Complex World. RWS Publications, Pittsburgh, PA), and on participatory approach, focusing on local community's concerns. The research compares four different waste collection and management alternatives: waste collection by using three tipper trucks, disposal and burning in an open area; waste collection by using seven dumpers and disposal in a landfill; waste collection by using seven dumpers and three tipper trucks and disposal in a landfill; waste collection by using three tipper trucks and disposal in a landfill. The results show that the second and the third solutions provide better scenarios for waste management. Furthermore, the discussion of the results points out the multidisciplinarity of the approach, and the equilibrium between social, environmental and technical impacts. This is a very important aspect in a humanitarian and environmental project, confirming the appropriateness of the chosen method.

  7. A review and classification of approaches for dealing with uncertainty in multi-criteria decision analysis for healthcare decisions.

    PubMed

    Broekhuizen, Henk; Groothuis-Oudshoorn, Catharina G M; van Til, Janine A; Hummel, J Marjan; IJzerman, Maarten J

    2015-05-01

    Multi-criteria decision analysis (MCDA) is increasingly used to support decisions in healthcare involving multiple and conflicting criteria. Although uncertainty is usually carefully addressed in health economic evaluations, whether and how the different sources of uncertainty are dealt with and with what methods in MCDA is less known. The objective of this study is to review how uncertainty can be explicitly taken into account in MCDA and to discuss which approach may be appropriate for healthcare decision makers. A literature review was conducted in the Scopus and PubMed databases. Two reviewers independently categorized studies according to research areas, the type of MCDA used, and the approach used to quantify uncertainty. Selected full text articles were read for methodological details. The search strategy identified 569 studies. The five approaches most identified were fuzzy set theory (45% of studies), probabilistic sensitivity analysis (15%), deterministic sensitivity analysis (31%), Bayesian framework (6%), and grey theory (3%). A large number of papers considered the analytic hierarchy process in combination with fuzzy set theory (31%). Only 3% of studies were published in healthcare-related journals. In conclusion, our review identified five different approaches to take uncertainty into account in MCDA. The deterministic approach is most likely sufficient for most healthcare policy decisions because of its low complexity and straightforward implementation. However, more complex approaches may be needed when multiple sources of uncertainty must be considered simultaneously.

  8. Decision Analysis For A Sustainable Environment, Economy, & Society

    EPA Science Inventory

    Environmental decisions are often made without consideration of the roles that ecosystem services play. Most decision-makers do not currently have access to useful or usable methods and approaches when they are presented with choices that will have significant ecosystem impacts....

  9. Decision Analysis for a Sustainable Environment, Economy & Society

    EPA Science Inventory

    Environmental decisions are often made without consideration of the roles that ecosystem services play. Most decision-makers do not currently have access to useful or usable methods and approaches when they are presented with choices that will have significant ecosystem impacts. ...

  10. Child Protection Decision Making: A Factorial Analysis Using Case Vignettes

    ERIC Educational Resources Information Center

    Stokes, Jacqueline; Schmidt, Glen

    2012-01-01

    This study explored decision making by child protection social workers in the province of British Columbia, Canada. A factorial survey method was used in which case vignettes were constructed by randomly assigning a number of key characteristics associated with decision making in child protection. Child protection social workers (n = 118) assessed…

  11. Suitability analysis for siting MSW landfills and its multicriteria spatial decision support system: method, implementation and case study.

    PubMed

    Demesouka, O E; Vavatsikos, A P; Anagnostopoulos, K P

    2013-05-01

    Multicriteria spatial decision support systems (MC-SDSS) have emerged as an integration of geographical information systems (GIS) and multiple criteria decision analysis (MCDA) methods for incorporating conflicting objectives and decision makers' (DMs') preferences into spatial decision models. This article presents a raster-based MC-SDSS that combines the analytic hierarchy process (AHP) and compromise programming methods, such as TOPSIS (technique for order preference by similarity to the ideal solution) and Ideal Point Methods. To the best of our knowledge it is the first time that a synergy of AHP and compromise programming methods is implemented in raster-driven GIS-based landfill suitability analysis. This procedure is supported by a spatial decision support system (SDSS) that was developed within a widely used commercial GIS software package. A real case study in the Thrace region in northeast Greece serves as a guide on how to conduct a suitability analysis for a MSW landfill site with the proposed MC-SDSS. Moreover, the procedure for identifying MSW disposal sites is accomplished by performing four computational models for synthesizing the DMs per criterion preferential system. Based on the case study results, a comparison analysis is performed according to suitability index estimations. According to them Euclidean distance metric and TOPSIS present strong similarities. When compared with Euclidean distance metric, TOPSIS seems to generate results closer to that derived by Manhattan distance metric. The comparison of Chebychev distance metric with all the other approaches revealed the greatest deviations. PMID:23453354

  12. Creating a GIS-Based Decision-Support System

    NASA Technical Reports Server (NTRS)

    Alvarado, Lori; Gates, Ann Q.; Gray, Bob; Reyes, Raul

    1998-01-01

    Tilting the Balance: Climate Variability and Water Resource Management in the Southwest, a regional conference hosted by the Pan American Center for Environmental Studies, will be held at The University of Texas at El Paso on March 2-4, 1998. The conference is supported through the US Global Change Research Program (USGCRP) established by the President in 1989, and codified by Congress in the Global Change Research Act of 1990. The NASA Mission to Planet Earth program is one of the workshops sponsors. The purpose of the regional workshops is to improve understanding of the consequences of global change. This workshop will be focused on issues along the border and the Rio Grande River and thus will bring together stakeholders from Mexico, California, Texas, New Mexico, Arizona and Colorado representing federal, state, and local governments; universities and laboratories; industry, agricultural and natural resource managers; and non-governmental organizations. This paper discusses the efforts of the NASA PACES center create a GIS-based decision-support system that can be used to facilitate discussion of the complex issues of resource management within the targeted international region.

  13. Hippocampal Attractor Dynamics Predict Memory-Based Decision Making.

    PubMed

    Steemers, Ben; Vicente-Grabovetsky, Alejandro; Barry, Caswell; Smulders, Peter; Schröder, Tobias Navarro; Burgess, Neil; Doeller, Christian F

    2016-07-11

    Memories are thought to be retrieved by attractor dynamics if a given input is sufficiently similar to a stored attractor state [1-5]. The hippocampus, a region crucial for spatial navigation [6-12] and episodic memory [13-18], has been associated with attractor-based computations [5, 9], receiving support from the way rodent place cells "remap" nonlinearly between spatial representations [19-22]. In humans, nonlinear response patterns have been reported in perceptual categorization tasks [23-25]; however, it remains elusive whether human memory retrieval is driven by attractor dynamics and what neural mechanisms might underpin them. To test this, we used a virtual reality [7, 11, 26-28] task where participants learned object-location associations within two distinct virtual reality environments. Participants were subsequently exposed to four novel intermediate environments, generated by linearly morphing the background landscapes of the familiar environments, while tracking fMRI activity. We show that linear changes in environmental context cause linear changes in activity patterns in sensory cortex but cause dynamic, nonlinear changes in both hippocampal activity pattern and remembered locations. Furthermore, the sigmoidal response in the hippocampus scaled with the strength of the sigmoidal pattern in spatial memory. These results indicate that mnemonic decisions in an ambiguous novel context relate to putative attractor dynamics in the hippocampus, which support the dynamic remapping of memories. PMID:27345167

  14. Selection of Representative Models for Decision Analysis Under Uncertainty

    NASA Astrophysics Data System (ADS)

    Meira, Luis A. A.; Coelho, Guilherme P.; Santos, Antonio Alberto S.; Schiozer, Denis J.

    2016-03-01

    The decision-making process in oil fields includes a step of risk analysis associated with the uncertainties present in the variables of the problem. Such uncertainties lead to hundreds, even thousands, of possible scenarios that are supposed to be analyzed so an effective production strategy can be selected. Given this high number of scenarios, a technique to reduce this set to a smaller, feasible subset of representative scenarios is imperative. The selected scenarios must be representative of the original set and also free of optimistic and pessimistic bias. This paper is devoted to propose an assisted methodology to identify representative models in oil fields. To do so, first a mathematical function was developed to model the representativeness of a subset of models with respect to the full set that characterizes the problem. Then, an optimization tool was implemented to identify the representative models of any problem, considering not only the cross-plots of the main output variables, but also the risk curves and the probability distribution of the attribute-levels of the problem. The proposed technique was applied to two benchmark cases and the results, evaluated by experts in the field, indicate that the obtained solutions are richer than those identified by previously adopted manual approaches. The program bytecode is available under request.

  15. CAUSAL ANALYSIS / DIAGNOSIS DECISION INFORMATION SYSTEM (CADDIS) WORKSHOP 2002

    EPA Science Inventory

    Increasingly, the regulatory, remedial and restoration actions taken to manage impaired environments are based on measurement and analysis of the state of the biotic community. When an aquatic community has been identified as impaired, the cause of the impairment must be determi...

  16. Understandings of the nature of science and decision making on science and technology based issues

    NASA Astrophysics Data System (ADS)

    Bell, Randy L.; Lederman, Norman G.

    2003-05-01

    The purpose of this investigation was to explicate the role of the nature of science in decision making on science and technology based issues and to delineate factors and reasoning associated with these types of decisions. Twenty-one volunteer participants purposively selected from the faculty of geographically diverse universities completed an open-ended questionnaire and follow-up interview designed to assess their decision making on science and technology based issues. Participants were subsequently placed in one of two groups based upon their divergent views of the nature of science as assessed by a second open-ended questionnaire and follow-up interview. Profiles of each group's decision making were then constructed, based on participants' previous responses to the decision making questionnaire and follow-up interviews. Finally, the two groups' decisions, decision influencing factors, and decision making strategies were compared. No differences were found between the decisions of the two groups, despite their disparate views of the nature of science. Participants in both groups based their decisions primarily on personal values, morals/ethics, and social concerns. While all participants considered scientific evidence in their decision making, most did not require absolute proof, even though many participants held absolute conceptions of the nature of science. Overall, the nature of science did not figure prominently in either group's decisions. These findings contrast with basic assumptions of current science education reform efforts and call for a re-examination of the goals of nature of science instruction. Developing better decision making skills - even on science and technology based issues - may involve other factors, including more value-based instruction and attention to intellectual/moral development.

  17. Initial decision analysis (IDA): a participatory approach for developing resource policies

    NASA Astrophysics Data System (ADS)

    Bonnicksen, Thomas M.

    1985-09-01

    Initial decision analysis (IDA) is a microcomputer based decision-making technique that is organized so that a rational, step-by-step, procedure can be followed to use existing knowledge to develop resource policies. The IDA process provides a systematic way for participants to define their own problem and to explore jointly alternative solutions. IDA is particularly suited to resolving complex problems involving many groups with conflicting interests. IDA is illustrated with data from the US Forest Service's Draft Environmental Impact Statement for the 1985 to 2030 Resource Planning Act Program for the United States. Four policy options are evaluated: maximization of timber production, of grazing, and of wilderness, and a dominant use policy that concentrates timber management on productive sites. Policies were evaluated using a new mathematical satisficing procedure. Mathematical satisficing of simulated policy consequences showed that, for selected performance standards, current RPA policies are superior to the four alternative policies examined.

  18. Health economics and outcomes methods in risk-based decision-making for blood safety.

    PubMed

    Custer, Brian; Janssen, Mart P

    2015-08-01

    Analytical methods appropriate for health economic assessments of transfusion safety interventions have not previously been described in ways that facilitate their use. Within the context of risk-based decision-making (RBDM), health economics can be important for optimizing decisions among competing interventions. The objective of this review is to address key considerations and limitations of current methods as they apply to blood safety. Because a voluntary blood supply is an example of a public good, analyses should be conducted from the societal perspective when possible. Two primary study designs are recommended for most blood safety intervention assessments: budget impact analysis (BIA), which measures the cost to implement an intervention both to the blood operator but also in a broader context, and cost-utility analysis (CUA), which measures the ratio between costs and health gain achieved, in terms of reduced morbidity and mortality, by use of an intervention. These analyses often have important limitations because data that reflect specific aspects, for example, blood recipient population characteristics or complication rates, are not available. Sensitivity analyses play an important role. The impact of various uncertain factors can be studied conjointly in probabilistic sensitivity analyses. The use of BIA and CUA together provides a comprehensive assessment of the costs and benefits from implementing (or not) specific interventions. RBDM is multifaceted and impacts a broad spectrum of stakeholders. Gathering and analyzing health economic evidence as part of the RBDM process enhances the quality, completeness, and transparency of decision-making.

  19. GUIDED TOUR OF A WEB-BASED ENVIRONMENTAL DECISION TOOLKIT

    EPA Science Inventory

    Decision-making regarding the targeting of vulnerable resources and prioritization of actions requires synthesis of data on condition, vulnerability, and feasibility of risk management alternatives. EP A's Regional Vulnerability Assessment (ReV A) Program has evaluated existing a...

  20. Environmental criteria in industrial facility siting decisions: An analysis

    NASA Astrophysics Data System (ADS)

    Briassoulis, Helen

    1995-03-01

    Environmental criteria are increasingly being employed in industrial facility siting, usually in multicriteria decision contexts, together with technical, socioeconomic and other considerations. This paper analyzes the criteria that have appeared in the published literature with the aim to offer guidance for their selection in a particular facility location problem. A number of alternative classification schemes are presented, first based on the most prevalent classification dimensions which are: the economy-environment relationship, purpose of the criterion, complexity, spatial and temporal scale, and level of measurement. The major scheme adopted draws from the economy-environment relationship and assigns environmental critera to one of seven categories: general characterizations of the environment, characteristics of individual environmental components, measures of the magnitude and intensity of the activity, measures of the nature and volume of wastes which are produced, characteristics of impacts on separate environmental media and receptors, general characterizations of environmental quality, and impacts on humans. Within each of these categories the criteria are analyzed in terms of the other classification dimensions. Common characteristics among the various criteria as well as future trends in their development are identified. This paper also discusses the most important factors conditioning the choice of criteria in a particular facility siting context and outlines a systematic procedure for their selection in real-world applications.

  1. Harnessing ecosystem models and multi-criteria decision analysis for the support of forest management.

    PubMed

    Wolfslehner, Bernhard; Seidl, Rupert

    2010-12-01

    The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

  2. Harnessing Ecosystem Models and Multi-Criteria Decision Analysis for the Support of Forest Management

    NASA Astrophysics Data System (ADS)

    Wolfslehner, Bernhard; Seidl, Rupert

    2010-12-01

    The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

  3. A decision-theoretic framework for the application of cost-effectiveness analysis in regulatory processes.

    PubMed

    Baio, Gianluca; Russo, Pierluigi

    2009-01-01

    Cost-effectiveness analysis (CEA) represents the most important tool in the health economics literature to quantify and qualify the reasoning behind the optimal decision process in terms of the allocation of resources to a given health intervention. However, the practical application of CEA in the regulatory process is often limited by some critical barriers, and decisions in clinical practice are frequently influenced by factors that do not contribute to efficient resource allocation, leading to inappropriate drug prescription and utilization. Moreover, most of the time there is uncertainty about the real cost-effectiveness profile of an innovative intervention, with the consequence that it is usually impossible to obtain an immediate and perfect substitution of a product with another having a better cost-effectiveness ratio. The objective of this article is to propose a rational approach to CEA within regulatory processes, basing our analysis in a Bayesian decision-theoretic framework and proposing an extension of the application of well known tools (such as the expected value of information) to such cases. The regulator can use these tools to identify the economic value of reducing the uncertainty surrounding the cost-effectiveness profile of the several alternatives. This value can be compared with the one that is generated by the actual market share of the different treatment options: one that is the most cost effective and others in the same therapeutic category that, despite producing clinical benefits, are less cost effective.

  4. Application of multicriteria decision analysis tools to two contaminated sediment case studies.

    PubMed

    Yatsalo, Boris I; Kiker, Gregory A; Kim, St Jongbum; Bridges, Todd S; Seager, Thomas P; Gardner, Kevin; Satterstrom, F Kyle; Linkov, Igor

    2007-04-01

    Environmental decision making is becoming increasingly more information intensive and complex. Our previous work shows that multicriteria decision analysis (MCDA) tools offer a scientifically sound decision analytical framework for environmental management, in general, and specifically for selecting optimal sediment management alternatives. Integration of MCDA into risk assessment and sediment management may require linkage of different models and software platforms whose results may lead to somewhat different conclusions. This paper illustrates the application of 3 different MCDA methods in 2 case studies involving contaminated sediment management. These case studies are based on real sediment management problems experienced by the US Army Corps of Engineers and other stakeholders in New York/New Jersey Harbor, USA, and the Cocheco River Superfund Site in New Hampshire, USA. Our analysis shows that application of 3 different MCDA tools points to similar management solutions no matter which tool is applied. MCDA tools and approaches were constructively used to elicit the strengths and weaknesses of each method when solving the problem. PMID:17477290

  5. Two hypothetical problems in radioactive waste management: a comparison of cost/benefit analysis and decision analysis

    SciTech Connect

    Watson, S.R.; Hayward, G.M.

    1982-03-01

    In particular the presentation has argued that Decision Analysis (DA) has considerable advantages over Cost Benefit Analysis (CBA), a view which may not be acceptable to practitioners of CBA. The criticism may be levelled that the authors have misinterpreted CBA in order to make their point. As mentioned above, however, the authors have taken a particular view of CBA in order to emphasize the distinction between an approach based in economics, and one based in psychology and management studies. Moreover many formal analyses of public policy today contain elements from both approaches, so that the distinction between CBA and DA may not be as clear-cut as indicated. There is however a basic difference of approach which it is hoped has been spelt out in the studies of chapters 2 and 3; the essential difference is between a device which seeks to determine what is socially best, in an objective manner, and a device to assist a group of decision-makers in clarifying their understanding of a complex decision problem.

  6. An analysis of symbolic linguistic computing models in decision making

    NASA Astrophysics Data System (ADS)

    Rodríguez, Rosa M.; Martínez, Luis

    2013-01-01

    It is common that experts involved in complex real-world decision problems use natural language for expressing their knowledge in uncertain frameworks. The language is inherent vague, hence probabilistic decision models are not very suitable in such cases. Therefore, other tools such as fuzzy logic and fuzzy linguistic approaches have been successfully used to model and manage such vagueness. The use of linguistic information implies to operate with such a type of information, i.e. processes of computing with words (CWW). Different schemes have been proposed to deal with those processes, and diverse symbolic linguistic computing models have been introduced to accomplish the linguistic computations. In this paper, we overview the relationship between decision making and CWW, and focus on symbolic linguistic computing models that have been widely used in linguistic decision making to analyse if all of them can be considered inside of the CWW paradigm.

  7. A decision tree – based method for the differential diagnosis of Aortic Stenosis from Mitral Regurgitation using heart sounds

    PubMed Central

    Pavlopoulos, Sotiris A; Stasis, Antonis CH; Loukis, Euripides N

    2004-01-01

    Background New technologies like echocardiography, color Doppler, CT, and MRI provide more direct and accurate evidence of heart disease than heart auscultation. However, these modalities are costly, large in size and operationally complex and therefore are not suitable for use in rural areas, in homecare and generally in primary healthcare set-ups. Furthermore the majority of internal medicine and cardiology training programs underestimate the value of cardiac auscultation and junior clinicians are not adequately trained in this field. Therefore efficient decision support systems would be very useful for supporting clinicians to make better heart sound diagnosis. In this study a rule-based method, based on decision trees, has been developed for differential diagnosis between "clear" Aortic Stenosis (AS) and "clear" Mitral Regurgitation (MR) using heart sounds. Methods For the purposes of our experiment we used a collection of 84 heart sound signals including 41 heart sound signals with "clear" AS systolic murmur and 43 with "clear" MR systolic murmur. Signals were initially preprocessed to detect 1st and 2nd heart sounds. Next a total of 100 features were determined for every heart sound signal and relevance to the differentiation between AS and MR was estimated. The performance of fully expanded decision tree classifiers and Pruned decision tree classifiers were studied based on various training and test datasets. Similarly, pruned decision tree classifiers were used to examine their differentiation capabilities. In order to build a generalized decision support system for heart sound diagnosis, we have divided the problem into sub problems, dealing with either one morphological characteristic of the heart-sound waveform or with difficult to distinguish cases. Results Relevance analysis on the different heart sound features demonstrated that the most relevant features are the frequency features and the morphological features that describe S1, S2 and the systolic

  8. Addressing preference heterogeneity in public health policy by combining Cluster Analysis and Multi-Criteria Decision Analysis: Proof of Method.

    PubMed

    Kaltoft, Mette Kjer; Turner, Robin; Cunich, Michelle; Salkeld, Glenn; Nielsen, Jesper Bo; Dowie, Jack

    2015-01-01

    The use of subgroups based on biological-clinical and socio-demographic variables to deal with population heterogeneity is well-established in public policy. The use of subgroups based on preferences is rare, except when religion based, and controversial. If it were decided to treat subgroup preferences as valid determinants of public policy, a transparent analytical procedure is needed. In this proof of method study we show how public preferences could be incorporated into policy decisions in a way that respects both the multi-criterial nature of those decisions, and the heterogeneity of the population in relation to the importance assigned to relevant criteria. It involves combining Cluster Analysis (CA), to generate the subgroup sets of preferences, with Multi-Criteria Decision Analysis (MCDA), to provide the policy framework into which the clustered preferences are entered. We employ three techniques of CA to demonstrate that not only do different techniques produce different clusters, but that choosing among techniques (as well as developing the MCDA structure) is an important task to be undertaken in implementing the approach outlined in any specific policy context. Data for the illustrative, not substantive, application are from a Randomized Controlled Trial of online decision aids for Australian men aged 40-69 years considering Prostate-specific Antigen testing for prostate cancer. We show that such analyses can provide policy-makers with insights into the criterion-specific needs of different subgroups. Implementing CA and MCDA in combination to assist in the development of policies on important health and community issues such as drug coverage, reimbursement, and screening programs, poses major challenges -conceptual, methodological, ethical-political, and practical - but most are exposed by the techniques, not created by them.

  9. LiteVis: Integrated Visualization for Simulation-Based Decision Support in Lighting Design.

    PubMed

    Sorger, Johannes; Ortner, Thomas; Luksch, Christian; Schwärzler, Michael; Gröller, Eduard; Piringer, Harald

    2016-01-01

    State-of-the-art lighting design is based on physically accurate lighting simulations of scenes such as offices. The simulation results support lighting designers in the creation of lighting configurations, which must meet contradicting customer objectives regarding quality and price while conforming to industry standards. However, current tools for lighting design impede rapid feedback cycles. On the one side, they decouple analysis and simulation specification. On the other side, they lack capabilities for a detailed comparison of multiple configurations. The primary contribution of this paper is a design study of LiteVis, a system for efficient decision support in lighting design. LiteVis tightly integrates global illumination-based lighting simulation, a spatial representation of the scene, and non-spatial visualizations of parameters and result indicators. This enables an efficient iterative cycle of simulation parametrization and analysis. Specifically, a novel visualization supports decision making by ranking simulated lighting configurations with regard to a weight-based prioritization of objectives that considers both spatial and non-spatial characteristics. In the spatial domain, novel concepts support a detailed comparison of illumination scenarios. We demonstrate LiteVis using a real-world use case and report qualitative feedback of lighting designers. This feedback indicates that LiteVis successfully supports lighting designers to achieve key tasks more efficiently and with greater certainty. PMID:26529708

  10. Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

    NASA Astrophysics Data System (ADS)

    Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza

    2012-06-01

    It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes

  11. 40 CFR 761.298 - Decisions based on PCB concentration measurements resulting from sampling.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 32 2012-07-01 2012-07-01 false Decisions based on PCB concentration....61(a)(6) § 761.298 Decisions based on PCB concentration measurements resulting from sampling. (a) For grid samples which are chemically analyzed individually, the PCB concentration applies to the area...

  12. 40 CFR 761.298 - Decisions based on PCB concentration measurements resulting from sampling.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 31 2011-07-01 2011-07-01 false Decisions based on PCB concentration....61(a)(6) § 761.298 Decisions based on PCB concentration measurements resulting from sampling. (a) For grid samples which are chemically analyzed individually, the PCB concentration applies to the area...

  13. 40 CFR 761.298 - Decisions based on PCB concentration measurements resulting from sampling.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 32 2013-07-01 2013-07-01 false Decisions based on PCB concentration....61(a)(6) § 761.298 Decisions based on PCB concentration measurements resulting from sampling. (a) For grid samples which are chemically analyzed individually, the PCB concentration applies to the area...

  14. 40 CFR 761.298 - Decisions based on PCB concentration measurements resulting from sampling.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 31 2014-07-01 2014-07-01 false Decisions based on PCB concentration....61(a)(6) § 761.298 Decisions based on PCB concentration measurements resulting from sampling. (a) For grid samples which are chemically analyzed individually, the PCB concentration applies to the area...

  15. Data-Based Decisions Guidelines for Teachers of Students with Severe Intellectual and Developmental Disabilities

    ERIC Educational Resources Information Center

    Jimenez, Bree A.; Mims, Pamela J.; Browder, Diane M.

    2012-01-01

    Effective practices in student data collection and implementation of data-based instructional decisions are needed for all educators, but are especially important when students have severe intellectual and developmental disabilities. Although research in the area of data-based instructional decisions for students with severe disabilities shows…

  16. The Relative Success of Recognition-Based Inference in Multichoice Decisions

    ERIC Educational Resources Information Center

    McCloy, Rachel; Beaman, C. Philip; Smith, Philip T.

    2008-01-01

    The utility of an "ecologically rational" recognition-based decision rule in multichoice decision problems is analyzed, varying the type of judgment required (greater or lesser). The maximum size and range of a counterintuitive advantage associated with recognition-based judgment (the "less-is-more effect") is identified for a range of cue…

  17. Multicriteria decision analysis in ranking of analytical procedures for aldrin determination in water.

    PubMed

    Tobiszewski, Marek; Orłowski, Aleksander

    2015-03-27

    The study presents the possibility of multi-criteria decision analysis (MCDA) application when choosing analytical procedures with low environmental impact. A type of MCDA, Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), was chosen as versatile tool that meets all the analytical chemists--decision makers requirements. Twenty five analytical procedures for aldrin determination in water samples (as an example) were selected as input alternatives to MCDA analysis. Nine different criteria describing the alternatives were chosen from different groups--metrological, economical and the most importantly--environmental impact. The weights for each criterion were obtained from questionnaires that were sent to experts, giving three different scenarios for MCDA results. The results of analysis show that PROMETHEE is very promising tool to choose the analytical procedure with respect to its greenness. The rankings for all three scenarios placed solid phase microextraction and liquid phase microextraction--based procedures high, while liquid-liquid extraction, solid phase extraction and stir bar sorptive extraction--based procedures were placed low in the ranking. The results show that although some of the experts do not intentionally choose green analytical chemistry procedures, their MCDA choice is in accordance with green chemistry principles. The PROMETHEE ranking results were compared with more widely accepted green analytical chemistry tools--NEMI and Eco-Scale. As PROMETHEE involved more different factors than NEMI, the assessment results were only weakly correlated. Oppositely, the results of Eco-Scale assessment were well-correlated as both methodologies involved similar criteria of assessment.

  18. VisualDecisionLinc: a visual analytics approach for comparative effectiveness-based clinical decision support in psychiatry.

    PubMed

    Mane, Ketan K; Bizon, Chris; Schmitt, Charles; Owen, Phillips; Burchett, Bruce; Pietrobon, Ricardo; Gersing, Kenneth

    2012-02-01

    Comparative Effectiveness Research (CER) is designed to provide research evidence on the effectiveness and risks of different therapeutic options on the basis of data compiled from subpopulations of patients with similar medical conditions. Electronic Health Record (EHR) system contain large volumes of patient data that could be used for CER, but the data contained in EHR system are typically accessible only in formats that are not conducive to rapid synthesis and interpretation of therapeutic outcomes. In the time-pressured clinical setting, clinicians faced with large amounts of patient data in formats that are not readily interpretable often feel 'information overload'. Decision support tools that enable rapid access at the point of care to aggregate data on the most effective therapeutic outcomes derived from CER would greatly aid the clinical decision-making process and individualize patient care. In this manuscript, we highlight the role that visual analytics can play in CER-based clinical decision support. We developed a 'VisualDecisionLinc' (VDL) tool prototype that uses visual analytics to provide summarized CER-derived data views to facilitate rapid interpretation of large amounts of data. We highlight the flexibility that visual analytics offers to gain an overview of therapeutic options and outcomes and if needed, to instantly customize the evidence to the needs of the patient or clinician. The VDL tool uses visual analytics to help the clinician evaluate and understand the effectiveness and risk of different therapeutic options for different subpopulations of patients.

  19. Decision support for simulation-based operation planning

    NASA Astrophysics Data System (ADS)

    Schubert, Johan; Hörling, Pontus

    2016-05-01

    In this paper, we develop methods for analyzing large amounts of data from a military ground combat simulation system. Through a series of processes, we focus the big data set on situations that correspond to important questions and show advantageous outcomes. The result is a decision support methodology that provides commanders with results that answer specific questions of interest, such as what the consequences for the Blue side are in various Red scenarios or what a particular Blue force can withstand. This approach is a step toward taking the traditional data farming methodology from its analytical view into a prescriptive operation planning context and a decision making mode.

  20. Development of a Decision Support System for Analysis and Solutions of Prolonged Standing in the Workplace

    PubMed Central

    Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

    2014-01-01

    Background Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. Methods The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Results Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. Conclusion The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially. PMID:25180141

  1. Application of Effective Discharge Analysis to Environmental Flow Decision-Making.

    PubMed

    McKay, S Kyle; Freeman, Mary C; Covich, Alan P

    2016-06-01

    Well-informed river management decisions rely on an explicit statement of objectives, repeatable analyses, and a transparent system for assessing trade-offs. These components may then be applied to compare alternative operational regimes for water resource infrastructure (e.g., diversions, locks, and dams). Intra- and inter-annual hydrologic variability further complicates these already complex environmental flow decisions. Effective discharge analysis (developed in studies of geomorphology) is a powerful tool for integrating temporal variability of flow magnitude and associated ecological consequences. Here, we adapt the effectiveness framework to include multiple elements of the natural flow regime (i.e., timing, duration, and rate-of-change) as well as two flow variables. We demonstrate this analytical approach using a case study of environmental flow management based on long-term (60 years) daily discharge records in the Middle Oconee River near Athens, GA, USA. Specifically, we apply an existing model for estimating young-of-year fish recruitment based on flow-dependent metrics to an effective discharge analysis that incorporates hydrologic variability and multiple focal taxa. We then compare three alternative methods of environmental flow provision. Percentage-based withdrawal schemes outcompete other environmental flow methods across all levels of water withdrawal and ecological outcomes.

  2. Application of effective discharge analysis to environmental flow decision-making

    USGS Publications Warehouse

    McKay, S. Kyle; Freeman, Mary C.; Covich, A.P.

    2016-01-01

    Well-informed river management decisions rely on an explicit statement of objectives, repeatable analyses, and a transparent system for assessing trade-offs. These components may then be applied to compare alternative operational regimes for water resource infrastructure (e.g., diversions, locks, and dams). Intra- and inter-annual hydrologic variability further complicates these already complex environmental flow decisions. Effective discharge analysis (developed in studies of geomorphology) is a powerful tool for integrating temporal variability of flow magnitude and associated ecological consequences. Here, we adapt the effectiveness framework to include multiple elements of the natural flow regime (i.e., timing, duration, and rate-of-change) as well as two flow variables. We demonstrate this analytical approach using a case study of environmental flow management based on long-term (60 years) daily discharge records in the Middle Oconee River near Athens, GA, USA. Specifically, we apply an existing model for estimating young-of-year fish recruitment based on flow-dependent metrics to an effective discharge analysis that incorporates hydrologic variability and multiple focal taxa. We then compare three alternative methods of environmental flow provision. Percentage-based withdrawal schemes outcompete other environmental flow methods across all levels of water withdrawal and ecological outcomes.

  3. Application of Effective Discharge Analysis to Environmental Flow Decision-Making

    NASA Astrophysics Data System (ADS)

    McKay, S. Kyle; Freeman, Mary C.; Covich, Alan P.

    2016-06-01

    Well-informed river management decisions rely on an explicit statement of objectives, repeatable analyses, and a transparent system for assessing trade-offs. These components may then be applied to compare alternative operational regimes for water resource infrastructure (e.g., diversions, locks, and dams). Intra- and inter-annual hydrologic variability further complicates these already complex environmental flow decisions. Effective discharge analysis (developed in studies of geomorphology) is a powerful tool for integrating temporal variability of flow magnitude and associated ecological consequences. Here, we adapt the effectiveness framework to include multiple elements of the natural flow regime (i.e., timing, duration, and rate-of-change) as well as two flow variables. We demonstrate this analytical approach using a case study of environmental flow management based on long-term (60 years) daily discharge records in the Middle Oconee River near Athens, GA, USA. Specifically, we apply an existing model for estimating young-of-year fish recruitment based on flow-dependent metrics to an effective discharge analysis that incorporates hydrologic variability and multiple focal taxa. We then compare three alternative methods of environmental flow provision. Percentage-based withdrawal schemes outcompete other environmental flow methods across all levels of water withdrawal and ecological outcomes.

  4. Application of Effective Discharge Analysis to Environmental Flow Decision-Making.

    PubMed

    McKay, S Kyle; Freeman, Mary C; Covich, Alan P

    2016-06-01

    Well-informed river management decisions rely on an explicit statement of objectives, repeatable analyses, and a transparent system for assessing trade-offs. These components may then be applied to compare alternative operational regimes for water resource infrastructure (e.g., diversions, locks, and dams). Intra- and inter-annual hydrologic variability further complicates these already complex environmental flow decisions. Effective discharge analysis (developed in studies of geomorphology) is a powerful tool for integrating temporal variability of flow magnitude and associated ecological consequences. Here, we adapt the effectiveness framework to include multiple elements of the natural flow regime (i.e., timing, duration, and rate-of-change) as well as two flow variables. We demonstrate this analytical approach using a case study of environmental flow management based on long-term (60 years) daily discharge records in the Middle Oconee River near Athens, GA, USA. Specifically, we apply an existing model for estimating young-of-year fish recruitment based on flow-dependent metrics to an effective discharge analysis that incorporates hydrologic variability and multiple focal taxa. We then compare three alternative methods of environmental flow provision. Percentage-based withdrawal schemes outcompete other environmental flow methods across all levels of water withdrawal and ecological outcomes. PMID:26961419

  5. Factors influencing first childbearing timing decisions among men: Path analysis

    PubMed Central

    Kariman, Nourossadat; Amerian, Maliheh; Jannati, Padideh; Salmani, Fatemeh

    2016-01-01

    Background: Factors that influence men’s childbearing intentions have been relatively unexplored in the literature. Objective: This study aimed to determine the influencing factors about the first childbearing timing decisions of men. Materials and Methods: In this cross-sectional study, 300 men who were referred to private and governmental healthcare centers in Shahrood, Iran were randomly recruited from April to September 2014. Data were collected using a demographic questionnaire, the Quality of Life Questionnaire; ENRICH Marital Satisfaction Questionnaire, Synder’s Hope Scale, and the Multidimensional Scale of Perceived Social Support. Results: After removing the statistically insignificant paths, men’s age at marriage had the highest direct effect (β=0.86) on their first childbearing decision. Marital satisfaction (β=-0.09), social support (β=0.06), economic status (β=0.06), and quality of life (β=-0.08) were other effective factors on men’s first childbearing decisions. Moreover, marital satisfaction and social support had significant indirect effects on men’s childbearing decisions (β=-0.04 and -0.01, respectively). Conclusion: Many factors, including personal factors (age at marriage and quality of life), family factors (marital satisfaction), and social factors (social support), can affect men’s decision to have a child. Policymakers are hence required to develop strategies to promote the socioeconomic and family conditions of the couples and to encourage them to have as many children as they desire at an appropriate time. PMID:27738661

  6. Image data integration and analysis for natural disaster decision support systems

    NASA Astrophysics Data System (ADS)

    Roper, William E.

    2001-06-01

    Natural disasters have a major impact, globally and within the United States causing injury and loss of life, as well as economic losses. To better address disaster response needs, a task force has been established to leverage technological capabilities to improve disaster response management. Web based geospatial analysis is one of these important capabilities. Samples of geospatial technologies applicable to disaster management are presented. These include 3D visualization, hyperspectral imagery, LIDAR, use of spectral libraries, digital multispectral video, radar imaging systems, photogeologic analysis and geographic information systems. An example scenario of a hurricane with landfall at Mobile, Alabama is used to demonstrate the interoperable use of web-based geospatial information to support decision support systems and assist public information communication.

  7. Randomness in the network inhibits cooperation based on the bounded rational collective altruistic decision

    NASA Astrophysics Data System (ADS)

    Ohdaira, Tetsushi

    2014-07-01

    Previous studies discussing cooperation employ the best decision that every player knows all information regarding the payoff matrix and selects the strategy of the highest payoff. Therefore, they do not discuss cooperation based on the altruistic decision with limited information (bounded rational altruistic decision). In addition, they do not cover the case where every player can submit his/her strategy several times in a match of the game. This paper is based on Ohdaira's reconsideration of the bounded rational altruistic decision, and also employs the framework of the prisoner's dilemma game (PDG) with sequential strategy. The distinction between this study and the Ohdaira's reconsideration is that the former covers the model of multiple groups, but the latter deals with the model of only two groups. Ohdaira's reconsideration shows that the bounded rational altruistic decision facilitates much more cooperation in the PDG with sequential strategy than Ohdaira and Terano's bounded rational second-best decision does. However, the detail of cooperation of multiple groups based on the bounded rational altruistic decision has not been resolved yet. This study, therefore, shows how randomness in the network composed of multiple groups affects the increase of the average frequency of mutual cooperation (cooperation between groups) based on the bounded rational altruistic decision of multiple groups. We also discuss the results of the model in comparison with related studies which employ the best decision.

  8. Decision analyses for optimization of monitoring networks based on uncertainty quantification of model predictions of contaminant transport

    NASA Astrophysics Data System (ADS)

    Vesselinov, V. V.; Harp, D.

    2011-12-01

    Model-based decision making related to environmental management problems is a challenging problem. There has been substantial theoretical research and practical applications related to this problem. However, there are very few cases in which the actual decision analyses have been tested in the field to evaluate their adequacy. Over the last several years, we have performed a series of decision analyses to support optimization of a monitoring network at the Los Alamos National Laboratory (LANL) site. The problem deals with contaminant transport in the regional aquifer beneath the LANL site. At three separate stages, the existing monitoring network was augmented based on analyses of the existing uncertainties; in total, five new monitoring wells were proposed. At each stage, the data collected at the new monitoring wells demonstrated the adequacy of the prior uncertainty and decision analyses. The decision analyses required a detailed estimation of uncertainties in model predictions. Various uncertainties, including measurement errors and uncertainties in the conceptualization and model parameters, contributed to the uncertainties in the model predictions. The decision analyses were computationally intensive requiring on the order of one million model simulations; computational efficiency is achieved using (1) high-performance computing (LANL multiprocessor clusters), (2) novel computational techniques for model analysis, and (3) a simple analytical 3D simulator to simulate contaminant transport. Decision support related to optimal design of monitoring networks required optimization of the proposed new monitoring well locations in order to reduce existing model-prediction uncertainties and environmental risk. An important aspect of the analysis is the application of novel techniques for optimization (SQUADS based on coupling of Particle Swarm and Levenberg-Marquardt optimization methods; Vesselinov & Harp, 2011) and uncertainty quantification (ABAGUS: Agent-Based

  9. Reducing Diagnostic Error with Computer-Based Clinical Decision Support

    ERIC Educational Resources Information Center

    Greenes, Robert A.

    2009-01-01

    Information technology approaches to delivering diagnostic clinical decision support (CDS) are the subject of the papers to follow in the proceedings. These will address the history of CDS and present day approaches (Miller), evaluation of diagnostic CDS methods (Friedman), and the role of clinical documentation in supporting diagnostic decision…

  10. Multiple-Reason Decision Making Based on Automatic Processing

    ERIC Educational Resources Information Center

    Glockner, Andreas; Betsch, Tilmann

    2008-01-01

    It has been repeatedly shown that in decisions under time constraints, individuals predominantly use noncompensatory strategies rather than complex compensatory ones. The authors argue that these findings might be due not to limitations of cognitive capacity but instead to limitations of information search imposed by the commonly used experimental…

  11. Multiple-reason decision making based on automatic processing.

    PubMed

    Glöckner, Andreas; Betsch, Tilmann

    2008-09-01

    It has been repeatedly shown that in decisions under time constraints, individuals predominantly use noncompensatory strategies rather than complex compensatory ones. The authors argue that these findings might be due not to limitations of cognitive capacity but instead to limitations of information search imposed by the commonly used experimental tool Mouselab (J. W. Payne, J. R. Bettman, & E. J. Johnson, 1988). The authors tested this assumption in 3 experiments. In the 1st experiment, information was openly presented, whereas in the 2nd experiment, the standard Mouselab program was used under different time limits. The results indicate that individuals are able to compute weighted additive decision strategies extremely quickly if information search is not restricted by the experimental procedure. In a 3rd experiment, these results were replicated using more complex decision tasks, and the major alternative explanations that individuals use more complex heuristics or that they merely encode the constellation of cues were ruled out. In sum, the findings challenge the fundaments of bounded rationality and highlight the importance of automatic processes in decision making.

  12. Strategy selection in cue-based decision making.

    PubMed

    Bryant, David J

    2014-06-01

    People can make use of a range of heuristic and rational, compensatory strategies to perform a multiple-cue judgment task. It has been proposed that people are sensitive to the amount of cognitive effort required to employ decision strategies. Experiment 1 employed a dual-task methodology to investigate whether participants' preference for heuristic versus compensatory decision strategies can be altered by increasing the cognitive demands of the task. As indicated by participants' decision times, a secondary task interfered more with the performance of a heuristic than compensatory decision strategy but did not affect the proportions of participants using either type of strategy. A stimulus set effect suggested that the conjunction of cue salience and cue validity might play a determining role in strategy selection. The results of Experiment 2 indicated that when a perceptually salient cue was also the most valid, the majority of participants preferred a single-cue heuristic strategy. Overall, the results contradict the view that heuristics are more likely to be adopted when a task is made more cognitively demanding. It is argued that people employ 2 learning processes during training, one an associative learning process in which cue-outcome associations are developed by sampling multiple cues, and another that involves the sequential examination of single cues to serve as a basis for a single-cue heuristic.

  13. A Core Journal Decision Model Based on Weighted Page Rank

    ERIC Educational Resources Information Center

    Wang, Hei-Chia; Chou, Ya-lin; Guo, Jiunn-Liang

    2011-01-01

    Purpose: The paper's aim is to propose a core journal decision method, called the local impact factor (LIF), which can evaluate the requirements of the local user community by combining both the access rate and the weighted impact factor, and by tracking citation information on the local users' articles. Design/methodology/approach: Many…

  14. Strategy selection in cue-based decision making.

    PubMed

    Bryant, David J

    2014-06-01

    People can make use of a range of heuristic and rational, compensatory strategies to perform a multiple-cue judgment task. It has been proposed that people are sensitive to the amount of cognitive effort required to employ decision strategies. Experiment 1 employed a dual-task methodology to investigate whether participants' preference for heuristic versus compensatory decision strategies can be altered by increasing the cognitive demands of the task. As indicated by participants' decision times, a secondary task interfered more with the performance of a heuristic than compensatory decision strategy but did not affect the proportions of participants using either type of strategy. A stimulus set effect suggested that the conjunction of cue salience and cue validity might play a determining role in strategy selection. The results of Experiment 2 indicated that when a perceptually salient cue was also the most valid, the majority of participants preferred a single-cue heuristic strategy. Overall, the results contradict the view that heuristics are more likely to be adopted when a task is made more cognitively demanding. It is argued that people employ 2 learning processes during training, one an associative learning process in which cue-outcome associations are developed by sampling multiple cues, and another that involves the sequential examination of single cues to serve as a basis for a single-cue heuristic. PMID:24884389

  15. Decisions, Science, and Values: Crafting Regulatory Alternatives Analysis.

    PubMed

    Malloy, Timothy; Blake, Ann; Linkov, Igor; Sinsheimer, Peter

    2015-12-01

    Emerging "prevention-based" approaches to chemical regulation seek to minimize the use of toxic chemicals by mandating or directly incentivizing the adoption of viable safer alternative chemicals or processes. California and Maine are beginning to implement such programs, requiring manufacturers of consumer products containing certain chemicals of concern to identify and evaluate potential safer alternatives. In the European Union, the REACH program imposes similar obligations on manufacturers of certain substances of very high concern. Effective prevention-based regulation requires regulatory alternatives analysis (RAA), a methodology for comparing and evaluating the regulated chemical or process and its alternatives across a range of relevant criteria. RAA has both public and private dimensions. To a significant degree, alternatives analysis is an aspect of product design; that is, the process by which private industry designs the goods it sells. Accordingly, an RAA method should reflect the attributes of well-crafted product design tools used by businesses. But RAA adds health and environmental objectives to the mix of concerns taken into account by the product designer. Moreover, as part of a prevention-based regulatory regime, it implicates important public values such as legitimacy, equity, public engagement, and accountability. Thus, an RAA should reflect both private standards and public values, and be evaluated against them. This article adopts that perspective, identifying an integrated set of design principles for RAA, and illustrating the application of those principles. PMID:26299695

  16. Reducing diagnostic error with computer-based clinical decision support.

    PubMed

    Greenes, Robert A

    2009-09-01

    Information technology approaches to delivering diagnostic clinical decision support (CDS) are the subject of the papers to follow in the proceedings. These will address the history of CDS and present day approaches (Miller), evaluation of diagnostic CDS methods (Friedman), and the role of clinical documentation in supporting diagnostic decision making (Schiff). In addition, several other considerations relating to this topic are interesting to ponder. We are moving toward increased understanding of gene regulation and gene expression, identification of biomarkers, and the ability to predict patient response to disease and to tailor treatments to these individual variations-referred to as "personalized" or, more recently, "predictive" medicine. Consequently, diagnostic decision making is more and more linked to management decision making, and generic diagnostic labels like "diabetes" or "colon cancer" will no longer be sufficient, because they don't tell us what to do. Ultimately, if we have more complete data including more structured capture of phenomic data as well as the characterization of the patient's genome, direct prediction from responses of highly refined subsets of similar patients in a database can be used to select appropriate management, the effectiveness of which was demonstrated in projects in selected limited domains as early as the 1970s. In general, there are six classes of methodologies, including the above, which can be applied to delivering CDS. In addition, patients are becoming more knowledgeable and should be regarded as active participants, not only in helping to obtain data but also in their own status assessment and as recipients of decision support. With the above advances, this is a very promising time to be engaged in pursuit of methods of CDS. PMID:19669915

  17. An improved poly(A) motifs recognition method based on decision level fusion.

    PubMed

    Zhang, Shanxin; Han, Jiuqiang; Liu, Jun; Zheng, Jiguang; Liu, Ruiling

    2015-02-01

    Polyadenylation is the process of addition of poly(A) tail to mRNA 3' ends. Identification of motifs controlling polyadenylation plays an essential role in improving genome annotation accuracy and better understanding of the mechanisms governing gene regulation. The bioinformatics methods used for poly(A) motifs recognition have demonstrated that information extracted from sequences surrounding the candidate motifs can differentiate true motifs from the false ones greatly. However, these methods depend on either domain features or string kernels. To date, methods combining information from different sources have not been found yet. Here, we proposed an improved poly(A) motifs recognition method by combing different sources based on decision level fusion. First of all, two novel prediction methods was proposed based on support vector machine (SVM): one method is achieved by using the domain-specific features and principle component analysis (PCA) method to eliminate the redundancy (PCA-SVM); the other method is based on Oligo string kernel (Oligo-SVM). Then we proposed a novel machine-learning method for poly(A) motif prediction by marrying four poly(A) motifs recognition methods, including two state-of-the-art methods (Random Forest (RF) and HMM-SVM), and two novel proposed methods (PCA-SVM and Oligo-SVM). A decision level information fusion method was employed to combine the decision values of different classifiers by applying the DS evidence theory. We evaluated our method on a comprehensive poly(A) dataset that consists of 14,740 samples on 12 variants of poly(A) motifs and 2750 samples containing none of these motifs. Our method has achieved accuracy up to 86.13%. Compared with the four classifiers, our evidence theory based method reduces the average error rate by about 30%, 27%, 26% and 16%, respectively. The experimental results suggest that the proposed method is more effective for poly(A) motif recognition. PMID:25594576

  18. An improved poly(A) motifs recognition method based on decision level fusion.

    PubMed

    Zhang, Shanxin; Han, Jiuqiang; Liu, Jun; Zheng, Jiguang; Liu, Ruiling

    2015-02-01

    Polyadenylation is the process of addition of poly(A) tail to mRNA 3' ends. Identification of motifs controlling polyadenylation plays an essential role in improving genome annotation accuracy and better understanding of the mechanisms governing gene regulation. The bioinformatics methods used for poly(A) motifs recognition have demonstrated that information extracted from sequences surrounding the candidate motifs can differentiate true motifs from the false ones greatly. However, these methods depend on either domain features or string kernels. To date, methods combining information from different sources have not been found yet. Here, we proposed an improved poly(A) motifs recognition method by combing different sources based on decision level fusion. First of all, two novel prediction methods was proposed based on support vector machine (SVM): one method is achieved by using the domain-specific features and principle component analysis (PCA) method to eliminate the redundancy (PCA-SVM); the other method is based on Oligo string kernel (Oligo-SVM). Then we proposed a novel machine-learning method for poly(A) motif prediction by marrying four poly(A) motifs recognition methods, including two state-of-the-art methods (Random Forest (RF) and HMM-SVM), and two novel proposed methods (PCA-SVM and Oligo-SVM). A decision level information fusion method was employed to combine the decision values of different classifiers by applying the DS evidence theory. We evaluated our method on a comprehensive poly(A) dataset that consists of 14,740 samples on 12 variants of poly(A) motifs and 2750 samples containing none of these motifs. Our method has achieved accuracy up to 86.13%. Compared with the four classifiers, our evidence theory based method reduces the average error rate by about 30%, 27%, 26% and 16%, respectively. The experimental results suggest that the proposed method is more effective for poly(A) motif recognition.

  19. Design Decisions in Developing Learning Trajectories-Based Assessments in Mathematics: A Case Study

    ERIC Educational Resources Information Center

    Penuel, William R.; Confrey, Jere; Maloney, Alan; Rupp, André A.

    2014-01-01

    This article analyzes the design decisions of a team developing diagnostic assessments for a learning trajectory focused on rational number reasoning. The analysis focuses on the design rationale for key decisions about how to develop the cognitive assessments and related validity arguments within a fluid state and national policy context. The…

  20. Decision analysis framing study; in-valley drainage management strategies for the western San Joaquin Valley, California

    USGS Publications Warehouse

    Presser, Theresa S.; Jenni, Karen E.; Nieman, Timothy; Coleman, James

    2010-01-01

    Constraints on drainage management in the western San Joaquin Valley and implications of proposed approaches to management were recently evaluated by the U.S. Geological Survey (USGS). The USGS found that a significant amount of data for relevant technical issues was available and that a structured, analytical decision support tool could help optimize combinations of specific in-valley drainage management strategies, address uncertainties, and document underlying data analysis for future use. To follow-up on USGS's technical analysis and to help define a scientific basis for decisionmaking in implementing in-valley drainage management strategies, this report describes the first step (that is, a framing study) in a Decision Analysis process. In general, a Decision Analysis process includes four steps: (1) problem framing to establish the scope of the decision problem(s) and a set of fundamental objectives to evaluate potential solutions, (2) generation of strategies to address identified decision problem(s), (3) identification of uncertainties and their relationships, and (4) construction of a decision support model. Participation in such a systematic approach can help to promote consensus and to build a record of qualified supporting data for planning and implementation. In December 2008, a Decision Analysis framing study was initiated with a series of meetings designed to obtain preliminary input from key stakeholder groups on the scope of decisions relevant to drainage management that were of interest to them, and on the fundamental objectives each group considered relevant to those decisions. Two key findings of this framing study are: (1) participating stakeholders have many drainage management objectives in common; and (2) understanding the links between drainage management and water management is necessary both for sound science-based decisionmaking and for resolving stakeholder differences about the value of proposed drainage management solutions. Citing

  1. Understandings of the nature of science and decision making on science and technology-based issues

    NASA Astrophysics Data System (ADS)

    Bell, Randy Lee

    Current reforms emphasize the development of scientific literacy as the principal goal of science education. The nature of science is considered a critical component of scientific literacy and is assumed to be an important factor in decision making on science and technology based issues. However, little research exists that delineates the role of the nature of science in decision making. The purpose of this investigation was to explicate the role of the nature of science in decision making on science and technology based issues and to delineate the reasoning and factors associated with these types of decisions. The 15-item, open-ended "Decision Making Questionnaire" (DMQ) based on four different scenarios concerning science and technology issues was developed to assess decision making. Twenty-one volunteer participants purposively selected from the faculty of geographically diverse universities completed the questionnaire and follow-up interviews. Participants were subsequently grouped according to their understandings of the nature of science, based on responses to a second open-ended questionnaire and follow-up interview. Profiles of each group's decision making were constructed, based on their previous responses to the DMQ and follow-up interviews. Finally, the two groups' decisions, decision making factors, and decision making strategies were compared. No differences were found between the decisions of the two groups, despite their disparate views of the nature of science. While their reasoning did not follow formal lines of argumentation, several influencing factors and general reasoning patterns were identified. Participants in both groups based their decisions primarily on personal values, morals/ethics, and social concerns. While all participants said they considered scientific evidence in their decision making, most did not require absolute "proof," even though Group B participants held more absolute conceptions of the nature of science. Overall, the

  2. A novel anomaly detection approach based on clustering and decision-level fusion

    NASA Astrophysics Data System (ADS)

    Zhong, Shengwei; Zhang, Ye

    2015-09-01

    In hyperspectral image processing, anomaly detection is a valuable way of searching targets whose spectral characteristics are not known, and the estimation of background signals is the key procedure. On account of the high dimensionality and complexity of hyperspectral image, dimensionality reduction and background suppression is necessary. In addition, the complementarity of different anomaly detection algorithms can be utilized to improve the effectiveness of anomaly detection. In this paper, we propose a novel method of anomaly detection, which is based on clustering of optimized K-means and decision-level fusion. In our proposed method, pixels with similar features are firstly clustered using an optimized k-means method. Secondly, dimensionality reduction is conducted using principle component analysis to reduce the amount of calculation. Then, to increase the accuracy of detection and decrease the false-alarm ratio, both Reed-Xiaoli (RX) and Kernel RX algorithm are used on processed image. Lastly, a decision-level fusion is processed on the detection results. A simulated hyperspectral image and a real hyperspectral one are both used to evaluate the performance of our proposed method. Visual analysis and quantative analysis of receiver operating characteristic (ROC) curves show that our algorithm can achieve better performance when compared with other classic approaches and state-of-the-art approaches.

  3. A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

    PubMed

    Clark, Renee M; Besterfield-Sacre, Mary E

    2009-03-01

    We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.

  4. A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

    PubMed

    Clark, Renee M; Besterfield-Sacre, Mary E

    2009-03-01

    We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk. PMID:19087232

  5. Medical decision analysis for first-line therapy of chronic myeloid leukemia.

    PubMed

    Rochau, Ursula; Sroczynski, Gaby; Wolf, Dominik; Schmidt, Stefan; Conrads-Frank, Annette; Jahn, Beate; Saverno, Kim; Brixner, Diana; Radich, Jerald; Gastl, Guenther; Siebert, Uwe

    2014-08-01

    Several tyrosine kinase inhibitors (TKIs) are approved for the treatment of chronic myeloid leukemia (CML). Our goal was to develop a clinical decision-analytic model for evaluation of the long-term effectiveness of different therapy regimens. We developed a Markov cohort model with a lifelong time horizon for first-line treatment with imatinib, dasatinib or nilotinib. Seven strategies including combinations of TKIs, chemotherapy and stem cell transplant were evaluated. The model was parameterized using published trial data, the Austrian CML registry and practice patterns estimated by experts. Health outcomes evaluated were life-years (LYs) and quality-adjusted LYs (QALYs). Based on our decision analysis, dasatinib following nilotinib failure was the most effective treatment in terms of LYs (19.8 LYs) and QALYs (16.1 QALYs). Sensitivity analyses showed that the ranking of strategies was mostly influenced by the duration of first- and second-line therapies. Our results may support decision-making regarding the sequential application of TKIs. PMID:24160847

  6. Radiological emergency response for community agencies with cognitive task analysis, risk analysis, and decision support framework.

    PubMed

    Meyer, Travis S; Muething, Joseph Z; Lima, Gustavo Amoras Souza; Torres, Breno Raemy Rangel; del Rosario, Trystyn Keia; Gomes, José Orlando; Lambert, James H

    2012-01-01

    Radiological nuclear emergency responders must be able to coordinate evacuation and relief efforts following the release of radioactive material into populated areas. In order to respond quickly and effectively to a nuclear emergency, high-level coordination is needed between a number of large, independent organizations, including police, military, hazmat, and transportation authorities. Given the complexity, scale, time-pressure, and potential negative consequences inherent in radiological emergency responses, tracking and communicating information that will assist decision makers during a crisis is crucial. The emergency response team at the Angra dos Reis nuclear power facility, located outside of Rio de Janeiro, Brazil, presently conducts emergency response simulations once every two years to prepare organizational leaders for real-life emergency situations. However, current exercises are conducted without the aid of electronic or software tools, resulting in possible cognitive overload and delays in decision-making. This paper describes the development of a decision support system employing systems methodologies, including cognitive task analysis and human-machine interface design. The decision support system can aid the coordination team by automating cognitive functions and improving information sharing. A prototype of the design will be evaluated by plant officials in Brazil and incorporated to a future trial run of a response simulation.

  7. Radiological emergency response for community agencies with cognitive task analysis, risk analysis, and decision support framework.

    PubMed

    Meyer, Travis S; Muething, Joseph Z; Lima, Gustavo Amoras Souza; Torres, Breno Raemy Rangel; del Rosario, Trystyn Keia; Gomes, José Orlando; Lambert, James H

    2012-01-01

    Radiological nuclear emergency responders must be able to coordinate evacuation and relief efforts following the release of radioactive material into populated areas. In order to respond quickly and effectively to a nuclear emergency, high-level coordination is needed between a number of large, independent organizations, including police, military, hazmat, and transportation authorities. Given the complexity, scale, time-pressure, and potential negative consequences inherent in radiological emergency responses, tracking and communicating information that will assist decision makers during a crisis is crucial. The emergency response team at the Angra dos Reis nuclear power facility, located outside of Rio de Janeiro, Brazil, presently conducts emergency response simulations once every two years to prepare organizational leaders for real-life emergency situations. However, current exercises are conducted without the aid of electronic or software tools, resulting in possible cognitive overload and delays in decision-making. This paper describes the development of a decision support system employing systems methodologies, including cognitive task analysis and human-machine interface design. The decision support system can aid the coordination team by automating cognitive functions and improving information sharing. A prototype of the design will be evaluated by plant officials in Brazil and incorporated to a future trial run of a response simulation. PMID:22317163

  8. Multi-criteria multi-stakeholder decision analysis using a fuzzy-stochastic approach for hydrosystem management

    NASA Astrophysics Data System (ADS)

    Subagadis, Y. H.; Schütze, N.; Grundmann, J.

    2014-09-01

    The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water-society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA) using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

  9. Doubly Bayesian Analysis of Confidence in Perceptual Decision-Making

    PubMed Central

    Bahrami, Bahador; Latham, Peter E.

    2015-01-01

    Humans stand out from other animals in that they are able to explicitly report on the reliability of their internal operations. This ability, which is known as metacognition, is typically studied by asking people to report their confidence in the correctness of some decision. However, the computations underlying confidence reports remain unclear. In this paper, we present a fully Bayesian method for directly comparing models of confidence. Using a visual two-interval forced-choice task, we tested whether confidence reports reflect heuristic computations (e.g. the magnitude of sensory data) or Bayes optimal ones (i.e. how likely a decision is to be correct given the sensory data). In a standard design in which subjects were first asked to make a decision, and only then gave their confidence, subjects were mostly Bayes optimal. In contrast, in a less-commonly used design in which subjects indicated their confidence and decision simultaneously, they were roughly equally likely to use the Bayes optimal strategy or to use a heuristic but suboptimal strategy. Our results suggest that, while people’s confidence reports can reflect Bayes optimal computations, even a small unusual twist or additional element of complexity can prevent optimality. PMID:26517475

  10. Situated Analysis of Team Handball Players' Decisions: An Exploratory Study

    ERIC Educational Resources Information Center

    Lenzen, Benoit; Theunissen, Catherine; Cloes, Marc

    2009-01-01

    This exploratory study aimed to investigate elements involved in decision making in team handball live situations and to provide coaches and educators with teaching recommendations. The study was positioned within the framework of the situated-action paradigm of which two aspects were of particular interest for this project: (a) the relationship…

  11. Doubly Bayesian Analysis of Confidence in Perceptual Decision-Making.

    PubMed

    Aitchison, Laurence; Bang, Dan; Bahrami, Bahador; Latham, Peter E

    2015-10-01

    Humans stand out from other animals in that they are able to explicitly report on the reliability of their internal operations. This ability, which is known as metacognition, is typically studied by asking people to report their confidence in the correctness of some decision. However, the computations underlying confidence reports remain unclear. In this paper, we present a fully Bayesian method for directly comparing models of confidence. Using a visual two-interval forced-choice task, we tested whether confidence reports reflect heuristic computations (e.g. the magnitude of sensory data) or Bayes optimal ones (i.e. how likely a decision is to be correct given the sensory data). In a standard design in which subjects were first asked to make a decision, and only then gave their confidence, subjects were mostly Bayes optimal. In contrast, in a less-commonly used design in which subjects indicated their confidence and decision simultaneously, they were roughly equally likely to use the Bayes optimal strategy or to use a heuristic but suboptimal strategy. Our results suggest that, while people's confidence reports can reflect Bayes optimal computations, even a small unusual twist or additional element of complexity can prevent optimality. PMID:26517475

  12. Ethanol or Biodiesel? A Systems-Analysis Decision

    ERIC Educational Resources Information Center

    Dinan, Frank; Stabler, Tom

    2008-01-01

    This case study stresses the need to broadly consider an entire system, including all of the energy inputs and outputs involved, to determine the real efficiency of that system. It also asks its student audience to consider the role that scientific input plays in policy decision-making processes. It emphasizes that, despite the importance of this…

  13. The Role of Research and Analysis in Resource Allocation Decisions

    ERIC Educational Resources Information Center

    Lea, Dennis; Polster, Patty Poppe

    2011-01-01

    In a time of diminishing resources and increased accountability, it is important for school leaders to make the most of every dollar they spend. One approach to ensuring responsible resource allocation is to closely examine the organizational culture surrounding decision making and provide a structure and process to incorporate research and data…

  14. Marital Decision Making: A Language-Action Analysis.

    ERIC Educational Resources Information Center

    Krueger, Dorothy Lenk

    A study analyzed the decision making process of a dual-career married couple debating whether they should relocate for his or her career. Their interaction was examined and interpreted through multiple components of conversational context, such as institutional constraints influencing the couple, their shared knowledge and perceptions, the…

  15. Managerial Analysis and Decision Support: A Guidebook and Case Studies

    ERIC Educational Resources Information Center

    National Association of College and University Business Officers (NJ3), 2004

    2004-01-01

    Developed and edited by the National Association of College and University Business Officers' (NACUBO's) Accounting Principles Council, this guidebook, written by highly experienced, seasoned college and university leaders, is designed to help readers make sense of today's world and provide the right tools to make the right decisions. The book,…

  16. Strategic rehabilitation planning of piped water networks using multi-criteria decision analysis.

    PubMed

    Scholten, Lisa; Scheidegger, Andreas; Reichert, Peter; Maurer, Max; Mauer, Max; Lienert, Judit

    2014-02-01

    To overcome the difficulties of strategic asset management of water distribution networks, a pipe failure and a rehabilitation model are combined to predict the long-term performance of rehabilitation strategies. Bayesian parameter estimation is performed to calibrate the failure and replacement model based on a prior distribution inferred from three large water utilities in Switzerland. Multi-criteria decision analysis (MCDA) and scenario planning build the framework for evaluating 18 strategic rehabilitation alternatives under future uncertainty. Outcomes for three fundamental objectives (low costs, high reliability, and high intergenerational equity) are assessed. Exploitation of stochastic dominance concepts helps to identify twelve non-dominated alternatives and local sensitivity analysis of stakeholder preferences is used to rank them under four scenarios. Strategies with annual replacement of 1.5-2% of the network perform reasonably well under all scenarios. In contrast, the commonly used reactive replacement is not recommendable unless cost is the only relevant objective. Exemplified for a small Swiss water utility, this approach can readily be adapted to support strategic asset management for any utility size and based on objectives and preferences that matter to the respective decision makers.

  17. Application of multicriteria decision analysis in health care: a systematic review and bibliometric analysis

    PubMed Central

    Adunlin, Georges; Diaby, Vakaramoko; Xiao, Hong

    2015-01-01

    Background The use of Multi-Criteria Decision Analysis (MCDA) in health care has become common. However, the literature lacks systematic review trend analysis on the application of MCDA in health care. Aim To systematically identify applications of MCDA to the areas of health care, and to report on publication trends. Methods English language studies published from January 1, 1980 until October 1, 2013 were included. Electronic databases searches were supplemented by searching conference proceedings and relevant journals. Studies considered for inclusion were those using MCDA techniques within the areas of health care, and involving the participation of decision makers. A bibliometric analysis was undertaken to present the publication trends. Results A total of 66 citations met the inclusion criteria. An increase in publication trend occurred in the years 1990, 1997, 1999, 2005, 2008, and 2012. For the remaining years, the publication trend was either steady or declining. The trend shows that the number of publications reached its highest peak in 2012 (n = 9). Medical Decision Making was the dominant with the highest number published papers (n = 7). The majority of the studies were conducted in the US (n = 29). Medical Decision Making journal published the highest number of articles (n = 7). Analytic Hierarchy Process (n = 33) was the most used MCDA technique. Cancer was the most researched disease topic (n = 12). The most covered area of application was diagnosis and treatment (n = 26). Conclusion The review shows that MCDA has been applied to a broad range of areas in the health care, with the use of a variety of methodological approaches. Further research is needed to develop practice guidelines for the appropriate application and reporting of MCDA methods. PMID:25327341

  18. A decision-theory approach to interpretable set analysis for high-dimensional data.

    PubMed

    Boca, Simina M; Bravo, Héctor Céorrada; Caffo, Brian; Leek, Jeffrey T; Parmigiani, Giovanni

    2013-09-01

    A key problem in high-dimensional significance analysis is to find pre-defined sets that show enrichment for a statistical signal of interest; the classic example is the enrichment of gene sets for differentially expressed genes. Here, we propose a new decision-theory approach to the analysis of gene sets which focuses on estimating the fraction of non-null variables in a set. We introduce the idea of "atoms," non-overlapping sets based on the original pre-defined set annotations. Our approach focuses on finding the union of atoms that minimizes a weighted average of the number of false discoveries and missed discoveries. We introduce a new false discovery rate for sets, called the atomic false discovery rate (afdr), and prove that the optimal estimator in our decision-theory framework is to threshold the afdr. These results provide a coherent and interpretable framework for the analysis of sets that addresses the key issues of overlapping annotations and difficulty in interpreting p values in both competitive and self-contained tests. We illustrate our method and compare it to a popular existing method using simulated examples, as well as gene-set and brain ROI data analyses.

  19. A decision-theory approach to interpretable set analysis for high-dimensional data.

    PubMed

    Boca, Simina M; Bravo, Héctor Céorrada; Caffo, Brian; Leek, Jeffrey T; Parmigiani, Giovanni

    2013-09-01

    A key problem in high-dimensional significance analysis is to find pre-defined sets that show enrichment for a statistical signal of interest; the classic example is the enrichment of gene sets for differentially expressed genes. Here, we propose a new decision-theory approach to the analysis of gene sets which focuses on estimating the fraction of non-null variables in a set. We introduce the idea of "atoms," non-overlapping sets based on the original pre-defined set annotations. Our approach focuses on finding the union of atoms that minimizes a weighted average of the number of false discoveries and missed discoveries. We introduce a new false discovery rate for sets, called the atomic false discovery rate (afdr), and prove that the optimal estimator in our decision-theory framework is to threshold the afdr. These results provide a coherent and interpretable framework for the analysis of sets that addresses the key issues of overlapping annotations and difficulty in interpreting p values in both competitive and self-contained tests. We illustrate our method and compare it to a popular existing method using simulated examples, as well as gene-set and brain ROI data analyses. PMID:23909925

  20. A Cercla-Based Decision Model to Support Remedy Selection for an Uncertain Volume of Contaminants at a DOE Facility

    SciTech Connect

    Christine E. Kerschus

    1999-03-31

    The Paducah Gaseous Diffusion Plant (PGDP) operated by the Department of Energy is challenged with selecting the appropriate remediation technology to cleanup contaminants at Waste Area Group (WAG) 6. This research utilizes value-focused thinking and multiattribute preference theory concepts to produce a decision analysis model designed to aid the decision makers in their selection process. The model is based on CERCLA's five primary balancing criteria, tailored specifically to WAG 6 and the contaminants of concern, utilizes expert opinion and the best available engineering, cost, and performance data, and accounts for uncertainty in contaminant volume. The model ranks 23 remediation technologies (trains) in their ability to achieve the CERCLA criteria at various contaminant volumes. A sensitivity analysis is performed to examine the effects of changes in expert opinion and uncertainty in volume. Further analysis reveals how volume uncertainty is expected to affect technology cost, time and ability to meet the CERCLA criteria. The model provides the decision makers with a CERCLA-based decision analysis methodology that is objective, traceable, and robust to support the WAG 6 Feasibility Study. In addition, the model can be adjusted to address other DOE contaminated sites.

  1. Decision Analysis Methods Used to Make Appropriate Investments in Human Exploration Capabilities and Technologies

    NASA Technical Reports Server (NTRS)

    Williams-Byrd, Julie; Arney, Dale C.; Hay, Jason; Reeves, John D.; Craig, Douglas

    2016-01-01

    NASA is transforming human spaceflight. The Agency is shifting from an exploration-based program with human activities in low Earth orbit (LEO) and targeted robotic missions in deep space to a more sustainable and integrated pioneering approach. Through pioneering, NASA seeks to address national goals to develop the capacity for people to work, learn, operate, live, and thrive safely beyond Earth for extended periods of time. However, pioneering space involves daunting technical challenges of transportation, maintaining health, and enabling crew productivity for long durations in remote, hostile, and alien environments. Prudent investments in capability and technology developments, based on mission need, are critical for enabling a campaign of human exploration missions. There are a wide variety of capabilities and technologies that could enable these missions, so it is a major challenge for NASA's Human Exploration and Operations Mission Directorate (HEOMD) to make knowledgeable portfolio decisions. It is critical for this pioneering initiative that these investment decisions are informed with a prioritization process that is robust and defensible. It is NASA's role to invest in targeted technologies and capabilities that would enable exploration missions even though specific requirements have not been identified. To inform these investments decisions, NASA's HEOMD has supported a variety of analysis activities that prioritize capabilities and technologies. These activities are often based on input from subject matter experts within the NASA community who understand the technical challenges of enabling human exploration missions. This paper will review a variety of processes and methods that NASA has used to prioritize and rank capabilities and technologies applicable to human space exploration. The paper will show the similarities in the various processes and showcase instances were customer specified priorities force modifications to the process. Specifically

  2. Distinct and Overlapping Brain Areas Engaged during Value-Based, Mathematical, and Emotional Decision Processing

    PubMed Central

    Hsu, Chun-Wei; Goh, Joshua O. S.

    2016-01-01

    When comparing between the values of different choices, human beings can rely on either more cognitive processes, such as using mathematical computation, or more affective processes, such as using emotion. However, the neural correlates of how these two types of processes operate during value-based decision-making remain unclear. In this study, we investigated the extent to which neural regions engaged during value-based decision-making overlap with those engaged during mathematical and emotional processing in a within-subject manner. In a functional magnetic resonance imaging experiment, participants viewed stimuli that always consisted of numbers and emotional faces that depicted two choices. Across tasks, participants decided between the two choices based on the expected value of the numbers, a mathematical result of the numbers, or the emotional face stimuli. We found that all three tasks commonly involved various cortical areas including frontal, parietal, motor, somatosensory, and visual regions. Critically, the mathematical task shared common areas with the value but not emotion task in bilateral striatum. Although the emotion task overlapped with the value task in parietal, motor, and sensory areas, the mathematical task also evoked responses in other areas within these same cortical structures. Minimal areas were uniquely engaged for the value task apart from the other two tasks. The emotion task elicited a more expansive area of neural activity whereas value and mathematical task responses were in more focal regions. Whole-brain spatial correlation analysis showed that valuative processing engaged functional brain responses more similarly to mathematical processing than emotional processing. While decisions on expected value entail both mathematical and emotional processing regions, mathematical processes have a more prominent contribution particularly in subcortical processes. PMID:27375466

  3. Distinct and Overlapping Brain Areas Engaged during Value-Based, Mathematical, and Emotional Decision Processing.

    PubMed

    Hsu, Chun-Wei; Goh, Joshua O S

    2016-01-01

    When comparing between the values of different choices, human beings can rely on either more cognitive processes, such as using mathematical computation, or more affective processes, such as using emotion. However, the neural correlates of how these two types of processes operate during value-based decision-making remain unclear. In this study, we investigated the extent to which neural regions engaged during value-based decision-making overlap with those engaged during mathematical and emotional processing in a within-subject manner. In a functional magnetic resonance imaging experiment, participants viewed stimuli that always consisted of numbers and emotional faces that depicted two choices. Across tasks, participants decided between the two choices based on the expected value of the numbers, a mathematical result of the numbers, or the emotional face stimuli. We found that all three tasks commonly involved various cortical areas including frontal, parietal, motor, somatosensory, and visual regions. Critically, the mathematical task shared common areas with the value but not emotion task in bilateral striatum. Although the emotion task overlapped with the value task in parietal, motor, and sensory areas, the mathematical task also evoked responses in other areas within these same cortical structures. Minimal areas were uniquely engaged for the value task apart from the other two tasks. The emotion task elicited a more expansive area of neural activity whereas value and mathematical task responses were in more focal regions. Whole-brain spatial correlation analysis showed that valuative processing engaged functional brain responses more similarly to mathematical processing than emotional processing. While decisions on expected value entail both mathematical and emotional processing regions, mathematical processes have a more prominent contribution particularly in subcortical processes. PMID:27375466

  4. Ex post power economic analysis of record of decision operational restrictions at Glen Canyon Dam.

    SciTech Connect

    Veselka, T. D.; Poch, L. A.; Palmer, C. S.; Loftin, S.; Osiek, B; Decision and Information Sciences; Western Area Power Administration

    2010-07-31

    On October 9, 1996, Bruce Babbitt, then-Secretary of the U.S. Department of the Interior signed the Record of Decision (ROD) on operating criteria for the Glen Canyon Dam (GCD). Criteria selected were based on the Modified Low Fluctuating Flow (MLFF) Alternative as described in the Operation of Glen Canyon Dam, Colorado River Storage Project, Arizona, Final Environmental Impact Statement (EIS) (Reclamation 1995). These restrictions reduced the operating flexibility of the hydroelectric power plant and therefore its economic value. The EIS provided impact information to support the ROD, including an analysis of operating criteria alternatives on power system economics. This ex post study reevaluates ROD power economic impacts and compares these results to the economic analysis performed prior (ex ante) to the ROD for the MLFF Alternative. On the basis of the methodology used in the ex ante analysis, anticipated annual economic impacts of the ROD were estimated to range from approximately $15.1 million to $44.2 million in terms of 1991 dollars ($1991). This ex post analysis incorporates historical events that took place between 1997 and 2005, including the evolution of power markets in the Western Electricity Coordinating Council as reflected in market prices for capacity and energy. Prompted by ROD operational restrictions, this analysis also incorporates a decision made by the Western Area Power Administration to modify commitments that it made to its customers. Simulated operations of GCD were based on the premise that hourly production patterns would maximize the economic value of the hydropower resource. On the basis of this assumption, it was estimated that economic impacts were on average $26.3 million in $1991, or $39 million in $2009.

  5. The development of a multi-criteria decision analysis aid to help with contraceptive choices: My Contraception Tool.

    PubMed

    French, Rebecca S; Cowan, Frances M; Wellings, Kaye; Dowie, Jack

    2014-04-01

    My Contraception Tool (MCT) applies the principles of multi-criteria decision analysis to the choice of contraceptive method. Its purpose is to make the decision-making process transparent to the user and to suggest a method to them based on their own preferences. The contraceptive option that emerges as optimal from the analysis takes account of the probability of a range of outcomes and the relative weight ascribed to them by the user. The development of MCT was a collaborative project between London School of Hygiene & Tropical Medicine, Brook, FPA and Maldaba Ltd. MCT is available online via the Brook and FPA websites. In this article we describe MCT's development and how it works. Further work is needed to assess the impact it has on decision quality and contraceptive behaviour.

  6. Decision Engines for Software Analysis Using Satisfiability Modulo Theories Solvers

    NASA Technical Reports Server (NTRS)

    Bjorner, Nikolaj

    2010-01-01

    The area of software analysis, testing and verification is now undergoing a revolution thanks to the use of automated and scalable support for logical methods. A well-recognized premise is that at the core of software analysis engines is invariably a component using logical formulas for describing states and transformations between system states. The process of using this information for discovering and checking program properties (including such important properties as safety and security) amounts to automatic theorem proving. In particular, theorem provers that directly support common software constructs offer a compelling basis. Such provers are commonly called satisfiability modulo theories (SMT) solvers. Z3 is a state-of-the-art SMT solver. It is developed at Microsoft Research. It can be used to check the satisfiability of logical formulas over one or more theories such as arithmetic, bit-vectors, lists, records and arrays. The talk describes some of the technology behind modern SMT solvers, including the solver Z3. Z3 is currently mainly targeted at solving problems that arise in software analysis and verification. It has been applied to various contexts, such as systems for dynamic symbolic simulation (Pex, SAGE, Vigilante), for program verification and extended static checking (Spec#/Boggie, VCC, HAVOC), for software model checking (Yogi, SLAM), model-based design (FORMULA), security protocol code (F7), program run-time analysis and invariant generation (VS3). We will describe how it integrates support for a variety of theories that arise naturally in the context of the applications. There are several new promising avenues and the talk will touch on some of these and the challenges related to SMT solvers. Proceedings

  7. A new web-based framework development for fuzzy multi-criteria group decision-making.

    PubMed

    Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

    2016-01-01

    Fuzzy multi-criteria group decision making (FMCGDM) process is usually used when a group of decision-makers faces imprecise data or linguistic variables to solve the problems. However, this process contains many methods that require many time-consuming calculations depending on the number of criteria, alternatives and decision-makers in order to reach the optimal solution. In this study, a web-based FMCGDM framework that offers decision-makers a fast and reliable response service is proposed. The proposed framework includes commonly used tools for multi-criteria decision-making problems such as fuzzy Delphi, fuzzy AHP and fuzzy TOPSIS methods. The integration of these methods enables taking advantages of the strengths and complements each method's weakness. Finally, a case study of location selection for landfill waste in Morocco is performed to demonstrate how this framework can facilitate decision-making process. The results demonstrate that the proposed framework can successfully accomplish the goal of this study.

  8. Autonomous mobile robot fast hybrid decision system DT-FAM based on laser system measurement LSM

    NASA Astrophysics Data System (ADS)

    Będkowski, Janusz; Jankowski, Stanisław

    2006-10-01

    In this paper the new intelligent data processing system for mobile robot is described. The robot perception uses the LSM - Laser System Measurement. The innovative fast hybrid decision system is based on fuzzy ARTMAP supported by decision tree. The virtual laboratory of robotics was implemented to execute experiments.

  9. Optimal and Nonoptimal Computer-Based Test Designs for Making Pass-Fail Decisions

    ERIC Educational Resources Information Center

    Hambleton, Ronald K.; Xing, Dehui

    2006-01-01

    Now that many credentialing exams are being routinely administered by computer, new computer-based test designs, along with item response theory models, are being aggressively researched to identify specific designs that can increase the decision consistency and accuracy of pass-fail decisions. The purpose of this study was to investigate the…

  10. School-Based Management: An Approach to Decision-Making Quality in Egyptian General Secondary Schools

    ERIC Educational Resources Information Center

    Elmelegy, Reda Ibrahim

    2015-01-01

    The current research aims at clarifying how school-based management (SBM) can contribute to achieve the decision-making quality in Egyptian general secondary schools and determine the requirements of quality decision-making. It depends on the descriptive method in order to acknowledge the basics of the SBM and its relationship with the quality of…

  11. Introduction to Decision Support Systems for Risk Based Management of Contaminated Sites

    EPA Science Inventory

    A book on Decision Support Systems for Risk-based Management of contaminated sites is appealing for two reasons. First, it addresses the problem of contaminated sites, which has worldwide importance. Second, it presents Decision Support Systems (DSSs), which are powerful comput...

  12. Distance-Based and Distributed Learning: A Decision Tool for Education Leaders.

    ERIC Educational Resources Information Center

    McGraw, Tammy M.; Ross, John D.

    This decision tool presents a progression of data collection and decision-making strategies that can increase the effectiveness of distance-based or distributed learning instruction. A narrative and flow chart cover the following steps: (1) basic assumptions, including purpose of instruction, market scan, and financial resources; (2) needs…

  13. Multiple Criteria Decision Analysis for Health Care Decision Making--An Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force.

    PubMed

    Thokala, Praveen; Devlin, Nancy; Marsh, Kevin; Baltussen, Rob; Boysen, Meindert; Kalo, Zoltan; Longrenn, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Ijzerman, Maarten

    2016-01-01

    Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting, objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making and a set of techniques, known under the collective heading multiple criteria decision analysis (MCDA), are useful for this purpose. MCDA methods are widely used in other sectors, and recently there has been an increase in health care applications. In 2014, ISPOR established an MCDA Emerging Good Practices Task Force. It was charged with establishing a common definition for MCDA in health care decision making and developing good practice guidelines for conducting MCDA to aid health care decision making. This initial ISPOR MCDA task force report provides an introduction to MCDA - it defines MCDA; provides examples of its use in different kinds of decision making in health care (including benefit risk analysis, health technology assessment, resource allocation, portfolio decision analysis, shared patient clinician decision making and prioritizing patients' access to services); provides an overview of the principal methods of MCDA; and describes the key steps involved. Upon reviewing this report, readers should have a solid overview of MCDA methods and their potential for supporting health care decision making. PMID:26797229

  14. Multiple Criteria Decision Analysis for Health Care Decision Making--An Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force.

    PubMed

    Thokala, Praveen; Devlin, Nancy; Marsh, Kevin; Baltussen, Rob; Boysen, Meindert; Kalo, Zoltan; Longrenn, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Ijzerman, Maarten

    2016-01-01

    Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting, objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making and a set of techniques, known under the collective heading multiple criteria decision analysis (MCDA), are useful for this purpose. MCDA methods are widely used in other sectors, and recently there has been an increase in health care applications. In 2014, ISPOR established an MCDA Emerging Good Practices Task Force. It was charged with establishing a common definition for MCDA in health care decision making and developing good practice guidelines for conducting MCDA to aid health care decision making. This initial ISPOR MCDA task force report provides an introduction to MCDA - it defines MCDA; provides examples of its use in different kinds of decision making in health care (including benefit risk analysis, health technology assessment, resource allocation, portfolio decision analysis, shared patient clinician decision making and prioritizing patients' access to services); provides an overview of the principal methods of MCDA; and describes the key steps involved. Upon reviewing this report, readers should have a solid overview of MCDA methods and their potential for supporting health care decision making.

  15. When is enough evidence enough? - Using systematic decision analysis and value-of-information analysis to determine the need for further evidence.

    PubMed

    Siebert, Uwe; Rochau, Ursula; Claxton, Karl

    2013-01-01

    Decision analysis (DA) and value-of-information (VOI) analysis provide a systematic, quantitative methodological framework that explicitly considers the uncertainty surrounding the currently available evidence to guide healthcare decisions. In medical decision making under uncertainty, there are two fundamental questions: 1) What decision should be made now given the best available evidence (and its uncertainty)?; 2) Subsequent to the current decision and given the magnitude of the remaining uncertainty, should we gather further evidence (i.e., perform additional studies), and if yes, which studies should be undertaken (e.g., efficacy, side effects, quality of life, costs), and what sample sizes are needed? Using the currently best available evidence, VoI analysis focuses on the likelihood of making a wrong decision if the new intervention is adopted. The value of performing further studies and gathering additional evidence is based on the extent to which the additional information will reduce this uncertainty. A quantitative framework allows for the valuation of the additional information that is generated by further research, and considers the decision maker's objectives and resource constraints. Claxton et al. summarise: "Value of information analysis can be used to inform a range of policy questions including whether a new technology should be approved based on existing evidence, whether it should be approved but additional research conducted or whether approval should be withheld until the additional evidence becomes available." [Claxton K. Value of information entry in Encyclopaedia of Health Economics, Elsevier, forthcoming 2014.] The purpose of this tutorial is to introduce the framework of systematic VoI analysis to guide further research. In our tutorial article, we explain the theoretical foundations and practical methods of decision analysis and value-of-information analysis. To illustrate, we use a simple case example of a foot ulcer (e.g., with

  16. When is enough evidence enough? - Using systematic decision analysis and value-of-information analysis to determine the need for further evidence.

    PubMed

    Siebert, Uwe; Rochau, Ursula; Claxton, Karl

    2013-01-01

    Decision analysis (DA) and value-of-information (VOI) analysis provide a systematic, quantitative methodological framework that explicitly considers the uncertainty surrounding the currently available evidence to guide healthcare decisions. In medical decision making under uncertainty, there are two fundamental questions: 1) What decision should be made now given the best available evidence (and its uncertainty)?; 2) Subsequent to the current decision and given the magnitude of the remaining uncertainty, should we gather further evidence (i.e., perform additional studies), and if yes, which studies should be undertaken (e.g., efficacy, side effects, quality of life, costs), and what sample sizes are needed? Using the currently best available evidence, VoI analysis focuses on the likelihood of making a wrong decision if the new intervention is adopted. The value of performing further studies and gathering additional evidence is based on the extent to which the additional information will reduce this uncertainty. A quantitative framework allows for the valuation of the additional information that is generated by further research, and considers the decision maker's objectives and resource constraints. Claxton et al. summarise: "Value of information analysis can be used to inform a range of policy questions including whether a new technology should be approved based on existing evidence, whether it should be approved but additional research conducted or whether approval should be withheld until the additional evidence becomes available." [Claxton K. Value of information entry in Encyclopaedia of Health Economics, Elsevier, forthcoming 2014.] The purpose of this tutorial is to introduce the framework of systematic VoI analysis to guide further research. In our tutorial article, we explain the theoretical foundations and practical methods of decision analysis and value-of-information analysis. To illustrate, we use a simple case example of a foot ulcer (e.g., with

  17. The multi-objective decision making methods based on MULTIMOORA and MOOSRA for the laptop selection problem

    NASA Astrophysics Data System (ADS)

    Aytaç Adalı, Esra; Tuş Işık, Ayşegül

    2016-10-01

    A decision making process requires the values of conflicting objectives for alternatives and the selection of the best alternative according to the needs of decision makers. Multi-objective optimization methods may provide solution for this selection. In this paper it is aimed to present the laptop selection problem based on MOORA plus full multiplicative form (MULTIMOORA) and multi-objective optimization on the basis of simple ratio analysis (MOOSRA) which are relatively new multi-objective optimization methods. The novelty of this paper is solving this problem with the MULTIMOORA and MOOSRA methods for the first time.

  18. Hanford Site cleanup and transition: Risk data needs for decision making (Hanford risk data gap analysis decision guide)

    SciTech Connect

    Gajewski, S.; Glantz, C.; Harper, B.; Bilyard, G.; Miller, P.

    1995-10-01

    Given the broad array of environmental problems, technical alternatives, and outcomes desired by different stakeholders at Hanford, DOE will have to make difficult resource allocations over the next few decades. Although some of these allocations will be driven purely by legal requirements, almost all of the major objectives of the cleanup and economic transition missions involve choices among alternative pathways. This study examined the following questions: what risk information is needed to make good decisions at Hanford; how do those data needs compare to the set(s) of risk data that will be generated by regulatory compliance activities and various non-compliance studies that are also concerned with risk? This analysis examined the Hanford Site missions, the Hanford Strategic Plan, known stakeholder values, and the most important decisions that have to be made at Hanford to determine a minimum domain of risk information required to make good decisions that will withstand legal, political, and technical scrutiny. The primary risk categories include (1) public health, (2) occupational health and safety, (3) ecological integrity, (4) cultural-religious welfare, and (5) socio-economic welfare.

  19. Closed-Loop Analysis of Soft Decisions for Serial Links

    NASA Technical Reports Server (NTRS)

    Lansdowne, Chatwin A.; Steele, Glen F.; Zucha, Joan P.; Schlensinger, Adam M.

    2012-01-01

    Modern receivers are providing soft decision symbol synchronization as radio links are challenged to push more data and more overhead through noisier channels, and software-defined radios use error-correction techniques that approach Shannon s theoretical limit of performance. The authors describe the benefit of closed-loop measurements for a receiver when paired with a counterpart transmitter and representative channel conditions. We also describe a real-time Soft Decision Analyzer (SDA) implementation for closed-loop measurements on single- or dual- (orthogonal) channel serial data communication links. The analyzer has been used to identify, quantify, and prioritize contributors to implementation loss in real-time during the development of software defined radios.

  20. Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses

    PubMed Central

    Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

    2016-01-01

    Background Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. Objective The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Methods Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Results Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however

  1. The analysis of the pilot's cognitive and decision processes

    NASA Technical Reports Server (NTRS)

    Curry, R. E.

    1975-01-01

    Articles are presented on pilot performance in zero-visibility precision approach, failure detection by pilots during automatic landing, experiments in pilot decision-making during simulated low visibility approaches, a multinomial maximum likelihood program, and a random search algorithm for laboratory computers. Other topics discussed include detection of system failures in multi-axis tasks and changes in pilot workload during an instrument landing.

  2. Warfighter decision making performance analysis as an investment priority driver

    NASA Astrophysics Data System (ADS)

    Thornley, David J.; Dean, David F.; Kirk, James C.

    2010-04-01

    Estimating the relative value of alternative tactics, techniques and procedures (TTP) and information systems requires measures of the costs and benefits of each, and methods for combining and comparing those measures. The NATO Code of Best Practice for Command and Control Assessment explains that decision making quality would ideally be best assessed on outcomes. Lessons learned in practice can be assessed statistically to support this, but experimentation with alternate measures in live conflict is undesirable. To this end, the development of practical experimentation to parameterize effective constructive simulation and analytic modelling for system utility prediction is desirable. The Land Battlespace Systems Department of Dstl has modeled human development of situational awareness to support constructive simulation by empirically discovering how evidence is weighed according to circumstance, personality, training and briefing. The human decision maker (DM) provides the backbone of the information processing activity associated with military engagements because of inherent uncertainty associated with combat operations. To develop methods for representing the process in order to assess equipment and non-technological interventions such as training and TTPs we are developing componentized or modularized timed analytic stochastic model components and instruments as part of a framework to support quantitative assessment of intelligence production and consumption methods in a human decision maker-centric mission space. In this paper, we formulate an abstraction of the human intelligence fusion process from the Defence Science and Technology Laboratory's (Dstl's) INCIDER model to include in our framework, and synthesize relevant cost and benefit characteristics.

  3. A Primer on Decision Analysis for Individually Prescribed Instruction. ACT Technical Bulletin No. 17.

    ERIC Educational Resources Information Center

    Davis, Charles E.; And Others

    A coherent system of decision making is described that may be incorporated into an instructional sequence to provide a supplement to the experience-based judgment of the classroom teacher. The elements of this decision process incorporate prior information such as a teacher's past experience, experimental results such as a test score, and…

  4. Partially observable Markov decision processes for risk-based screening

    NASA Astrophysics Data System (ADS)

    Mrozack, Alex; Liao, Xuejun; Skatter, Sondre; Carin, Lawrence

    2016-05-01

    A long-term goal for checked baggage screening in airports has been to include passenger information, or at least a predetermined passenger risk level, in the screening process. One method for including that information could be treating the checked baggage screening process as a system-of-systems. This would allow for an optimized policy builder, such as one trained using the methodology of partially observable Markov decision processes (POMDP), to navigate the different sensors available for screening. In this paper we describe the necessary steps to tailor a POMDP for baggage screening, as well as results of simulations for specific screening scenarios.

  5. Evidence-Based Medicine in Otolaryngology, Part 5: Patient Decision Aids.

    PubMed

    Pynnonen, Melissa A; Randolph, Gregory W; Shin, Jennifer J

    2015-09-01

    Modern medical decision making is a complex task requiring collaboration between patients and physicians. Related clinical evidence may delineate a clearly favorable path, but in other instances, uncertainty remains. Even in these circumstances, however, there are techniques that optimize decision making by blending existing evidence with individual patient values in the context of physician counseling. This installment of "Evidence-Based Medicine in Otolaryngology" focuses on the crucial issue of how practitioners may approach clinical situations where the data do not delineate a single irrefutable path. We describe decision aids-tools that can educate patients about data related to complex clinical decisions. We review their definition, quality standards, patient interface, benefits, and limitations. We also discuss the related concept of option grids and the role of decision aids in evidence-based practice.

  6. Decision-making in honeybee swarms based on quality and distance information of candidate nest sites.

    PubMed

    Laomettachit, Teeraphan; Termsaithong, Teerasit; Sae-Tang, Anuwat; Duangphakdee, Orawan

    2015-01-01

    In the nest-site selection process of honeybee swarms, an individual bee performs a waggle dance to communicate information about direction, quality, and distance of a discovered site to other bees at the swarm. Initially, different groups of bees dance to represent different potential sites, but eventually the swarm usually reaches an agreement for only one site. Here, we model the nest-site selection process in honeybee swarms of Apis mellifera and show how the swarms make adaptive decisions based on a trade-off between the quality and distance to candidate nest sites. We use bifurcation analysis and stochastic simulations to reveal that the swarm's site distance preference is moderate>near>far when the swarms choose between low quality sites. However, the distance preference becomes near>moderate>far when the swarms choose between high quality sites. Our simulations also indicate that swarms with large population size prefer nearer sites and, in addition, are more adaptive at making decisions based on available information compared to swarms with smaller population size. PMID:25218431

  7. Building the Evidence Base for Decision-making in Cancer Genomic Medicine Using Comparative Effectiveness Research

    PubMed Central

    Goddard, Katrina A.B.; Knaus, William A.; Whitlock, Evelyn; Lyman, Gary H.; Feigelson, Heather Spencer; Schully, Sheri D.; Ramsey, Scott; Tunis, Sean; Freedman, Andrew N.; Khoury, Muin J.; Veenstra, David L.

    2013-01-01

    Background The clinical utility is uncertain for many cancer genomic applications. Comparative effectiveness research (CER) can provide evidence to clarify this uncertainty. Objectives To identify approaches to help stakeholders make evidence-based decisions, and to describe potential challenges and opportunities using CER to produce evidence-based guidance. Methods We identified general CER approaches for genomic applications through literature review, the authors’ experiences, and lessons learned from a recent, seven-site CER initiative in cancer genomic medicine. Case studies illustrate the use of CER approaches. Results Evidence generation and synthesis approaches include comparative observational and randomized trials, patient reported outcomes, decision modeling, and economic analysis. We identified significant challenges to conducting CER in cancer genomics: the rapid pace of innovation, the lack of regulation, the limited evidence for clinical utility, and the beliefs that genomic tests could have personal utility without having clinical utility. Opportunities to capitalize on CER methods in cancer genomics include improvements in the conduct of evidence synthesis, stakeholder engagement, increasing the number of comparative studies, and developing approaches to inform clinical guidelines and research prioritization. Conclusions CER offers a variety of methodological approaches to address stakeholders’ needs. Innovative approaches are needed to ensure an effective translation of genomic discoveries. PMID:22516979

  8. Computeer-based decision support tools for evaluation of actions affecting flow and water quality in the San Joaquin Basin

    SciTech Connect

    Quinn, N.W.T.

    1993-01-01

    This document is a preliminary effort to draw together some of the important simulation models that are available to Reclamation or that have been developed by Reclamation since 1987. This document has also attempted to lay out a framework by which these models might be used both for the purposes for which they were originally intended and to support the analysis of other issues that relate to the hydrology and to salt and water quality management within the San Joaquin Valley. To be successful as components of a larger Decision Support System the models should to be linked together using custom designed interfaces that permit data sharing between models and that are easy to use. Several initiatives are currently underway within Reclamation to develop GIS - based and graphics - based decision support systems to improve the general level of understanding of the models currently in use, to standardize the methodology used in making planning and operations studies and to permit improved data analysis, interpretation and display. The decision support systems should allow greater participation in the planning process, allow the analysis of innovative actions that are currently difficult to study with present models and should lead to better integrated and more comprehensive plans and policy decisions in future years.

  9. Holistic risk-based environmental decision making: a Native perspective.

    PubMed Central

    Arquette, Mary; Cole, Maxine; Cook, Katsi; LaFrance, Brenda; Peters, Margaret; Ransom, James; Sargent, Elvera; Smoke, Vivian; Stairs, Arlene

    2002-01-01

    Native American Nations have become increasingly concerned about the impacts of toxic substances. Although risk assessment and risk management processes have been used by government agencies to help estimate and manage risks associated with exposure to toxicants, these tools have many inadequacies and as a result have not served Native people well. In addition, resources have not always been adequate to address the concerns of Native Nations, and involvement of Native decision makers on a government-to-government basis in discussions regarding risk has only recently become common. Finally, because the definitions of health used by Native people are strikingly different from that of risk assessors, there is also a need to expand current definitions and incorporate traditional knowledge into decision making. Examples are discussed from the First Environment Restoration Initiative, a project that is working to address toxicant issues facing the Mohawk territory of Akwesasne. This project is developing a community-defined model in which health is protected at the same time that traditional cultural practices, which have long been the key to individual and community health, are maintained and restored. PMID:11929736

  10. Evidence-based decision-making 7: Knowledge translation.

    PubMed

    Manns, Braden J

    2015-01-01

    There is a significant gap between what is known and what is implemented by key stakeholders in practice (the evidence to practice gap). The primary purpose of knowledge translation is to address this gap, bridging evidence to clinical practice. The knowledge to action cycle is one framework for knowledge translation that integrates policy-makers throughout the research cycle. The knowledge to action cycle begins with the identification of a problem (usually a gap in care provision). After identification of the problem, knowledge creation is undertaken, depicted at the center of the cycle as a funnel. Knowledge inquiry is at the wide end of the funnel, and moving down the funnel, the primary data is synthesized into knowledge products in the form of educational materials, guidelines, decision aids, or clinical pathways. The remaining components of the knowledge to action cycle refer to the action of applying the knowledge that has been created. This includes adapting knowledge to local context, assessing barriers to knowledge use, selecting, tailoring implementing interventions, monitoring knowledge use, evaluating outcomes, and sustaining knowledge use. Each of these steps is connected by bidirectional arrows and ideally involves healthcare decision-makers and key stakeholders at each transition.

  11. From "weight of evidence" to quantitative data integration using multicriteria decision analysis and Bayesian methods.

    PubMed

    Linkov, Igor; Massey, Olivia; Keisler, Jeff; Rusyn, Ivan; Hartung, Thomas

    2015-01-01

    "Weighing" available evidence in the process of decision-making is unavoidable, yet it is one step that routinely raises suspicions: what evidence should be used, how much does it weigh, and whose thumb may be tipping the scales? This commentary aims to evaluate the current state and future roles of various types of evidence for hazard assessment as it applies to environmental health. In its recent evaluation of the US Environmental Protection Agency's Integrated Risk Information System assessment process, the National Research Council committee singled out the term "weight of evidence" (WoE) for critique, deeming the process too vague and detractive to the practice of evaluating human health risks of chemicals. Moving the methodology away from qualitative, vague and controversial methods towards generalizable, quantitative and transparent methods for appropriately managing diverse lines of evidence is paramount for both regulatory and public acceptance of the hazard assessments. The choice of terminology notwithstanding, a number of recent Bayesian WoE-based methods, the emergence of multi criteria decision analysis for WoE applications, as well as the general principles behind the foundational concepts of WoE, show promise in how to move forward and regain trust in the data integration step of the assessments. We offer our thoughts on the current state of WoE as a whole and while we acknowledge that many WoE applications have been largely qualitative and subjective in nature, we see this as an opportunity to turn WoE towards a quantitative direction that includes Bayesian and multi criteria decision analysis.

  12. From "weight of evidence" to quantitative data integration using multicriteria decision analysis and Bayesian methods.

    PubMed

    Linkov, Igor; Massey, Olivia; Keisler, Jeff; Rusyn, Ivan; Hartung, Thomas

    2015-01-01

    "Weighing" available evidence in the process of decision-making is unavoidable, yet it is one step that routinely raises suspicions: what evidence should be used, how much does it weigh, and whose thumb may be tipping the scales? This commentary aims to evaluate the current state and future roles of various types of evidence for hazard assessment as it applies to environmental health. In its recent evaluation of the US Environmental Protection Agency's Integrated Risk Information System assessment process, the National Research Council committee singled out the term "weight of evidence" (WoE) for critique, deeming the process too vague and detractive to the practice of evaluating human health risks of chemicals. Moving the methodology away from qualitative, vague and controversial methods towards generalizable, quantitative and transparent methods for appropriately managing diverse lines of evidence is paramount for both regulatory and public acceptance of the hazard assessments. The choice of terminology notwithstanding, a number of recent Bayesian WoE-based methods, the emergence of multi criteria decision analysis for WoE applications, as well as the general principles behind the foundational concepts of WoE, show promise in how to move forward and regain trust in the data integration step of the assessments. We offer our thoughts on the current state of WoE as a whole and while we acknowledge that many WoE applications have been largely qualitative and subjective in nature, we see this as an opportunity to turn WoE towards a quantitative direction that includes Bayesian and multi criteria decision analysis. PMID:25592482

  13. Decision Styles and Rationality: An Analysis of the Predictive Validity of the General Decision-Making Style Inventory

    ERIC Educational Resources Information Center

    Curseu, Petru Lucian; Schruijer, Sandra G. L.

    2012-01-01

    This study investigates the relationship between the five decision-making styles evaluated by the General Decision-Making Style Inventory, indecisiveness, and rationality in decision making. Using a sample of 102 middle-level managers, the results show that the rational style positively predicts rationality in decision making and negatively…

  14. Learning to maximize reward rate: a model based on semi-Markov decision processes.

    PubMed

    Khodadadi, Arash; Fakhari, Pegah; Busemeyer, Jerome R

    2014-01-01

    WHEN ANIMALS HAVE TO MAKE A NUMBER OF DECISIONS DURING A LIMITED TIME INTERVAL, THEY FACE A FUNDAMENTAL PROBLEM: how much time they should spend on each decision in order to achieve the maximum possible total outcome. Deliberating more on one decision usually leads to more outcome but less time will remain for other decisions. In the framework of sequential sampling models, the question is how animals learn to set their decision threshold such that the total expected outcome achieved during a limited time is maximized. The aim of this paper is to provide a theoretical framework for answering this question. To this end, we consider an experimental design in which each trial can come from one of the several possible "conditions." A condition specifies the difficulty of the trial, the reward, the penalty and so on. We show that to maximize the expected reward during a limited time, the subject should set a separate value of decision threshold for each condition. We propose a model of learning the optimal value of decision thresholds based on the theory of semi-Markov decision processes (SMDP). In our model, the experimental environment is modeled as an SMDP with each "condition" being a "state" and the value of decision thresholds being the "actions" taken in those states. The problem of finding the optimal decision thresholds then is cast as the stochastic optimal control problem of taking actions in each state in the corresponding SMDP such that the average reward rate is maximized. Our model utilizes a biologically plausible learning algorithm to solve this problem. The simulation results show that at the beginning of learning the model choses high values of decision threshold which lead to sub-optimal performance. With experience, however, the model learns to lower the value of decision thresholds till finally it finds the optimal values.

  15. Learning to maximize reward rate: a model based on semi-Markov decision processes

    PubMed Central

    Khodadadi, Arash; Fakhari, Pegah; Busemeyer, Jerome R.

    2014-01-01

    When animals have to make a number of decisions during a limited time interval, they face a fundamental problem: how much time they should spend on each decision in order to achieve the maximum possible total outcome. Deliberating more on one decision usually leads to more outcome but less time will remain for other decisions. In the framework of sequential sampling models, the question is how animals learn to set their decision threshold such that the total expected outcome achieved during a limited time is maximized. The aim of this paper is to provide a theoretical framework for answering this question. To this end, we consider an experimental design in which each trial can come from one of the several possible “conditions.” A condition specifies the difficulty of the trial, the reward, the penalty and so on. We show that to maximize the expected reward during a limited time, the subject should set a separate value of decision threshold for each condition. We propose a model of learning the optimal value of decision thresholds based on the theory of semi-Markov decision processes (SMDP). In our model, the experimental environment is modeled as an SMDP with each “condition” being a “state” and the value of decision thresholds being the “actions” taken in those states. The problem of finding the optimal decision thresholds then is cast as the stochastic optimal control problem of taking actions in each state in the corresponding SMDP such that the average reward rate is maximized. Our model utilizes a biologically plausible learning algorithm to solve this problem. The simulation results show that at the beginning of learning the model choses high values of decision threshold which lead to sub-optimal performance. With experience, however, the model learns to lower the value of decision thresholds till finally it finds the optimal values. PMID:24904252

  16. Thermal power systems small power systems applications project. Decision analysis for evaluating and ranking small solar thermal power system technologies. Volume 1: A brief introduction to multiattribute decision analysis. [explanation of multiattribute decision analysis methods used in evaluating alternatives for small powered systems

    NASA Technical Reports Server (NTRS)

    Feinberg, A.; Miles, R. F., Jr.

    1978-01-01

    The principal concepts of the Keeney and Raiffa approach to multiattribute decision analysis are described. Topics discussed include the concepts of decision alternatives, outcomes, objectives, attributes and their states, attribute utility functions, and the necessary independence properties for the attribute states to be aggregated into a numerical representation of the preferences of the decision maker for the outcomes and decision alternatives.

  17. Evidence-based decision-making (part 1): Origins and evolution in the health sciences.

    PubMed

    Bradt, David A

    2009-01-01

    Evidence is defined as data on which a judgment or conclusion may be based. In the early 1990s, medical clinicians pioneered evidence-based decision-making. The discipline emerged as the use of current best evidence in making decisions about the care of individual patients. The practice of evidence-based medicine required the integration of individual clinical expertise with the best available, external clinical evidence from systematic research and the patient's unique values and circumstances. In this context, evidence acquired a hierarchy of strength based upon the method of data acquisition. Subsequently, evidence-based decision-making expanded throughout the allied health field. In public health, and particularly for populations in crisis, three major data-gathering tools now dominate: (1) rapid health assessments; (2) population based surveys; and (3) disease surveillance. Unfortunately, the strength of evidence obtained by these tools is not easily measured by the grading scales of evidence based medicine. This is complicated by the many purposes for which evidence can be applied in public health: strategic decision-making, program implementation, monitoring, and evaluation. Different applications have different requirements for strength of evidence as well as different time frames for decision-making. Given the challenges of integrating data from multiple sources that are collected by different methods, public health experts have defined best available evidence as the use of all available sources used to provide relevant inputs for decision-making. PMID:19806553

  18. Decision and function problems based on boson sampling

    NASA Astrophysics Data System (ADS)

    Nikolopoulos, Georgios M.; Brougham, Thomas

    2016-07-01

    Boson sampling is a mathematical problem that is strongly believed to be intractable for classical computers, whereas passive linear interferometers can produce samples efficiently. So far, the problem remains a computational curiosity, and the possible usefulness of boson-sampling devices is mainly limited to the proof of quantum supremacy. The purpose of this work is to investigate whether boson sampling can be used as a resource of decision and function problems that are computationally hard, and may thus have cryptographic applications. After the definition of a rather general theoretical framework for the design of such problems, we discuss their solution by means of a brute-force numerical approach, as well as by means of nonboson samplers. Moreover, we estimate the sample sizes required for their solution by passive linear interferometers, and it is shown that they are independent of the size of the Hilbert space.

  19. Prenatal Diagnosis: A Directive Approach to Genetic Counseling Using Decision Analysis 1

    PubMed Central

    Pauker, Susan P.; Pauker, Stephen G.

    1977-01-01

    The decision which prospective parents face concerning mid-trimester amniocentesis for prenatal diagnosis was examined by decision analysis. The prospective parents' decision depends on the likelihood of the birth of a child affected by a genetic disorder, the risk of amniocentesis, and the probability that the diagnoses provided by the amniocentesis will be correct. The couple's decision must also depend on their attitudes toward each possible outcome. The likelihoods of the outcomes can be obtained from appropriate medical consultation, while the relative costs or burdens of the outcomes should be obtained from the prospective parents. A truly informed decision for this couple can then be formulated from these probabilities and values, thus allowing genetic counseling to be more directive. The technique is illustrated for the prenatal diagnosis of Down's syndrome, meningomyelocele, and Duchenne muscular dystrophy. PMID:142379

  20. Geothermal well-field and power-plant investment-decision analysis

    SciTech Connect

    Cassel, T.A.V.; Amundsen, C.B.; Edelstein, R.H.; Blair, P.D.

    1981-05-31

    Investment decisions pertaining to hydrothermal well fields and electric power plants are analyzed. Geothermal investment decision models were developed which, when coupled to a site-specific stochastic cash flow model, estimate the conditional probability of a positive decision to invest in the development of geothermal resource areas. Quantitative decision models have been developed for each major category of investor currently involved in the hydrothermal projects. These categories include: large, diversified energy resource corporations; independently operating resource firms; investor-owned electric utilities; municipal electric utilities; state-run resource agencies; and private third-party power plant investors. The geothermal cash flow, the investment decision analysis, and an example of model application for assessing the likely development of geothermal resource areas are described. The sensitivity of this investment behavior to federal incentives and research goals is also analyzed and discussed.

  1. On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems

    NASA Technical Reports Server (NTRS)

    Tunstel, Edward; Jamshidi, Mo

    1997-01-01

    Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.

  2. A study on spatial decision support systems for HIV/AIDS prevention based on COM GIS technology

    NASA Astrophysics Data System (ADS)

    Yang, Kun; Luo, Huasong; Peng, Shungyun; Xu, Quanli

    2007-06-01

    Based on the deeply analysis of the current status and the existing problems of GIS technology applications in Epidemiology, this paper has proposed the method and process for establishing the spatial decision support systems of AIDS epidemic prevention by integrating the COM GIS, Spatial Database, GPS, Remote Sensing, and Communication technologies, as well as ASP and ActiveX software development technologies. One of the most important issues for constructing the spatial decision support systems of AIDS epidemic prevention is how to integrate the AIDS spreading models with GIS. The capabilities of GIS applications in the AIDS epidemic prevention have been described here in this paper firstly. Then some mature epidemic spreading models have also been discussed for extracting the computation parameters. Furthermore, a technical schema has been proposed for integrating the AIDS spreading models with GIS and relevant geospatial technologies, in which the GIS and model running platforms share a common spatial database and the computing results can be spatially visualized on Desktop or Web GIS clients. Finally, a complete solution for establishing the decision support systems of AIDS epidemic prevention has been offered in this paper based on the model integrating methods and ESRI COM GIS software packages. The general decision support systems are composed of data acquisition sub-systems, network communication sub-systems, model integrating sub-systems, AIDS epidemic information spatial database sub-systems, AIDS epidemic information querying and statistical analysis sub-systems, AIDS epidemic dynamic surveillance sub-systems, AIDS epidemic information spatial analysis and decision support sub-systems, as well as AIDS epidemic information publishing sub-systems based on Web GIS.

  3. Using the fuzzy majority approach for GIS-based multicriteria group decision-making

    NASA Astrophysics Data System (ADS)

    Boroushaki, Soheil; Malczewski, Jacek

    2010-03-01

    This paper is concerned with developing a framework for GIS-based multicriteria group decision-making using the fuzzy majority approach. The procedure for solving a spatial group decision-making problem involves two stages. First, each decision-maker solves the problem individually. Second, the individual solutions are aggregated to obtain a group solution. The first stage is operationalized by a linguistic quantifier-guided ordered weighted averaging (OWA) procedure to create individual decision-maker's solution maps. Then the individual maps are combined using the fuzzy majority procedure to generate the group solution map which synthesizes the majority of the decision-makers' preferences. The paper provides an illustrative example of the fuzzy majority method for a land suitability problem. It also demonstrates the implementation of the framework within the ArcGIS environment.

  4. Propagating Water Quality Analysis Uncertainty Into Resource Management Decisions Through Probabilistic Modeling

    NASA Astrophysics Data System (ADS)

    Gronewold, A. D.; Wolpert, R. L.; Reckhow, K. H.

    2007-12-01

    Most probable number (MPN) and colony-forming-unit (CFU) are two estimates of fecal coliform bacteria concentration commonly used as measures of water quality in United States shellfish harvesting waters. The MPN is the maximum likelihood estimate (or MLE) of the true fecal coliform concentration based on counts of non-sterile tubes in serial dilution of a sample aliquot, indicating bacterial metabolic activity. The CFU is the MLE of the true fecal coliform concentration based on the number of bacteria colonies emerging on a growth plate after inoculation from a sample aliquot. Each estimating procedure has intrinsic variability and is subject to additional uncertainty arising from minor variations in experimental protocol. Several versions of each procedure (using different sized aliquots or different numbers of tubes, for example) are in common use, each with its own levels of probabilistic and experimental error and uncertainty. It has been observed empirically that the MPN procedure is more variable than the CFU procedure, and that MPN estimates are somewhat higher on average than CFU estimates, on split samples from the same water bodies. We construct a probabilistic model that provides a clear theoretical explanation for the observed variability in, and discrepancy between, MPN and CFU measurements. We then explore how this variability and uncertainty might propagate into shellfish harvesting area management decisions through a two-phased modeling strategy. First, we apply our probabilistic model in a simulation-based analysis of future water quality standard violation frequencies under alternative land use scenarios, such as those evaluated under guidelines of the total maximum daily load (TMDL) program. Second, we apply our model to water quality data from shellfish harvesting areas which at present are closed (either conditionally or permanently) to shellfishing, to determine if alternative laboratory analysis procedures might have led to different

  5. A decision analysis framework to support long-term planning for nuclear fuel cycle technology research, development, demonstration and deployment

    SciTech Connect

    Sowder, A.G.; Machiels, A.J.; Dykes, A.A.; Johnson, D.H.

    2013-07-01

    To address challenges and gaps in nuclear fuel cycle option assessment and to support research, develop and demonstration programs oriented toward commercial deployment, EPRI (Electric Power Research Institute) is seeking to develop and maintain an independent analysis and assessment capability by building a suite of assessment tools based on a platform of software, simplified relationships, and explicit decision-making and evaluation guidelines. As a demonstration of the decision-support framework, EPRI examines a relatively near-term fuel cycle option, i.e., use of reactor-grade mixed-oxide fuel (MOX) in U.S. light water reactors. The results appear as a list of significant concerns (like cooling of spent fuels, criticality risk...) that have to be taken into account for the final decision.

  6. Do choosing wisely tools meet criteria for patient decision aids? A descriptive analysis of patient materials

    PubMed Central

    Légaré, France; Hébert, Jessica; Goh, Larissa; Lewis, Krystina B; Leiva Portocarrero, Maria Ester; Robitaille, Hubert; Stacey, Dawn

    2016-01-01

    Objectives Choosing Wisely is a remarkable physician-led campaign to reduce unnecessary or harmful health services. Some of the literature identifies Choosing Wisely as a shared decision-making approach. We evaluated the patient materials developed by Choosing Wisely Canada to determine whether they meet the criteria for shared decision-making tools known as patient decision aids. Design Descriptive analysis of all Choosing Wisely Canada patient materials. Data source In May 2015, we selected all Choosing Wisely Canada patient materials from its official website. Main outcomes and measures Four team members independently extracted characteristics of the English materials using the International Patient Decision Aid Standards (IPDAS) modified 16-item minimum criteria for qualifying and certifying patient decision aids. The research team discussed discrepancies between data extractors and reached a consensus. Descriptive analysis was conducted. Results Of the 24 patient materials assessed, 12 were about treatments, 11 were about screening and 1 was about prevention. The median score for patient materials using IPDAS criteria was 10/16 (range: 8–11) for screening topics and 6/12 (range: 6–9) for prevention and treatment topics. Commonly missed criteria were stating the decision (21/24 did not), providing balanced information on option benefits/harms (24/24 did not), citing evidence (24/24 did not) and updating policy (24/24 did not). Out of 24 patient materials, only 2 met the 6 IPDAS criteria to qualify as patient decision aids, and neither of these 2 met the 6 certifying criteria. Conclusions Patient materials developed by Choosing Wisely Canada do not meet the IPDAS minimal qualifying or certifying criteria for patient decision aids. Modifications to the Choosing Wisely Canada patient materials would help to ensure that they qualify as patient decision aids and thus as more effective shared decision-making tools. PMID:27566638

  7. Toward Reflective Judgment in Exploratory Factor Analysis Decisions: Determining the Extraction Method and Number of Factors To Retain.

    ERIC Educational Resources Information Center

    Knight, Jennifer L.

    This paper considers some decisions that must be made by the researcher conducting an exploratory factor analysis. The primary purpose is to aid the researcher in making informed decisions during the factor analysis instead of relying on defaults in statistical programs or traditions of previous researchers. Three decision areas are addressed.…

  8. tropical cyclone risk analysis: a decisive role of its track

    NASA Astrophysics Data System (ADS)

    Chelsea Nam, C.; Park, Doo-Sun R.; Ho, Chang-Hoi

    2016-04-01

    The tracks of 85 tropical cyclones (TCs) that made landfall to South Korea for the period 1979-2010 are classified into four clusters by using a fuzzy c-means clustering method. The four clusters are characterized by 1) east-short, 2) east-long, 3) west-long, and 4) west-short based on the moving routes around Korean peninsula. We conducted risk comparison analysis for these four clusters regarding their hazards, exposure, and damages. Here, hazard parameters are calculated from two different sources independently, one from the best-track data (BT) and the other from the 60 weather stations over the country (WS). The results show distinct characteristics of the four clusters in terms of the hazard parameters and economic losses (EL), suggesting that there is a clear track-dependency in the overall TC risk. It is appeared that whether there occurred an "effective collision" overweighs the intensity of the TC per se. The EL ranking did not agree with the BT parameters (maximum wind speed, central pressure, or storm radius), but matches to WS parameter (especially, daily accumulated rainfall and TC-influenced period). The west-approaching TCs (i.e. west-long and west-short clusters) generally recorded larger EL than the east-approaching TCs (i.e. east-short and east-long clusters), although the east-long clusters are the strongest in BT point of view. This can be explained through the spatial distribution of the WS parameters and the regional EL maps corresponding to it. West-approaching TCs accompanied heavy rainfall on the southern regions with the helps of the topographic effect on their tracks, and of the extended stay on the Korean Peninsula in their extratropical transition, that were not allowed to the east-approaching TCs. On the other hand, some regions had EL that are not directly proportional to the hazards, and this is partly attributed to spatial disparity in wealth and vulnerability. Correlation analysis also revealed the importance of rainfall; daily

  9. Usability testing of ANSWER: a web-based methotrexate decision aid for patients with rheumatoid arthritis

    PubMed Central

    2013-01-01

    Background Decision aids are evidence-based tools designed to inform people of the potential benefit and harm of treatment options, clarify their preferences and provide a shared decision-making structure for discussion at a clinic visit. For patients with rheumatoid arthritis (RA) who are considering methotrexate, we have developed a web-based patient decision aid called the ANSWER (Animated, Self-serve, Web-based Research Tool). This study aimed to: 1) assess the usability of the ANSWER prototype; 2) identify strengths and limitations of the ANSWER from the patient’s perspective. Methods The ANSWER prototype consisted of: 1) six animated patient stories and narrated information on the evidence of methotrexate for RA; 2) interactive questionnaires to clarify patients’ treatment preferences. Eligible participants for the usability test were patients with RA who had been prescribed methotrexate. They were asked to verbalize their thoughts (i.e., think aloud) while using the ANSWER, and to complete the System Usability Scale (SUS) to assess overall usability (range = 0-100; higher = more user friendly). Participants were audiotaped and observed, and field notes were taken. The testing continued until no new modifiable issues were found. We used descriptive statistics to summarize participant characteristics and the SUS scores. Content analysis was used to identified usability issues and navigation problems. Results 15 patients participated in the usability testing. The majority were aged 50 or over and were university/college graduates (n = 8, 53.4%). On average they took 56 minutes (SD = 34.8) to complete the tool. The mean SUS score was 81.2 (SD = 13.5). Content analysis of audiotapes and field notes revealed four categories of modifiable usability issues: 1) information delivery (i.e., clarity of the information and presentation style); 2) navigation control (i.e., difficulties in recognizing and using the navigation control buttons); 3

  10. Web-based environmental simulation: bridging the gap between scientific modeling and decision-making.

    PubMed

    Buytaert, Wouter; Baez, Selene; Bustamante, Macarena; Dewulf, Art

    2012-02-21

    Data availability in environmental sciences is growing rapidly. Conventional monitoring systems are collecting data at increasing spatial and temporal resolutions; satellites provide a constant stream of global observations, and citizen scientist generate local data with electronic gadgets and cheap devices. There is a need to process this stream of heterogeneous data into useful information, both for science and for decision-making. Advances in networking and computer technologies increasingly enable accessing, combining, processing, and visualizing these data. This Feature reflects upon the role of environmental models in this process. We consider models as the primary tool for data processing, pattern identification, and scenario analysis. As such, they are an essential element of science-based decision-making. The new technologies analyzed here have the potential to turn the typical top-down flow of information from scientists to users into a much more direct, interactive approach. This may accelerate the dissemination of environmental information to a larger community of users. It may also facilitate harvesting feedback, and evaluating simulations and predictions from different perspectives. However, the evolution poses challenges, not only to model development but also to the communication of model results and their assumptions, shortcomings, and errors.

  11. Evaluating a Web-Based MMR Decision Aid to Support Informed Decision-Making by UK Parents: A Before-and-After Feasibility Study

    ERIC Educational Resources Information Center

    Jackson, Cath; Cheater, Francine M.; Peacock, Rose; Leask, Julie; Trevena, Lyndal

    2010-01-01

    Objective: The objective of this feasibility study was to evaluate the acceptability and potential effectiveness of a web-based MMR decision aid in supporting informed decision-making for the MMR vaccine. Design: This was a prospective before-and-after evaluation. Setting: Thirty parents of children eligible for MMR vaccination were recruited from…

  12. The Effect of Conflict Theory Based Decision-Making Skill Training Psycho-Educational Group Experience on Decision Making Styles of Adolescents

    ERIC Educational Resources Information Center

    Colakkadioglu, Oguzhan; Gucray, S. Sonay

    2012-01-01

    In this study, the effect of conflict theory based decision making skill training group applications on decision making styles of adolescents was investigated. A total of 36 students, including 18 students in experimental group and 18 students in control group, participated in the research. When assigning students to experimental group or control…

  13. An intelligent, knowledge-based multiple criteria decision making advisor for systems design

    NASA Astrophysics Data System (ADS)

    Li, Yongchang

    of an appropriate decision making method. Furthermore, some DMs may be exclusively using one or two specific methods which they are familiar with or trust and not realizing that they may be inappropriate to handle certain classes of the problems, thus yielding erroneous results. These issues reveal that in order to ensure a good decision a suitable decision method should be chosen before the decision making process proceeds. The first part of this dissertation proposes an MCDM process supported by an intelligent, knowledge-based advisor system referred to as Multi-Criteria Interactive Decision-Making Advisor and Synthesis process (MIDAS), which is able to facilitate the selection of the most appropriate decision making method and which provides insight to the user for fulfilling different preferences. The second part of this dissertation presents an autonomous decision making advisor which is capable of dealing with ever-evolving real time information and making autonomous decisions under uncertain conditions. The advisor encompasses a Markov Decision Process (MDP) formulation which takes uncertainty into account when determines the best action for each system state. (Abstract shortened by UMI.)

  14. SER performance analysis of MPPM FSO system with three decision thresholds over exponentiated Weibull fading channels

    NASA Astrophysics Data System (ADS)

    Wang, Ping; Yang, Bensheng; Guo, Lixin; Shang, Tao

    2015-11-01

    In this work, the symbol error rate (SER) performance of the multiple pulse position modulation (MPPM) based free-space optical communication (FSO) system with three different decision thresholds, fixed decision threshold (FDT), optimized decision threshold (ODT) and dynamic decision threshold (DDT) over exponentiated Weibull (EW) fading channels has been investigated in detail. The effects of aperture averaging on each decision threshold under weak-to-strong turbulence conditions are further studied and compared. The closed-form SER expressions for three thresholds derived with the help of generalized Gauss-Laguerre quadrature rule are verified by the Monte Carlo simulations. This work is helpful for the design of receivers for FSO communication systems.

  15. Strengthening capacity in developing countries for evidence-based public health: the data for decision-making project.

    PubMed

    Pappaioanou, Marguerite; Malison, Michael; Wilkins, Karen; Otto, Bradley; Goodman, Richard A; Churchill, R Elliott; White, Mark; Thacker, Stephen B

    2003-11-01

    Public health officials and the communities they serve need to: identify priority health problems; formulate effective health policies; respond to public health emergencies; select, implement, and evaluate cost-effective interventions to prevent and control disease and injury; and allocate human and financial resources. Despite agreement that rational, data-based decisions will lead to improved health outcomes, many public health decisions appear to be made intuitively or politically. During 1991-1996, the US Centers for Disease Control and Prevention implemented the US Agency for International Development funded Data for Decision-Making (DDM) Project. DDM goals were to: (a) strengthen the capacity of decision makers to identify data needs for solving problems and to interpret and use data appropriately for public health decisions; (b) enhance the capacity of technical advisors to provide valid, essential, and timely data to decision makers clearly and effectively; and (c) strengthen health information systems (HISs) to facilitate the collection, analysis, reporting, presentation, and use of data at local, district, regional, and national levels. Assessments were conducted to identify important health problems, problem-driven implementation plans with data-based solutions as objectives were developed, interdisciplinary, in-service training programs for mid-level policy makers, program managers, and technical advisors in applied epidemiology, management and leadership, communications, economic evaluation, and HISs were designed and implemented, national staff were trained in the refinement of HISs to improve access to essential data from multiple sources, and the effectiveness of the strategy was evaluated. This strategy was tested in Bolivia, Cameroon, Mexico, and the Philippines, where decentralization of health services led to a need to strengthen the capacity of policy makers and health officers at sub-national levels to use information more effectively. Results

  16. Research-based-decision-making in Canadian health organizations: a behavioural approach.

    PubMed

    Jbilou, Jalila; Amara, Nabil; Landry, Réjean

    2007-06-01

    Decision making in Health sector is affected by a several elements such as economic constraints, political agendas, epidemiologic events, managers' values and environment... These competing elements create a complex environment for decision making. Research-Based-Decision-Making (RBDM) offers an opportunity to reduce the generated uncertainty and to ensure efficacy and efficiency in health administrations. We assume that RBDM is dependant on decision makers' behaviour and the identification of the determinants of this behaviour can help to enhance research results utilization in health sector decision making. This paper explores the determinants of RBDM as a personal behaviour among managers and professionals in health administrations in Canada. From the behavioural theories and the existing literature, we build a model measuring "RBDM" as an index based on five items. These items refer to the steps accomplished by a decision maker while developing a decision which is based on evidence. The determinants of RBDM behaviour are identified using data collected from 942 health care decision makers in Canadian health organizations. Linear regression is used to model the behaviour RBDM. Determinants of this behaviour are derived from Triandis Theory and Bandura's construct "self-efficacy." The results suggest that to improve research use among managers in Canadian governmental health organizations, strategies should focus on enhancing exposition to evidence through facilitating communication networks, partnerships and links between researchers and decision makers, with the key long-term objective of developing a culture that supports and values the contribution that research can make to decision making in governmental health organizations. Nevertheless, depending on the organizational level, determinants of RBDM are different. This difference has to be taken into account if RBDM adoption is desired. Decision makers in Canadian health organizations (CHO) can help to build

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

    PubMed

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

    2015-01-01

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

  18. 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

  19. Lean production tools and decision latitude enable conditions for innovative learning in organizations: a multilevel analysis.

    PubMed

    Fagerlind Ståhl, Anna-Carin; Gustavsson, Maria; Karlsson, Nadine; Johansson, Gun; Ekberg, Kerstin

    2015-03-01

    The effect of lean production on conditions for learning is debated. This study aimed to investigate how tools inspired by lean production (standardization, resource reduction, visual monitoring, housekeeping, value flow analysis) were associated with an innovative learning climate and with collective dispersion of ideas in organizations, and whether decision latitude contributed to these associations. A questionnaire was sent out to employees in public, private, production and service organizations (n = 4442). Multilevel linear regression analyses were used. Use of lean tools and decision latitude were positively associated with an innovative learning climate and collective dispersion of ideas. A low degree of decision latitude was a modifier in the association to collective dispersion of ideas. Lean tools can enable shared understanding and collective spreading of ideas, needed for the development of work processes, especially when decision latitude is low. Value flow analysis played a pivotal role in the associations. PMID:25479999

  20. Lean production tools and decision latitude enable conditions for innovative learning in organizations: a multilevel analysis.

    PubMed

    Fagerlind Ståhl, Anna-Carin; Gustavsson, Maria; Karlsson, Nadine; Johansson, Gun; Ekberg, Kerstin

    2015-03-01

    The effect of lean production on conditions for learning is debated. This study aimed to investigate how tools inspired by lean production (standardization, resource reduction, visual monitoring, housekeeping, value flow analysis) were associated with an innovative learning climate and with collective dispersion of ideas in organizations, and whether decision latitude contributed to these associations. A questionnaire was sent out to employees in public, private, production and service organizations (n = 4442). Multilevel linear regression analyses were used. Use of lean tools and decision latitude were positively associated with an innovative learning climate and collective dispersion of ideas. A low degree of decision latitude was a modifier in the association to collective dispersion of ideas. Lean tools can enable shared understanding and collective spreading of ideas, needed for the development of work processes, especially when decision latitude is low. Value flow analysis played a pivotal role in the associations.

  1. Mechanical versus clinical data combination in selection and admissions decisions: a meta-analysis.

    PubMed

    Kuncel, Nathan R; Klieger, David M; Connelly, Brian S; Ones, Deniz S

    2013-11-01

    In employee selection and academic admission decisions, holistic (clinical) data combination methods continue to be relied upon and preferred by practitioners in our field. This meta-analysis examined and compared the relative predictive power of mechanical methods versus holistic methods in predicting multiple work (advancement, supervisory ratings of performance, and training performance) and academic (grade point average) criteria. There was consistent and substantial loss of validity when data were combined holistically-even by experts who are knowledgeable about the jobs and organizations in question-across multiple criteria in work and academic settings. In predicting job performance, the difference between the validity of mechanical and holistic data combination methods translated into an improvement in prediction of more than 50%. Implications for evidence-based practice are discussed. PMID:24041118

  2. Multicriteria Decision Analysis of Material Selection of High Energy Performance Residential Building

    NASA Astrophysics Data System (ADS)

    Čuláková, Monika; Vilčeková, Silvia; Katunská, Jana; Krídlová Burdová, Eva

    2013-11-01

    In world with limited amount of energy sources and with serious environmental pollution, interest in comparing the environmental embodied impacts of buildings using different structure systems and alternative building materials will be increased. This paper shows the significance of life cycle energy and carbon perspective and the material selection in reducing energy consumption and emissions production in the built environment. The study evaluates embodied environmental impacts of nearly zero energy residential structures. The environmental assessment uses framework of LCA within boundary: cradle to gate. Designed alternative scenarios of material compositions are also assessed in terms of energy effectiveness through selected thermal-physical parameters. This study uses multi-criteria decision analysis for making clearer selection between alternative scenarios. The results of MCDA show that alternative E from materials on nature plant base (wood, straw bales, massive wood panel) present possible way to sustainable perspective of nearly zero energy houses in Slovak republic

  3. The boundaries of instance-based learning theory for explaining decisions from experience.

    PubMed

    Gonzalez, Cleotilde

    2013-01-01

    Most demonstrations of how people make decisions in risky situations rely on decisions from description, where outcomes and their probabilities are explicitly stated. But recently, more attention has been given to decisions from experience where people discover these outcomes and probabilities through exploration. More importantly, risky behavior depends on how decisions are made (from description or experience), and although prospect theory explains decisions from description, a comprehensive model of decisions from experience is yet to be found. Instance-based learning theory (IBLT) explains how decisions are made from experience through interactions with dynamic environments (Gonzalez et al., 2003). The theory has shown robust explanations of behavior across multiple tasks and contexts, but it is becoming unclear what the theory is able to explain and what it does not. The goal of this chapter is to start addressing this problem. I will introduce IBLT and a recent cognitive model based on this theory: the IBL model of repeated binary choice; then I will discuss the phenomena that the IBL model explains and those that the model does not. The argument is for the theory's robustness but also for clarity in terms of concrete effects that the theory can or cannot account for.

  4. A decision model and cost analysis of intra-operative cell salvage during hepatic resection

    PubMed Central

    Lemke, Madeline; Eeson, Gareth; Lin, Yulia; Tarshis, Jordan; Hallet, Julie; Coburn, Natalie; Law, Calvin; Karanicolas, Paul J.

    2016-01-01

    Background Intraoperative cell salvage (ICS) can reduce allogeneic transfusions but with notable direct costs. This study assessed whether routine use of ICS is cost minimizing in hepatectomy and defines a subpopulation of patients where ICS is most cost minimizing based on patient transfusion risk. Methods A decision model from a health systems perspective was developed to examine adoption and non-adoption of ICS use for hepatectomy. A prospectively maintained database of hepatectomy patients provided data to populate the model. Probabilistic sensitivity analysis was used to determine the probability of ICS being cost-minimizing at specified transfusion risks. One-way sensitivity analysis was used to identify factors most relevant to institutions considering adoption of ICS for hepatectomies. Results In the base case analysis (transfusion risk of 28.8%) the probability that routine utilization of ICS is cost-minimizing is 64%. The probability that ICS is cost-minimizing exceeds 50% if the patient transfusion risk exceeds 25%. The model was most sensitive to patient transfusion risk, variation in costs of allogeneic blood, and number of appropriate cases the device could be used for. Conclusions ICS is cost-minimizing for routine use in liver resection, particularly when used for patients with a risk of transfusion of 25% or greater. PMID:27154806

  5. Team-based learning instruction for responsible conduct of research positively impacts ethical decision-making.

    PubMed

    McCormack, Wayne T; Garvan, Cynthia W

    2014-01-01

    Common practices for responsible conduct of research (RCR) instruction have recently been shown to have no positive impact on and possibly to undermine ethical decision-making (EDM). We show that a team-based learning (TBL) RCR curriculum results in some gains in decision ethicality, the use of more helpful metacognitive reasoning strategies in decision-making, and elimination of most negative effects of other forms of RCR instruction on social-behavioral responses. TBL supports the reasoning strategies and social mechanisms that underlie EDM and ethics instruction, and may provide a more effective method for RCR instruction than lectures and small group discussion.

  6. Team-Based Learning Instruction for Responsible Conduct of Research Positively Impacts Ethical Decision-Making

    PubMed Central

    McCormack, Wayne T.; Garvan, Cynthia W.

    2013-01-01

    Common practices for responsible conduct of research (RCR) instruction have recently been shown to have no positive impact on and possibly to undermine ethical decision-making (EDM). We show that a team-based learning (TBL) RCR curriculum results in some gains in decision ethicality, the use of more helpful meta-cognitive reasoning strategies in decision-making, and elimination of most negative effects of other forms of RCR instruction on social–behavioral responses. TBL supports the reasoning strategies and social mechanisms that underlie EDM and ethics instruction, and may provide a more effective method for RCR instruction than lectures and small group discussion. PMID:24073606

  7. Improved Frame Mode Selection for AMR-WB+ Based on Decision Tree

    NASA Astrophysics Data System (ADS)

    Kim, Jong Kyu; Kim, Nam Soo

    In this letter, we propose a coding mode selection method for the AMR-WB+ audio coder based on a decision tree. In order to reduce computation while maintaining good performance, decision tree classifier is adopted with the closed loop mode selection results as the target classification labels. The size of the decision tree is controlled by pruning, so the proposed method does not increase the memory requirement significantly. Through an evaluation test on a database covering both speech and music materials, the proposed method is found to achieve a much better mode selection accuracy compared with the open loop mode selection module in the AMR-WB+.

  8. The impact of activity based cost accounting on health care capital investment decisions.

    PubMed

    Greene, J K; Metwalli, A

    2001-01-01

    For the future survival of the rural hospitals in the U.S., there is a need to make sound financial decisions. The Activity Based Cost Accounting (ABC) provides more accurate and detailed cost information to make an informed capital investment decision taking into consideration all the costs and revenue reimbursement from third party payors. The paper analyzes, evaluates and compares two scenarios of acquiring capital equipment and attempts to show the importance of utilizing the ABC method in making a sound financial decision as compared to the traditional cost method. PMID:11794757

  9. Spatial multi-criteria decision analysis to predict suitability for African swine fever endemicity in Africa

    PubMed Central

    2014-01-01

    Background African swine fever (ASF) is endemic in several countries of Africa and may pose a risk to all pig producing areas on the continent. Official ASF reporting is often rare and there remains limited awareness of the continent-wide distribution of the disease. In the absence of accurate ASF outbreak data and few quantitative studies on the epidemiology of the disease in Africa, we used spatial multi-criteria decision analysis (MCDA) to derive predictions of the continental distribution of suitability for ASF persistence in domestic pig populations as part of sylvatic or domestic transmission cycles. In order to incorporate the uncertainty in the relative importance of different criteria in defining suitability, we modelled decisions within the MCDA framework using a stochastic approach. The predictive performance of suitability estimates was assessed via a partial ROC analysis using ASF outbreak data reported to the OIE since 2005. Results Outputs from the spatial MCDA indicate that large areas of sub-Saharan Africa may be suitable for ASF persistence as part of either domestic or sylvatic transmission cycles. Areas with high suitability for pig to pig transmission (‘domestic cycles’) were estimated to occur throughout sub-Saharan Africa, whilst areas with high suitability for introduction from wildlife reservoirs (‘sylvatic cycles’) were found predominantly in East, Central and Southern Africa. Based on average AUC ratios from the partial ROC analysis, the predictive ability of suitability estimates for domestic cycles alone was considerably higher than suitability estimates for sylvatic cycles alone, or domestic and sylvatic cycles in combination. Conclusions This study provides the first standardised estimates of the distribution of suitability for ASF transmission associated with domestic and sylvatic cycles in Africa. We provide further evidence for the utility of knowledge-driven risk mapping in animal health, particularly in data

  10. Regional risk assessment for contaminated sites part 1: vulnerability assessment by multicriteria decision analysis.

    PubMed

    Zabeo, A; Pizzol, L; Agostini, P; Critto, A; Giove, S; Marcomini, A

    2011-11-01

    As highlighted in the EU Soil Communication, local contamination is one of the main soil threats and it is often related to present and past industrial activities which left a legacy of a high number of contaminated sites in Europe. These contaminated sites can be harmful to many different receptors according to their sensitivity/susceptibility to contamination, and specific vulnerability evaluations are needed in order to manage this widely spread environmental issue. In this paper a novel comprehensive vulnerability assessment framework to assess regional receptor susceptibility to contaminated site is presented. The developed methodology, which combines multi criteria decision analysis (MCDA) techniques and spatial analysis, can be applied to different receptors recognized as relevant for regional assessment. In order to characterize each receptor, picked parameters significant for the estimation of the vulnerability to contaminated sites have been selected, normalized and aggregated by means of multi criteria decision analysis (MCDA) techniques. The developed MCDA methodology, based on the Choquet integral, allows to include expert judgments for the elicitation of synergic and conflicting effects between involved criteria and is applied to all the geographical objects representing the identified receptors. To test the potential of the vulnerability methodology, it has been applied to a specific case study area in the upper Silesia region of Poland where it proved to be reliable and consistent with the environmental experts' expected results. The vulnerability assessment results indicate that groundwater is the most vulnerable receptor characterized by a wide area with vulnerability scores belonging to the highest vulnerability class. As far as the other receptors are concerned, human health and surface water are characterized by quite homogeneous vulnerability scores falling in the medium-high vulnerability classes, while protected areas resulted to be the less

  11. Fuzzy Cognitive Map scenario-based medical decision support systems for education.

    PubMed

    Georgopoulos, Voula C; Chouliara, Spyridoula; Stylios, Chrysostomos D

    2014-01-01

    Soft Computing (SC) techniques are based on exploiting human knowledge and experience and they are extremely useful to model any complex decision making procedure. Thus, they have a key role in the development of Medical Decision Support Systems (MDSS). The soft computing methodology of Fuzzy Cognitive Maps has successfully been used to represent human reasoning and to infer conclusions and decisions in a human-like way and thus, FCM-MDSSs have been developed. Such systems are able to assist in critical decision-making, support diagnosis procedures and consult medical professionals. Here a new methodology is introduced to expand the utilization of FCM-MDSS for learning and educational purposes using a scenario-based learning (SBL) approach. This is particularly important in medical education since it allows future medical professionals to safely explore extensive "what-if" scenarios in case studies and prepare for dealing with critical adverse events.

  12. Eielson Air Force Base operable unit 2 and other areas record of decision

    SciTech Connect

    Lewis, R.E.; Smith, R.M.

    1994-10-01

    This decision document presents the selected remedial actions and no action decisions for Operable Unit 2 (OU2) at Eielson Air Force Base (AFB), Alaska, chosen in accordance with state and federal regulations. This document also presents the decision that no further action is required for 21 other source areas at Eielson AFB. This decision is based on the administrative record file for this site. OU2 addresses sites contaminated by leaks and spills of fuels. Soils contaminated with petroleum products occur at or near the source of contamination. Contaminated subsurface soil and groundwater occur in plumes on the top of a shallow groundwater table that fluctuates seasonally. These sites pose a risk to human health and the environment because of ingestion, inhalation, and dermal contact with contaminated groundwater. The purpose of this response is to prevent current or future exposure to the contaminated groundwater, to reduce further contaminant migration into the groundwater, and to remediate groundwater.

  13. A decision model for cost effective design of biomass based green energy supply chains.

    PubMed

    Yılmaz Balaman, Şebnem; Selim, Hasan

    2015-09-01

    The core driver of this study is to deal with the design of anaerobic digestion based biomass to energy supply chains in a cost effective manner. In this concern, a decision model is developed. The model is based on fuzzy multi objective decision making in order to simultaneously optimize multiple economic objectives and tackle the inherent uncertainties in the parameters and decision makers' aspiration levels for the goals. The viability of the decision model is explored with computational experiments on a real-world biomass to energy supply chain and further analyses are performed to observe the effects of different conditions. To this aim, scenario analyses are conducted to investigate the effects of energy crop utilization and operational costs on supply chain structure and performance measures.

  14. A decision model for cost effective design of biomass based green energy supply chains.

    PubMed

    Yılmaz Balaman, Şebnem; Selim, Hasan

    2015-09-01

    The core driver of this study is to deal with the design of anaerobic digestion based biomass to energy supply chains in a cost effective manner. In this concern, a decision model is developed. The model is based on fuzzy multi objective decision making in order to simultaneously optimize multiple economic objectives and tackle the inherent uncertainties in the parameters and decision makers' aspiration levels for the goals. The viability of the decision model is explored with computational experiments on a real-world biomass to energy supply chain and further analyses are performed to observe the effects of different conditions. To this aim, scenario analyses are conducted to investigate the effects of energy crop utilization and operational costs on supply chain structure and performance measures. PMID:25983228

  15. Evidence-Based Practice: A Framework for Making Effective Decisions

    ERIC Educational Resources Information Center

    Spencer, Trina D.; Detrich, Ronnie; Slocum, Timothy A.

    2012-01-01

    The research to practice gap in education has been a long-standing concern. The enactment of No Child Left Behind brought increased emphasis on the value of using scientifically based instructional practices to improve educational outcomes. It also brought education into the broader evidence-based practice movement that started in medicine and has…

  16. An fMRI-Based Neural Signature of Decisions to Smoke Cannabis.

    PubMed

    Bedi, Gillinder; Lindquist, Martin A; Haney, Margaret

    2015-11-01

    Drug dependence may be at its core a pathology of choice, defined by continued decisions to use drugs irrespective of negative consequences. Despite evidence of dysregulated decision making in addiction, little is known about the neural processes underlying the most clinically relevant decisions drug users make: decisions to use drugs. Here, we combined functional magnetic resonance imaging (fMRI), machine learning, and human laboratory drug administration to investigate neural activation underlying decisions to smoke cannabis. Nontreatment-seeking daily cannabis smokers completed an fMRI choice task, making repeated decisions to purchase or decline 1-12 placebo or active cannabis 'puffs' ($0.25-$5/puff). One randomly selected decision was implemented. If the selected choice had been bought, the cost was deducted from study earnings and the purchased cannabis smoked in the laboratory; alternatively, the participant remained in the laboratory without cannabis. Machine learning with leave-one-subject-out cross-validation identified distributed neural activation patterns discriminating decisions to buy cannabis from declined offers. A total of 21 participants were included in behavioral analyses; 17 purchased cannabis and were thus included in fMRI analyses. Purchasing varied lawfully with dose and cost. The classifier discriminated with 100% accuracy between fMRI activation patterns for purchased vs declined cannabis at the level of the individual. Dorsal striatum, insula, posterior parietal regions, anterior and posterior cingulate, and dorsolateral prefrontal cortex all contributed reliably to this neural signature of decisions to smoke cannabis. These findings provide the basis for a brain-based characterization of drug-related decision making in drug abuse, including effects of psychological and pharmacological interventions on these processes.

  17. Risk patterns and correlated brain activities. Multidimensional statistical analysis of FMRI data in economic decision making study.

    PubMed

    van Bömmel, Alena; Song, Song; Majer, Piotr; Mohr, Peter N C; Heekeren, Hauke R; Härdle, Wolfgang K

    2014-07-01

    Decision making usually involves uncertainty and risk. Understanding which parts of the human brain are activated during decisions under risk and which neural processes underly (risky) investment decisions are important goals in neuroeconomics. Here, we analyze functional magnetic resonance imaging (fMRI) data on 17 subjects who were exposed to an investment decision task from Mohr, Biele, Krugel, Li, and Heekeren (in NeuroImage 49, 2556-2563, 2010b). We obtain a time series of three-dimensional images of the blood-oxygen-level dependent (BOLD) fMRI signals. We apply a panel version of the dynamic semiparametric factor model (DSFM) presented in Park, Mammen, Wolfgang, and Borak (in Journal of the American Statistical Association 104(485), 284-298, 2009) and identify task-related activations in space and dynamics in time. With the panel DSFM (PDSFM) we can capture the dynamic behavior of the specific brain regions common for all subjects and represent the high-dimensional time-series data in easily interpretable low-dimensional dynamic factors without large loss of variability. Further, we classify the risk attitudes of all subjects based on the estimated low-dimensional time series. Our classification analysis successfully confirms the estimated risk attitudes derived directly from subjects' decision behavior. PMID:25205006

  18. Proceedings of a consensus conference: Risk-Based Decision Making for Blood Safety.

    PubMed

    Leach Bennett, Judie; Blajchman, Morris A; Delage, Gilles; Fearon, Margaret; Devine, Dana

    2011-10-01

    Blood safety decision making has become increasingly complex, and a framework for risk-based decision making is, thus, needed. The purpose of this consensus conference was to bring together international experts in an effort to develop the foundations for such a framework. These proceedings are described with a view to making available to the transfusion medicine community the considerable amount of information and insight that was presented and that emerged through debate by the experts, panel members, and delegates.

  19. Proceedings of a consensus conference: Risk-Based Decision Making for Blood Safety.

    PubMed

    Leach Bennett, Judie; Blajchman, Morris A; Delage, Gilles; Fearon, Margaret; Devine, Dana

    2011-10-01

    Blood safety decision making has become increasingly complex, and a framework for risk-based decision making is, thus, needed. The purpose of this consensus conference was to bring together international experts in an effort to develop the foundations for such a framework. These proceedings are described with a view to making available to the transfusion medicine community the considerable amount of information and insight that was presented and that emerged through debate by the experts, panel members, and delegates. PMID:21763103

  20. Levels of Analysis in Mass Media Decision-Making: A Taxonomy and Research Strategy.

    ERIC Educational Resources Information Center

    Dimmick, John W.

    A taxonomy of levels of analysis in mass media decision making is presented in this paper, and a strategy is proposed for incorporating the different levels into the design of research. Following a clarification of the concept of influence and its relationship to the levels of analysis used in the taxonomic structure, the paper describes the…

  1. Realtime Decision Making on EO-1 Using Onboard Science Analysis

    NASA Technical Reports Server (NTRS)

    Sherwood, Robert; Chien, Steve; Davies, Ashley; Mandl, Dan; Frye, Stu

    2004-01-01

    Recent autonomy experiments conducted on Earth Observing 1 (EO-1) using the Autonomous Sciencecraft Experiment (ASE) flight software has been used to classify key features in hyperspectral images captured by EO-1. Furthermore, analysis is performed by this software onboard EO-1 and then used to modify the operational plan without interaction from the ground. This paper will outline the overall operations concept and provide some details and examples of the onboard science processing, science analysis, and replanning.

  2. Negative decision outcomes are more common among people with lower decision-making competence: an item-level analysis of the Decision Outcome Inventory (DOI)

    PubMed Central

    Parker, Andrew M.; Bruine de Bruin, Wändi; Fischhoff, Baruch

    2015-01-01

    Most behavioral decision research takes place in carefully controlled laboratory settings, and examination of relationships between performance and specific real-world decision outcomes is rare. One prior study shows that people who perform better on hypothetical decision tasks, assessed using the Adult Decision-Making Competence (A-DMC) measure, also tend to experience better real-world decision outcomes, as reported on the Decision Outcomes Inventory (DOI). The DOI score reflects avoidance of outcomes that could result from poor decisions, ranging from serious (e.g., bankruptcy) to minor (e.g., blisters from sunburn). The present analyses go beyond the initial work, which focused on the overall DOI score, by analyzing the relationships between specific decision outcomes and A-DMC performance. Most outcomes are significantly more likely among people with lower A-DMC scores, even after taking into account two variables expected to produce worse real-world decision outcomes: younger age and lower socio-economic status. We discuss the usefulness of DOI as a measure of successful real-world decision-making. PMID:25904876

  3. General Formalism of Decision Making Based on Theory of Open Quantum Systems

    NASA Astrophysics Data System (ADS)

    Asano, M.; Ohya, M.; Basieva, I.; Khrennikov, A.

    2013-01-01

    We present the general formalism of decision making which is based on the theory of open quantum systems. A person (decision maker), say Alice, is considered as a quantum-like system, i.e., a system which information processing follows the laws of quantum information theory. To make decision, Alice interacts with a huge mental bath. Depending on context of decision making this bath can include her social environment, mass media (TV, newspapers, INTERNET), and memory. Dynamics of an ensemble of such Alices is described by Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) equation. We speculate that in the processes of evolution biosystems (especially human beings) designed such "mental Hamiltonians" and GKSL-operators that any solution of the corresponding GKSL-equation stabilizes to a diagonal density operator (In the basis of decision making.) This limiting density operator describes population in which all superpositions of possible decisions has already been resolved. In principle, this approach can be used for the prediction of the distribution of possible decisions in human populations.

  4. Prevalence of clinically significant decisional conflict: an analysis of five studies on decision-making in primary care

    PubMed Central

    Thompson-Leduc, Philippe; Turcotte, Stéphane; Labrecque, Michel; Légaré, France

    2016-01-01

    Objectives Unresolved clinically significant decisional conflict (CSDC) in patients following a consultation with health professionals is often the result of inadequate patient involvement in decision-making and may result in poor outcomes. We sought to identify the prevalence of CSDC in studies on decision-making in primary care and to explore its risk factors. Setting We performed a secondary analysis of existing data sets from studies conducted in Primary Care Practice-Based Research Networks in Québec and Ontario, Canada. Participants Eligible studies included a patient-reported measure on the 16-item Decisional Conflict Scale (DCS) following a decision made with a healthcare professional with no study design restriction. Primary and secondary outcome measures CSDC was defined as a score ≥25/100 on the DCS. The prevalence of CSDC was stratified by sex; and patient-level logistic regression analysis was performed to explore its potential risk factors. Data sets of studies were analysed individually and qualitatively compared. Results 5 projects conducted between 2003 and 2010 were included. They covered a range of decisions: prenatal genetic screening, antibiotics for acute respiratory infections and miscellaneous. Altogether, the 5 projects gathered data from encounters with a total of 1338 primary care patients (69% female; range of age 15–83). The prevalence of CSDC in patients varied across studies and ranged from 10.3% (95% CI 7.2% to 13.4%) to 31.1% (95% CI 26.6% to 35.6%). Across the 5 studies, risk factors of CSDC included being male, living alone and being 45 or older. Conclusions Prevalence of CSDC in patients who had enrolled in studies conducted in primary care contexts was substantial and appeared to vary according to the type of decision as well as to patient characteristics such as sex, living arrangement and age. Patients presenting risk factors of CSDC should be offered tools to increase their involvement in decision-making. PMID:27354076

  5. Reward-based decision signals in parietal cortex are partially embodied.

    PubMed

    Kubanek, Jan; Snyder, Lawrence H

    2015-03-25

    Recordings in the lateral intraparietal area (LIP) reveal that parietal cortex encodes variables related to spatial decision-making, the selection of desirable targets in space. It has been unclear whether parietal cortex is involved in spatial decision-making in general, or whether specific parietal compartments subserve decisions made using specific actions. To test this, we engaged monkeys (Macaca mulatta) in a reward-based decision task in which they selected a target based on its desirability. The animals' choice behavior in this task followed the molar matching law, and in each trial was governed by the desirability of the choice targets. Critically, animals were instructed to make the choice using one of two actions: eye movements (saccades) and arm movements (reaches). We recorded the discharge activity of neurons in area LIP and the parietal reach region (PRR) of the parietal cortex. In line with previous studies, we found that both LIP and PRR encode a reward-based decision variable, the target desirability. Crucially, the target desirability was encoded in LIP at least twice as strongly when choices were made using saccades compared with reaches. In contrast, PRR encoded target desirability only for reaches and not for saccades. These data suggest that decisions can evolve in dedicated parietal circuits in the context of specific actions. This finding supports the hypothesis of an intentional representation of developing decisions in parietal cortex. Furthermore, the close link between the cognitive (decision-related) and bodily (action-related) processes presents a neural contribution to the theories of embodied cognition. PMID:25810518

  6. Expected Utility Based Decision Making under Z-Information and Its Application.

    PubMed

    Aliev, Rashad R; Mraiziq, Derar Atallah Talal; Huseynov, Oleg H

    2015-01-01

    Real-world decision relevant information is often partially reliable. The reasons are partial reliability of the source of information, misperceptions, psychological biases, incompetence, and so forth. Z-numbers based formalization of information (Z-information) represents a natural language (NL) based value of a variable of interest in line with the related NL based reliability. What is important is that Z-information not only is the most general representation of real-world imperfect information but also has the highest descriptive power from human perception point of view as compared to fuzzy number. In this study, we present an approach to decision making under Z-information based on direct computation over Z-numbers. This approach utilizes expected utility paradigm and is applied to a benchmark decision problem in the field of economics. PMID:26366163

  7. Expected Utility Based Decision Making under Z-Information and Its Application

    PubMed Central

    Aliev, Rashad R.; Mraiziq, Derar Atallah Talal; Huseynov, Oleg H.

    2015-01-01

    Real-world decision relevant information is often partially reliable. The reasons are partial reliability of the source of information, misperceptions, psychological biases, incompetence, and so forth. Z-numbers based formalization of information (Z-information) represents a natural language (NL) based value of a variable of interest in line with the related NL based reliability. What is important is that Z-information not only is the most general representation of real-world imperfect information but also has the highest descriptive power from human perception point of view as compared to fuzzy number. In this study, we present an approach to decision making under Z-information based on direct computation over Z-numbers. This approach utilizes expected utility paradigm and is applied to a benchmark decision problem in the field of economics. PMID:26366163

  8. Expected Utility Based Decision Making under Z-Information and Its Application.

    PubMed

    Aliev, Rashad R; Mraiziq, Derar Atallah Talal; Huseynov, Oleg H

    2015-01-01

    Real-world decision relevant information is often partially reliable. The reasons are partial reliability of the source of information, misperceptions, psychological biases, incompetence, and so forth. Z-numbers based formalization of information (Z-information) represents a natural language (NL) based value of a variable of interest in line with the related NL based reliability. What is important is that Z-information not only is the most general representation of real-world imperfect information but also has the highest descriptive power from human perception point of view as compared to fuzzy number. In this study, we present an approach to decision making under Z-information based on direct computation over Z-numbers. This approach utilizes expected utility paradigm and is applied to a benchmark decision problem in the field of economics.

  9. Diverter AI based decision aid, phases 1 and 2

    NASA Technical Reports Server (NTRS)

    Sexton, George A.; Bayles, Scott J.; Patterson, Robert W.; Schulke, Duane A.; Williams, Deborah C.

    1989-01-01

    It was determined that a system to incorporate artificial intelligence (AI) into airborne flight management computers is feasible. The AI functions that would be most useful to the pilot are to perform situational assessment, evaluate outside influences on the contemplated rerouting, perform flight planning/replanning, and perform maneuver planning. A study of the software architecture and software tools capable of demonstrating Diverter was also made. A skeletal planner known as the Knowledge Acquisition Development Tool (KADET), which is a combination script-based and rule-based system, was used to implement the system. A prototype system was developed which demonstrates advanced in-flight planning/replanning capabilities.

  10. 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

  11. Development of a Geographic Information System-Based Decision Support Tool for Evaluating Windfarm Sitings in Great Lakes Aquatic Habitats

    SciTech Connect

    Wehrly, Kevin E.; Rutherford, Edward S.; Wang, Lizhu; Breck, Jason; Mason, Lacey; Nelson, Scott

    2011-07-31

    As an outcome of our research project, we developed software and data for the Lakebed Alteration Decision Support Tool (LADST), a web-based decision support program to assist resource managers in making siting decisions for offshore wind farms (as well as other lakebed-altering projects) in the United States' waters of the Great Lakes. Users of the LADST can create their own offshore wind farm suitability maps, based upon suitability criteria of their own choosing by visiting a public web site. The LADST can be used to represent the different priorities or values of different Great Lakes stakeholders for wind farm siting, as well as the different suitability requirements of wind farms (or different types of development projects) in a single suitability analysis system. The LADST makes this type of customized suitability analysis easily accessible to users who have no specialized software or experience with geographic information systems (GIS). It also may increase the transparency of the siting and permitting process for offshore wind farms, as it makes the suitability analysis equally accessible to resource managers, wind farm developers, and concerned citizens.

  12. Tier III Assessments, Data-Based Decision Making, and Interventions

    ERIC Educational Resources Information Center

    Powers, Kristin; Mandal, Arpita

    2011-01-01

    Within the Response-to-Intervention framework, students who fail to profit from high-quality general education instruction, accommodations, and supplemental instruction progress to a more intensive intervention program, sometimes referred to as "Tier III." This article describes a problem-solving approach to designing such intensive, data-based,…

  13. Allocating health care: cost-utility analysis, informed democratic decision making, or the veil of ignorance?

    PubMed

    Goold, S D

    1996-01-01

    Assuming that rationing health care is unavoidable, and that it requires moral reasoning, how should we allocate limited health care resources? This question is difficult because our pluralistic, liberal society has no consensus on a conception of distributive justice. In this article I focus on an alternative: Who shall decide how to ration health care, and how shall this be done to respect autonomy, pluralism, liberalism, and fairness? I explore three processes for making rationing decisions: cost-utility analysis, informed democratic decision making, and applications of the veil of ignorance. I evaluate these processes as examples of procedural justice, assuming that there is no outcome considered the most just. I use consent as a criterion to judge competing processes so that rationing decisions are, to some extent, self-imposed. I also examine the processes' feasibility in our current health care system. Cost-utility analysis does not meet criteria for actual or presumed consent, even if costs and health-related utility could be measured perfectly. Existing structures of government cannot creditably assimilate the information required for sound rationing decisions, and grassroots efforts are not representative. Applications of the veil of ignorance are more useful for identifying principles relevant to health care rationing than for making concrete rationing decisions. I outline a process of decision making, specifically for health care, that relies on substantive, selected representation, respects pluralism, liberalism, and deliberative democracy, and could be implemented at the community or organizational level.

  14. Learning from examples - Generation and evaluation of decision trees for software resource analysis

    NASA Technical Reports Server (NTRS)

    Selby, Richard W.; Porter, Adam A.

    1988-01-01

    A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for software resource data analysis. The trees identify classes of objects (software modules) that had high development effort. Sixteen software systems ranging from 3,000 to 112,000 source lines were selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4,700 objects, captured information about the development effort, faults, changes, design style, and implementation style. A total of 9,600 decision trees were automatically generated and evaluated. The trees correctly identified 79.3 percent of the software modules that had high development effort or faults, and the trees generated from the best parameter combinations correctly identified 88.4 percent of the modules on the average.

  15. Shaping the Conversation: A Secondary Analysis of Reproductive Decision-Making Among Black Mothers with HIV

    PubMed Central

    Amutah, Ndidiamaka N.; Gifuni, Jacqueline; Wesley, Yvonne

    2016-01-01

    The purpose of this qualitative secondary data analysis is to examine the major influencers on mothers with HIV in their childbearing decisions, as well as how those influencers shape conversations with clinicians and health-care providers regarding HIV treatment and prevention. The original study gained insight into the reproductive decision-making of mothers with HIV. By analyzing a subsample of 15 interviews from an original cohort of 25 participants in the earlier study, three major themes were identified as follows: (1) family members, not health-care providers, influence reproductive decisions; (2) negative attitudes toward subsequent pregnancies are mainly due to HIV transmission; and (3) birth control decisions were predominately supported by family members, while health-care providers were not consulted. PMID:27158227

  16. Return or relocate? An inductive analysis of decision-making in a disaster.

    PubMed

    Henry, Jacques

    2013-04-01

    This paper proposes an inductive analysis of the decision as to whether to return or to relocate by persons in the State of Louisiana, United States, who evacuated after Hurricanes Katrina and Rita in August and September 2005, respectively. Drawing on interviews with evacuees in these events and extensive fieldwork in the impacted area, the paper seeks to identify the folk dimensions of the decision-making process, assess their arrangements, and situate the process in the larger context of risk and resilience in an advanced society. It suggests that, despite the material and emotional upheaval experienced by affected persons, the decision-making process is a rational endeavour combining a definite set of tightly interconnected factors, involving material dimensions and substantive values that can act in concert or in conflict. In addition, it indicates that there are significant variations by geographic areas, homeownership, and kind of decision. Some theoretical implications, practical measures, and suggestions for future research are examined. PMID:23278427

  17. Return or relocate? An inductive analysis of decision-making in a disaster.

    PubMed

    Henry, Jacques

    2013-04-01

    This paper proposes an inductive analysis of the decision as to whether to return or to relocate by persons in the State of Louisiana, United States, who evacuated after Hurricanes Katrina and Rita in August and September 2005, respectively. Drawing on interviews with evacuees in these events and extensive fieldwork in the impacted area, the paper seeks to identify the folk dimensions of the decision-making process, assess their arrangements, and situate the process in the larger context of risk and resilience in an advanced society. It suggests that, despite the material and emotional upheaval experienced by affected persons, the decision-making process is a rational endeavour combining a definite set of tightly interconnected factors, involving material dimensions and substantive values that can act in concert or in conflict. In addition, it indicates that there are significant variations by geographic areas, homeownership, and kind of decision. Some theoretical implications, practical measures, and suggestions for future research are examined.

  18. Shaping the Conversation: A Secondary Analysis of Reproductive Decision-Making Among Black Mothers with HIV.

    PubMed

    Amutah, Ndidiamaka N; Gifuni, Jacqueline; Wesley, Yvonne

    2016-01-01

    The purpose of this qualitative secondary data analysis is to examine the major influencers on mothers with HIV in their childbearing decisions, as well as how those influencers shape conversations with clinicians and health-care providers regarding HIV treatment and prevention. The original study gained insight into the reproductive decision-making of mothers with HIV. By analyzing a subsample of 15 interviews from an original cohort of 25 participants in the earlier study, three major themes were identified as follows: (1) family members, not health-care providers, influence reproductive decisions; (2) negative attitudes toward subsequent pregnancies are mainly due to HIV transmission; and (3) birth control decisions were predominately supported by family members, while health-care providers were not consulted. PMID:27158227

  19. Impact of proximity-adjusted preferences on rank-order stability in geographical multicriteria decision analysis

    NASA Astrophysics Data System (ADS)

    Ligmann-Zielinska, Arika; Jankowski, Piotr

    2012-04-01

    This paper presents a new approach to deriving preferences assigned to evaluation criteria in geographical multicriteria decision analysis. In this approach, the preferences, expressed by numeric weights, are adjusted by distance measures derived from the explicit consideration of a locational structure. The structure is given by locations of decision options and high importance reference objects. The approach is demonstrated on the example of a house selection case study in San Diego, California. The results show that proximity-adjusted preferences for the evaluation criteria can alter significantly the rank order of decision options. Consequently, the explicit modeling of spatial preference variability may be needed in order to better account for decision-maker's preferences.

  20. Evidence-based patient choice: a prostate cancer decision aid in plain language

    PubMed Central

    Holmes-Rovner, Margaret; Stableford, Sue; Fagerlin, Angela; Wei, John T; Dunn, Rodney L; Ohene-Frempong, Janet; Kelly-Blake, Karen; Rovner, David R

    2005-01-01

    Background Decision aids (DA) to assist patients in evaluating treatment options and sharing in decision making have proliferated in recent years. Most require high literacy and do not use plain language principles. We describe one of the first attempts to design a decision aid using principles from reading research and document design. The plain language DA prototype addressed treatment decisions for localized prostate cancer. Evaluation assessed impact on knowledge, decisions, and discussions with doctors in men newly diagnosed with prostate cancer. Methods Document development steps included preparing an evidence-based DA in standard medical parlance, iteratively translating it to emphasize shared decision making and plain language in three formats (booklet, Internet, and audio-tape). Scientific review of medical content was integrated with expert health literacy review of document structure and design. Formative evaluation methods included focus groups (n = 4) and survey of a new sample of men newly diagnosed with prostate cancer (n = 60), compared with historical controls (n = 184). Results A transparent description of the development process and design elements is reported. Formative evaluation among newly diagnosed prostate cancer patients found the DA to be clear and useful in reaching a decision. Newly diagnosed patients reported more discussions with doctors about treatment options, and showed increases in knowledge of side effects of radiation therapy. Conclusion The plain language DA presenting medical evidence in text and numerical formats appears acceptable and useful in decision-making about localized prostate cancer treatment. Further testing should evaluate the impact of all three media on decisions made and quality of life in the survivorship period, especially among very low literacy men. PMID:15963238