Science.gov

Sample records for decision analysis based

  1. Rule-based analysis of pilot decisions

    NASA Technical Reports Server (NTRS)

    Lewis, C. M.

    1985-01-01

    The application of the rule identification technique to the analysis of human performance data is proposed. The relation between the language and identifiable consistencies is discussed. The advantages of production system models for the description of complex human behavior are studied. The use of a Monte Carlo significance testing procedure to assure the validity of the rule identification is examined. An example of the rule-based analysis of Palmer's (1983) data is presented.

  2. Risk Analysis Based Business Rule Enforcement for Intelligent Decision Support

    NASA Astrophysics Data System (ADS)

    Vasilecas, Olegas; Smaizys, Aidas; Brazinskas, Ramunas

    Intelligent information systems are acting by structured rules and do not deal with possible impact on the business environment or future consequences. That is the main reason why automated decisions based on such rules cannot take responsibility and requires involvement or approval of dedicated business people. This limits decision automation possibilities in information systems. However, business rules describe business policy and represent business logics. This can be used in intelligent information systems, together with risk assessment model to simulate real business environment and evaluate possible impact of automated decisions, to support intelligent decision automation. The chapter proposes risk and business rule model integration to provide full intelligent decision automation model used for business rule enforcement and implementation into intelligent software systems of information systems.

  3. Prediction model based on decision tree analysis for laccase mediators.

    PubMed

    Medina, Fabiola; Aguila, Sergio; Baratto, Maria Camilla; Martorana, Andrea; Basosi, Riccardo; Alderete, Joel B; Vazquez-Duhalt, Rafael

    2013-01-10

    A Structure Activity Relationship (SAR) study for laccase mediator systems was performed in order to correctly classify different natural phenolic mediators. Decision tree (DT) classification models with a set of five quantum-chemical calculated molecular descriptors were used. These descriptors included redox potential (ɛ°), ionization energy (E(i)), pK(a), enthalpy of formation of radical (Δ(f)H), and OH bond dissociation energy (D(O-H)). The rationale for selecting these descriptors is derived from the laccase-mediator mechanism. To validate the DT predictions, the kinetic constants of different compounds as laccase substrates, their ability for pesticide transformation as laccase-mediators, and radical stability were experimentally determined using Coriolopsis gallica laccase and the pesticide dichlorophen. The prediction capability of the DT model based on three proposed descriptors showed a complete agreement with the obtained experimental results. PMID:23199741

  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. Item-Based Analysis of Delayed Reward Discounting Decision Making

    PubMed Central

    Gray, Joshua C.; Amlung, Michael; Acker, John; Sweet, Lawrence H.; MacKillop, James

    2014-01-01

    Delayed reward discounting (DRD) is a behavioral economic index of time preference, referring to how much an individual devalues a reward based on its delay in time, and has been linked to a wide array of health behaviors. It is commonly assessed using a task that asks participants to make dichotomous choices between two monetary rewards, one available immediately and the other after a delay. This study sought to shorten an extended iterative DRD assessment to increase its versatility and efficiency. Data were drawn from two young adult samples, an exploratory sample (N = 130) and a confirmatory sample (N = 247). In the exploratory sample, eight items were identified as predicting the majority of the variance in the full task area under the curve (AUC) (R2 = .821; p < .001). In the confirmatory sample, the same eight items similarly predicted the majority of variance in the full task AUC (R2 = .844, p < .001). These results provide initial support for the validity of a brief 8-item assessment of DRD. Priorities for further validation and potential applications are discussed. PMID:24440196

  6. Item-based analysis of delayed reward discounting decision making.

    PubMed

    Gray, Joshua C; Amlung, Michael T; Acker, John D; Sweet, Lawrence H; MacKillop, James

    2014-03-01

    Delayed reward discounting (DRD) is a behavioral economic index of time preference, referring to how much an individual devalues a reward based on its delay in time, and has been linked to a wide array of health behaviors. It is commonly assessed using a task that asks participants to make dichotomous choices between two monetary rewards, one available immediately and the other after a delay. This study sought to shorten an extended iterative DRD assessment to increase its versatility and efficiency. Data were drawn from two young adult samples, an exploratory sample (N=130) and a confirmatory sample (N=247). In the exploratory sample, eight items were identified as predicting the majority of the variance in the full task area under the curve (AUC) (R(2)=.821; p<.001). In the confirmatory sample, the same eight items similarly predicted the majority of variance in the full task AUC (R(2)=.844, p<.001). These results provide initial support for the validity of a brief 8-item assessment of DRD. Priorities for further validation and potential applications are discussed. PMID:24440196

  7. Stochastic decision analysis

    NASA Technical Reports Server (NTRS)

    Lacksonen, Thomas A.

    1994-01-01

    Small space flight project design at NASA Langley Research Center goes through a multi-phase process from preliminary analysis to flight operations. The process insures that each system achieves its technical objectives with demonstrated quality and within planned budgets and schedules. A key technical component of early phases is decision analysis, which is a structure procedure for determining the best of a number of feasible concepts based upon project objectives. Feasible system concepts are generated by the designers and analyzed for schedule, cost, risk, and technical measures. Each performance measure value is normalized between the best and worst values and a weighted average score of all measures is calculated for each concept. The concept(s) with the highest scores are retained, while others are eliminated from further analysis. This project automated and enhanced the decision analysis process. Automation of the decision analysis process was done by creating a user-friendly, menu-driven, spreadsheet macro based decision analysis software program. The program contains data entry dialog boxes, automated data and output report generation, and automated output chart generation. The enhancements to the decision analysis process permit stochastic data entry and analysis. Rather than enter single measure values, the designers enter the range and most likely value for each measure and concept. The data can be entered at the system or subsystem level. System level data can be calculated as either sum, maximum, or product functions of the subsystem data. For each concept, the probability distributions are approximated for each measure and the total score for each concept as either constant, triangular, normal, or log-normal distributions. Based on these distributions, formulas are derived for the probability that the concept meets any given constraint, the probability that the concept meets all constraints, and the probability that the concept is within a given

  8. 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. PMID:25613797

  9. 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.

  10. Rural tourism spatial distribution based on multi-criteria decision analysis and GIS

    NASA Astrophysics Data System (ADS)

    Zhang, Hongxian; Yang, Qingsheng

    2008-10-01

    To study spatial distribution of rural tourism can provide scientific decision basis for developing rural economics. Traditional ways of tourism spatial distribution have some limitations in quantifying priority locations of tourism development on small units. They can only produce the overall tourism distribution locations and whether locations are suitable to tourism development simply while the tourism develop ranking with different decision objectives should be considered. This paper presents a way to find ranking of location of rural tourism development in spatial by integrating multi-criteria decision analysis (MCDA) and geography information system (GIS). In order to develop country economics with inconvenient transportation, undeveloped economy and better tourism resource, these locations should be firstly develop rural tourism. Based on this objective, the tourism develop priority utility of each town is calculated with MCDA and GIS. Towns which should be first develop rural tourism can be selected with higher tourism develop priority utility. The method is used to find ranking of location of rural tourism in Ningbo City successfully. The result shows that MCDA is an effective way for distribution rural tourism in spatial based on special decision objectives and rural tourism can promote economic development.

  11. 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.

  12. 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)

  13. The evolutionary analysis of the ultimatum game based on the net-profit decision

    NASA Astrophysics Data System (ADS)

    Wang, Lu; Ye, Shun-qiang; Jones, Michael C.; Ye, Ye; Wang, Meng; Xie, Neng-gang

    2015-07-01

    In an ultimatum game where competitive pressures and alternating roles exist, we suppose that players make their decisions based on the net profit of their own. Here we conduct a behavioral experiment in a selection examination, and then we establish a model and study the evolution of strategies on square lattices. In this model, we specify a player's strategy with two parameters: offer level α ∈ [ 0 , 1) and net profit acceptance level β ∈ [ - 1 , 1) . Evolutionary results show that individuals characterized by fairness (α → 0.5) and moderate kindness (β < 0, β → 0.0) prevail over other individuals. Further analysis demonstrates that individuals' kindness rather than fairness increases the average payoff of the whole population. Moreover, we conclude that the emergence of kindness is promoted by the spatial structure, and eventually the evolutionary advantage is gained by kindness.

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  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. PMID:27586069

  19. 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.

  20. 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

  1. 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...

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

    NASA Astrophysics Data System (ADS)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-03-01

    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.

  3. 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.

  4. 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. PMID:26734840

  5. 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.

  6. 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.

  7. 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.

  8. 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. PMID:26089862

  9. 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

  10. 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

  11. Point-of-decision prompts for increasing park-based physical activity: a crowdsource analysis

    PubMed Central

    Wilhelm Stanis, Sonja A.; Hipp, J. Aaron

    2014-01-01

    Objective To examine the potential efficacy of using point-of-decision prompts to influence intentions to be active in a park setting. Methods In June 2013, participants from across the U.S. (n=250) completed an online experiment using Amazon’s Mechanical Turk and Survey Monkey. Participants were randomly exposed to a park photo containing a persuasive, theoretically-based message in the form of a sign (treatment) or an identical photo with no sign (control). Differences in intentions to engage in moderate-to-vigorous physical activity within the park were examined between the two conditions for multiple gender, age, and race groups. Results Participants who were exposed to the park photo with the sign reported significantly greater intentions to be active than those who viewed the photo without a sign. This effect was especially strong for women compared to men, but no differences were observed across age or race groups. Conclusion Point-of-decision prompts are a relatively inexpensive, simple, sustainable, and scalable strategy for evoking behavior change in parks and further testing of diverse messages in actual park settings is warranted. PMID:25204987

  12. 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,…

  13. 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

  14. 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

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

    ERIC Educational Resources Information Center

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

    As learners use World Wide Web-based distance learning systems over a period of years, large amounts of learning logs are generated. An instructor needs analysis tools to manage the logs and discover unusual patterns within them to improve instruction. However, logs of a Web server cannot serve as learners' portfolios to satisfy the requirements…

  16. 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.

  17. 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).

  18. 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

  19. APPROACH TO LEVEL 2 ANALYSIS BASED ON LEVEL 1 RESULTS, MEG CATEGORIES AND COMPOUNDS, AND DECISION CRITERIA

    EPA Science Inventory

    The report describes an approach to the decision criteria needed to proceed from the initial emission screening analysis (Level 1) to the detailed emission characterization (Level 2), and a Level 2 analytical approach. The decision criteria, considering only the available Level 1...

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. 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. PMID:25694324

  5. 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

  6. 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

  7. 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…

  8. 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.

  9. 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). PMID:26298253

  10. 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.

  11. 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).

  12. "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…

  13. 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.

  14. Object-based image analysis for scaling properties of rangeland ecosystems: Linking field and image data for management decision making

    NASA Astrophysics Data System (ADS)

    Karl, Jason William

    Management of semi-arid shrub-steppe ecosystems (i.e., rangelands) requires accurate information over large landscapes, and remote sensing is an attractive option for collecting such data. To successfully use remotely-sensed data in landscape-level rangeland management, questions as to the relevance of image data to landscape patterns and optimal scales of analysis must be addressed. Object-based image analysis (OBIA), which segments image pixels into homogeneous regions, or objects, has been suggested as a way to increase accuracy of remotely-sensed products, but little research has gone into how to determine sizes of image objects with regard to scaling of ecosystem properties. The purpose of my dissertation was to determine if OBIA could be used to generate observational scales to match ecological scales in rangelands and to explore the potential for OBIA to generate accurate and repeatable remote-sensing products for managers. The work presented here was conducted in southern Idaho's Snake River Plain region. By comparing OBIA segmentation of satellite imagery into successively coarser objects to pixel-based aggregation methods, I found that canonical correlations between field-collected and image data were similar at the finest scales, but higher for image segmentation as scale increased. I also detected scaling thresholds with image segmentation that were confirmed via semi-variograms of field data. This approach proved useful for evaluating the overall utility of an image to address an objective, and identifying scaling limits for analysis. I next used observations of percent bare-ground cover from 346 field sites to consider how hierarchies of image objects created through OBIA could be used to discover appropriate scales for analysis given a specific objective. Using a regression-based approach, I found that segmentation levels whose predictions of bare-ground cover had spatial dependence that most closely matched the spatial dependence of the field

  15. 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

  16. Decision analysis with approximate probabilities

    NASA Technical Reports Server (NTRS)

    Whalen, Thomas

    1992-01-01

    This paper concerns decisions under uncertainty in which the probabilities of the states of nature are only approximately known. Decision problems involving three states of nature are studied. This is due to the fact that some key issues do not arise in two-state problems, while probability spaces with more than three states of nature are essentially impossible to graph. The primary focus is on two levels of probabilistic information. In one level, the three probabilities are separately rounded to the nearest tenth. This can lead to sets of rounded probabilities which add up to 0.9, 1.0, or 1.1. In the other level, probabilities are rounded to the nearest tenth in such a way that the rounded probabilities are forced to sum to 1.0. For comparison, six additional levels of probabilistic information, previously analyzed, were also included in the present analysis. A simulation experiment compared four criteria for decisionmaking using linearly constrained probabilities (Maximin, Midpoint, Standard Laplace, and Extended Laplace) under the eight different levels of information about probability. The Extended Laplace criterion, which uses a second order maximum entropy principle, performed best overall.

  17. 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

  18. NASA program decisions using reliability analysis.

    NASA Technical Reports Server (NTRS)

    Steinberg, A.

    1972-01-01

    NASA made use of the analytical outputs of reliability people to make management decisions on the Apollo program. Such decisions affected the amount of the incentive fees, how much acceptance testing was necessary, how to optimize development testing, whether to approve engineering changes, and certification of flight readiness. Examples of such analysis are discussed and related to programmatic decisions.-

  19. A GIS based decision support system for estimation, visualization and analysis of air pollution for large Turkish cities

    NASA Astrophysics Data System (ADS)

    Elbir, Tolga

    A decision support system has been developed to support local authorities in air quality management for big Turkish cities. The system is based on CALPUFF dispersion model, digital maps and related databases to estimate the emissions and spatial distribution of air pollutants. It applies a geographical information system. The system estimates ambient air pollution levels at high temporal and spatial resolutions. The system enables mapping of emissions and air quality levels. Mapping and scenario results can be compared with air quality limits. Impact assessment of air pollution abatement measures can also be carried out.

  20. 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

  1. Who Values Information from a Health Plan Internet-Based Decision Tool and Why: A Demographic and Utilization Analysis

    PubMed Central

    Chen, Song; Karaca-Mandic, Pinar; Levin, Regina

    2012-01-01

    Objectives The aim of this study was to investigate factors associated with utilization of health plan Internet-based decision tools. Data Sources and Study Setting Enrollment, claims, plan design, and web transaction data during 2008 provided by a national health insurer for 253,398 subscribers from 919 employers. Study Design Multivariate models of the effects of demographic, health, employer, and plan benefit design characteristics on the use of the tool and its individual function categories. Data Extraction Methods Subscribers, who were either an individual member or a family, were included if at least one family member had 12 months of coverage in 2008. Members older than 65 and those with multiple insurance carriers were excluded. Principal Findings Higher education, higher income, younger age, female gender, higher co-morbidity risk, prevalence of chronic conditions, Caucasian race, and English as the primary language were positively associated with using the tool. Plan benefit characteristics such as free preventive coverage, higher deductible, moderate coinsurance rate, family coverage, and enrollment in health savings accounts were also associated with higher likelihood of using the tool. Conclusions Insurers provide consumers information on cost efficiency, quality, and wellness through Internet-based decision tools, but more effort is needed to reach certain demographics. PMID:22091487

  2. An online evidence-based decision support system for distinguishing benign from malignant vertebral compression fractures by magnetic resonance imaging feature analysis.

    PubMed

    Wang, Kenneth C; Jeanmenne, Anthony; Weber, Griffin M; Thawait, Shrey K; Thawait, Shrey; Carrino, John A

    2011-06-01

    Decision support systems have been used to promote the practice of evidence-based medicine. Computer-assisted diagnosis can serve as one element of evidence-based radiology. One area where such tools may provide benefit is analysis of vertebral compression fractures (VCFs), which can be a challenge in MRI interpretation. VCFs may be benign or malignant in etiology, and several MRI features may help to make this important distinction. We describe a web-based decision support system for discriminating benign from malignant VCFs as a prototype for a more general diagnostic decision support framework for radiologists. The system has three components: a feature checklist with an image gallery derived from proven reference cases, a prediction model, and a reporting mechanism. The website allows users to input the findings for a case to be interpreted using a structured feature checklist. The image gallery complements the checklist, for clarity and training purposes. The input from the checklist is then used to calculate the likelihood of malignancy by a logistic regression prediction model. Standardized report text is generated that summarizes pertinent positive and negative findings. This computer-assisted diagnosis system demonstrates the integration of three areas where diagnostic decision support can aid radiologists: first, in image interpretation, through feature checklists and illustrative image galleries; second, in feature-based prediction modeling; and third, in structured reporting. We present a diagnostic decision support tool that provides radiologists with evidence-based guidance for discriminating benign from malignant VCF. This model may be useful in other difficult-diagnosis situations and requires further clinical testing. PMID:20680384

  3. Experimental analysis of multi-attribute decision-making based on Atanassov intuitionistic fuzzy sets: a discussion of anchor dependency and accuracy functions

    NASA Astrophysics Data System (ADS)

    Chen, Ting-Yu

    2012-06-01

    This article presents a useful method for relating anchor dependency and accuracy functions to multiple attribute decision-making (MADM) problems in the context of Atanassov intuitionistic fuzzy sets (A-IFSs). Considering anchored judgement with displaced ideals and solution precision with minimal hesitation, several auxiliary optimisation models have proposed to obtain the optimal weights of the attributes and to acquire the corresponding TOPSIS (the technique for order preference by similarity to the ideal solution) index for alternative rankings. Aside from the TOPSIS index, as a decision-maker's personal characteristics and own perception of self may also influence the direction in the axiom of choice, the evaluation of alternatives is conducted based on distances of each alternative from the positive and negative ideal alternatives, respectively. This article originates from Li's [Li, D.-F. (2005), 'Multiattribute Decision Making Models and Methods Using Intuitionistic Fuzzy Sets', Journal of Computer and System Sciences, 70, 73-85] work, which is a seminal study of intuitionistic fuzzy decision analysis using deduced auxiliary programming models, and deems it a benchmark method for comparative studies on anchor dependency and accuracy functions. The feasibility and effectiveness of the proposed methods are illustrated by a numerical example. Finally, a comparative analysis is illustrated with computational experiments on averaging accuracy functions, TOPSIS indices, separation measures from positive and negative ideal alternatives, consistency rates of ranking orders, contradiction rates of the top alternative and average Spearman correlation coefficients.

  4. Decision Analysis Tools for Volcano Observatories

    NASA Astrophysics Data System (ADS)

    Hincks, T. H.; Aspinall, W.; Woo, G.

    2005-12-01

    Staff at volcano observatories are predominantly engaged in scientific activities related to volcano monitoring and instrumentation, data acquisition and analysis. Accordingly, the academic education and professional training of observatory staff tend to focus on these scientific functions. From time to time, however, staff may be called upon to provide decision support to government officials responsible for civil protection. Recognizing that Earth scientists may have limited technical familiarity with formal decision analysis methods, specialist software tools that assist decision support in a crisis should be welcome. A review is given of two software tools that have been under development recently. The first is for probabilistic risk assessment of human and economic loss from volcanic eruptions, and is of practical use in short and medium-term risk-informed planning of exclusion zones, post-disaster response, etc. A multiple branch event-tree architecture for the software, together with a formalism for ascribing probabilities to branches, have been developed within the context of the European Community EXPLORIS project. The second software tool utilizes the principles of the Bayesian Belief Network (BBN) for evidence-based assessment of volcanic state and probabilistic threat evaluation. This is of practical application in short-term volcano hazard forecasting and real-time crisis management, including the difficult challenge of deciding when an eruption is over. An open-source BBN library is the software foundation for this tool, which is capable of combining synoptically different strands of observational data from diverse monitoring sources. A conceptual vision is presented of the practical deployment of these decision analysis tools in a future volcano observatory environment. Summary retrospective analyses are given of previous volcanic crises to illustrate the hazard and risk insights gained from use of these tools.

  5. Data Decision Analysis: Project Shoal

    SciTech Connect

    Forsgren, Frank; Pohll, Greg; Tracy, John

    1999-01-01

    The purpose of this study was to determine the most appropriate field activities in terms of reducing the uncertainty in the groundwater flow and transport model at the Project Shoal area. The data decision analysis relied on well-known tools of statistics and uncertainty analysis. This procedure identified nine parameters that were deemed uncertain. These included effective porosity, hydraulic head, surface recharge, hydraulic conductivity, fracture correlation scale, fracture orientation, dip angle, dissolution rate of radionuclides from the puddle glass, and the retardation coefficient, which describes the sorption characteristics. The parameter uncertainty was described by assigning prior distributions for each of these parameters. Next, the various field activities were identified that would provide additional information on these parameters. Each of the field activities was evaluated by an expert panel to estimate posterior distribution of the parameters assuming a field activity was performed. The posterior distributions describe the ability of the field activity to estimate the true value of the nine parameters. Monte Carlo techniques were used to determine the current uncertainty, the reduction of uncertainty if a single parameter was known with certainty, and the reduction of uncertainty expected from each field activity on the model predictions. The mean breakthrough time to the downgradient land withdrawal boundary and the peak concentration at the control boundary were used to evaluate the uncertainty reduction. The radionuclide 137Cs was used as the reference solute, as its migration is dependent on all of the parameters. The results indicate that the current uncertainty of the model yields a 95 percent confidence interval between 42 and 1,412 years for the mean breakthrough time and an 18 order-of-magnitude range in peak concentration. The uncertainty in effective porosity and recharge dominates the uncertainty in the model predictions, while the

  6. 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 ...

  7. 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...

  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. SANDS - Sediment Analysis Network for Decision Support

    NASA Astrophysics Data System (ADS)

    Hardin, D. M.; Hawkins, L.; He, M.; Ebersole, S.

    2010-12-01

    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 SANDS project is also investigating the effects of sediment immersed oil from the Deepwater Horizon disaster in April 2010 which has the potential to resurface as a result of tropical storm activity. 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 Sediment Analysis Network for Decision Support has generated a number of decision support products derived from MODIS, Landsat and SeaWiFS instruments that potentially support

  10. [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

  11. [Spectral classification based on Bayes decision].

    PubMed

    Liu, Rong; Jin, Hong-Mei; Duan, Fu-Qing

    2010-03-01

    The rapid development of astronomical observation has led to many large sky surveys such as SDSS (Sloan digital sky survey) and LAMOST (large sky area multi-object spectroscopic telescope). Since these surveys have produced very large numbers of spectra, automated spectral analysis becomes desirable and necessary. The present paper studies the spectral classification method based on Bayes decision theory, which divides spectra into three types: star, galaxy and quasar. Firstly, principal component analysis (PCA) is used in feature extraction, and spectra are projected into the 3D PCA feature space; secondly, the class conditional probability density functions are estimated using the non-parametric density estimation technique, Parzen window approach; finally, the minimum error Bayes decision rule is used for classification. In Parzen window approach, the kernel width affects the density estimation, and then affects the classification effect. Extensive experiments have been performed to analyze the relationship between the kernel widths and the correct classification rates. The authors found that the correct rate increases with the kernel width being close to some threshold, while it decreases with the kernel width being less than this threshold. PMID:20496722

  12. Discrete wavelet-aided delineation of PCG signal events via analysis of an area curve length-based decision statistic.

    PubMed

    Homaeinezhad, M R; Atyabi, S A; Daneshvar, E; Ghaffari, A; Tahmasebi, M

    2010-12-01

    The aim of this study is to describe a robust unified framework for segmentation of the phonocardiogram (PCG) signal sounds based on the false-alarm probability (FAP) bounded segmentation of a properly calculated detection measure. To this end, first the original PCG signal is appropriately pre-processed and then, a fixed sample size sliding window is moved on the pre-processed signal. In each slid, the area under the excerpted segment is multiplied by its curve-length to generate the Area Curve Length (ACL) metric to be used as the segmentation decision statistic (DS). Afterwards, histogram parameters of the nonlinearly enhanced DS metric are used for regulation of the α-level Neyman-Pearson classifier for FAP-bounded delineation of the PCG events. The proposed method was applied to all 85 records of Nursing Student Heart Sounds database (NSHSDB) including stenosis, insufficiency, regurgitation, gallop, septal defect, split sound, rumble, murmur, clicks, friction rub and snap disorders with different sampling frequencies. Also, the method was applied to the records obtained from an electronic stethoscope board designed for fulfillment of this study in the presence of high-level power-line noise and external disturbing sounds and as the results, no false positive (FP) or false negative (FN) errors were detected. High noise robustness, acceptable detection-segmentation accuracy of PCG events in various cardiac system conditions, and having no parameters dependency to the acquisition sampling frequency can be mentioned as the principal virtues and abilities of the proposed ACL-based PCG events detection-segmentation algorithm. PMID:21181267

  13. Classification based on full decision trees

    NASA Astrophysics Data System (ADS)

    Genrikhov, I. E.; Djukova, E. V.

    2012-04-01

    The ideas underlying a series of the authors' studies dealing with the design of classification algorithms based on full decision trees are further developed. It is shown that the decision tree construction under consideration takes into account all the features satisfying a branching criterion. Full decision trees with an entropy branching criterion are studied as applied to precedent-based pattern recognition problems with real-valued data. Recognition procedures are constructed for solving problems with incomplete data (gaps in the feature descriptions of the objects) in the case when the learning objects are nonuniformly distributed over the classes. The authors' basic results previously obtained in this area are overviewed.

  14. 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

  15. How decision analysis can further nanoinformatics.

    PubMed

    Bates, Matthew E; Larkin, Sabrina; Keisler, Jeffrey M; Linkov, Igor

    2015-01-01

    The increase in nanomaterial research has resulted in increased nanomaterial data. The next challenge is to meaningfully integrate and interpret these data for better and more efficient decisions. Due to the complex nature of nanomaterials, rapid changes in technology, and disunified testing and data publishing strategies, information regarding material properties is often illusive, uncertain, and/or of varying quality, which limits the ability of researchers and regulatory agencies to process and use the data. The vision of nanoinformatics is to address this problem by identifying the information necessary to support specific decisions (a top-down approach) and collecting and visualizing these relevant data (a bottom-up approach). Current nanoinformatics efforts, however, have yet to efficiently focus data acquisition efforts on the research most relevant for bridging specific nanomaterial data gaps. Collecting unnecessary data and visualizing irrelevant information are expensive activities that overwhelm decision makers. We propose that the decision analytic techniques of multicriteria decision analysis (MCDA), value of information (VOI), weight of evidence (WOE), and portfolio decision analysis (PDA) can bridge the gap from current data collection and visualization efforts to present information relevant to specific decision needs. Decision analytic and Bayesian models could be a natural extension of mechanistic and statistical models for nanoinformatics practitioners to master in solving complex nanotechnology challenges. PMID:26425410

  16. A Method for Fuzzy Soft Sets in Decision Making Based on Grey Relational Analysis and D-S Theory of Evidence: Application to Medical Diagnosis

    PubMed Central

    Xie, Ningxin; Wen, Guoqiu; Li, Zhaowen

    2014-01-01

    A method based on grey relational analysis and D-S theory of evidence is proposed for fuzzy soft sets in decision making. Firstly, grey relational analysis is used to calculate grey mean relational degrees and determine uncertain degrees of parameters. Then based on uncertain degrees, suitable mass functions of different independent alternatives with different parameters can be constructed. Next, D-S rule of evidence combination is applied to aggregate these alternatives into a collective alternative. Finally, these alternatives are ranked and the best alternative(s) are obtained. Moreover, the effectiveness and feasibility of this method are demonstrated by comparing with the mean potentiality approach and giving an application to medical diagnosis. PMID:24982687

  17. 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

  18. Which Bisphosphonate? It's the Compliance!: Decision Analysis

    PubMed Central

    Lee, You Jin; Park, Chan Ho; Ha, Yong-Chan; Koo, Kyung-Hoi

    2016-01-01

    Background The best options of several bisphosphonates for prevention of osteoporotic fractures in postmenopausal women remain controversial. We determined which bisphosphonate provides better efficacy in prevention of osteoporotic fractures using a decision analysis tool, in terms of quality of life. Methods A decision analysis model was constructed containing final outcome score and the probability of vertebral and hip fracture within 1 year. Final outcome was defined as health-related quality of life, and was used as an utility in the decision tree. Probabilities were obtained by literature review, and health-related quality of life was evaluated by consensus committee. A roll back tool was used to determine the best bisphosphonate, and sensitivity analysis was performed to compensate for decision model uncertainty. Results The decision model favored bisphosphonate with higher compliance in terms of quality of life. In one-way sensitivity analysis, ibandronate was more beneficial than the others, when probability of compliance on ibandronate was above 0.589. Conclusions In terms of quality of life, the decision analysis model showed that compliance was most important for patients in real world, regardless of type of bisphosphonate.

  19. 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…

  20. 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.

  1. A Statistical Model-Based Decision Support System for Managing Summer Stream Temperatures with Quantified Confidence Analysis

    NASA Astrophysics Data System (ADS)

    Neumann, D. W.; Zagona, E. A.; Rajagopalan, B.

    2005-12-01

    Warm summer stream temperatures due to low flows and high air temperatures are a critical water quality problem in many western U.S. river basins because they impact threatened fish species' habitat. Releases from storage reservoirs and river diversions are typically driven by human demands such as irrigation, municipal and industrial uses and hydropower production. Historically, fish needs have not been formally incorporated in the operating procedures, which do not supply adequate flows for fish in the warmest, driest periods. One way to address this problem is for local and federal organizations to purchase water rights to be used to increase flows, hence decrease temperatures. A statistical model-predictive technique for efficient and effective use of a limited supply of fish water has been developed and incorporated in a Decision Support System (DSS) that can be used in an operations mode to effectively use water acquired to mitigate warm stream temperatures. The DSS is a rule-based system that uses the empirical, statistical predictive model to predict maximum daily stream temperatures based on flows that meet the non-fish operating criteria, and to compute reservoir releases of allocated fish water when predicted temperatures exceed fish habitat temperature targets with a user specified confidence of the temperature predictions. The empirical model is developed using a step-wise linear regression procedure to select significant predictors, and includes the computation of a prediction confidence interval to quantify the uncertainty of the prediction. The DSS also includes a strategy for managing a limited amount of water throughout the season based on degree-days in which temperatures are allowed to exceed the preferred targets for a limited number of days that can be tolerated by the fish. The DSS is demonstrated by an example application to the Truckee River near Reno, Nevada using historical flows from 1988 through 1994. In this case, the statistical model

  2. 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. PMID:26436538

  3. Decision-making based on emotional images.

    PubMed

    Katahira, Kentaro; Fujimura, Tomomi; Okanoya, Kazuo; Okada, Masato

    2011-01-01

    The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants' choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward, the "reward value" of the decision outcome, which guided the update of value for each choice, is unknown beforehand. To estimate the reward value of emotional pictures from participants' choice data, we used reinforcement learning models that have successfully been used in previous studies for modeling value-based decision making. Consequently, we found that the estimated reward value was asymmetric between positive and negative pictures. The negative reward value of negative pictures (relative to neutral pictures) was larger in magnitude than the positive reward value of positive pictures. This asymmetry was not observed in valence for an individual picture, which was rated by the participants regarding the emotion experienced upon viewing it. These results suggest that there may be a difference between experienced emotion and the effect of the experienced emotion on subsequent behavior. Our experimental and computational paradigm provides a novel way for quantifying how and what aspects of emotional events affect human behavior. The present study is a first step toward relating a large amount of knowledge in emotion science and in taking computational approaches to value-based decision making. PMID:22059086

  4. 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

  5. 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…

  6. 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

  7. 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…

  8. Economic aspects of clinical decision making: applications of clinical decision analysis.

    PubMed

    Crane, V S

    1988-03-01

    Clinical decision analysis as a basic tool for decision making is described, and potential applications of decision analysis in six areas of clinical practice are identified. Clinical decision analysis is a systematic method of describing clinical problems in a quantitative fashion, identifying possible courses of action, assessing the probability and value of outcomes, and then making a calculation to select the ultimate course of action. Clinical decision analysis provides a structure for clinical decision problems, helps clarify medical controversies, and encourages decision makers to speak a common language. Applications of clinical decision analysis in the areas of diagnostic testing, patient management, product and program selection, research and education, patient preferences, and health-care-policy evaluation are described. Decision analysis offers health professionals a tool for making quantifiable, cost-effective clinical decisions, especially in terms of clinical outcomes. PMID:3285672

  9. 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

  10. 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.

  11. 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…

  12. 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…

  13. 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

  14. 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. PMID:26405856

  15. 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.

  16. 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

  17. 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. PMID:26581731

  18. Teaching the Tools of Pharmaceutical Care Decision-Analysis.

    ERIC Educational Resources Information Center

    Rittenhouse, Brian E.

    1994-01-01

    A method of decision-analysis in pharmaceutical care that integrates epidemiology and economics is presented, including an example illustrating both the deceptive nature of medical decision making and the power of decision analysis. Principles in determining both general and specific probabilities of interest and use of decision trees for…

  19. 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.

  20. Defense against nuclear weapons: a decision analysis

    SciTech Connect

    Orient, J.M.

    1985-02-01

    Response to the public health threat posed by nuclear weapons is a medical imperative. The United States, in contrast to other nations, has chosen a course that assures maximal casualties in the event of a nuclear attack, on the theory that prevention of the attack is incompatible with preventive measures against its consequences, such as blast injuries and radiation sickness. A decision analysis approach clarifies the risks and benefits of a change to a strategy of preparedness.

  1. 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.

  2. Decision aid tools to support women's decision making in pregnancy and birth: a systematic review and meta-analysis.

    PubMed

    Dugas, Marylène; Shorten, Allison; Dubé, Eric; Wassef, Maggy; Bujold, Emmanuel; Chaillet, Nils

    2012-06-01

    Support for a model of shared medical decision making, where women and their care providers discuss risks and benefits of their different options, reveal their preferences, and jointly make a decision, is a growing expectation in obstetric care. The objective of this study was to conduct a systematic review and meta-analysis of randomized controlled trials evaluating the efficacy of different decision aid tools compared to regular care for women facing several options in the specific field of obstetric care. We included published studies about interventions designed to aid mothers' decision making and provide information about obstetrical treatment or screening options. Following a search of electronic databases for articles published in English and French from 1994 to 2010, we found ten studies that met the inclusion criteria. In this systematic review and meta-analysis we found that all decision aid tools, except for Decision Trees, facilitated significant increases in knowledge. The Computer-based Information Tool, the Decision Analysis Tools, Individual Counseling and Group Counseling intervention presented significant results in reducing anxiety levels. The Decision Analysis Tools and the Computer-based Information tool were associated with a reduction in levels of decisional conflict. The Decision Analysis Tool was the only tool that presented evidence of an impact on the final choice and final outcome. Decision aid tools can assist health professionals to provide information and counseling about choices during pregnancy and support women in shared decision making. The choice of a specific tool should depend on resources available to support their use as well as the specific decisions being faced by women, their health care setting and providers. PMID:22475401

  3. 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.

  4. Decision analysis as a life support technology assessment capability.

    PubMed

    Ballin, M G

    1995-01-01

    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, especially in a resource-constrained environment. In the application of life support technology to future manned space flight, new technology concepts typically are characterized by 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 confronting a decision maker. It also accounts for the limits of knowledge 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 useful insight for making technology development resource allocation decisions. PMID:11538570

  5. 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

  6. 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.

  7. Using real options analysis to support strategic management decisions

    NASA Astrophysics Data System (ADS)

    Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

    2013-12-01

    Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.

  8. Hierarchical neural networks for autonomous data analysis and decision making

    NASA Technical Reports Server (NTRS)

    Eberlein, Susan; Yates, Gigi

    1988-01-01

    A neural network based data analysis and decision making system to increase the autonomy of a planetary rover or similar exploratory vehicle is presented. A hierarchical series of neural networks for real time analysis of scientific images is used. The system under development emphasizes analysis of multispectral images by classifier and feature detector neural networks, to provide information on the mineral composition of a scene. A hierarchy of alternating analysis and decision making networks is being developed to allow increasingly fine scale analysis in regions of the image that are potentially important. It is noted that this system will facilitate both the selection of high priorty scientific information for transmission to earth, and the autonomous collection of rocks and soil for sample return.

  9. 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.

  10. 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.

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

    DOE PAGESBeta

    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.

  12. Mice can count and optimize count-based decisions.

    PubMed

    Çavdaroğlu, Bilgehan; Balcı, Fuat

    2016-06-01

    Previous studies showed that rats and pigeons can count their responses, and the resultant count-based judgments exhibit the scalar property (also known as Weber's Law), a psychophysical property that also characterizes interval-timing behavior. Animals were found to take a nearly normative account of these well-established endogenous uncertainty characteristics in their time-based decision-making. On the other hand, no study has yet tested the implications of scalar property of numerosity representations for reward-rate maximization in count-based decision-making. The current study tested mice on a task that required them to press one lever for a minimum number of times before pressing the second lever to collect the armed reward (fixed consecutive number schedule, FCN). Fewer than necessary number of responses reset the response count without reinforcement, whereas emitting responses at least for the minimum number of times reset the response counter with reinforcement. Each mouse was tested with three different FCN schedules (FCN10, FCN20, FCN40). The number of responses emitted on the first lever before pressing the second lever constituted the main unit of analysis. Our findings for the first time showed that mice count their responses with scalar property. We then defined the reward-rate maximizing numerical decision strategies in this task based on the subject-based estimates of the endogenous counting uncertainty. Our results showed that mice learn to maximize the reward-rate by incorporating the uncertainty in their numerosity judgments into their count-based decisions. Our findings extend the scope of optimal temporal risk-assessment to the domain of count-based decision-making. PMID:26463617

  13. 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

  14. Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data

    NASA Astrophysics Data System (ADS)

    Hamedianfar, Alireza; Shafri, Helmi Zulhaidi Mohd

    2016-04-01

    This paper integrates decision tree-based data mining (DM) and object-based image analysis (OBIA) to provide a transferable model for the detailed characterization of urban land-cover classes using WorldView-2 (WV-2) satellite images. Many articles have been published on OBIA in recent years based on DM for different applications. However, less attention has been paid to the generation of a transferable model for characterizing detailed urban land cover features. Three subsets of WV-2 images were used in this paper to generate transferable OBIA rule-sets. Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. The developed DT algorithm was applied to object-based classifications in the first study area. After this process, we validated the capability and transferability of the classification rules into second and third subsets. Detailed ground truth samples were collected to assess the classification results. The first, second, and third study areas achieved 88%, 85%, and 85% overall accuracies, respectively. Results from the investigation indicate that DM was an efficient method to provide the optimal and transferable classification rules for OBIA, which accelerates the rule-sets creation stage in the OBIA classification domain.

  15. 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.

  16. [Economic studies and decision analysis as tools for decision making].

    PubMed

    Rodríguez-Pimentel, Leticia; Silva-Romo, Rodolfo; Wacher-Rodarte, Niels

    2007-01-01

    Management implies decision-making and economics deals with efficiency which means to obtain the best possible results with the available resources, and to compare such results with those that were foreseen. The economic evaluation comprises a set of techniques aimed at comparing resource allocation on alternate courses of action and its consequences. In health care, these results are the overall well-being of the society. This paper summarizes the techniques that are customarily used in economic evaluation, and intends to serve as an introductory text to increasing the ability of the readers to grasp original articles in the field of health economics. PMID:17692169

  17. Decision support using causation knowledge base

    SciTech Connect

    Nakamura, K.; Iwai, S.; Sawaragi, T.

    1982-11-01

    A decision support system using a knowledge base of documentary data is presented. Causal assertions in documents are extracted and organized into cognitive maps, which are networks of causal relations, by the methodology of documentary coding. The knowledge base is constructed by joining cognitive maps of several documents concerned with a societal complex problem. The knowledge base is an integration of several expertises described in documents, though it is only concerned with causal structure of the problem, and includes overall and detailed information about the problem. Decisionmakers concerned with the problem interactively retrieve relevant information from the knowledge base in the process of decisionmaking and form their overall and detailed understanding of the complex problem based on the expertises stored in the knowledge base. Three retrieval modes are proposed according to types of the decisionmakers requests: 1) skeleton maps indicate overall causal structure of the problem, 2) hierarchical graphs give detailed information about parts of the causal structure, and 3) sources of causal relations are presented when necessary, for example when the decisionmaker wants to browse the causal assertions in documents. 10 references.

  18. 46 CFR 201.160 - Decision based on official notice.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 46 Shipping 8 2013-10-01 2013-10-01 false Decision based on official notice. 201.160 Section 201.160 Shipping MARITIME ADMINISTRATION, DEPARTMENT OF TRANSPORTATION POLICY, PRACTICE AND PROCEDURE RULES OF PRACTICE AND PROCEDURE Briefs, Requests for Findings, Decisions, Exceptions (Rule 16) § 201.160 Decision based on official notice....

  19. 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

  20. Exposure Models for the Prior Distribution in Bayesian Decision Analysis for Occupational Hygiene Decision Making

    PubMed Central

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

    2015-01-01

    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

  1. 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

  2. Optimal policy for value-based decision-making.

    PubMed

    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

  3. 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.

  4. Risk-based decision making for terrorism applications.

    PubMed

    Dillon, Robin L; Liebe, Robert M; Bestafka, Thomas

    2009-03-01

    This article describes the anti-terrorism risk-based decision aid (ARDA), a risk-based decision-making approach for prioritizing anti-terrorism measures. The ARDA model was developed as part of a larger effort to assess investments for protecting U.S. Navy assets at risk and determine whether the most effective anti-terrorism alternatives are being used to reduce the risk to the facilities and war-fighting assets. With ARDA and some support from subject matter experts, we examine thousands of scenarios composed of 15 attack modes against 160 facility types on two installations and hundreds of portfolios of 22 mitigation alternatives. ARDA uses multiattribute utility theory to solve some of the commonly identified challenges in security risk analysis. This article describes the process and documents lessons learned from applying the ARDA model for this application. PMID:19187486

  5. 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. PMID:24696645

  6. 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

  7. Web-based health services and clinical decision support.

    PubMed

    Jegelevicius, Darius; Marozas, Vaidotas; Lukosevicius, Arunas; Patasius, Martynas

    2004-01-01

    The purpose of this study was the development of a Web-based e-health service for comprehensive assistance and clinical decision support. The service structure consists of a Web server, a PHP-based Web interface linked to a clinical SQL database, Java applets for interactive manipulation and visualization of signals and a Matlab server linked with signal and data processing algorithms implemented by Matlab programs. The service ensures diagnostic signal- and image analysis-sbased clinical decision support. By using the discussed methodology, a pilot service for pathology specialists for automatic calculation of the proliferation index has been developed. Physicians use a simple Web interface for uploading the pictures under investigation to the server; subsequently a Java applet interface is used for outlining the region of interest and, after processing on the server, the requested proliferation index value is calculated. There is also an "expert corner", where experts can submit their index estimates and comments on particular images, which is especially important for system developers. These expert evaluations are used for optimization and verification of automatic analysis algorithms. Decision support trials have been conducted for ECG and ophthalmology ultrasonic investigations of intraocular tumor differentiation. Data mining algorithms have been applied and decision support trees constructed. These services are under implementation by a Web-based system too. The study has shown that the Web-based structure ensures more effective, flexible and accessible services compared with standalone programs and is very convenient for biomedical engineers and physicians, especially in the development phase. PMID:15718591

  8. 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...

  9. 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

  10. Comprehensive evaluation of water resources security in the Yellow River basin based on a fuzzy multi-attribute decision analysis approach

    NASA Astrophysics Data System (ADS)

    Liu, K. K.; Li, C. H.; Cai, Y. P.; Xu, M.; Xia, X. H.

    2014-05-01

    In this paper, a fuzzy multi-attribute decision analysis approach (FMADAA) was developed for supporting the evaluation of water resources security in nine provinces within the Yellow River basin. A numerical approximation system and a modified left-right scoring approach were adopted to cope with the uncertainties in the acquired information. Also, four conventional multi-attribute decision analysis (MADA) methods were implemented in the evaluation model for impact evaluation, including simple weighted addition (SWA), weighted product (WP), cooperative game theory (CGT) and technique for order preference by similarity to ideal solution (TOPSIS). Moreover, several aggregation methods including average ranking procedure, Borda and Copeland methods were used to integrate the ranking results, helping rank the water resources security in those nine provinces as well as improving reliability of evaluation results. The ranking results showed that the water resources security of the entire basin was in critical condition, including the insecurity and absolute insecurity states, especially in Shanxi, Inner Mongolia and Ningxia provinces in which water resources were lower than the average quantity in China. Hence, the improvement of water eco-environment statuses in the above-mentioned provinces should be prioritized in the future planning of the Yellow River basin.

  11. 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.

  12. Special Issue: Decision Support and Knowledge-Based Systems.

    ERIC Educational Resources Information Center

    Stohr, Edward A.; And Others

    1987-01-01

    Six papers dealing with decision support and knowledge based systems are presented. Five of the papers are concerned in some way with the use of artificial intelligence techniques in individual or group decision support. The sixth paper presents empirical results from the use of a group decision support system. (CLB)

  13. Sequential decision analysis for nonstationary stochastic processes

    NASA Technical Reports Server (NTRS)

    Schaefer, B.

    1974-01-01

    A formulation of the problem of making decisions concerning the state of nonstationary stochastic processes is given. An optimal decision rule, for the case in which the stochastic process is independent of the decisions made, is derived. It is shown that this rule is a generalization of the Bayesian likelihood ratio test; and an analog to Wald's sequential likelihood ratio test is given, in which the optimal thresholds may vary with time.

  14. 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.

  15. Comprehensive evaluation of water resources security in the Yellow River basin based on a Fuzzy Multi-Attribute Decision Analysis Approach

    NASA Astrophysics Data System (ADS)

    Liu, K. K.; Li, C. H.; Cai, Y. P.; Xu, M.; Xia, X. H.

    2014-01-01

    In this paper, a Fuzzy Multi-Attribute Decision Analysis Approach (FMADAA) was adopted in water resources security evaluation for the nine provinces in the Yellow River basin in 2006. A numerical approximation system and a modified left-right scoring approach were adopted to cope with the uncertainties in the acquired information. Four multi-attribute decision making methods were implemented in the evaluation model for impact evaluation, including simple weighted addition (SWA), weighted product (WP), cooperative game theory (CGT) and technique for order preference by similarity to ideal solution (TOPSIS) which could be used for helping rank the water resources security in those nine provinces as well as the criteria alternatives. Moreover, several aggregation methods including average ranking procedure, borda and copeland methods were used to integrate the ranking results. The ranking results showed that the water resources security of the entire basin is in critical, insecurity and absolute insecurity state, especially in Shanxi, Inner Mongolia and Ningxia provinces in which water resources were lower than the average quantity in China. Hence, future planning of the Yellow River basin should mainly focus on the improvement of water eco-environment status in the provinces above.

  16. 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 ...

  17. Computer-Based Medical Decision Support System based on guidelines, clinical pathways and decision nodes.

    PubMed

    Tomaszewski, Wiesław

    2012-01-01

    A continuous and dynamic development of medical sciences which is currently taking place all over the world is associated with a considerable increase in the number of scientific reports and papers of importance in enhancing the effectiveness of treatment and quality of medical care. However, it is difficult, or, indeed, impossible, for physicians to regularly follow all recent innovations in medical knowledge and to apply the latest research findings to their daily clinical practice. More and more studies conducted both in Poland and worldwide as well as experience from clinical practice in various countries provide convincing evidence that various systems supporting medical decision-making by physicians or other medical professionals visibly improve the quality of medical care. The use of such systems is already possible and recently has been developing especially dynamically, as the level of knowledge and information and communication technology now permits their effective implementation. Currently, electronic knowledge bases, together with inference procedures, form intelligent medical information systems, which offer many possibilities for the support of medical decision-making, mainly in regard to interactive diagnostic work-up, but also the selection of the most suitable treatment plan (clinical pathway). Regardless of their scale and area of application, these systems are referred to as Computer-Based Medical Decision Support Systems (CBMDSS). PMID:22741924

  18. 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

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

    PubMed

    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

  20. A Primer on Bayesian Decision Analysis With an Application to a Kidney Transplant Decision.

    PubMed

    Neapolitan, Richard; Jiang, Xia; Ladner, Daniela P; Kaplan, Bruce

    2016-03-01

    A clinical decision support system (CDSS) is a computer program, which is designed to assist health care professionals with decision making tasks. A well-developed CDSS weighs the benefits of therapy versus the cost in terms of loss of quality of life and financial loss and recommends the decision that can be expected to provide maximum overall benefit. This article provides an introduction to developing CDSSs using Bayesian networks, such CDSS can help with the often complex decisions involving transplants. First, we review Bayes theorem in the context of medical decision making. Then, we introduce Bayesian networks, which can model probabilistic relationships among many related variables and are based on Bayes theorem. Next, we discuss influence diagrams, which are Bayesian networks augmented with decision and value nodes and which can be used to develop CDSSs that are able to recommend decisions that maximize the expected utility of the predicted outcomes to the patient. By way of comparison, we examine the benefit and challenges of using the Kidney Donor Risk Index as the sole decision tool. Finally, we develop a schema for an influence diagram that models generalized kidney transplant decisions and show how the influence diagram approach can provide the clinician and the potential transplant recipient with a valuable decision support tool. PMID:26900809

  1. A fast mode decision algorithm for multiview auto-stereoscopic 3D video coding based on mode and disparity statistic analysis

    NASA Astrophysics Data System (ADS)

    Ding, Cong; Sang, Xinzhu; Zhao, Tianqi; Yan, Binbin; Leng, Junmin; Yuan, Jinhui; Zhang, Ying

    2012-11-01

    Multiview video coding (MVC) is essential for applications of the auto-stereoscopic three-dimensional displays. However, the computational complexity of MVC encoders is tremendously huge. Fast algorithms are very desirable for the practical applications of MVC. Based on joint early termination , the selection of inter-view prediction and the optimization of the process of Inter8×8 modes by comparison, a fast macroblock(MB) mode selection algorithm is presented. Comparing with the full mode decision in MVC, the experimental results show that the proposed algorithm can reduce up to 78.13% on average and maximum 90.21% encoding time with a little increase in bit rates and loss in PSNR.

  2. 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...

  3. 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...

  4. 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…

  5. A Training Model for School-Based Decision Making.

    ERIC Educational Resources Information Center

    Horgan, Dianne D.

    The development of a comprehensive training model designed specifically for school-based decision making is discussed in this report, with a focus on teaching relevant skills and when to utilize them. Loosely based on Vroom and Yetton's 1973 model of participative decision making, the model is characterized by a general-to-specific continuum and…

  6. 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

  7. 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

  8. 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. PMID:25698915

  9. 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

  10. The Weighted Gray Situation Decision-Making Model Based on the Gray Theory of Decision-Making and Its Application -- An Example of Forest Health Park of Hainan Province

    NASA Astrophysics Data System (ADS)

    Huang, Kuailin; Bai, Zhiyong

    This paper analyses the complication of influence construction of eco-tourism park decision-making, through study on gray situation theory of decision making establishes an new model of decision-making, -- weighted gray situation decision-making model based on the gray situation theory of decision-making, and on the empirical analysis, it gives a new method of gray situation theory used in decision-making of construction.

  11. Risk analysis in bioequivalence and biowaiver decisions.

    PubMed

    Kubbinga, Marlies; Langguth, Peter; Barends, Dirk

    2013-07-01

    This article evaluates the current biowaiver guidance documents published by the FDA, EU and WHO from a risk based perspective. The authors introduce the use of a Failure Mode and Effect Analysis (FMEA) risk calculation tool to show that current regulatory documents implicitly limit the risk for bioinequivalence after granting a biowaiver by reduction of the incidence, improving the detection and limiting the severity of any unforeseen bioinequivalent product. In addition, the authors use the risk calculation to expose yet unexplored options for future extension of comparative in vitro tools for biowaivers. PMID:23280474

  12. 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…

  13. 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

  14. Significant Labor Decisions--An Analysis

    ERIC Educational Resources Information Center

    Polhemus, Graig E.

    1977-01-01

    Major labor cases decided during 1976 did not project a clear or simple path for further Constitutional and statutory interpretation, but the year's labor decisions did reveal a new willingness on the part of the U.S. Supreme Court to depart from earlier views of Constitutional law. (JT)

  15. 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

  16. 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.

  17. 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.…

  18. 46 CFR 201.160 - Decision based on official notice.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 46 Shipping 8 2012-10-01 2012-10-01 false Decision based on official notice. 201.160 Section 201.160 Shipping MARITIME ADMINISTRATION, DEPARTMENT OF TRANSPORTATION POLICY, PRACTICE AND PROCEDURE RULES OF PRACTICE AND PROCEDURE Briefs, Requests for Findings, Decisions, Exceptions (Rule 16) §...

  19. 46 CFR 201.160 - Decision based on official notice.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 46 Shipping 8 2011-10-01 2011-10-01 false Decision based on official notice. 201.160 Section 201.160 Shipping MARITIME ADMINISTRATION, DEPARTMENT OF TRANSPORTATION POLICY, PRACTICE AND PROCEDURE RULES OF PRACTICE AND PROCEDURE Briefs, Requests for Findings, Decisions, Exceptions (Rule 16) §...

  20. 46 CFR 201.160 - Decision based on official notice.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 46 Shipping 8 2014-10-01 2014-10-01 false Decision based on official notice. 201.160 Section 201.160 Shipping MARITIME ADMINISTRATION, DEPARTMENT OF TRANSPORTATION POLICY, PRACTICE AND PROCEDURE RULES OF PRACTICE AND PROCEDURE Briefs, Requests for Findings, Decisions, Exceptions (Rule 16) §...

  1. 46 CFR 201.160 - Decision based on official notice.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 46 Shipping 8 2010-10-01 2010-10-01 false Decision based on official notice. 201.160 Section 201.160 Shipping MARITIME ADMINISTRATION, DEPARTMENT OF TRANSPORTATION POLICY, PRACTICE AND PROCEDURE RULES OF PRACTICE AND PROCEDURE Briefs, Requests for Findings, Decisions, Exceptions (Rule 16) §...

  2. 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

  3. 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.

  4. 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.

  5. 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.

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

    EPA Science Inventory

    NRMRL-CIN-1351A Hofstetter**, P., and Hammitt, J. K. Human Health Metrics for Environmental Decision Support Tools: Lessons from Health Economics and Decision Analysis. EPA/600/R-01/104 (NTIS PB2002-102119). Decision makers using environmental decision support tools are often ...

  8. Decision Theoretic Analysis of Improving Epidemic Detection

    PubMed Central

    Izadi, Masoumeh T.; Buckeridge, David L.

    2007-01-01

    The potentially catastrophic impact of an epidemic specially those due to bioterrorist attack, makes developing effective detection methods essential for public health. Current detection methods trade off reliability of alarms for early detection of outbreaks. The performance of these methods can be improved by disease-specific modeling techniques that take into account the potential costs and effects of an attack to provide optimal warnings and the cost and effectiveness of interventions. We study this optimization problem in the framework of sequential decision making under uncertainty. Our approach relies on estimating the future benefit of true alarms and the costs of false alarms. Using these quantities it identifies optimal decisions regarding the credibility of outputs from a traditional detection method at each point in time. The key contribution of this paper is to apply Partially Observable Markov Decision Processes (POMDPs) on outbreak detection methods for improving alarm function in the case of anthrax. We present empirical evidence illustrating that at a fixed specificity, the performance of detection methods with respect to sensitivity and timeliness is improved significantly by utilizing POMDPs in detection of anthrax attacks. PMID:18693857

  9. Web based collaborative decision making in flood risk management

    NASA Astrophysics Data System (ADS)

    Evers, Mariele; Almoradie, Adrian; Jonoski, Andreja

    2014-05-01

    Stakeholder participation in the development of flood risk management (FRM) plans is essential since stakeholders often have a better understanding or knowledge of the potentials and limitation of their local area. Moreover, a participatory approach also creates trust amongst stakeholders, leading to a successful implementation of measures. Stakeholder participation however has its challenges and potential pitfalls that could lead to its premature termination. Such challenges and pitfalls are the limitation of financial resources, stakeholders' spatial distribution and their interest to participate. Different type of participation in FRM may encounter diverse challenges. These types of participation in FRM can be classified into (1) Information and knowledge sharing (IKS), (2) Consultative participation (CP) or (3) Collaborative decision making (CDM)- the most challenging type of participation. An innovative approach to address these challenges and potential pitfalls is a web-based mobile or computer-aided environment for stakeholder participation. This enhances the remote interaction between participating entities such as stakeholders. This paper presents a developed framework and an implementation of CDM web based environment for the Alster catchment (Hamburg, Germany) and Cranbrook catchment (London, UK). The CDM framework consists of two main stages: (1) Collaborative modelling and (2) Participatory decision making. This paper also highlights the stakeholder analyses, modelling approach and application of General Public License (GPL) technologies in developing the web-based environments. Actual test and evaluation of the environments was through series of stakeholders workshops. The overall results based from stakeholders' evaluation shows that web-based environments can address the challenges and potential pitfalls in stakeholder participation and it enhances participation in flood risk management. The web-based environment was developed within the DIANE

  10. 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.

  11. 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...

  12. Using multiple criteria decision analysis for supporting decisions of solid waste management.

    PubMed

    Cheng, Steven; Chan, Christine W; Huang, Guo H

    2002-01-01

    Design of solid-waste management systems requires consideration of multiple alternative solutions and evaluation criteria because the systems can have complex and conflicting impacts on different stakeholders. Multiple criteria decision analysis (MCDA) has been found to be a fruitful approach to solve this design problem. In this paper, the MCDA approach is applied to solve the landfill selection problem in Regina of Saskatchewan Canada. The systematic approach of MCDA helps decision makers select the most preferable decision and provides the basis of a decision support system. The techniques that are used in this study include: 1) Simple Weighted Addition method, 2) Weighted Product method, 3) TOPSIS, 4) cooperative game theory, and 5) ELECTRE. The results generated with these methods are compared and ranked so that the most preferable solution is identified. PMID:12090287

  13. Decision analysis for prioritizing recommended energy conservation options

    SciTech Connect

    Meadows, K.L. ); Brothers, P.W. )

    1989-01-01

    Knowledge engineering techniques were used to study the decision process for choosing which of a set of recommended energy conservation options would be implemented. Building management decision-makers from both the private and public sectors were interviewed to gain an understanding of the decision-making process. Decision objectives were identified and the process computerized. Results of the study are twofold. The first is a formalization of the decision-making process. The formalization enables both efficient treatment of large numbers of objectives and demonstration of optimality in meeting objectives. Second, the knowledge-based system produced is programmed in a conventional programming environment rather than a rule-based expert system shell, demonstrating the range of applicability of knowledge engineering techniques.

  14. Decision boxes for clinicians to support evidence-based practice and shared decision making: the user experience

    PubMed Central

    2012-01-01

    Background This project engages patients and physicians in the development of Decision Boxes, short clinical topic summaries covering medical questions that have no single best answer. Decision Boxes aim to prepare the clinician to communicate the risks and benefits of the available options to the patient so they can make an informed decision together. Methods Seven researchers (including four practicing family physicians) selected 10 clinical topics relevant to primary care practice through a Delphi survey. We then developed two one-page prototypes on two of these topics: prostate cancer screening with the prostate-specific antigen test, and prenatal screening for trisomy 21 with the serum integrated test. We presented the prototypes to purposeful samples of family physicians distributed in two focus groups, and patients distributed in four focus groups. We used the User Experience Honeycomb to explore barriers and facilitators to the communication design used in Decision Boxes. All discussions were transcribed, and three researchers proceeded to thematic content analysis of the transcriptions. The coding scheme was first developed from the Honeycomb’s seven themes (valuable, usable, credible, useful, desirable, accessible, and findable), and included new themes suggested by the data. Prototypes were modified in light of our findings. Results Three rounds were necessary for a majority of researchers to select 10 clinical topics. Fifteen physicians and 33 patients participated in the focus groups. Following analyses, three sections were added to the Decision Boxes: introduction, patient counseling, and references. The information was spread to two pages to try to make the Decision Boxes less busy and improve users’ first impression. To try to improve credibility, we gave more visibility to the research institutions involved in development. A statement on the boxes’ purpose and a flow chart representing the shared decision-making process were added with the

  15. An Entropy Approach for Utility Assignment in Decision Analysis

    NASA Astrophysics Data System (ADS)

    Abbas, Ali E.

    2003-03-01

    A fundamental step in decision analysis is the elicitation of the decision-maker's preferences about the prospects of a decision situation in the form of utility values. However, this can be a difficult task to perform in practice as the number of prospects may be large, and eliciting a utility value for each prospect may be a time consuming and stressful task for the decision maker. To relieve some of the burden of this task, this paper presents a normative method to assign unbiased utility values when only incomplete preference information is available about the decision maker. We introduce the notion of a utility density function and propose a maximum entropy utility principle for utility assignment.

  16. Social influence and perceptual decision making: a diffusion model analysis.

    PubMed

    Germar, Markus; Schlemmer, Alexander; Krug, Kristine; Voss, Andreas; Mojzisch, Andreas

    2014-02-01

    Classic studies on social influence used simple perceptual decision-making tasks to examine how the opinions of others change individuals' judgments. Since then, one of the most fundamental questions in social psychology has been whether social influence can alter basic perceptual processes. To address this issue, we used a diffusion model analysis. Diffusion models provide a stochastic approach for separating the cognitive processes underlying speeded binary decisions. Following this approach, our study is the first to disentangle whether social influence on decision making is due to altering the uptake of available sensory information or due to shifting the decision criteria. In two experiments, we found consistent evidence for the idea that social influence alters the uptake of available sensory evidence. By contrast, participants did not adjust their decision criteria. PMID:24154917

  17. 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

  18. Decision analysis for the selection of tank waste retrieval technology

    SciTech Connect

    DAVIS,FREDDIE J.; DEWEESE,GREGORY C.; PICKETT,WILLIAM W.

    2000-03-01

    The objective of this report is to supplement the C-104 Alternatives Generation and Analysis (AGA) by providing a decision analysis for the alternative technologies described therein. The decision analysis used the Multi-Attribute Utility Analysis (MUA) technique. To the extent possible information will come from the AGA. Where data are not available, elicitation of expert opinion or engineering judgment is used and reviewed by the authors of the AGA. A key element of this particular analysis is the consideration of varying perspectives of parties interested in or affected by the decision. The six alternatives discussed are: sluicing; sluicing with vehicle mounted transfer pump; borehole mining; vehicle with attached sluicing nozzle and pump; articulated arm with attached sluicing nozzle; and mechanical dry retrieval. These are evaluated using four attributes, namely: schedule, cost, environmental impact, and safety.

  19. Use of probabilistic methods for analysis of cost and duration uncertainties in a decision analysis framework

    SciTech Connect

    Boak, D.M.; Painton, L.

    1995-12-08

    Probabilistic forecasting techniques have been used in many risk assessment and performance assessment applications on radioactive waste disposal projects such as Yucca Mountain and the Waste Isolation Pilot Plant (WIPP). Probabilistic techniques such as Monte Carlo and Latin Hypercube sampling methods are routinely used to treat uncertainties in physical parameters important in simulating radionuclide transport in a coupled geohydrologic system and assessing the ability of that system to comply with regulatory release limits. However, the use of probabilistic techniques in the treatment of uncertainties in the cost and duration of programmatic alternatives on risk and performance assessment projects is less common. Where significant uncertainties exist and where programmatic decisions must be made despite existing uncertainties, probabilistic techniques may yield important insights into decision options, especially when used in a decision analysis framework and when properly balanced with deterministic analyses. For relatively simple evaluations, these types of probabilistic evaluations can be made using personal computer-based software.

  20. 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

  1. 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

  2. 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.

  3. 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.…

  4. 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.

  5. 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

  6. 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.

  7. 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 PMID:27175984

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

    PubMed

    Dias, Eduardo Rocha; Silva Junior, Geraldo Bezerra da

    2016-03-01

    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

  9. 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

  10. Fast mode decision for multiview video coding based on depth maps

    NASA Astrophysics Data System (ADS)

    Cernigliaro, Gianluca; Jaureguizar, Fernando; Ortega, Antonio; Cabrera, Julián; García, Narciso

    2009-01-01

    A new fast mode decision (FMD) algorithm for multi-view video coding (MVC) is presented. One of the multiple views is encoded based on traditional methods, which provides a mode decision (MD) map, while encoding of the other views is based on the analysis of the homogeneity of the depth map. This approach reduces the burden of the rate-distortion (RD) motion analysis based on the availability of a depth map, which is assumed to be provided by the acquisition process. Although there is a slight decrease of performance in rate-distortion terms, there is a significant reduction in computational cost.

  11. Decision curve analysis for assessing the usefulness of tests for making decisions to treat: an application to tests for prodromal psychosis.

    PubMed

    Pulleyblank, Ryan; Chuma, Jefter; Gilbody, Simon M; Thompson, Carl

    2013-09-01

    For a test to be considered useful for making treatment decisions, it is necessary that making treatment decisions based on the results of the test be a preferable strategy to making treatment decisions without the test. Decision curve analysis is a framework for assessing when a test would be expected to be useful, which integrates evidence of a test's performance characteristics (sensitivity and specificity), condition prevalence among at-risk patients, and patient preferences for treatment. We describe decision curve analysis generally and illustrate its potential through an application to tests for prodromal psychosis. Clinical psychosis is often preceded by a prodromal phase, but not all those with prodromal symptoms proceed to develop full psychosis. Patients identified as at risk for developing psychosis may be considered for proactive treatment to mitigate development of clinically defined psychosis. Tests exist to help identify those at-risk patients most likely to develop psychosis, but it is uncertain when these tests would be considered useful for making proactive treatment decisions. We apply decision curve analysis to results from a systematic review of studies investigating clinical tests for predicting the development of psychosis in at-risk populations, and present resulting decision curves that illustrate when the tests may be expected to be useful for making proactive treatment decisions. PMID:23544398

  12. 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

  13. 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.

  14. 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

  15. 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)

  16. 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.

  17. 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. PMID:23869557

  18. 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.

  19. 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

  20. Comparative effectiveness research: decision-based evidence.

    PubMed

    Kowalski, Charles Joseph; Mrdjenovich, Adam Joel

    2014-01-01

    In the clinical research context, comparative effectiveness research (CER) refers to the comparison of several health-care interventions administered under real-world conditions to individuals representative of the day-to-day clinical practice target population. We provide a brief history of CER and argue that CER can be used to deliver useful, but currently lacking information. Three study designs that can accomplish this are discussed, and incorporating CER into cost-benefit analyses is examined. The relationships between CER and evidence-based and personalized medicine are also considered, as is the challenge of implementing CER results into routine clinical practice. PMID:25544326

  1. Model-based decision support in diabetes care.

    PubMed

    Salzsieder, E; Vogt, L; Kohnert, K-D; Heinke, P; Augstein, P

    2011-05-01

    The model-based Karlsburg Diabetes Management System (KADIS®) has been developed as a patient-focused decision-support tool to provide evidence-based advice for physicians in their daily efforts to optimize metabolic control in diabetes care of their patients on an individualized basis. For this purpose, KADIS® was established in terms of a personalized, interactive in silico simulation procedure, implemented into a problem-related diabetes health care network and evaluated under different conditions by conducting open-label mono- and polycentric trials, and a case-control study, and last but not least, by application in routine diabetes outpatient care. The trial outcomes clearly show that the recommendations provided to the physicians by KADIS® lead to significant improvement of metabolic control. This model-based decision-support system provides an excellent tool to effectively guide physicians in personalized decision-making to achieve optimal metabolic control for their patients. PMID:20621384

  2. Decision analysis framework for evaluating CTBT seismic verification options

    SciTech Connect

    Judd, B.R.; Strait, R.S.; Younker, L.W.

    1986-09-01

    This report describes a decision analysis framework for evaluating seismic verification options for a Comprehensive Test Ban Treaty (CTBT). In addition to providing policy makers with insights into the relative merits of different options, the framework is intended to assist in formulating and evaluating political decisions - such as responses to evidence of violations - and in setting research priorities related to the options. To provide these broad analytical capabilities to decision makers, the framework incorporates a wide variety of issues. These include seismic monitoring capabilities, evasion possibilities, evidence produced by seismic systems, US response to the evidence, the dependence between US and Soviet decision-making, and the relative values of possible outcomes to the US and the Soviet Union. An added benefit of the framework is its potential use to improve communication about these CTBT verification issues among US experts and decision makers. The framework has been implemented on a portable microcomputer to facilitate this communication through demonstration and rapid evaluation of alternative judgments and policy choices. The report presents the framework and its application in four parts. The first part describes the decision analysis framework and the types of analytical results produced. In the second part, the framework is used to evaluate representative seismic verification options. The third part describes the results of sensitivity analyses that determine the relative importance of the uncertainties or subjective judgments that influence the evaluation of the options. The fourth (and final) part summaries conclusions and presents implications of the sample analytical results for further research and for policy-making related to CTBT verification. The fourth section also describes the next steps in the development and use of the decision analysis framework.

  3. 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

  4. 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

  5. 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

  6. A decision-analysis methodology for consideration of morbidity factors in clinical decision-making.

    PubMed

    Corder, M P; Ellwein, L B

    1984-02-01

    An explicit and systematic means of incorporation of good medical practice plus individual patient preferences (utilities) for pretreatment and treatment options for a serious but curable neoplastic disease has been investigated. The methodology allows important quality-of-life information to be transmitted to patients, with the goal of providing an improved basis for informed consent. The example of Hodgkin's lymphoma staging and treatment selection is used. Individual patient utilities can be expressed and incorporated into a formal decision analysis for those who face the option of selecting MOPP chemotherapy or of pursuing the staging process in order to obtain a chance of being treated appropriately with irradiation. Equal survival probabilities for the two options are assumed, thus the short- and long-term toxicities (quality of Life) are the determinants of the decision. Patient-derived utilities can be developed for the 15 categories of anticipated toxicity. This, together with probabilistic inputs regarding toxicity severity and duration, will yield expected utilities for each of the decision options. Three physicians were studied and evaluated in the role of a patient. The physicians' toxicity preferences were different and because of this the management option of choice was different for each. This methodology allows explicit patient preferences to be incorporated into medical decisions without the requirement for detailed patient understanding of testing and/or treatment morbidity frequency and severity. PMID:6546469

  7. 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.

  8. 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.

  9. 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

  10. Annotated bibliography on decision analysis with applications to project management

    SciTech Connect

    Booker, J.M.; Bryson, M.C.

    1984-02-01

    The results of an extensive literature survey on decision analysis, with specific application to problems in research and development project management, are summarized in bibliographic form. Approximately 215 references are organized by subject matter and also summarized and annotated (several lines per reference) in a separate listing.

  11. 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…

  12. 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

  13. 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

  14. 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

  15. Decision-fusion-based automated drill bit toolmark correlator

    NASA Astrophysics Data System (ADS)

    Jones, Brett C.; Press, Michael J.; Guerci, Joseph R.

    1999-02-01

    This paper describes a recent study conducted to investigate the reproducibility of toolmarks left by drill bits. This paper focuses on the automated analysis aspect of the study, and particularly the advantages of using decision fusion methods in the comparisons. To enable the study to encompass a large number of samples, existing technology was adapted to the task of automatically comparing the test impressions. Advanced forensic pattern recognition algorithms that had been developed for the comparison of ballistic evidence in the DRUGFIRETM system were modified for use in this test. The results of the decision fusion architecture closely matched those obtained by expert visual examination. The study, aided by the improved pattern recognition algorithm, showed that drill bit impressions do contain reproducible marks. In a blind test, the DRUGFIRE pattern recognition algorithm, enhanced with the decision fusion architecture, consistently identified the correct bit as the source of the test impressions.

  16. 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…

  17. 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.…

  18. 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…

  19. Collaborative Inquiry to Make Data-Based Decisions in Schools.

    ERIC Educational Resources Information Center

    Huffman, Douglas; Kalnin, Julie

    2003-01-01

    Investigated the impact of a collaborative inquiry involving diverse teams of teachers, administrators, school board members, and parents. The teams collected and analyzed local data to make data-based decisions about improving teaching and learning. The collaboration helped teachers engage in a continuous improvement process that allowed them to…

  20. 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

  1. A Web-Based Tool to Support Data-Based Early Intervention Decision Making

    ERIC Educational Resources Information Center

    Buzhardt, Jay; Greenwood, Charles; Walker, Dale; Carta, Judith; Terry, Barbara; Garrett, Matthew

    2010-01-01

    Progress monitoring and data-based intervention decision making have become key components of providing evidence-based early childhood special education services. Unfortunately, there is a lack of tools to support early childhood service providers' decision-making efforts. The authors describe a Web-based system that guides service providers…

  2. 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.

  3. 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.

  4. 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

  5. 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. PMID:26221623

  6. 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.

  7. Using Decision Analysis to Improve Malaria Control Policy Making

    PubMed Central

    Kramer, Randall; Dickinson, Katherine L.; Anderson, Richard M.; Fowler, Vance G.; Miranda, Marie Lynn; Mutero, Clifford M.; Saterson, Kathryn A.; Wiener, Jonathan B.

    2013-01-01

    Malaria and other vector-borne diseases represent a significant and growing burden in many tropical countries. Successfully addressing these threats will require policies that expand access to and use of existing control methods, such as insecticide-treated bed nets and artemesinin combination therapies for malaria, while weighing the costs and benefits of alternative approaches over time. This paper argues that decision analysis provides a valuable framework for formulating such policies and combating the emergence and re-emergence of malaria and other diseases. We outline five challenges that policy makers and practitioners face in the struggle against malaria, and demonstrate how decision analysis can help to address and overcome these challenges. A prototype decision analysis framework for malaria control in Tanzania is presented, highlighting the key components that a decision support tool should include. Developing and applying such a framework can promote stronger and more effective linkages between research and policy, ultimately helping to reduce the burden of malaria and other vector-borne diseases. PMID:19356821

  8. HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS: JOURNAL ARTICLE

    EPA Science Inventory

    NRMRL-CIN-1351 Hofstetter**, P., and Hammitt, J. K. Human Health Metrics for Environmental Decision Support Tools: Lessons from Health Economics and Decision Analysis. Risk Analysis 600/R/01/104, Available: on internet, www.epa.gov/ORD/NRMRL/Pubs/600R01104, [NET]. 03/07/2001 D...

  9. 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

  10. THE CAUSAL ANALYSIS / DIAGNOSIS DECISION INFORMATION SYSTEM (CADDIS) - 2007 UPDATE

    EPA Science Inventory

    CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based ...

  11. 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.…

  12. 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

  13. 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. PMID:12865746

  14. 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.

  15. An Analysis of a Computerized System for Managing Curriculum Decisions and Tracking Student Progress in a Home-Based Pre-School Education Project.

    ERIC Educational Resources Information Center

    Lutz, John E.; And Others

    The degree of success of the computerized Child-Based Information System (CBIS) was analyzed in two areas--presenting, delivering, and managing a developmental curriculum; and recording, filing, and monitoring child tracking data, including requirements for Individualized Education Plans (IEP's). Preschool handicapped and high-risk children and…

  16. Dynamic clinical data mining: search engine-based decision support.

    PubMed

    Celi, Leo Anthony; Zimolzak, Andrew J; Stone, David J

    2014-01-01

    The research world is undergoing a transformation into one in which data, on massive levels, is freely shared. In the clinical world, the capture of data on a consistent basis has only recently begun. We propose an operational vision for a digitally based care system that incorporates data-based clinical decision making. The system would aggregate individual patient electronic medical data in the course of care; query a universal, de-identified clinical database using modified search engine technology in real time; identify prior cases of sufficient similarity as to be instructive to the case at hand; and populate the individual patient's electronic medical record with pertinent decision support material such as suggested interventions and prognosis, based on prior outcomes. Every individual's course, including subsequent outcomes, would then further populate the population database to create a feedback loop to benefit the care of future patients. PMID:25600664

  17. A vertical handoff decision algorithm based on ARMA prediction model

    NASA Astrophysics Data System (ADS)

    Li, Ru; Shen, Jiao; Chen, Jun; Liu, Qiuhuan

    2011-12-01

    With the development of computer technology and the increasing demand for mobile communications, the next generation wireless networks will be composed of various wireless networks (e.g., WiMAX and WiFi). Vertical handoff is a key technology of next generation wireless networks. During the vertical handoff procedure, handoff decision is a crucial issue for an efficient mobility. Based on auto regression moving average (ARMA) prediction model, we propose a vertical handoff decision algorithm, which aims to improve the performance of vertical handoff and avoid unnecessary handoff. Based on the current received signal strength (RSS) and the previous RSS, the proposed approach adopt ARMA model to predict the next RSS. And then according to the predicted RSS to determine whether trigger the link layer triggering event and complete vertical handoff. The simulation results indicate that the proposed algorithm outperforms the RSS-based scheme with a threshold in the performance of handoff and the number of handoff.

  18. A vertical handoff decision algorithm based on ARMA prediction model

    NASA Astrophysics Data System (ADS)

    Li, Ru; Shen, Jiao; Chen, Jun; Liu, Qiuhuan

    2012-01-01

    With the development of computer technology and the increasing demand for mobile communications, the next generation wireless networks will be composed of various wireless networks (e.g., WiMAX and WiFi). Vertical handoff is a key technology of next generation wireless networks. During the vertical handoff procedure, handoff decision is a crucial issue for an efficient mobility. Based on auto regression moving average (ARMA) prediction model, we propose a vertical handoff decision algorithm, which aims to improve the performance of vertical handoff and avoid unnecessary handoff. Based on the current received signal strength (RSS) and the previous RSS, the proposed approach adopt ARMA model to predict the next RSS. And then according to the predicted RSS to determine whether trigger the link layer triggering event and complete vertical handoff. The simulation results indicate that the proposed algorithm outperforms the RSS-based scheme with a threshold in the performance of handoff and the number of handoff.

  19. Dynamic Clinical Data Mining: Search Engine-Based Decision Support

    PubMed Central

    Zimolzak, Andrew J; Stone, David J

    2014-01-01

    The research world is undergoing a transformation into one in which data, on massive levels, is freely shared. In the clinical world, the capture of data on a consistent basis has only recently begun. We propose an operational vision for a digitally based care system that incorporates data-based clinical decision making. The system would aggregate individual patient electronic medical data in the course of care; query a universal, de-identified clinical database using modified search engine technology in real time; identify prior cases of sufficient similarity as to be instructive to the case at hand; and populate the individual patient's electronic medical record with pertinent decision support material such as suggested interventions and prognosis, based on prior outcomes. Every individual's course, including subsequent outcomes, would then further populate the population database to create a feedback loop to benefit the care of future patients. PMID:25600664

  20. Operative Versus Nonoperative Treatment of Jones Fractures: A Decision Analysis Model.

    PubMed

    Bishop, Julius A; Braun, Hillary J; Hunt, Kenneth J

    2016-01-01

    Optimal management of metadiaphyseal fifth metatarsal fractures (Jones fractures) remains controversial. Decision analysis can optimize clinical decision-making based on available evidence and patient preferences. We conducted a study to establish the determinants of decision-making and to determine the optimal treatment strategy for Jones fractures using a decision analysis model. Probabilities for potential outcomes of operative and nonoperative treatment of Jones fractures were determined from a review of the literature. Patient preferences for outcomes were obtained by questionnaire completed by 32 healthy adults with no history of foot fracture. Derived values were used in the model as a measure of utility. A decision tree was constructed, and fold-back and sensitivity analyses were performed to determine optimal treatment. Nonoperative treatment was associated with a value of 7.74, and operative treatment with an intramedullary screw was associated with a value of 7.88 given the outcome probabilities and utilities studied, making operative treatment the optimal strategy. When parameters were varied, nonoperative treatment was favored when the likelihood of healing with nonoperative treatment rose above 82% and when the probability of healing after surgery fell below 92%. In this decision analysis model, operative fixation is the preferred management strategy for Jones fractures. PMID:26991586

  1. Assessing the accuracy of GIS-based elementary multi criteria decision analysis as a spatial prediction tool - A case of predicting potential zones of sustainable groundwater resources

    NASA Astrophysics Data System (ADS)

    Adiat, K. A. N.; Nawawi, M. N. M.; Abdullah, K.

    2012-05-01

    SummaryInappropriate handling/integration of data from various sources is a problem that can make any spatial prediction tasking and inaccurate. Attempt was made in this study to offer solution to this problem by exploring the capability of GIS-based elementary MCDA as a spatial prediction tool. In order to achieve the set objectives, spatial prediction of potential zones of sustainable groundwater resources in a given study area was used as a case study. A total of five set of criteria/factors believed to be influencing groundwater storage potential in the area were selected. Each criterion/factor was assigned appropriate weight based on Saaty's 9 point scale and the weights were normalized through the analytic hierarchy process (AHP). The process was integrated in the GIS environment to produce the groundwater potential prediction map for the area. The effect of coherence of criteria on the efficiency of MCDA as a prediction tool was also examined. The prediction map produced was found to be 81.25% accurate. The results of the examination of the effect of coherence of criteria revealed that the ability of the method to produce accurate prediction is dependent on the exhaustiveness of the set of criteria used. It was established in the study that the GIS-based elementary MCDA technique is capable of producing accurate and reliable prediction particularly if the set of criteria use for the prediction is coherent.

  2. 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

  3. 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

  4. 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

  5. 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…

  6. DEVELOPMENT PLAN FOR THE CAUSAL ANALYSIS / DIAGNOSIS DECISION INFORMATION SYSTEM (CADDIS) 2001-2004

    EPA Science Inventory

    The Causal Analysis/Diagnosis Decision Information System (CADDIS) is a web-based system that provides technical support for states, tribes and other users of the Office of Water's Stressor Identification Guidance. The Stressor Identific...

  7. Promoting justified risk-based decisions in contaminated land management.

    PubMed

    Reinikainen, Jussi; Sorvari, Jaana

    2016-09-01

    Decision making and regulatory policies on contaminated land management (CLM) are commonly governed by risk assessment. Risk assessment, thus, has to comply with legislation, but also provide valid information in terms of actual risks to correctly focus the potentially required measures and allocate the available resources. Hence, reliable risk assessment is a prerequisite for justified and sustainable risk management. This paper gives an introduction to the Finnish risk-based regulatory framework, outlines the challenges within the policies and the practice and provides an overview of the new guidance document to promote risk-based and sustainable CLM. We argue that the current risk assessment approaches in the policy frameworks are not necessarily efficient enough in supporting justified risk-based decisions. One of the main reasons for this is the excessive emphasis put on conservative risk assessments and on generic guideline values without contributing to their appropriate application. This paper presents how some of the challenges in risk-based decision making have been tackled in the Finnish regulatory framework on contaminated land. We believe that our study will also stimulate interest with regard to policy frameworks in other countries. PMID:26767620

  8. A web-based decision support system for slopeland hazard warning.

    PubMed

    Yu, Fan-Chieh; Chen, Chien-Yuan; Lin, Sheng-Chi; Lin, Yu-Ching; Wu, Shang-Yu; Cheung, Kei-Wai

    2007-04-01

    A WebGIS decision support system for slopeland hazard warning based on real-time monitored rainfall is introduced herein. This paper presents its framework, database, processes of setting up the threshold line for debris flow triggering and the calculation algorithm implemented in the system. The web-based GIS via the Microsoft Internet Explorer is designed for analysis of areas prone to debris flows outburst and landslides during torrential rain. Its function is to provide suggestions to commander for immediate response to the possibility of slopeland hazards, and determine if pre-evacuation is necessary. The defining characteristics of the internet-based decision support system is not to automatically show the dangerous areas but acts as part of the decision process via information collection to help experts judge the prone debris flow creeks and the tendency of landslides initiation. The combination with real-time rainfall estimation by the QPESUMS radar system is suggested for further enhancement. PMID:17171289

  9. 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. PMID:22191941

  10. 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.

  11. Commercial pharmacogenetic-based decision-support tools in psychiatry.

    PubMed

    Bousman, Chad A; Hopwood, Malcolm

    2016-06-01

    Despite a compendium of pharmacotherapies available for treating psychiatric illnesses, suboptimal response to these therapies is typical and thought to be in part a result of genetic variation. This notion has sparked a personalised psychiatry movement, which has in turn led to the development of several commercial pharmacogenetic-based decision support tools marketed to psychiatrists as an alternative to typical, trial-and-error, prescribing. However, there is considerable uncertainty about the validity and usefulness of these tools and whether there is sufficient evidence to support their adoption. In this Personal View, we provide an introduction to these tools and assess their potential usefulness in psychiatry practice. We conclude with clinical considerations and development strategies for improving future pharmacogenetic-based decision support tools for clinical use. PMID:27133546

  12. 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.

  13. Decision Analysis Tool to Compare Energy Pathways for Transportation

    SciTech Connect

    Bloyd, Cary N.; Stork, Kevin

    2011-02-01

    With the goals of reducing greenhouse gas emissions, oil imports, and energy costs, a wide variety of automotive technologies are proposed to replace the traditional gasoline-powered internal combustion engine (g-ICE). A prototype model, Analytica Transportation Energy Analysis Model (ATEAM), has been developed using the Analytica decision modeling environment, visualizing the structure as a hierarchy of influence diagrams. The report summarized the FY2010 ATEAM accomplishments.

  14. Multicriteria decision analysis and core values for enhancing vaccine-related decision-making.

    PubMed

    Barocchi, Michèle A; Black, Steve; Rappuoli, Rino

    2016-06-29

    Vaccines have the potential to transform the health of all individuals and to reduce the health inequality between rich and poor countries. However, to achieve these goals, it is no longer sufficient to prioritize vaccine development using cost-effectiveness as the sole indicator. During a symposium entitled "Mission Grand Convergence-The Role of Vaccines," held in Siena, Italy, in July 2015, key stakeholders agreed that the prioritization of vaccine development and deployment must use multicriteria decision-making based on the following core concepts: (i) mortality and severity of the disease, (ii) vaccine safety considerations, and (iii) economic evaluation that captures the full benefits of vaccination. PMID:27358496

  15. A critical narrative analysis of shared decision-making in acute inpatient mental health care.

    PubMed

    Stacey, Gemma; Felton, Anne; Morgan, Alastair; Stickley, Theo; Willis, Martin; Diamond, Bob; Houghton, Philip; Johnson, Beverley; Dumenya, John

    2016-01-01

    Shared decision-making (SDM) is a high priority in healthcare policy and is complementary to the recovery philosophy in mental health care. This agenda has been operationalised within the Values-Based Practice (VBP) framework, which offers a theoretical and practical model to promote democratic interprofessional approaches to decision-making. However, these are limited by a lack of recognition of the implications of power implicit within the mental health system. This study considers issues of power within the context of decision-making and examines to what extent decisions about patients' care on acute in-patient wards are perceived to be shared. Focus groups were conducted with 46 mental health professionals, service users, and carers. The data were analysed using the framework of critical narrative analysis (CNA). The findings of the study suggested each group constructed different identity positions, which placed them as inside or outside of the decision-making process. This reflected their view of themselves as best placed to influence a decision on behalf of the service user. In conclusion, the discourse of VBP and SDM needs to take account of how differentials of power and the positioning of speakers affect the context in which decisions take place. PMID:26833106

  16. 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

  17. 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.

  18. Entropy Methods For Univariate Distributions in Decision Analysis

    NASA Astrophysics Data System (ADS)

    Abbas, Ali E.

    2003-03-01

    One of the most important steps in decision analysis practice is the elicitation of the decision-maker's belief about an uncertainty of interest in the form of a representative probability distribution. However, the probability elicitation process is a task that involves many cognitive and motivational biases. Alternatively, the decision-maker may provide other information about the distribution of interest, such as its moments, and the maximum entropy method can be used to obtain a full distribution subject to the given moment constraints. In practice however, decision makers cannot readily provide moments for the distribution, and are much more comfortable providing information about the fractiles of the distribution of interest or bounds on its cumulative probabilities. In this paper we present a graphical method to determine the maximum entropy distribution between upper and lower probability bounds and provide an interpretation for the shape of the maximum entropy distribution subject to fractile constraints, (FMED). We also discuss the problems with the FMED in that it is discontinuous and flat over each fractile interval. We present a heuristic approximation to a distribution if in addition to its fractiles, we also know it is continuous and work through full examples to illustrate the approach.

  19. Estimating Classification Accuracy for Complex Decision Rules Based on Multiple Scores

    ERIC Educational Resources Information Center

    Douglas, Karen M.; Mislevy, Robert J.

    2010-01-01

    Important decisions about students are made by combining multiple measures using complex decision rules. Although methods for characterizing the accuracy of decisions based on a single measure have been suggested by numerous researchers, such methods are not useful for estimating the accuracy of decisions based on multiple measures. This study…

  20. 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

  1. 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.

  2. 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.

  3. Reliability-Based Decision Fusion in Multimodal Biometric Verification Systems

    NASA Astrophysics Data System (ADS)

    Kryszczuk, Krzysztof; Richiardi, Jonas; Prodanov, Plamen; Drygajlo, Andrzej

    2007-12-01

    We present a methodology of reliability estimation in the multimodal biometric verification scenario. Reliability estimation has shown to be an efficient and accurate way of predicting and correcting erroneous classification decisions in both unimodal (speech, face, online signature) and multimodal (speech and face) systems. While the initial research results indicate the high potential of the proposed methodology, the performance of the reliability estimation in a multimodal setting has not been sufficiently studied or evaluated. In this paper, we demonstrate the advantages of using the unimodal reliability information in order to perform an efficient biometric fusion of two modalities. We further show the presented method to be superior to state-of-the-art multimodal decision-level fusion schemes. The experimental evaluation presented in this paper is based on the popular benchmarking bimodal BANCA database.

  4. 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. PMID:22874401

  5. Decision tree based transient stability method -- A case study

    SciTech Connect

    Wehenkel, L.; Pavella, M. . Inst. Montefiore); Euxibie, E.; Heilbronn, B. . Direction des Etudes et Recherches)

    1994-02-01

    The decision tree transient stability method is revisited via a case study carried out on the French EHV power system. In short, the method consists of building off-line decision trees, able to subsequently assess the system transient behavior in terms of precontingency parameters (or attributes'') of it, likely to drive the stability phenomena. This case study aims at investigating practical feasibility aspects and features of the trees, at enhancing their reliability to the extent possible, and at generalizing them. Feasibility aspects encompass data base generation, candidate attributes, stability classes; tree features concern in particular complexity in terms of their size and interpretability capabilities, robustness with respect to both their building and use. Reliability is enhanced by defining and exploiting pragmatic quality measures. Generalization concerns multicontingency, instead of single-contingency trees. The results obtained show real promise for the method to meet practical needs of electric power utilities.

  6. Lunar mission architecture evaluation using a decision analysis approach

    NASA Technical Reports Server (NTRS)

    Gleave, Janet

    1990-01-01

    President Bush's call for a return to the Moon, followed by the human exploration of Mars, has spawned numerous ideas for implementing what has been called the Space Exploration Initiative (SEI). Because a return to the Moon has been designated as the first step of SEI, the time is rapidly approaching to select one of the many mission architectures proposed for the exploration, settlement, and exploitation of the Moon. The evaluation of alternative archictures, and the subsequent selection of the 'best' alternative will be critical to the success of this, and other, space programs. The following presentation discusses the application of systems analysis to the evaluation and selection of a Lunar outpost mission architecture. The role of a decision model in the evaluation/selection process is discussed, and different types of decision models are presented. These models are analyzed and discussed in terms of their applicability to the selection of a Lunar outpost mission architecture.

  7. Multi-Attribute Decision Theory methodology for pollution control measure analysis

    SciTech Connect

    Barrera Roldan, A.S.; Corona Juarez, A.; Hardie, R.W.; Thayer, G.R.

    1992-12-31

    A methodology based in Multi-Attribute Decision Theory was developed to prioritize air pollution control measures and strategies (a set of measures) for Mexico City Metropolitan Area (MCMA). We have developed a framework that takes into account economic, technical feasibility, environmental, social, political, and institutional factors to evaluate pollution mitigation measures and strategies utilizing a decision analysis process. In a series of meetings with a panel of experts in air pollution from different offices of the mexican government we have developed General and Specific criteria for a decision analysis tree. With these tools the measures or strategies can be graded and a figure of merit can be assigned to each of them, so they can be ranked. Two pollution mitigation measures were analyzed to test the methodology, the results are presented. This methodology was developed specifically for Mexico City, though the experience gained in this work can be used to develop similar methodologies for other metropolitan areas throughout the world.

  8. Multi-Attribute Decision Theory methodology for pollution control measure analysis

    SciTech Connect

    Barrera Roldan, A.S.; Corona Juarez, A. ); Hardie, R.W.; Thayer, G.R. )

    1992-01-01

    A methodology based in Multi-Attribute Decision Theory was developed to prioritize air pollution control measures and strategies (a set of measures) for Mexico City Metropolitan Area (MCMA). We have developed a framework that takes into account economic, technical feasibility, environmental, social, political, and institutional factors to evaluate pollution mitigation measures and strategies utilizing a decision analysis process. In a series of meetings with a panel of experts in air pollution from different offices of the mexican government we have developed General and Specific criteria for a decision analysis tree. With these tools the measures or strategies can be graded and a figure of merit can be assigned to each of them, so they can be ranked. Two pollution mitigation measures were analyzed to test the methodology, the results are presented. This methodology was developed specifically for Mexico City, though the experience gained in this work can be used to develop similar methodologies for other metropolitan areas throughout the world.

  9. [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. PMID:27093326

  10. A critical review and meta-analysis of the unconscious thought effect in medical decision making.

    PubMed

    Vadillo, Miguel A; Kostopoulou, Olga; Shanks, David R

    2015-01-01

    Based on research on the increasingly popular unconscious thought effect (UTE), it has been suggested that physicians might make better diagnostic decisions after a period of distraction than after an equivalent amount of time of conscious deliberation. However, published attempts to demonstrate the UTE in medical decision making have yielded inconsistent results. In the present study, we report the results of a meta-analysis of all the available evidence on the UTE in medical decisions made by expert and novice clinicians. The meta-analysis failed to find a significant contribution of unconscious thought (UT) to the accuracy of medical decisions. This result cannot be easily attributed to any of the potential moderators of the UTE that have been discussed in the literature. Furthermore, a Bayes factor analysis shows that most experimental conditions provide positive support for the null hypothesis, suggesting that these null results do not reflect a simple lack of statistical power. We suggest ways in which new studies could usefully provide further evidence on the UTE. Unless future research shows otherwise, the recommendation of using UT to improve medical decisions lacks empirical support. PMID:26042068

  11. 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...

  12. 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…

  13. 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.

  14. THE INTERACTIVE DECISION COMMITTEE FOR CHEMICAL TOXICITY ANALYSIS.

    PubMed

    Kang, Chaeryon; Zhu, Hao; Wright, Fred A; Zou, Fei; Kosorok, Michael R

    2012-01-01

    We introduce the Interactive Decision Committee method for classification when high-dimensional feature variables are grouped into feature categories. The proposed method uses the interactive relationships among feature categories to build base classifiers which are combined using decision committees. A two-stage or a single-stage 5-fold cross-validation technique is utilized to decide the total number of base classifiers to be combined. The proposed procedure is useful for classifying biochemicals on the basis of toxicity activity, where the feature space consists of chemical descriptors and the responses are binary indicators of toxicity activity. Each descriptor belongs to at least one descriptor category. The support vector machine, the random forests, and the tree-based AdaBoost algorithms are utilized as classifier inducers. Forward selection is used to select the best combinations of the base classifiers given the number of base classifiers. Simulation studies demonstrate that the proposed method outperforms a single large, unaggregated classifier in the presence of interactive feature category information. We applied the proposed method to two toxicity data sets associated with chemical compounds. For these data sets, the proposed method improved classification performance for the majority of outcomes compared to a single large, unaggregated classifier. PMID:24415822

  15. 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.

  16. 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.

  17. 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…

  18. 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

  19. 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

  20. Nicotine-dopamine-transporter interactions during reward-based decision making.

    PubMed

    Kambeitz, Joseph; la Fougère, Christian; Werner, Natalie; Pogarell, Oliver; Riedel, Michael; Falkai, Peter; Ettinger, Ulrich

    2016-06-01

    Our everyday-life comprises a multitude of decisions that we take whilst trying to maximize advantageous outcomes, limit risks and update current needs. The cognitive processes that guide decision making as well as the brain circuits they are based on are only poorly understood. Numerous studies point to a potential role of dopamine and nicotine in decision making but less is known about their interactions. Here, 26 healthy male subjects performed the Iowa Gambling Task (IGT) in two sessions following the administration of either nicotine or placebo. Striatal dopamine transporter (DAT) binding was measured by single-photon emission computed tomography (SPECT). Results indicate that lower DAT levels were associated with better performance in the IGT (p=0.0004). Cognitive modelling analysis using the prospect valence learning (PVL) model indicated that low DAT subjects' performance deteriorated following nicotine administration as indicated by an increased learning rate and a decreased response consistency. Our results shed light on the neurochemistry underlying reward-based decision making in humans by demonstrating a significant interaction between nicotine and the DAT. The observed interaction is consistent with the hypothesized associations between DAT expression and extracellular dopamine levels, suggestive of an inverted U-shape relationship between baseline dopamine and magnitude in response to a pro-dopaminergic compound. Our findings are of particular interest in the context of psychiatric disorders where aberrant decision making represents a part of the core symptomatology, such as addiction, schizophrenia or depression. PMID:27112968

  1. 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.

  2. 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

  3. Spatial decision support system for tobacco enterprise based on spatial data mining

    NASA Astrophysics Data System (ADS)

    Mei, Xin; Liu, Junyi; Zhang, Xuexia; Cui, Weihong

    2007-11-01

    Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique and spatial data mining (SDM) to construct spatial decision support system (SDSS) of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision based on SDM is given. This paper describes how to use spatial analysis and data mining to realize the spatial decision processing such as monitoring tobacco planted acreage, analyzing and planning the cigarette sale network and so on.

  4. 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

  5. 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

  6. 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

  7. 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

  8. Associative and similarity-based processes in categorization decisions.

    PubMed

    Hampton, J A

    1997-09-01

    Two experiments were directed at distinguishing associative and similarity-based accounts of systematic differences in categorization time for different items in natural categories. Experiment 1 investigated the correlation of categorization time with three measures of instance centrality in a category. Production frequency (PF), rated typicality, and familiarity from category norms for British participants (Hampton & Gardiner, 1983) were used to predict mean categorization times for 531 words in 12 semantic categories. PF and typicality (but not familarity) were found to make significant and independent contributions to categorization time. Error rates were related only to typicality (apart from errors made to ambiguous or unknown items). Experiment 2 provided a further dissociation of PF and typicality. Manipulating the difficulty of the task through the relatedness of the false items interacted primarily with the effect of typicality on categorization time, whereas, under conditions of easy discrimination, prior exposure to the category exemplars affected only the contribution of PF to the decision time. The dissociation of typicality and PF measures is interpreted as providing evidence that speeded categorization involves both retrieval of associations indexed by PF and a similarity-based decision process indexed by typicality. PMID:9337581

  9. 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

  10. Decision Making Method Based on Paraconsistent Annotated Logic and Statistical Method: a Comparison

    NASA Astrophysics Data System (ADS)

    de Carvalho, Fábio Romeu; Brunstein, Israel; Abe, Jair Minoro

    2008-10-01

    Presently, there are new kinds of logic capable of handling uncertain and contradictory data without becoming trivial. Decision making theories based on these logics have shown to be powerful in many aspects regarding more traditional methods based on Statistics. In this paper we intend to outline a first study for a decision making theory based on Paraconsistent Annotated Evidential Logic Eτ (Paraconsistent Decision Method (PDM)) and classical Statistical Decision Method (SDM). Some discussion is presented below.

  11. 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.

  12. Implementation of a web-based prostate cancer decision site.

    PubMed

    Moul, J W; Esther, T A; Bauer, J J

    2000-08-01

    Carcinoma of the prostate is the most common form of cancer in males in the United States, second only to skin cancer. Recently, there has been increased public awareness of cancer-related diseases and specifically prostate cancer. As a result, more individuals are routinely screened and diagnosed with prostate cancer. When a man first discovers he has prostate cancer, he is faced with a multitude of questions. Health care providers realize in counseling patients that there is no single treatment choice best suited for every patient. Because of multiple treatment choices for prostate cancer and complex counseling needs due to a varied side effect profiles of the different options, the Internet may be an ideal tool to extend the health care provider. Furthermore, because men may be reluctant to discuss issues with the health care provider directly, the anonymity of the Internet may be of particular value in the disease. The Internet has created a massive body of information with an estimated 320 million Web sites. The provider can use the Internet as a patient educational tool thus affording the patient time to absorb sometimes complicated information. The Internet can help patients focus on specific aspects of their disease making the patient-provider encounter more productive and allow the patient to take an active role in the treatment decision-making process. More knowledgeable patients can make better decisions about treatment options and have more realistic expectations of their outcomes. We have developed an Internet-based decision for prostate cancer available to both patients and physicians. PMID:10975497

  13. 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).

  14. A Primer on Bayesian Decision Analysis With an Application to a Personalized Kidney Transplant Decision

    PubMed Central

    Neapolitan, Richard; Jiang, Xia; Ladner, Daniela P.; Kaplan, Bruce

    2016-01-01

    To provide personalized medicine, we not only must determine the treatments and other decisions most likely to be effective for a patient, but also consider the patient’s tradeoff between possible benefits of therapy versus possible loss of quality of life. There are numerous studies indicating that various treatments can negatively affect quality of life. Even if we have all information available for a given patient, it is an arduous task to amass the information to reach a decision that maximizes the utility of the decision to the patient. A clinical decision support system (CDSS) is a computer program, which is designed to assist healthcare professionals with decision making tasks. By utilizing emerging large datasets, we hold promise for developing CDSSs that can predict how treatments and other decisions can affect outcomes. However, we need to go beyond that; namely our CDSS needs to account for the extent to which these decisions can affect quality of life. This manuscript provides an introduction to developing CDSSs using Bayesian networks and influence diagrams. Such CDSSs are able to recommend decisions that maximize the expected utility of the predicted outcomes to the patient. By way of comparison, we examine the benefit and challenges of the Kidney Donor Risk Index (KDRI) as a decision support tool, and we discuss several difficulties with this index. Most importantly, the KDRI does not provide a measure of the expected quality of life if the kidney is accepted versus the expected quality of life if the patient stays on dialysis. Finally, we develop a schema for an influence diagram that models the kidney transplant decision, and show how the influence diagram approach can resolve these difficulties and provide the clinician and the potential transplant recipient with a valuable decision support tool. PMID:26900809

  15. 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

  16. Visual cluster analysis in support of clinical decision intelligence.

    PubMed

    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

  17. 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

  18. 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

  19. 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

  20. Examining Preservice Teachers' Decision Behaviors and Individual Differences in Three Online Case-Based Approaches

    ERIC Educational Resources Information Center

    Cevik, Yasemin Demiraslan; Andre, Thomas

    2013-01-01

    This study compared the impact of three types of case-based methods (case-based reasoning, worked example, and faded worked example) on preservice teachers' (n = 71) interaction with decision tasks and whether decision related measures (task difficulty, mental effort, decision making performance) were associated with the differences in student…

  1. 46 CFR 502.226 - Decision based on official notice; public documents.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 46 Shipping 9 2014-10-01 2014-10-01 false Decision based on official notice; public documents. 502... OF PRACTICE AND PROCEDURE Briefs; Requests for Findings; Decisions; Exceptions § 502.226 Decision based on official notice; public documents. (a) Official notice may be taken of such matters as might...

  2. 46 CFR 502.226 - Decision based on official notice; public documents.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 46 Shipping 9 2010-10-01 2010-10-01 false Decision based on official notice; public documents. 502... OF PRACTICE AND PROCEDURE Briefs; Requests for Findings; Decisions; Exceptions § 502.226 Decision based on official notice; public documents. (a) Official notice may be taken of such matters as might...

  3. 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. PMID:25197706

  4. 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

  5. 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.

  6. 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.

  7. Longitudinal Teaching of Evidence-Based Decision Making

    PubMed Central

    Martin, Beth A.; Kraus, Connie K.; Kim, Su-Young

    2012-01-01

    Objective. To determine whether longitudinal design and delivery of evidence-based decision making (EBDM) content was effective in increasing students’ knowledge, skills, and confidence as they progressed through a doctor of pharmacy (PharmD) curriculum. Design. Three student cohorts were followed from 2005 to 2009 (n=367), as they learned about EBDM through lectures, actively researching case-based questions, and researching and writing answers to therapy-based questions generated in practice settings. Assessment. Longitudinal evaluations included repeated multiple-choice examinations, confidence surveys, and written answers to practice-based questions (clinical inquiries). Students’ knowledge and perception of EBDM principles increased over each of the 3 years. Students’ self-efficacy (10-items, p<0.0001) and perceived skills (7-items, p<0.0001) in applying EBDM skills to answer practice-based questions also increased. Graded clinical inquiries verified that students performed satisfactorily in the final 2 years of the program. Conclusions. This study demonstrated a successful integration of EBDM throughout the curriculum. EBDM can effectively be taught by repetition, use of real examples, and provision of feedback. PMID:23275662

  8. 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.

  9. Clinical decision guidelines for NHS cosmetic surgery: analysis of current limitations and recommendations for future development.

    PubMed

    Cook, S A; Rosser, R; Meah, S; James, M I; Salmon, P

    2003-07-01

    Because of increasing demand for publicly funded elective cosmetic surgery, clinical decision guidelines have been developed to select those patients who should receive it. The aims of this study were to identify: the main characteristics of such guidelines; whether and how they influence clinical decision making; and ways in which they should be improved. UK health authorities were asked for their current guidelines for elective cosmetic surgery and, in a single plastic surgery unit, we examined the impact of its guidelines by observing consultations and interviewing surgeons and managers. Of 115 authorities approached, 32 reported using guidelines and provided sufficient information for analysis. Guidelines mostly concerned arbitrary sets of cosmetic procedures and lacked reference to an evidence base. They allowed surgery for specified anatomical, functional or symptomatic reasons, but these indications varied between guidelines. Most guidelines also permitted surgery 'exceptionally' for psychological reasons. The guidelines that were studied in detail did not appreciably influence surgeons' decisions, which reflected criteria that were not cited in the guidelines, including cost of the procedure and whether patients sought restoration or improvement of their appearance. Decision guidelines in this area have several limitations. Future guidelines should: include all cosmetic procedures; be informed by a broad range of evidence; and, arguably, include several nonclinical criteria that currently inform surgeons' decision-making. PMID:12890455

  10. Application of a web-based Decision Support System in risk management

    NASA Astrophysics Data System (ADS)

    Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

    2013-04-01

    Increasingly, risk information is widely available with the help of advanced technologies such as earth observation satellites, global positioning technologies, coupled with hazard modeling and analysis, and geographical information systems (GIS). Even though it exists, no effort will be put into action if it is not properly presented to the decision makers. These information need to be communicated clearly and show its usefulness so that people can make better informed decision. Therefore, communicating available risk information has become an important challenge and decision support systems have been one of the significant approaches which can help not only in presenting risk information to the decision makers but also in making efficient decisions while reducing human resources and time needed. In this study, the conceptual framework of an internet-based decision support system is presented to highlight its importance role in risk management framework and how it can be applied in case study areas chosen. The main purpose of the proposed system is to facilitate the available risk information in risk reduction by taking into account of the changes in climate, land use and socio-economic along with the risk scenarios. It allows the users to formulate, compare and select risk reduction scenarios (mainly for floods and landslides) through an enhanced participatory platform with diverse stakeholders' involvement in the decision making process. It is based on the three-tier (client-server) architecture which integrates web-GIS plus DSS functionalities together with cost benefit analysis and other supporting tools. Embedding web-GIS provides its end users to make better planning and informed decisions referenced to a geographical location, which is the one of the essential factors in disaster risk reduction programs. Different risk reduction measures of a specific area (local scale) will be evaluated using this web-GIS tool, available risk scenarios obtained from

  11. Reinforcement-based decision making in corticostriatal circuits: mutual constraints by neurocomputational and diffusion models.

    PubMed

    Ratcliff, Roger; Frank, Michael J

    2012-05-01

    In this letter, we examine the computational mechanisms of reinforce-ment-based decision making. We bridge the gap across multiple levels of analysis, from neural models of corticostriatal circuits-the basal ganglia (BG) model (Frank, 2005 , 2006 ) to simpler but mathematically tractable diffusion models of two-choice decision making. Specifically, we generated simulated data from the BG model and fit the diffusion model (Ratcliff, 1978 ) to it. The standard diffusion model fits underestimated response times under conditions of high response and reinforcement conflict. Follow-up fits showed good fits to the data both by increasing nondecision time and by raising decision thresholds as a function of conflict and by allowing this threshold to collapse with time. This profile captures the role and dynamics of the subthalamic nucleus in BG circuitry, and as such, parametric modulations of projection strengths from this nucleus were associated with parametric increases in decision boundary and its modulation by conflict. We then present data from a human reinforcement learning experiment involving decisions with low- and high-reinforcement conflict. Again, the standard model failed to fit the data, but we found that two variants similar to those that fit the BG model data fit the experimental data, thereby providing a convergence of theoretical accounts of complex interactive decision-making mechanisms consistent with available data. This work also demonstrates how to make modest modifications to diffusion models to summarize core computations of the BG model. The result is a better fit and understanding of reinforcement-based choice data than that which would have occurred with either model alone. PMID:22295983

  12. Helping patients make choices about breast reconstruction: A decision analysis approach

    PubMed Central

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

    2014-01-01

    Decision analysis can help breast reconstruction patients and their surgeons to methodically evaluate clinical alternatives and make hard decisions. The purpose of this paper 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 paper aims to illustrate decision analysis techniques from the patient perspective with an emphasis on her values and preferences. We introduce normative decision-making through a fictional breast reconstruction patient and systematically build the decision basis to help her make a good decision. We 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, we discuss how sensitivity analysis may test the robustness of the decision and how to evaluate the quality of decisions. We also present tools to help implement these concepts in practice. Finally, we examine limitations that hamper adoption of patient decision analysis in reconstructive surgery and healthcare in general. In particular, we emphasize the need for routine collection of quality of life information, out-of-pocket expense, and recovery time. PMID:25357022

  13. Design and construction of Spatial Decision Support System database based on metadata

    NASA Astrophysics Data System (ADS)

    Huang, Wenli; Liu, Huiping; Luan, Qingzu; Liu, Junping; Liu, Hua

    2009-10-01

    The Spatial Decision Support System (SDSS), as an emerging field of science and technology, is combined by Geographic Information System (GIS) and decision support system (DSS). Nowadays, more and more attentions have been paid to the technology of SDSS, and the construction of geographic database in SDSS has been a hot-spot for many years. One of the commonly used methods in geographical data management is directly entry spatial and attributes information into the relational database (generally used the Oracle relational database). Metadata plays an important role in process of building and in spatial data management. A case study is introduced. The Beijing Rural Resource Management Geographical Information System (BJRMGIS) is designed for the Beijing Agricultural Research Center, aiming for rural spatial decision support to facilitate its analysis operations. The paper mainly contains two parts from the viewpoint of database, that is, the design of database metadata table and the function of database maintenance. (1) The frame of metadata. According to report of needs analysis, the data in BJRMGIS are classified into four categories: fundamental data, remotely sensed image data, statistical data and multimedia data. Moreover, the map is a special form of data. (2) The database maintenance functions include three modules, that is, user management, database import and database management. This paper put forward the metadata-based database management decision support system model, and process from the practical problems to solve the applications. Also, the construction provides a reference for designing of other similar SDSS systems.

  14. 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.

  15. Identification of metabolic syndrome using decision tree analysis.

    PubMed

    Worachartcheewan, Apilak; Nantasenamat, Chanin; Isarankura-Na-Ayudhya, Chartchalerm; Pidetcha, Phannee; Prachayasittikul, Virapong

    2010-10-01

    This study employs decision tree as a decision support system for rapid and automated identification of individuals with metabolic syndrome (MS) among a Thai population. Results demonstrated strong predictivity of the decision tree in classification of individuals with and without MS, displaying an overall accuracy in excess of 99%. PMID:20619912

  16. 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…

  17. School-Leaving Decisions in Australia: A Cohort Analysis

    ERIC Educational Resources Information Center

    Le, Anh T.; Miller, Paul W.

    2004-01-01

    The decision to invest in education is influenced by a large number of economic, social, family, personal and institutional factors. Many of these changed in Australia during the 1970s and 1980s. Several of the more important of these changes, such as the Equal Pay for Equal Work decision of 1969, the Equal Pay for Work of Equal Value decision of…

  18. A decision analytic approach to exposure-based chemical prioritization.

    PubMed

    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

  19. 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

  20. [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

  1. 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. PMID:11432540

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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

  10. Analysis of 44 Cases before the Landlord and Tenant Board Involving Bed Bug Infestations in Ontario, Canada: Focus on Adjudicator Decisions Based on Entomological/Pest Management Evidence and Accountability under the Residential Tenancy Act and Other Applicable Legislation

    PubMed Central

    Bryks, Sam

    2011-01-01

    The resurgence of bed bugs in major urban centres in North America has resulted in conflict between landlords and tenants. This is commonly focused on attribution of blame for source of infestation, on responsibility, on costs for preparation, treatment and losses, and for compensation as rent abatement and/or alternative temporary housing. In Ontario, Canada, these issues are often decided by adjudicators at the Landlord and Tenant Board hearing claims, counter-claims and defense by legal representation (lawyers and paralegals) as well as through mediation. Evidence in these hearings may include photographs, invoices for costs as well as testimony by tenants, landlords and “expert witnesses” who are most often pest control firms representing their landlord clients. A total of 44 Landlord and Tenant Board adjudicated cases available online were analyzed. The analysis included elements of the decisions such as adjudicator, claimant (landlord or tenant), basis of claim, review of evidence, amount of claim, amount awarded, and evaluation of the quality of the evidence. The results of the analysis of these findings are discussed. Recommendations for improvement of adjudicator decisions on the basis of knowledge of bed bug biology and Integrated Pest Management best practices are presented as well as the importance of education of tenants and landlords to a process of mutual trust, support and accountability. PMID:26467732

  11. 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

  12. 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.

  13. Children's involvement in care order decision-making: A cross-country analysis.

    PubMed

    Berrick, Jill Duerr; Dickens, Jonathan; Pösö, Tarja; Skivenes, Marit

    2015-11-01

    This international comparative paper examines how child protection workers in four countries, England, Finland, Norway, USA (CA), involve children in decision making regarding involuntary child removal. The analysis is based on 772 workers' responses to a vignette describing preparations for care order proceedings. We examine children's involvement along three dimensions including information given to the child, information gathered from the child, and opportunities for their perspectives and interests to be considered. Results show that child protection workers weigh children's involvement differently based upon age. Staff in the four countries were more likely to talk with an older child, to provide information, to gather information, and to include in relevant decision making if the child were 11 compared to five in our vignette. Although the Nordic countries and England provide policy guidance regarding children's role in child protection decision making, we did not see consistently higher indicators of children's involvement from the respondents in these countries. Using child protection system frames to analyze the findings did not produce consistent differences between the family service systems and child protection systems included in this study. Findings highlight the wide range in practices concerning children's involvement in decision making, and the wide space for professional discretion in implementing practice with children at the local level. PMID:26232058

  14. 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

  15. Decision Maker based on Nanoscale Photo-excitation Transfer

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. Learning active fusion of multiple experts' decisions: an attention-based approach.

    PubMed

    Mirian, Maryam S; Ahmadabadi, Majid Nili; Araabi, Babak N; Siegwart, Roland R

    2011-02-01

    In this letter, we propose a learning system, active decision fusion learning (ADFL), for active fusion of decisions. Each decision maker, referred to as a local decision maker, provides its suggestion in the form of a probability distribution over all possible decisions. The goal of the system is to learn the active sequential selection of the local decision makers in order to consult with and thus learn the final decision based on the consultations. These two learning tasks are formulated as learning a single sequential decision-making problem in the form of a Markov decision process (MDP), and a continuous reinforcement learning method is employed to solve it. The states of this MDP are decisions of the attended local decision makers, and the actions are either attending to a local decision maker or declaring final decisions. The learning system is punished for each consultation and wrong final decision and rewarded for correct final decisions. This results in minimizing the consultation and decision-making costs through learning a sequential consultation policy where the most informative local decision makers are consulted and the least informative, misleading, and redundant ones are left unattended. An important property of this policy is that it acts locally. This means that the system handles any nonuniformity in the local decision maker's expertise over the state space. This property has been exploited in the design of local experts. ADFL is tested on a set of classification tasks, where it outperforms two well-known classification methods, Adaboost and bagging, as well as three benchmark fusion algorithms: OWA, Borda count, and majority voting. In addition, the effect of local experts design strategy on the performance of ADFL is studied, and some guidelines for the design of local experts are provided. Moreover, evaluating ADFL in some special cases proves that it is able to derive the maximum benefit from the informative local decision makers and to

  1. 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

  2. Recollection- and familiarity-based decisions reflect memory strength.

    PubMed

    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

  3. 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

  4. 75 FR 35457 - Draft of the 2010 Causal Analysis/Diagnosis Decision Information System (CADDIS)

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-06-22

    ... AGENCY Draft of the 2010 Causal Analysis/Diagnosis Decision Information System (CADDIS) AGENCY... period for the draft Web site, ``2010 release of the Causal Analysis/Diagnosis Decision Information... analysis; examples and applications; a library of conceptual models; and an online application...

  5. 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.

  6. 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...

  7. 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

  8. 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

  9. An Analysis of Consistency between Team Decisions and Reading Assessment Data within an RTI Model

    ERIC Educational Resources Information Center

    Shapiro, Edward S.; Hilt-Panahon, Alexandra; Gischlar, Karen L.; Semeniak, Kathleen; Leichman, Erin; Bowles, Shelly

    2012-01-01

    Data-based decision making by teams is central to implementation of response to intervention (RTI) models. Few studies have examined the actual decision-making process within RTI systems of service delivery. The purpose of this study was to examine the tier assignment decisions for students across grade-level teams in three K-5 elementary schools…

  10. 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.

  11. A life cycle analysis approach to D and D decision-making

    SciTech Connect

    Yuracko, K.L.; Gresalfi, M.; Yerace, P.; Flora, J.; Krstich, M.; Gerrick, D.

    1998-05-01

    This paper describes a life cycle analysis (LCA) approach that makes decontamination and decommissioning (D and D) of US Department of Energy facilities more efficient and more responsive to the concerns of the society. With the considerable complexity of D and D projects and their attendant environmental and health consequences, projects can no longer be designed based on engineering and economic criteria alone. Using the LCA D and D approach, the evaluation of material disposition alternatives explicitly includes environmental impacts, health and safety impacts, socioeconomic impacts, and stakeholder attitudes -- in addition to engineering and economic criteria. Multi-attribute decision analysis is used to take into consideration the uncertainties and value judgments that are an important part of all material disposition decisions. Use of the LCA D and D approach should lead to more appropriate selections of material disposition pathways and a decision-making process that is both understandable and defensible. The methodology and procedures of the LCA D and D approach are outlined and illustrated by an application of the approach at the Department of Energy`s West Valley Demonstration Project. Specifically, LCA was used to aid decisions on disposition of soil and concrete from the Tank Pad D and D Project. A decision tree and the Pollution Prevention/Waste Minimization Users Guide for Environmental Restoration Projects were used to identify possible alternatives for disposition of the soil and concrete. Eight alternatives encompassing source reduction, segregation, treatment, and disposal were defined for disposition of the soil; two alternatives were identified for disposition of the concrete. Preliminary results suggest that segregation and treatment are advantageous in the disposition of both the soil and the concrete. This and other recent applications illustrate the strength and ease of application of the LCA D and D approach.

  12. 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.

  13. The Neural Representation of Unexpected Uncertainty During Value-Based Decision Making

    PubMed Central

    Payzan-LeNestour, Elise; Dunne, Simon; Bossaerts, Peter; O'Doherty, John P.

    2016-01-01

    Summary Uncertainty is an inherent property of the environment and a central feature of models of decision-making and learning. Theoretical propositions suggest that one form, unexpected uncertainty, may be used to rapidly adapt to changes in the environment, while being influenced by two other forms: risk and estimation uncertainty. While previous studies have reported neural representations of estimation uncertainty and risk, relatively little is known about unexpected uncertainty. Here, participants performed a decision-making task while undergoing functional magnetic resonance imaging (fMRI), which, in combination with a Bayesian model-based analysis, enabled each form of uncertainty to be separately measured. We found representations of unexpected uncertainty in multiple cortical areas, as well as the noradrenergic brainstem nucleus locus coeruleus. Other unique cortical regions were found to encode risk, estimation uncertainty and learning rate. Collectively, these findings support theoretical models in which several formally separable uncertainty computations determine the speed of learning. PMID:23849203

  14. Shared decision making in chronic care in the context of evidence based practice in nursing.

    PubMed

    Friesen-Storms, Jolanda H H M; Bours, Gerrie J J W; van der Weijden, Trudy; Beurskens, Anna J H M

    2015-01-01

    In the decision-making environment of evidence-based practice, the following three sources of information must be integrated: research evidence of the intervention, clinical expertise, and the patient's values. In reality, evidence-based practice usually focuses on research evidence (which may be translated into clinical practice guidelines) and clinical expertise without considering the individual patient's values. The shared decision-making model seems to be helpful in the integration of the individual patient's values in evidence-based practice. We aim to discuss the relevance of shared decision making in chronic care and to suggest how it can be integrated with evidence-based practice in nursing. We start by describing the following three possible approaches to guide the decision-making process: the paternalistic approach, the informed approach, and the shared decision-making approach. Implementation of shared decision making has gained considerable interest in cases lacking a strong best-treatment recommendation, and when the available treatment options are equivalent to some extent. We discuss that in chronic care it is important to always invite the patient to participate in the decision-making process. We delineate the following six attributes of health care interventions in chronic care that influence the degree of shared decision making: the level of research evidence, the number of available intervention options, the burden of side effects, the impact on lifestyle, the patient group values, and the impact on resources. Furthermore, the patient's willingness to participate in shared decision making, the clinical expertise of the nurse, and the context in which the decision making takes place affect the shared decision-making process. A knowledgeable and skilled nurse with a positive attitude towards shared decision making—integrated with evidence-based practice—can facilitate the shared decision-making process. We conclude that nurses as well as other

  15. 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

  16. Optical flow based vehicle tracking strengthened by statistical decisions

    NASA Astrophysics Data System (ADS)

    Karimi Nejadasl, Fatemeh; Gorte, Ben G. H.; Hoogendoorn, Serge P.

    Reliable tracking of cars from aerial video imagery is one of the main ingredients of microscopic traffic monitoring. Current tracking methods however are not able yet to track all the vehicles in all frames of video imagery taken by e.g. a helicopter. Several problem scenarios can be distinguished, like situations with many similar cars in congested traffic areas, cars that appear in low contrast compared to the background and cars that are occluded in some frames by other cars or by traffic signs. In this paper an improved method is described that continuously tracks all vehicles from their appearance into the viewing area until their exit. Our algorithm starts by separately tracking individual car pixels and the complete car region as a whole using the gradient-based optical flow method. A scale space approach is used to initiate the optical flow method. The best result as obtained from the intermediate results is used in the following statistical decision making step. Finally, either the best results are accepted and by applying a rigid body assumption, one displacement result is adapted for the car as a whole, or the best results are rejected, because even the best results fail a quality criterion. Continuation of these steps for all frames constitutes the final tracking result. This method solves most of the sketched problem scenarios as is illustrated by applying it on suited helicopter video imagery.

  17. 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.

  18. 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…

  19. "Big data" needs an analysis of decision processes.

    PubMed

    Analytis, Pantelis P; Moussaïd, Mehdi; Artinger, Florian; Kämmer, Juliane E; Gigerenzer, Gerd

    2014-02-01

    We demonstrate by means of a simulation that the conceptual map presented by Bentley et al. is incomplete without taking into account people's decision processes. Within the same environment, two decision processes can generate strikingly different collective behavior; in two environments that fundamentally differ in transparency, a single process gives rise to virtually identical behavior. PMID:24572218

  20. 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....

  1. 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. ...

  2. Evidence-Based Decision-Making as a Practice-Based Learning Skill: A Pilot Study

    ERIC Educational Resources Information Center

    Falzer, Paul R.; Garman, Melissa

    2012-01-01

    Objectives: As physicians are being trained to adapt their practices to the needs and experience of patients, initiatives to standardize care have been gaining momentum. The resulting conflict can be addressed through a practice-based learning and improvement (PBL) program that develops competency in using treatment guidelines as decision aids and…

  3. 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. PMID:25630758

  4. Clinical Decision Analysis and Markov Modeling for Surgeons: An Introductory Overview.

    PubMed

    Hogendoorn, Wouter; Moll, Frans L; Sumpio, Bauer E; Hunink, M G Myriam

    2016-08-01

    This study addresses the use of decision analysis and Markov models to make contemplated decisions for surgical problems. Decision analysis and decision modeling in surgical research are increasing, but many surgeons are unfamiliar with the techniques and are skeptical of the results. The goal of this review is to familiarize surgeons with techniques and terminology used in decision analytic papers, to provide the reader a practical guide to read these papers, and to ensure that surgeons can critically appraise the quality of published clinical decision models and draw well founded conclusions from such reports.First, a brief explanation of decision analysis and Markov models is presented in simple steps, followed by an overview of the components of a decision and Markov model. Subsequently, commonly used terms and definitions are described and explained, including quality-adjusted life-years, disability-adjusted life-years, discounting, half-cycle correction, cycle length, probabilistic sensitivity analysis, incremental cost-effectiveness ratio, and the willingness-to-pay threshold.Finally, the advantages and limitations of research with Markov models are described, and new modeling techniques and future perspectives are discussed. It is important that surgeons are able to understand conclusions from decision analytic studies and are familiar with the specific definitions of the terminology used in the field to keep up with surgical research. Decision analysis can guide treatment strategies when complex clinical questions need to be answered and is a necessary and useful addition to the surgical research armamentarium. PMID:26756750

  5. 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

  6. 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...

  7. 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.

  8. From memory-based decisions to decision-based movements: a model of interval discrimination followed by action selection.

    PubMed

    Joshi, Prashant

    2007-04-01

    The interval discrimination task is a classical experimental paradigm that is employed to study working memory and decision making and typically involves four phases. First, the subject receives a stimulus, then holds it in the working memory, then makes a decision by comparing it with another stimulus and finally acts on this decision, usually by pressing one of the two buttons corresponding to the binary decision. This article demonstrates that simple linear readouts from generic neural microcircuits that send feedback of their activity to the circuit, can be trained using identical learning mechanisms to perform quite separate tasks of decision making and generation of subsequent motor commands. In this sense, the neurocomputational algorithm presented here is able to integrate the four computational stages into a single unified framework. The algorithm is tested using two-interval discrimination and delayed-match-to-sample experimental paradigms as benchmarks. PMID:17556113

  9. Integration of modeling and simulation into hospital-based decision support systems guiding pediatric pharmacotherapy

    PubMed Central

    Barrett, Jeffrey S; Mondick, John T; Narayan, Mahesh; Vijayakumar, Kalpana; Vijayakumar, Sundararajan

    2008-01-01

    Background Decision analysis in hospital-based settings is becoming more common place. The application of modeling and simulation approaches has likewise become more prevalent in order to support decision analytics. With respect to clinical decision making at the level of the patient, modeling and simulation approaches have been used to study and forecast treatment options, examine and rate caregiver performance and assign resources (staffing, beds, patient throughput). There us a great need to facilitate pharmacotherapeutic decision making in pediatrics given the often limited data available to guide dosing and manage patient response. We have employed nonlinear mixed effect models and Bayesian forecasting algorithms coupled with data summary and visualization tools to create drug-specific decision support systems that utilize individualized patient data from our electronic medical records systems. Methods Pharmacokinetic and pharmacodynamic nonlinear mixed-effect models of specific drugs are generated based on historical data in relevant pediatric populations or from adults when no pediatric data is available. These models are re-executed with individual patient data allowing for patient-specific guidance via a Bayesian forecasting approach. The models are called and executed in an interactive manner through our web-based dashboard environment which interfaces to the hospital's electronic medical records system. Results The methotrexate dashboard utilizes a two-compartment, population-based, PK mixed-effect model to project patient response to specific dosing events. Projected plasma concentrations are viewable against protocol-specific nomograms to provide dosing guidance for potential rescue therapy with leucovorin. These data are also viewable against common biomarkers used to assess patient safety (e.g., vital signs and plasma creatinine levels). As additional data become available via therapeutic drug monitoring, the model is re-executed and projections are

  10. 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.

  11. Video decision aids to assist with advance care planning: a systematic review and meta-analysis

    PubMed Central

    Jain, Ashu; Corriveau, Sophie; Quinn, Kathleen; Gardhouse, Amanda; Vegas, Daniel Brandt; You, John J

    2015-01-01

    Objective Advance care planning (ACP) can result in end-of-life care that is more congruent with patients’ values and preferences. There is increasing interest in video decision aids to assist with ACP. The objective of this study was to evaluate the impact of video decision aids on patients’ preferences regarding life-sustaining treatments (primary outcome). Design Systematic review and meta-analysis of randomised controlled trials. Data sources MEDLINE, EMBASE, PsycInfo, CINAHL, AMED and CENTRAL, between 1980 and February 2014, and correspondence with authors. Eligibility criteria for selecting studies Randomised controlled trials of adult patients that compared a video decision aid to a non-video-based intervention to assist with choices about use of life-sustaining treatments and reported at least one ACP-related outcome. Data extraction Reviewers worked independently and in pairs to screen potentially eligible articles, and to extract data regarding risk of bias, population, intervention, comparator and outcomes. Reviewers assessed quality of evidence (confidence in effect estimates) for each outcome using the Grading of Recommendations Assessment, Development and Evaluation framework. Results 10 trials enrolling 2220 patients were included. Low-quality evidence suggests that patients who use a video decision aid are less likely to indicate a preference for cardiopulmonary resuscitation (pooled risk ratio, 0.50 (95% CI 0.27 to 0.95); I2=65%). Moderate-quality evidence suggests that video decision aids result in greater knowledge related to ACP (standardised mean difference, 0.58 (95% CI 0.38 to 0.77); I2=0%). No study reported on the congruence of end-of-life treatments with patients’ wishes. No study evaluated the effect of video decision aids when integrated into clinical care. Conclusions Video decision aids may improve some ACP-related outcomes. Before recommending their use in clinical practice, more evidence is needed to confirm these findings and

  12. Using statistical process control to make data-based clinical decisions.

    PubMed Central

    Pfadt, A; Wheeler, D J

    1995-01-01

    Applied behavior analysis is based on an investigation of variability due to interrelationships among antecedents, behavior, and consequences. This permits testable hypotheses about the causes of behavior as well as for the course of treatment to be evaluated empirically. Such information provides corrective feedback for making data-based clinical decisions. This paper considers how a different approach to the analysis of variability based on the writings of Walter Shewart and W. Edwards Deming in the area of industrial quality control helps to achieve similar objectives. Statistical process control (SPC) was developed to implement a process of continual product improvement while achieving compliance with production standards and other requirements for promoting customer satisfaction. SPC involves the use of simple statistical tools, such as histograms and control charts, as well as problem-solving techniques, such as flow charts, cause-and-effect diagrams, and Pareto charts, to implement Deming's management philosophy. These data-analytic procedures can be incorporated into a human service organization to help to achieve its stated objectives in a manner that leads to continuous improvement in the functioning of the clients who are its customers. Examples are provided to illustrate how SPC procedures can be used to analyze behavioral data. Issues related to the application of these tools for making data-based clinical decisions and for creating an organizational climate that promotes their routine use in applied settings are also considered. PMID:7592154

  13. 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. PMID:21564145

  14. A risk-based decision-aiding tool for waste disposal

    SciTech Connect

    Weiner, R.F.; Reiser, A.S.; Elcock, C.G.; Nevins, S.

    1997-10-01

    N-CART (the National Spent Nuclear Fuel Program Cost Analysis and Risk Tool) is being developed to aid in low-risk, cost-effective, timely management of radioactive waste and spent nuclear fuel, and can therefore be used in management of mixed waste. N-CART provides evaluation of multiple alternatives and presents the consequences of proposed waste management activities in a clear and concise format. N-CART`s decision-aiding analyses include comparisons and sensitivity analyses of multiple alternatives and allows the user to perform quick turn-around {open_quotes}what if{close_quotes} studies to investigate various scenarios. Uncertainties in data (such as cost and schedule of various activities) are represented as distributions. N-CART centralizes documentation of the bases of program alternatives and program decisions, thereby supporting responses to stakeholders concerns. The initial N-CART design considers regulatory requirements, costs, and schedules for alternative courses of action. The final design will include risks (public health, occupational, economic, scheduling), economic benefits, and the impacts of secondary waste generation. An optimization tool is being incorporated that allows the user to specify the relative importance of cost, time risks, and other bases for decisions. The N-CART prototype can be used to compare the costs and schedules of disposal alternatives for mixed low-level radioactive waste (MLLW) and greater-than-Class-C (GTCC) waste, as well as spent nuclear fuel (SNF) and related scrap material.

  15. 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.

  16. Multi-criteria decision-making methods with optimism and pessimism based on Atanassov's intuitionistic fuzzy sets

    NASA Astrophysics Data System (ADS)

    Chen, Ting-Yu

    2012-05-01

    The theory of Atanassov's intuitionistic fuzzy sets (A-IFSs) developed over the last several decades has found useful application in fields requiring multiple-criteria decision analysis. Since the membership-nonmembership pair in A-IFSs belongs to the bivariate unipolarity type, this article describes an approach that relates optimism and pessimism to multi-criteria decision analysis in an intuitionistic fuzzy-decision environment. First, several optimistic and pessimistic point operators were defined to alter the estimation of decision outcomes. Next, based on the core of the estimations, optimistic and pessimistic score functions were developed to evaluate each alternative with respect to each criterion. The suitability function was then established to determine the degree to which each an alternative satisfies the decision maker's requirement. Because the information on multiple criteria corresponding to decision importance is often incomplete, this study included suitability functions in the optimisation models to account for poorly known membership grades. Using a linear equal-weighted summation method, these models were transformed into a single objective optimisation model to generate the optimal weights for criteria. The feasibility and effectiveness of the proposed methods were illustrated through a practical example. Finally, computational experiments with enormous amounts of simulation data were designed to conduct a comparative analysis on the ranking orders yielded by different optimistic/pessimistic point operators.

  17. 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.

  18. Decision support and analysis tool for planning in a semiconductor manufacturing facility

    NASA Astrophysics Data System (ADS)

    Fargher, Hugh E.; Smith, Richard A.

    1994-03-01

    As part of the recently completed Microelectronics Manufacturing Science and Technology (MMST) project, a decision support and analysis tool for planning in a semiconductor manufacturing facility has been developed. Design of the planning system uses an object- oriented approach, and implementation is performed in the Smalltalk programming environment. The system continually maintains a plan for wafer release into a facility, and predicts processing completion dates. The system has been built to run in a distributed environment, allowing simultaneous users in different parts of the facility. The system also provides several types of what-if analysis, both on the existing production plan and on production data. Production plan analysis is used to assist in making operational decisions related to the facility in its current state, such as determining the least disruptive time to take a piece of equipment down for maintenance. Production data analysis, which can be performed independent of the production plan, determines information such as equipment throughput rates to achieve given product cycle-times. All planning is performed using artificial intelligence search techniques, and is based on a time-phased capacity model of the facility. Uncertainty inherent in production data, such as cycle-times, is modeled using fuzzy arithmetic. This tool was used during the final 1000 wafer demonstration for MMST, and is currently being installed in other semiconductor manufacturing facilities. This paper describes the main goals of the planning system, the overall approach to planning and analysis, and a brief description of the current status.

  19. 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

  20. 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... Cleanup and On-Site Disposal of Bulk PCB Remediation Waste and Porous Surfaces in Accordance With § 761.61(a)(6) § 761.298 Decisions based on PCB concentration measurements resulting from sampling. (a)...

  1. 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... Cleanup and On-Site Disposal of Bulk PCB Remediation Waste and Porous Surfaces in Accordance With § 761.61(a)(6) § 761.298 Decisions based on PCB concentration measurements resulting from sampling. (a)...

  2. 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... Cleanup and On-Site Disposal of Bulk PCB Remediation Waste and Porous Surfaces in Accordance With § 761.61(a)(6) § 761.298 Decisions based on PCB concentration measurements resulting from sampling. (a)...

  3. 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...

  4. 40 CFR 761.298 - Decisions based on PCB concentration measurements resulting from sampling.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 30 2010-07-01 2010-07-01 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...

  5. 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…

  6. 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…

  7. 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

  8. 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. PMID:25704773

  9. 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.

  10. Genders of patients and clinicians and their effect on shared decision making: a participant-level meta-analysis

    PubMed Central

    2014-01-01

    Background Gender differences in communication styles between clinicians and patients have been postulated to impact patient care, but the extent to which the gender dyad structure impacts outcomes in shared decision making remains unclear. Methods Participant-level meta-analysis of 775 clinical encounters within 7 randomized trials where decision aids, shared decision making tools, were used at the point of care. Outcomes analysed include decisional conflict scale scores, satisfaction with the clinical encounter, concordance between stated decision and action taken, and degree of patient engagement by the clinician using the OPTION scale. An estimated minimal important difference was used to determine if nonsignificant results could be explained by low power. Results We did not find a statistically significant interaction between clinician/patient gender mix and arm for decisional conflict, satisfaction with the clinical encounter or patient engagement. A borderline significant interaction (p = 0.05) was observed for one outcome: concordance between stated decision and action taken, where encounters with female clinician/male patient showed increased concordance in the decision aid arm compared to control (8% more concordant encounters). All other gender dyads showed decreased concordance with decision aid use (6% fewer concordant encounters for same-gender, 16% fewer concordant encounters for male clinician/female patient). Conclusions In this participant-level meta-analysis of 7 randomized trials, decision aids used at the point of care demonstrated comparable efficacy across gender dyads. Purported barriers to shared decision making based on gender were not detected when tested for a minimum detected difference. Trial registrations ClinicalTrials.gov NCT00888537, NCT01077037, NCT01029288, NCT00388050, NCT00578981, NCT00949611, NCT00217061. PMID:25179289

  11. A Scalable Architecture for Rule Engine Based Clinical Decision Support Systems.

    PubMed

    Chattopadhyay, Soumi; Banerjee, Ansuman; Banerjee, Nilanjan

    2015-01-01

    Clinical Decision Support systems (CDSS) have reached a fair level of sophistication and have emerged as the popular system of choice for their aid in clinical decision making. These decision support systems are based on rule engines navigate through a repertoire of clinical rules and multitudes of facts to assist a clinical expert to decide on the set of actuations in response to a medical situation. In this paper, we present the design of a scalable architecture for a rule engine based clinical decision system. PMID:26262249

  12. Decision Model of Flight Safety Based on Flight Event

    NASA Astrophysics Data System (ADS)

    Xiao-yu, Zhang; Jiu-sheng, Chen

    To improve the management of flight safety for airline company, the hierarchy model is established about the evaluation of flight safety by flight event. Flight safety is evaluated by improved analytical hierarchy process (AHP). The method to rectify the consistency judgment matrix is given to improve the AHP. Then the weight can be given directly without consistency judgment matrix. It ensures absolute consistent of judgment matrix. By statistic of flight event incidence history data, the flight safety analysis is processed by means of static evaluation and dynamic evaluation. The hierarchy structure model is implemented based on .NET, and the simulation result proves the validity of the method.

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. Course-of-action decision support for effects-based operations

    NASA Astrophysics Data System (ADS)

    Stephenson, Mark M.

    2002-07-01

    Effects-Based Operations (EBO) is an approach to planning, executing, and assessing military operations where lower-level specific actions are derived from higher-level desired effects. Implementing EBO will require decision support capabilities that can model complex interactions and relationships, and then present the results to decision makers. Sponsored by the Air Force Research Laboratory Information Directorate (AFRL/IF), Science Applications International Corporation (SAIC) is developing a prototype collaborative Course-Of-Action (COA) decision-support system for real-time analysis of multiple possible COAs against multiple possible enemy COAs. This tool builds upon the SAIC-developed Geospatial Force Planning Tool (GFPT). GFPT is a distributed visual planning and collaboration tool within the Adaptive COA tool suite. GFPT allows geographically dispersed planners representing different planning echelons to collectively create, modify, and view a visual representation of an operational plan on top of a digital map. GFPT is being extended to support entry and visualization of both blue and red COAs. Using a COA-versus-COA simulation, expected results of various combinations of blue and red COAs will be analytically compared and visually presented. This paper will discuss the development process, the architecture, and the current results of this effort.

  18. EEG-fMRI Based Information Theoretic Characterization of the Human Perceptual Decision System

    PubMed Central

    Ostwald, Dirk; Porcaro, Camillo; Mayhew, Stephen D.; Bagshaw, Andrew P.

    2012-01-01

    The modern metaphor of the brain is that of a dynamic information processing device. In the current study we investigate how a core cognitive network of the human brain, the perceptual decision system, can be characterized regarding its spatiotemporal representation of task-relevant information. We capitalize on a recently developed information theoretic framework for the analysis of simultaneously acquired electroencephalography (EEG) and functional magnetic resonance imaging data (fMRI) (Ostwald et al. (2010), NeuroImage 49: 498–516). We show how this framework naturally extends from previous validations in the sensory to the cognitive domain and how it enables the economic description of neural spatiotemporal information encoding. Specifically, based on simultaneous EEG-fMRI data features from n = 13 observers performing a visual perceptual decision task, we demonstrate how the information theoretic framework is able to reproduce earlier findings on the neurobiological underpinnings of perceptual decisions from the response signal features' marginal distributions. Furthermore, using the joint EEG-fMRI feature distribution, we provide novel evidence for a highly distributed and dynamic encoding of task-relevant information in the human brain. PMID:22485152

  19. 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.

  20. 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…

  1. 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…

  2. 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…

  3. Benefits of probabilistic sensitivity analysis – a review of NICE decisions

    PubMed Central

    Adalsteinsson, Erpur; Toumi, Mondher

    2013-01-01

    Objective Since 2004, the National Institute of Health and Clinical Excellence (NICE) has required manufacturers to conduct a probabilistic sensitivity analysis (PSA) in their technology appraisals. The objective of this review is to assess the cost-effectiveness of different technology appraisals and compare them with the actual decision made by the NICE based on PSA. Methods The search term ‘probabilistic sensitivity analysis’ was used on the NICE home page (25 January 2012). The appraisals identified in the search were assessed and subjected to further review, if a probability of being cost-effective was provided, regardless of the threshold indicated. If several probabilities were provided, the number provided by the evidence review group was used. If several scenarios were presented, the base case scenario was chosen. Finally, the probabilities of being cost-effective were compared with the actual decision made, which could result in two outcomes: recommended or not recommended. Results A total of 31 assessments were included for the final review. The results were plotted on a graph to illustrate whether there was a relationship between the PSA outcomes and the final recommendation. The assessments were ranked according to their probability of being cost-effective. Conclusion A higher probability of a technology being cost-effective was correlated with more positive decision-making. There appeared to be a clear threshold at which technologies with a 40% certainty of being cost-effective tended to be recommended, whereas those below the threshold were not recommended. The reports suggested that the incremental cost-effectiveness ratios (ICER) estimate was not a robust driver of decision-making. A NICE applicant should pay increased attention to the PSA in addition to the ICER estimate.

  4. 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

  5. Model-Based Practice Analysis and Test Specifications.

    ERIC Educational Resources Information Center

    Kane, Michael

    1997-01-01

    Licensure and certification decisions are usually based on a chain of inference from results of a practice analysis to test specifications, the test, examinee performance, and a pass-fail decision. This article focuses on the design of practice analyses and translation of practice analyses results into test specifications. (SLD)

  6. 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

  7. 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

  8. 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

  9. Decision tree-based learning to predict patient controlled analgesia consumption and readjustment

    PubMed Central

    2012-01-01

    Background Appropriate postoperative pain management contributes to earlier mobilization, shorter hospitalization, and reduced cost. The under treatment of pain may impede short-term recovery and have a detrimental long-term effect on health. This study focuses on Patient Controlled Analgesia (PCA), which is a delivery system for pain medication. This study proposes and demonstrates how to use machine learning and data mining techniques to predict analgesic requirements and PCA readjustment. Methods The sample in this study included 1099 patients. Every patient was described by 280 attributes, including the class attribute. In addition to commonly studied demographic and physiological factors, this study emphasizes attributes related to PCA. We used decision tree-based learning algorithms to predict analgesic consumption and PCA control readjustment based on the first few hours of PCA medications. We also developed a nearest neighbor-based data cleaning method to alleviate the class-imbalance problem in PCA setting readjustment prediction. Results The prediction accuracies of total analgesic consumption (continuous dose and PCA dose) and PCA analgesic requirement (PCA dose only) by an ensemble of decision trees were 80.9% and 73.1%, respectively. Decision tree-based learning outperformed Artificial Neural Network, Support Vector Machine, Random Forest, Rotation Forest, and Naïve Bayesian classifiers in analgesic consumption prediction. The proposed data cleaning method improved the performance of every learning method in this study of PCA setting readjustment prediction. Comparative analysis identified the informative attributes from the data mining models and compared them with the correlates of analgesic requirement reported in previous works. Conclusion This study presents a real-world application of data mining to anesthesiology. Unlike previous research, this study considers a wider variety of predictive factors, including PCA demands over time. We analyzed

  10. 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…

  11. A UMLS-based Knowledge Acquisition Tool for Rule-based Clinical Decision Support System Development

    PubMed Central

    Achour, Soumeya L.; Dojat, Michel; Rieux, Claire; Bierling, Philippe; Lepage, Eric

    2001-01-01

    Decision support systems in the medical field have to be easily modified by medical experts themselves. The authors have designed a knowledge acquisition tool to facilitate the creation and maintenance of a knowledge base by the domain expert and its sharing and reuse by other institutions. The Unified Medical Language System (UMLS) contains the domain entities and constitutes the relations repository from which the expert builds, through a specific browser, the explicit domain ontology. The expert is then guided in creating the knowledge base according to the pre-established domain ontology and condition–action rule templates that are well adapted to several clinical decision-making processes. Corresponding medical logic modules are eventually generated. The application of this knowledge acquisition tool to the construction of a decision support system in blood transfusion demonstrates the value of such a pragmatic methodology for the design of rule-based clinical systems that rely on the highly progressive knowledge embedded in hospital information systems. PMID:11418542

  12. 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.

  13. 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

  14. 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

  15. 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

  16. 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

  17. Selecting a risk-based tool to aid in decision making

    SciTech Connect

    Bendure, A.O.

    1995-03-01

    Selecting a risk-based tool to aid in decision making is as much of a challenge as properly using the tool once it has been selected. Failure to consider customer and stakeholder requirements and the technical bases and differences in risk-based decision making tools will produce confounding and/or politically unacceptable results when the tool is used. Selecting a risk-based decisionmaking tool must therefore be undertaken with the same, if not greater, rigor than the use of the tool once it is selected. This paper presents a process for selecting a risk-based tool appropriate to a set of prioritization or resource allocation tasks, discusses the results of applying the process to four risk-based decision-making tools, and identifies the ``musts`` for successful selection and implementation of a risk-based tool to aid in decision making.

  18. 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.

  19. 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…

  20. 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…

  1. 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

  2. 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,…

  3. 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…

  4. 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…

  5. 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

  6. 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

  7. 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.

  8. Clinical decision support must be useful, functional is not enough: a qualitative study of computer-based clinical decision support in primary care

    PubMed Central

    2012-01-01

    Background Health information technology, particularly electronic decision support systems, can reduce the existing gap between evidence-based knowledge and health care practice but professionals have to accept and use this information. Evidence is scant on which features influence the use of computer-based clinical decision support (eCDS) in primary care and how different professional groups experience it. Our aim was to describe specific reasons for using or not using eCDS among primary care professionals. Methods The setting was a Finnish primary health care organization with 48 professionals receiving patient-specific guidance at the point of care. Multiple data (focus groups, questionnaire and spontaneous feedback) were analyzed using deductive content analysis and descriptive statistics. Results The content of the guidance is a significant feature of the primary care professional’s intention to use eCDS. The decisive reason for using or not using the eCDS is its perceived usefulness. Functional characteristics such as speed and ease of use are important but alone these are not enough. Specific information technology, professional, patient and environment features can help or hinder the use. Conclusions Primary care professionals have to perceive eCDS guidance useful for their work before they use it. PMID:23039113

  9. 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

  10. 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

  11. 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.

  12. Medical equipment classification: method and decision-making support based on paraconsistent annotated logic.

    PubMed

    Oshiyama, Natália F; Bassani, Rosana A; D'Ottaviano, Itala M L; Bassani, José W M

    2012-04-01

    As technology evolves, the role of medical equipment in the healthcare system, as well as technology management, becomes more important. Although the existence of large databases containing management information is currently common, extracting useful information from them is still difficult. A useful tool for identification of frequently failing equipment, which increases maintenance cost and downtime, would be the classification according to the corrective maintenance data. Nevertheless, establishment of classes may create inconsistencies, since an item may be close to two classes by the same extent. Paraconsistent logic might help solve this problem, as it allows the existence of inconsistent (contradictory) information without trivialization. In this paper, a methodology for medical equipment classification based on the ABC analysis of corrective maintenance data is presented, and complemented with a paraconsistent annotated logic analysis, which may enable the decision maker to take into consideration alerts created by the identification of inconsistencies and indeterminacies in the classification. PMID:22407498

  13. 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

  14. 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…

  15. Creating Smarter Classrooms: Data-Based Decision Making for Effective Classroom Management

    ERIC Educational Resources Information Center

    Gage, Nicholas A.; McDaniel, Sara

    2012-01-01

    The term "data-based decision making" (DBDM) has become pervasive in education and typically refers to the use of data to make decisions in schools, from assessment of an individual student's academic progress to whole-school reform efforts. Research suggests that special education teachers who use progress monitoring data (a DBDM approach) adapt…

  16. 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...

  17. 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…

  18. 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

  19. Recurrent Neural Networks in Computer-Based Clinical Decision Support for Laryngopathies: An Experimental Study

    PubMed Central

    Szkoła, Jarosław; Pancerz, Krzysztof; Warchoł, Jan

    2011-01-01

    The main goal of this paper is to give the basis for creating a computer-based clinical decision support (CDS) system for laryngopathies. One of approaches which can be used in the proposed CDS is based on the speech signal analysis using recurrent neural networks (RNNs). RNNs can be used for pattern recognition in time series data due to their ability of memorizing some information from the past. The Elman networks (ENs) are a classical representative of RNNs. To improve learning ability of ENs, we may modify and combine them with another kind of RNNs, namely, with the Jordan networks. The modified Elman-Jordan networks (EJNs) manifest a faster and more exact achievement of the target pattern. Validation experiments were carried out on speech signals of patients from the control group and with two kinds of laryngopathies. PMID:22007195

  20. Challenging evidence-based decision-making: a hypothetical case study about return to work.

    PubMed

    Aas, Randi W; Alexanderson, Kristina

    2012-03-01

    A hypothetical case study about return to work was used to explore the process of translating research into practice. The method involved constructing a case study derived from the characteristics of a typical, sick-listed employee with non-specific low back pain in Norway. Next, the five-step evidence-based process, including the Patient, Intervention, Co-Interventions and Outcome framework (PICO), was applied to the case study. An inductive analysis produced 10 technical and more fundamental challenges to incorporate research into intervention decisions for an individual with comorbidity. A more dynamic, interactive approach to the evidence-based practice process is proposed. It is recommended that this plus the 10 challenges are validated with real life cases, as the hypothetical case study may not be replicable. PMID:22162107

  1. 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

  2. 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

  3. 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.

  4. Using multicriteria decision analysis to support research priority setting in biomedical translational research projects.

    PubMed

    de Graaf, Gimon; Postmus, Douwe; Buskens, Erik

    2015-01-01

    Translational research is conducted to achieve a predefined set of economic or societal goals. As a result, investment decisions on where available resources have the highest potential in achieving these goals have to be made. In this paper, we first describe how multicriteria decision analysis can assist in defining the decision context and in ensuring that all relevant aspects of the decision problem are incorporated in the decision making process. We then present the results of a case study to support priority setting in a translational research consortium aimed at reducing the burden of disease of type 2 diabetes. During problem structuring, we identified four research alternatives (primary, secondary, tertiary microvascular, and tertiary macrovascular prevention) and a set of six decision criteria. Scoring of these alternatives against the criteria was done using a combination of expert judgement and previously published data. Lastly, decision analysis was performed using stochastic multicriteria acceptability analysis, which allows for the combined use of numerical and ordinal data. We found that the development of novel techniques applied in secondary prevention would be a poor investment of research funds. The ranking of the remaining alternatives was however strongly dependent on the decision maker's preferences for certain criteria. PMID:26495288

  5. Rule Acquisition in Formal Decision Contexts Based on Formal, Object-Oriented and Property-Oriented Concept Lattices

    PubMed Central

    Ren, Yue; Aswani Kumar, Cherukuri; Liu, Wenqi

    2014-01-01

    Rule acquisition is one of the main purposes in the analysis of formal decision contexts. Up to now, there have been several types of rules in formal decision contexts such as decision rules, decision implications, and granular rules, which can be viewed as ∧-rules since all of them have the following form: “if conditions 1,2,…, and m hold, then decisions hold.” In order to enrich the existing rule acquisition theory in formal decision contexts, this study puts forward two new types of rules which are called ∨-rules and ∨-∧ mixed rules based on formal, object-oriented, and property-oriented concept lattices. Moreover, a comparison of ∨-rules, ∨-∧ mixed rules, and ∧-rules is made from the perspectives of inclusion and inference relationships. Finally, some real examples and numerical experiments are conducted to compare the proposed rule acquisition algorithms with the existing one in terms of the running efficiency. PMID:25165744

  6. 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.

  7. 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.

  8. 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.

  9. Decision support system for the analysis of hospital operation indicators.

    PubMed

    Wu, Fan; Lin, Jiunn Rong; Tsai, Wen-Chen

    2002-12-01

    The inauguration of national health insurance (NHI) in many countries and their worsening financial condition has increased the sensitivity to operational cost and efficiency in hospitals. For several years, hospitals have been monitoring their operations by analyzing the financial and operational reports that are provided. Because of the rapidly changing character of the medical industry, statistical data shown on paper are no longer sufficient for decision makers. This paper describes a decision support system (DSS) for hospital administrators to assist in analyzing their operations efficiently and precisely. In hospitals, operational data of outpatients and inpatients are now stored on computers, resulting in much easier and faster data acquisition for administrators. The proposed system makes suggestions to hospital administrators and is able to self-learn to improve its future usefulness. With the dual capabilities of integrating evaluations and data collecting, the system can assist administrators in discovering and resolving problems quickly. The system provides multidimensional and multilevel analyses, by using data warehousing techniques, and generates appropriate advice to users by employing decision-making methodology. The self-learning function of the system makes it work like an expert, continually modifying its content (knowledge) and generating advice that is promptly updated to accord with changes in the medical industry. PMID:12594099

  10. 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…

  11. A Decision Making Analysis of Persuasive Argumentation and the Choice Shift Effect

    ERIC Educational Resources Information Center

    Vinokur, Amiram; And Others

    1975-01-01

    A subjective expected utility (SEU) decision-making analysis was performed on the content of arguments generated by subjects privately or during group discussion in response to choice-dilemmas shown to shift toward risk and caution. (Editor)

  12. 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

  13. 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. PMID:25108801

  14. A fuzzy logic based-method for prognostic decision making in breast and prostate cancers.

    PubMed

    Seker, Huseyin; Odetayo, Michael O; Petrovic, Dobrila; Naguib, Raouf N G

    2003-06-01

    Accurate and reliable decision making in oncological prognosis can help in the planning of suitable surgery and therapy, and generally, improve patient management through the different stages of the disease. In recent years, several prognostic markers have been used as indicators of disease progression in oncology. However, the rapid increase in the discovery of novel prognostic markers resulting from the development in medical technology, has dictated the need for developing reliable methods for extracting clinically significant markers where complex and nonlinear interactions between these markers naturally exist. The aim of this paper is to investigate the fuzzy k-nearest neighbor (FK-NN) classifier as a fuzzy logic method that provides a certainty degree for prognostic decision and assessment of the markers, and to compare it with: 1) logistic regression as a statistical method and 2) multilayer feedforward backpropagation neural networks an artificial neural-network tool, the latter two techniques having been widely used for oncological prognosis. In order to achieve this aim, breast and prostate cancer data sets are considered as benchmarks for this analysis. The overall results obtained indicate that the FK-NN-based method yields the highest predictive accuracy, and that it has produced a more reliable prognostic marker model than the statistical and artificial neural-network-based methods. PMID:12834167

  15. 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.

  16. 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

  17. Holistic risk-based environmental decision making: a Native perspective.

    PubMed

    Arquette, Mary; Cole, Maxine; Cook, Katsi; LaFrance, Brenda; Peters, Margaret; Ransom, James; Sargent, Elvera; Smoke, Vivian; Stairs, Arlene

    2002-04-01

    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

  18. Application of decision analysis to forest road deactivation in unstable terrain.

    PubMed

    Allison, Clay; Sidle, Roy C; Tait, David

    2004-02-01

    Resource managers require objective methodologies to optimize decisions related to forest road deactivation and other aspects of road management, especially in steep terrain, where road-related slope failures inflict extensive environmental damage. Decision analysis represents a systematic framework that clearly identifies real options and critical decision points. This framework links current decisions with expected future outcomes and provides advantages such as a common currency to systematically explore the liability consequences of limited budget expenditures to road deactivation and other road-related activities. Furthermore, the decision framework prevents the analysis from becoming hopelessly entangled by the vast number of possibilities generated by the alternative occurrences, magnitudes, and consequences of landslide/debris flow events and provides the information required for the first step of an adaptive management process. Here, a structured analysis of potential environmental risks for a road deactivation project in coastal British Columbia, Canada is presented. The application of decision analysis generates a ranking of the expected benefits of proposed deactivation activities on various road sections. The ranking distinguishes between road sections that offer high expected benefit from those that offer moderate to low expected benefit. Seventeen of 171, 100-m road segments accounted for 18% of the cumulative cost and 98% of the cumulative expected net benefits from road deactivation. Furthermore, the cost of deactivating a section of road is related to the expected benefit from such deactivation, thus providing the basis for more effective resource allocation and budgeting decisions. PMID:15285396

  19. Multi-attribute decision analysis for the protection of groundwater resources

    NASA Astrophysics Data System (ADS)

    Shih, C. S.; Ingram, J. W.

    1981-05-01

    Decision analysis is a powerful management tool for situations involving a complex set of alternatives for a particular set of objectives. Decision analysis, coupled with multi-attribute utility assessments, is shown to be a viable problem solving method for a complex water-resource management problem. The City of San Antonio is faced with the difficult decision of how to protect its sole water source, the Edwards aquifer, from the threat of pollution resulting from urban sprawl over the aquifer recharge zone. This decision problem has been structured as a decision analysis model in an effort to provide local decision-makers with a highly objective and easily-documented means of deciding among alternative management policies. Multi-attribute utility functions were used as the measure of effectiveness for the various alternatives. The necessary judgmental information was gathered from a group of local water-resource decision-makers through a series of cyclic opinion surveys. Sensitivity analysis was conducted to illustrate the degree to which the solution of the problem was dependent upon the identified uncertain events.

  20. onlineDeCISion.org: a web-based decision aid for DCIS treatment.

    PubMed

    Ozanne, Elissa M; Schneider, Katharine H; Soeteman, Djøra; Stout, Natasha; Schrag, Deborah; Fordis, Michael; Punglia, Rinaa S

    2015-11-01

    Women diagnosed with DCIS face complex treatment decisions and often do so with inaccurate and incomplete understanding of the risks and benefits involved. Our objective was to create a tool to guide these decisions for both providers and patients. We developed a web-based decision aid designed to provide clinicians with tailored information about a patient’s recurrence risks and survival outcomes following different treatment strategies for DCIS. A theoretical framework, microsimulation model (Soeteman et al., J Natl Cancer 105:774–781, 2013) and best practices for web-based decision tools guided the development of the decision aid. The development process used semi-structured interviews and usability testing with key stakeholders, including a diverse group of multidisciplinary clinicians and a patient advocate. We developed onlineDeCISion.​org to include the following features that were rated as important by the stakeholders: (1) descriptions of each of the standard treatment options available; (2) visual projections of the likelihood of time-specific (10-year and lifetime) breast-preservation, recurrence, and survival outcomes; and (3) side-by-side comparisons of down-stream effects of each treatment choice. All clinicians reviewing the decision aid in usability testing were interested in using it in their clinical practice. The decision aid is available in a web-based format and is planned to be publicly available. To improve treatment decision making in patients with DCIS, we have developed a web-based decision aid onlineDeCISion.​org that conforms to best practices and that clinicians are interested in using in their clinics with patients to better inform treatment decisions. PMID:26475704

  1. 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

  2. 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

  3. Introduction: School-Based Management/Shared Decision Making: "Perestroika" in Educational Governance.

    ERIC Educational Resources Information Center

    Cistone, Peter J.

    1989-01-01

    Compares the restructuring of educational governance using school-based management/shared decision making (SBM/SDM) to restructuring of Soviet government under the "perestroika" program. Reviews the other six articles in the theme issue. (FMW)

  4. 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.

  5. 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…

  6. Development of a decision support system for cost analysis.

    PubMed

    Chae, Y M

    1989-01-01

    Korean hospitals are experiencing an increasing amount of financial difficulty due to government control of hospital rates since national health insurance has been implemented. The decision support system (DSS) was developed to provide cost and revenue information for the services rendered by each department in an effort to reduce costs. This information may be used to identify the causes of financial loss if cost exceeds revenue and to develop budgets for the next year. The DSS was developed using a micromainframe interface approach where the mainframe computer collects and summarises daily cost data and the micro computer allocates the data to each department. PMID:10304295

  7. 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.

  8. Using decision analysis techniques to deal with "unanswerable" questions in idiopathic thrombocytopenic purpura.

    PubMed

    Klaassen, Robert

    2003-12-01

    Idiopathic thrombocytopenic purpura (ITP) is a common disorder with rare adverse outcomes. This makes it a particularly difficult area in which to undertake conventional studies. An alternative method for solving clinical questions is decision analysis, which is in essence a computer-assisted synthesis of the literature. Using the example of a newly diagnosed ITP patient, the author attempts to answer the question of whether a bone marrow aspirate (BMA) is required prior to starting steroids. Using decision analysis methodology, the author determines that BMA is not essential prior to starting steroids. More importantly, three variables critical to the decision-making process are determined: the risk of death from the BMA procedure, the altered chance of survival for a patient with acute lymphoblastic leukemia (ALL) inappropriately given steroids, and how sensitive the complete blood count is at determining the risk of ALL. This scenario demonstrates the value of decision analysis and lays the groundwork for future endeavors. PMID:14668643

  9. 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.

  10. 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.

  11. Comparison of Decision Models

    NASA Technical Reports Server (NTRS)

    Feinberg, A.; Miles, J. R. F.; Smith, J. H.; Scheuer, E. M.

    1986-01-01

    Two methods of multiattribute decision analysis compared in report. One method employs linear utility model. Other utilizes multiplicative utility model. Report based on interviews with experts in automotive technology to obtain their preferences regarding 10 new types of vehicles.

  12. 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.

  13. 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.

  14. A Model of Reward- and Effort-Based Optimal Decision Making and Motor Control

    PubMed Central

    Rigoux, Lionel; Guigon, Emmanuel

    2012-01-01

    Costs (e.g. energetic expenditure) and benefits (e.g. food) are central determinants of behavior. In ecology and economics, they are combined to form a utility function which is maximized to guide choices. This principle is widely used in neuroscience as a normative model of decision and action, but current versions of this model fail to consider how decisions are actually converted into actions (i.e. the formation of trajectories). Here, we describe an approach where decision making and motor control are optimal, iterative processes derived from the maximization of the discounted, weighted difference between expected rewards and foreseeable motor efforts. The model accounts for decision making in cost/benefit situations, and detailed characteristics of control and goal tracking in realistic motor tasks. As a normative construction, the model is relevant to address the neural bases and pathological aspects of decision making and motor control. PMID:23055916

  15. 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

  16. Evaluation of cabin design based on the method of multiple attribute group decision-making

    NASA Astrophysics Data System (ADS)

    Li, Xiaowen; Lv, Linlin; Li, Ping

    2013-07-01

    New century, cabin design has become an important factor affecting the compact capability of modern naval vessels. Traditional cabin design, based on naval rules and designer's subjective feeling and experience, holds that weapons and equipments are more important than habitability. So crew's satisfaction is not high to ships designed by traditional methods. In order to solve this problem, the method of multiple attribute group decision-making was proposed to evaluate the cabin design projects. This method considered many factors affecting cabin design, established a target system, quantified fuzzy factors in cabin design, analyzed the need of crews and gave a reasonable evaluation on cabin design projects. Finally, an illustrative example analysis validates the effectiveness and reliability of this method.

  17. 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.

  18. An application of principal component analysis and logistic regression to facilitate production scheduling decision support system: an automotive industry case

    NASA Astrophysics Data System (ADS)

    Mehrjoo, Saeed; Bashiri, Mahdi

    2013-05-01

    Production planning and control (PPC) systems have to deal with rising complexity and dynamics. The complexity of planning tasks is due to some existing multiple variables and dynamic factors derived from uncertainties surrounding the PPC. Although literatures on exact scheduling algorithms, simulation approaches, and heuristic methods are extensive in production planning, they seem to be inefficient because of daily fluctuations in real factories. Decision support systems can provide productive tools for production planners to offer a feasible and prompt decision in effective and robust production planning. In this paper, we propose a robust decision support tool for detailed production planning based on statistical multivariate method including principal component analysis and logistic regression. The proposed approach has been used in a real case in Iranian automotive industry. In the presence of existing multisource uncertainties, the results of applying the proposed method in the selected case show that the accuracy of daily production planning increases in comparison with the existing method.

  19. 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. PMID:22260091

  20. Risk-based decision-making: A reality at the INEL

    SciTech Connect

    Halford, V.E.; Nitschke, R.L.; Hula, G.A.

    1994-12-31

    Risk Analysis and Risk Management are major components of the Idaho National Engineering Laboratory`s (INEL`s) environmental restoration and waste management program. These tools help define responsible and cost-effective approaches to address potential human health and environmental risks from past operational practices. These techniques along with stake holder involvement, play a key role in the decision-making process which involves the US Department of Energy Idaho Operations Office (DOE), the US Environmental Protection Agency Region 10 (EPA), and the State of Idaho Department of Health and Welfare (IDHW), hereafter referred to as the agencies. An example of how this process works is Pad A, an above-ground mixed waste disposal site composed mainly of transuranic-contaminated evaporation pond salts. The site was constructed in 1972 for the disposal of solid radioactive wastes. A Comprehensive Environmental Response, Compensation and Liability Act (CERCLA) baseline risk assessment was conducted to determine the incremental cancer risk and potential for adverse health effects to the public and the impacts to the environment if no action was performed. The risk characterization indicated that the carcinogenic risk for current and future hypothetical scenarios was below or within the NCP acceptable risk range. There was a potential 10 year window for an adverse health effect to an infant from nitrate contamination of the groundwater in about 250 years. Based on these results, a responsible and sound decision was reached to maintain and recontour the existing soil cover and to perform monitoring to confirm modeling assumptions.

  1. 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

  2. Cortical and hippocampal correlates of deliberation during model-based decisions for rewards in humans.

    PubMed

    Bornstein, Aaron M; Daw, Nathaniel D

    2013-01-01

    How do we use our memories of the past to guide decisions we've never had to make before? Although extensive work describes how the brain learns to repeat rewarded actions, decisions can also be influenced by associations between stimuli or events not directly involving reward - such as when planning routes using a cognitive map or chess moves using predicted countermoves - and these sorts of associations are critical when deciding among novel options. This process is known as model-based decision making. While the learning of environmental relations that might support model-based decisions is well studied, and separately this sort of information has been inferred to impact decisions, there is little evidence concerning the full cycle by which such associations are acquired and drive choices. Of particular interest is whether decisions are directly supported by the same mnemonic systems characterized for relational learning more generally, or instead rely on other, specialized representations. Here, building on our previous work, which isolated dual representations underlying sequential predictive learning, we directly demonstrate that one such representation, encoded by the hippocampal memory system and adjacent cortical structures, supports goal-directed decisions. Using interleaved learning and decision tasks, we monitor predictive learning directly and also trace its influence on decisions for reward. We quantitatively compare the learning processes underlying multiple behavioral and fMRI observables using computational model fits. Across both tasks, a quantitatively consistent learning process explains reaction times, choices, and both expectation- and surprise-related neural activity. The same hippocampal and ventral stream regions engaged in anticipating stimuli during learning are also engaged in proportion to the difficulty of decisions. These results support a role for predictive associations learned by the hippocampal memory system to be recalled during

  3. 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

  4. 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.)

  5. A meta-analysis of blood glucose effects on human decision making.

    PubMed

    Orquin, Jacob L; Kurzban, Robert

    2016-05-01

    The academic and public interest in blood glucose and its relationship to decision making has been increasing over the last decade. To investigate and evaluate competing theories about this relationship, we conducted a psychometric meta-analysis on the effect of blood glucose on decision making. We identified 42 studies relating to 4 dimensions of decision making: willingness to pay, willingness to work, time discounting, and decision style. We did not find a uniform influence of blood glucose on decision making. Instead, we found that low levels of blood glucose increase the willingness to pay and willingness to work when a situation is food related, but decrease willingness to pay and work in all other situations. Low levels of blood glucose increase the future discount rate for food; that is, decision makers become more impatient, and to a lesser extent increase the future discount rate for money. Low levels of blood glucose also increase the tendency to make more intuitive rather than deliberate decisions. However, this effect was only observed in situations unrelated to food. We conclude that blood glucose has domain-specific effects, influencing decision making differently depending on the relevance of the situation to acquiring food. (PsycINFO Database Record PMID:26653865

  6. 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

  7. 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

  8. 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…

  9. 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…

  10. 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.

  11. 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

  12. 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

  13. 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

  14. Modeling Site-Based Decision Making: School Practices in the Age of Accountability

    ERIC Educational Resources Information Center

    Bauer, Scott C.; Bogotch, Ira E.

    2006-01-01

    Purpose: The primary purpose is to present empirical measures of variables relating to practices engaged in by site-based teams, and then to use these variables to test a model predicting significant outcomes of site-based decision making. The practice variables of site-based management (SBM) teams are essential in promoting research within a…

  15. Novel Architecture for supporting medical decision making of different data types based on Fuzzy Cognitive Map Framework.

    PubMed

    Papageorgiou, Elpiniki; Stylios, Chrysostomos; Groumpos, Peter

    2007-01-01

    Medical problems involve different types of variables and data, which have to be processed, analyzed and synthesized in order to reach a decision and/or conclude to a diagnosis. Usually, information and data set are both symbolic and numeric but most of the well-known data analysis methods deal with only one kind of data. Even when fuzzy approaches are considered, which are not depended on the scales of variables, usually only numeric data is considered. The medical decision support methods usually are accessed in only one type of available data. Thus, sophisticated methods have been proposed such as integrated hybrid learning approaches to process symbolic and numeric data for the decision support tasks. Fuzzy Cognitive Maps (FCM) is an efficient modelling method, which is based on human knowledge and experience and it can handle with uncertainty and it is constructed by extracted knowledge in the form of fuzzy rules. The FCM model can be enhanced if a fuzzy rule base (IF-THEN rules) is available. This rule base could be derived by a number of machine learning and knowledge extraction methods. Here it is introduced a hybrid attempt to handle situations with different types of available medical and/or clinical data and with difficulty to handle them for decision support tasks using soft computing techniques. PMID:18002176

  16. Design and realization of tourism spatial decision support system based on GIS

    NASA Astrophysics Data System (ADS)

    Ma, Zhangbao; Qi, Qingwen; Xu, Li

    2008-10-01

    In this paper, the existing problems of current tourism management information system are analyzed. GIS, tourism as well as spatial decision support system are introduced, and the application of geographic information system technology and spatial decision support system to tourism management and the establishment of tourism spatial decision support system based on GIS are proposed. System total structure, system hardware and software environment, database design and structure module design of this system are introduced. Finally, realization methods of this systemic core functions are elaborated.

  17. 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

  18. 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

  19. 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. PMID:24073606

  20. 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+.