Science.gov

Sample records for decision analysis based

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

    PubMed

    Bento, Antonio M; Klotz, Richard

    2014-05-20

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

  2. 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. An In-Depth Analysis of Decisions Made by Kentucky's School Based Decision-Making Councils.

    ERIC Educational Resources Information Center

    Klecker, Beverly M.; Austin, Jerry L.; Burns, Leonard T.

    This report describes the implementation of School-Based Decision-Making (SBDM) Councils. The research drew on a stratified random sample of high schools, middle and junior high schools, and elementary schools geographically distributed throughout the eight service regions of Kentucky. The paper also details the types of decisions being made by…

  4. Development and description of a decision analysis based decision support tool for stroke prevention in atrial fibrillation

    PubMed Central

    Thomson, R.; Robinson, A.; Greenaway, J.; Lowe, P.

    2002-01-01

    Background: There is an increasing move towards clinical decision making that engages the patient, which has led to the development and use of decision aids to support better decisions. The treatment of patients in atrial fibrillation (AF) with warfarin to prevent stroke is a decision that is sensitive to patient preferences as shown by a previous decision analysis. Aim: To develop a computerised decision support tool, building upon a previous decision analysis, which would engage individual patient preferences in reaching a shared decision on whether to take warfarin to prevent stroke. Methods: The development process had two main phases: (1) the development phase which employed focus groups and repeated interviews with GPs/practice nurses and patients alongside an iterative development of a computerised tool; (2) the training and testing phase in which GPs and practice nurses underwent training in the use of the tool, including the use of simulated patients. The tool was then used in a feasibility study in a small number of patients with AF to inform the design of a subsequent randomised controlled trial. Results: The prototype tool had three components: (1) derivation of an individual patient's values for relevant health states using a standard gamble; (2) presentation/discussion of a patient's risks of stroke using the Framingham equation and the benefits/risks of warfarin from a systematic literature review; and (3) decision making component incorporating the outcome of a Markov decision analysis model. Older patients could be taken through the decision analysis based computerised tool, and patients and clinicians welcomed information on risks and benefits of treatments. The tool required time and training to use. Patients' decisions in the feasibility phase did not necessarily coincide with the output of the decision analysis model, but decision conflict appeared to be reduced and both patients and GPs were satisfied with the process. Conclusions: It is

  5. The clinical decision analysis using decision tree.

    PubMed

    Bae, Jong-Myon

    2014-01-01

    The clinical decision analysis (CDA) has used to overcome complexity and uncertainty in medical problems. The CDA is a tool allowing decision-makers to apply evidence-based medicine to make objective clinical decisions when faced with complex situations. The usefulness and limitation including six steps in conducting CDA were reviewed. The application of CDA results should be done under shared decision with patients' value.

  6. The clinical decision analysis using decision tree

    PubMed Central

    Bae, Jong-Myon

    2014-01-01

    The clinical decision analysis (CDA) has used to overcome complexity and uncertainty in medical problems. The CDA is a tool allowing decision-makers to apply evidence-based medicine to make objective clinical decisions when faced with complex situations. The usefulness and limitation including six steps in conducting CDA were reviewed. The application of CDA results should be done under shared decision with patients’ value. PMID:25358466

  7. 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…

  8. 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

  9. A Computer Program for Statistically-Based Decision Analysis

    PubMed Central

    Polaschek, Jeanette X.; Lenert, Leslie A.; Garber, Alan M.

    1990-01-01

    The majority of patients with coronary artery disease do not fall into the well defined populations from randomized clinical trials. Observational databases contain a rich source of information that could be used by practicing physicians to evaluate treatment alternatives for their patients. We describe a computer system, the CABG Kibitzer, which uses an integrated approach to evaluate the treatment alternatives for CAD patients. We combine a statistical multivariate model for calculating survival advantages with DA techniques for assessing patient preferences and sensitivity analysis, to create one tool that physicians find easy to use in daily clinical practice. The development of tools of this kind is a necessary step in making the data of outcome studies accessible to practicing physicians.

  10. GPS Decision Analysis Process

    DTIC Science & Technology

    2005-06-23

    712 A/B: GPS Decision Analysis Process Revised title:___________________________________________________________________ Presented in (input and Bold...JUN 2005 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE GPS Decision Analysis Process 5a. CONTRACT NUMBER 5b. GRANT NUMBER...Prescribed by ANSI Std Z39-18 GPS Decision Analysis Process Nisha Shah The Boeing Company 73rd MORS Symposium US Military Academy – West Point 21-23

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Rough-interval-based multicriteria decision analysis for remediation of 1,1-dichloroethane contaminated groundwater.

    PubMed

    Ren, Lixia; He, Li; Lu, Hongwei; Li, Jing

    2017-02-01

    A rough-interval-based multicriteria decision analysis method (RI-MCDA) is developed for supporting the selection of remediation strategies for 1,1-dichloroethane contaminated sites. The concept of ''rough interval'' is introduced in the design framework to represent dual-uncertain parameters. Three rough-interval scenarios generated through pair-wise combining the values under three confidence levels (i.e. 68.3%, 95.4% and 99.7%) and one deterministic scenario adopted crisp numbers for parameters are introduced into the framework. The proposed method is then applied to a contaminated site in the Pudong district of Shanghai, China. Fifty remediation alternatives under four duration options (i.e. 5, 10, 15, and 20 years) and ten criteria, including daily total pumping rate, total cost and rough-interval risk information in light of uncertainty parameter (e.g. slope factor), are taken into consideration to compare different alternatives through RI-MCDA. Results indicated that the most desirable remediation strategy lied in A25 for the 5-year, A10 for the 10-year, A15 for the 15-year, and A11 for the 20-year remediation. Compared to the traditional MCDA, the proposed RI-MCDA shows the uniqueness in addressing the interaction between dual intervals of highly uncertain parameters, as well as their joint impact on the decision results, which reduces the subjectivity as much as possible.

  16. 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.

  17. 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...

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

    PubMed

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

    2010-05-01

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

  19. 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.

  20. 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.

  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.

    PubMed

    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.

  5. Heart rate monitoring from wrist-type PPG based on singular spectrum analysis with motion decision.

    PubMed

    Yang Wang; Zhiwen Liu; Bin Dong

    2016-08-01

    Heart rate (HR) monitoring is necessary for daily healthcare. Wrist-type photoplethsmography (PPG) is a convenient and non-invasive technique for HR monitoring. However, motion artifacts (MA) caused by subjects' movements can extremely interfere the results of HR monitoring. In this paper, we propose a high accuracy method using motion decision, singular spectrum analysis (SSA) and spectral peak searching for daily HR estimation. The proposed approach was evaluated on 8 subjects under a series of different motion states. Compared with electrocardiogram (ECG) recorded simultaneously, the experimental results indicated that the averaged absolute estimation error was 2.33 beats per minute (BPM).

  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. 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.

  8. 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

  9. 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,…

  10. 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

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

    SciTech Connect

    Yacout, A.M.; Orechwa, Y.

    1996-03-01

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

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

    PubMed

    Morris, James A

    2011-08-01

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

  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. 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…

  15. 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.

  16. 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).

  17. 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

  18. Training Decisions Technology Analysis

    DTIC Science & Technology

    1992-06-01

    Costs 89 5.3 Discussion of Constrained TDY-to- School Resources 90 5.4 Summary and Recommendations 93 6. Sensitivity Analysis 94 6.1 Methods 94 6.2...Analyzer Training 34 4.1 The ISEM-P Model 68 TABLE OF TABLES TablePage 5.1 25% Reduction in TDY-to- School Costs 76 5.2 25% Reduction in ABR Attendance 77 5.3...AFS 328X4 Reduced TDY-to- School 79 5.4 25% Reduction in ABR 328X4 Student Flow 79 5.5 Example Representative Site Training Capacity Results 81 5.6

  19. 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…

  20. 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.

  1. THE CAUSAL ANALYSIS / DIAGNOSIS DECISION ...

    EPA Pesticide Factsheets

    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 on the US EPA's Stressor Identification process which is a formal method for identifying causes of impairments in aquatic systems. CADDIS 2007 increases access to relevant information useful for causal analysis and provides methods and tools that practitioners can use to analyze their own data. The new Candidate Cause section provides overviews of commonly encountered causes of impairments to aquatic systems: metals, sediments, nutrients, flow alteration, temperature, ionic strength, and low dissolved oxygen. CADDIS includes new Conceptual Models that illustrate the relationships from sources to stressors to biological effects. An Interactive Conceptual Model for phosphorus links the diagram with supporting literature citations. The new Analyzing Data section helps practitioners analyze their data sets and interpret and use those results as evidence within the USEPA causal assessment process. Downloadable tools include a graphical user interface statistical package (CADStat), and programs for use with the freeware R statistical package, and a Microsoft Excel template. These tools can be used to quantify associations between causes and biological impairments using innovative methods such as species-sensitivity distributions, biological inferenc

  2. 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

  3. Life and Death Decision Analysis.

    DTIC Science & Technology

    1979-12-01

    LIFE SMOKING: CANCER, EMPHYSEMA, SHORTENED LIFE BATHING: FALLING, ELECTROCUTION CONTRACEPTION: DEATH , ILLNESS PREGNANCY: DEATH , ILLNESS ABORTION ...economic effect is the one with the highest probability of causing my death . -13- EXPECTED NET SYSTEM DESIGN BENEFIT TO ME DEATH DEATH (r A(excluding death ...0-AO81 424 STANFORD UNIV CALIF DEPT OF ENGtNEERING-ECONOM!C SYSTEMS F/6 12/1 LIFE ANDI DEATH DECISION ANALYSIS.CU) DEC 79 R A HOWARD N0OOIN-79-C-0036

  4. 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.

  5. 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.

  6. Neural signatures of fairness-related normative decision making in the ultimatum game: a coordinate-based meta-analysis.

    PubMed

    Feng, Chunliang; Luo, Yue-Jia; Krueger, Frank

    2015-02-01

    The willingness to incur personal costs to enforce prosocial norms represents a hallmark of human civilization. Although recent neuroscience studies have used the ultimatum game to understand the neuropsychological mechanisms that underlie the enforcement of fairness norms; however, a precise characterization of the neural systems underlying fairness-related norm enforcement remains elusive. In this study, we used a coordinate-based meta-analysis on functional magnetic resonance imaging (fMRI) studies using the ultimatum game with the goal to provide an additional level of evidence for the refinement of the underlying neural architecture of this human puzzling behavior. Our results demonstrated a convergence of reported activation foci in brain networks associated with psychological components of fairness-related normative decision making, presumably reflecting a reflexive and intuitive system (System 1) and a reflective and deliberate system (System 2). System 1 (anterior insula, ventromedial prefrontal cortex [PFC]) may be associated with the reflexive and intuitive responses to norm violations, representing a motivation to punish norm violators. Those intuitive responses conflict with economic self-interest, encoded in the dorsal anterior cingulate cortex (ACC), which may engage cognitive control from a reflective and deliberate System 2 to resolve the conflict by either suppressing (ventrolateral PFC, dorsomedial PFC, left dorsolateral PFC, and rostral ACC) the intuitive responses or over-riding self-interest (right dorsolateral PFC). Taken together, we suggest that fairness-related norm enforcement recruits an intuitive system for rapid evaluation of norm violations and a deliberate system for integrating both social norms and self-interest to regulate the intuitive system in favor of more flexible decision making.

  7. 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).

  8. Improved Acquisition for System Sustainment: Multiobjective Tradeoff Analysis for Condition-Based Decision-Making

    DTIC Science & Technology

    2013-10-21

    acquisition of multiple vendor maintenance, repair, and overhaul ( MRO ) supplies and services. To do so, we develop a multi-objective optimization...integrates with an acquisition algorithm to addresses vendor lead-time. Case studies broadly inspired by Tinker Air Force Base, the largest Air Force MRO ...trigger acquisition of multiple vendor maintenance, repair, and overhaul ( MRO ) supplies and services. To do so, we develop a multi-objective optimization

  9. 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).

  10. Risk-management and risk-analysis-based decision tools for attacks on electric power.

    PubMed

    Simonoff, Jeffrey S; Restrepo, Carlos E; Zimmerman, Rae

    2007-06-01

    Incident data about disruptions to the electric power grid provide useful information that can be used as inputs into risk management policies in the energy sector for disruptions from a variety of origins, including terrorist attacks. This article uses data from the Disturbance Analysis Working Group (DAWG) database, which is maintained by the North American Electric Reliability Council (NERC), to look at incidents over time in the United States and Canada for the period 1990-2004. Negative binomial regression, logistic regression, and weighted least squares regression are used to gain a better understanding of how these disturbances varied over time and by season during this period, and to analyze how characteristics such as number of customers lost and outage duration are related to different characteristics of the outages. The results of the models can be used as inputs to construct various scenarios to estimate potential outcomes of electric power outages, encompassing the risks, consequences, and costs of such outages.

  11. "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…

  12. 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

  13. A Multi-Attribute Utility Decision Analysis for Treatment Alternatives for the DOE/SR Aluminum-Based Spent Nuclear Fuel

    SciTech Connect

    Davis, F.; Kuzio, K.; Sorenson, K.; Weiner, R.; Wheeler, T.

    1998-11-01

    A multi-attribute utility analysis is applied to the decision to select a treatment method for the management of aluminum-based spent nuclear i%el (A1-SNF) owned by the United States Department of Energy (DOE). DOE will receive, treat, and temporarily store Al- SNF, most of which is composed of highly enriched uranium, at its Savannah River Site in South Carolina. DOE intends ultimately to send the treated Al-SNJ? to a geologic repository for permanent disposal. DOE initially considered ten treatment alternatives for the management of A1-SNF, and has narrowed the choice to two of these the direct disposal and melt and dilute alternatives. The decision analysis presented in this document focuses on a decision between these two remaining alternatives.

  14. A decision support system for fusion of hard and soft sensor information based on probabilistic latent semantic analysis technique

    NASA Astrophysics Data System (ADS)

    Shirkhodaie, Amir; Elangovan, Vinayak; Alkilani, Amjad; Habibi, Mohammad

    2013-05-01

    This paper presents an ongoing effort towards development of an intelligent Decision-Support System (iDSS) for fusion of information from multiple sources consisting of data from hard (physical sensors) and soft (textural sources. Primarily, this paper defines taxonomy of decision support systems for latent semantic data mining from heterogeneous data sources. A Probabilistic Latent Semantic Analysis (PLSA) approach is proposed for latent semantic concepts search from heterogeneous data sources. An architectural model for generating semantic annotation of multi-modality sensors in a modified Transducer Markup Language (TML) is described. A method for TML messages fusion is discussed for alignment and integration of spatiotemporally correlated and associated physical sensory observations. Lastly, the experimental results which exploit fusion of soft/hard sensor sources with support of iDSS are discussed.

  15. Assessing the predictive performance of risk-based water quality criteria using decision error estimates from receiver operating characteristics (ROC) analysis.

    PubMed

    McLaughlin, Douglas B

    2012-10-01

    Field data relating aquatic ecosystem responses with water quality constituents that are potential ecosystem stressors are being used increasingly in the United States in the derivation of water quality criteria to protect aquatic life. In light of this trend, there is a need for transparent quantitative methods to assess the performance of models that predict ecological conditions using a stressor-response relationship, a response variable threshold, and a stressor variable criterion. Analysis of receiver operating characteristics (ROC analysis) has a considerable history of successful use in medical diagnostic, industrial, and other fields for similarly structured decision problems, but its use for informing water quality management decisions involving risk-based environmental criteria is less common. In this article, ROC analysis is used to evaluate predictions of ecological response variable status for 3 water quality stressor-response data sets. Information on error rates is emphasized due in part to their common use in environmental studies to describe uncertainty. One data set is comprised of simulated data, and 2 involve field measurements described previously in the literature. These data sets are also analyzed using linear regression and conditional probability analysis for comparison. Results indicate that of the methods studied, ROC analysis provides the most comprehensive characterization of prediction error rates including false positive, false negative, positive predictive, and negative predictive errors. This information may be used along with other data analysis procedures to set quality objectives for and assess the predictive performance of risk-based criteria to support water quality management decisions.

  16. Decision Analysis: State of the Field.

    DTIC Science & Technology

    1982-03-01

    consequences of alternatives in terms of probabilities, Utility theory is used to quantify the values of decision makers for these conse- quences. Decision... utilities . The more common interpretation of decision theory is a sampling theor. involving statistical problems (see Waild 119501, Savage 119541. and...probability and utility , and Ramsey [1931] was the first to suggest a theory of decision making based on these two ideas. Two centuries earlicer

  17. 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.

  18. 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...

  19. 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.

  20. 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 ...

  1. 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

  2. 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

  3. 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

  4. Microcomputer-Based Expert System for Clinical Decision-Making

    PubMed Central

    Hudson, Donna L.; Estrin, Thelma

    1981-01-01

    A computerized rule-based expert system for chest pain analysis in the emergency room has been developed as a medical decision-making tool. The rules are based on a previously established criteria mapping procedure developed for evaluating emergency room decisions. The system is implemented in PASCAL, a standardized language, and hence is machine-independent, and also has modest memory requirements. The overall design permits usage by those unfamiliar with computers.

  5. Software Development for Decision Analysis

    DTIC Science & Technology

    1975-03-01

    34|"𔃻" ’’ " ’■|’■’ J - " ■»—w—"■ ■ 1 »I ■■ »I mill 1 11 1 MI independence (Category 1) or partial Independence (Categories 2 and 3) can >>e...place vandom variable 1 after decision 3 in the tree. In the nuit phase of our research, we hope to develop general algorithms for translating any...nMiu uiiim^p^M (^PLANT EFFICIENCY^ \\~r\\ |1T) % (CAPITAL COSTS Tris ^ /KW (OPERATING COSTS^) r=TTl MILLS /KWH (jmc^lTIQn-j] MILLS /KWH.*’** By

  6. An explorative cost-effectiveness analysis of school-based screening for child anxiety using a decision analytic model.

    PubMed

    Simon, Ellin; Dirksen, Carmen D; Bögels, Susan M

    2013-10-01

    Anxiety in children is highly frequent and causes severe dysfunction. Various studies have used screening procedures to identify high-anxious children and offer them indicated prevention, but the cost-effectiveness of these screening procedures in combination with a preventive intervention has never been examined. This study compared four potential strategies in relation to the prevention of child anxiety: (1) a one-time school-based screening which offers a child-focused intervention, (2) the screening and offering of a parent-focused intervention, (3) the screening and differentially offering a child- or parent-focused intervention, depending on whether or not the parents are anxious themselves, and (4) or doing nothing. An economic evaluation from a societal perspective (i.e. including direct healthcare costs, direct non-healthcare costs, indirect costs, and out-of-pocket costs), using a decision-analytic model. The model was based on the real-world 2-year participation rates of screening and intervention, and real-world costs and effects of high- and median-anxious children (aged 8-12) from regular primary schools. Incremental cost-effectiveness ratios were calculated, and several secondary and one-way sensitivity analyses were performed. The strategy of doing nothing and the strategy of screening and differentially offering the child- or parent-focused intervention, depending on parental anxiety levels were both worthwhile, with the latter strategy costing relatively little extra money compared to doing nothing. In conclusion, some evidence for the cost-effectiveness of screening and intervening was found. Screening and offering a parent-focused intervention to children of anxious parents, and a child-focused intervention to children of non-anxious parents, were found to be the most cost-effective approach.

  7. 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.

  8. 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

    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.

  9. NATO Guide for Judgment-Based Operational Analysis in Defence Decision Making (Guide OTAN pour l’analyse operationnelle basee sur le jugement dans la prise de decision de defense). Client-Oriented Volume

    DTIC Science & Technology

    2012-06-01

    fois qu’ils ont évalué des situations problématiques et pris des décisions. Les professionnels de l’OTAN ont établi que les approches utilisées...other cases, competing options without a common reference point may be encountered. For instance, decision makers may address WHAT IS JUDGEMENT...Table 5: Attributes of a Judgement-Based OA Analyst. A competent judgement-based OA analyst: • Is interested in practical solutions. • Can take a

  10. 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.

  11. Patient participation in palliative care decisions: An ethnographic discourse analysis.

    PubMed

    Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert

    2016-01-01

    The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize

  12. Patient participation in palliative care decisions: An ethnographic discourse analysis

    PubMed Central

    Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert

    2016-01-01

    The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize

  13. Clinical decision analysis using microcomputers. A case of coexistent hepatocellular carcinoma and abdominal aortic aneurysm.

    PubMed

    Wong, J B; Moskowitz, A J; Pauker, S G

    1986-12-01

    Many difficult medical decisions involve uncertainty. Decision analysis-an explicit, normative and analytic approach to making decisions under uncertainty-provides a probabilistic framework for exploring difficult problems in nondeterministic domains. As the methodology has advanced, clinical decision analysis has been applied to increasingly complex medical problems and disseminated widely in the medical literature. Unfortunately, this approach imposes a heavy computational burden on analysts. Microcomputer-based decision-support software can ease this burden.

  14. 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

  15. Enhanced Decision Analysis Support System.

    DTIC Science & Technology

    1981-03-01

    vklues will have. Any entry sta:ting with an R will be treated 0.430.2 0.43 .1 III ALT LO ALT A RRECCE Value F-4 45.0 .0.0 50.0 50.0 50.0 50.0 r-is...analysis. CtttttttttS C A V T I 0 t t i. ANY ENTRY STARTING WITH THE LETTER R WILL BE TREATED AS REGRET (LESS IS BETTER) IN THE SENSITIVITY ANALYSIS. ALL...CHARACTERS STARTING WITH ANY OTHER LETTERINUMERALI 01 CHARACTER WILL BE TREATED A VALUE (MORE IS SETTER) IN THE SENSITIVITY ANALYSIS. ts t t t t t t t t5

  16. 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…

  17. A Make/Buy Decision Analysis and Its Computer Program for Optimization of Cogeneration Plant Operation at Naval Submarine Base, New London, Connecticut.

    DTIC Science & Technology

    1980-11-01

    the total thermal energy to be converted into the predetermined electrical power, W + W 3 4 F + W while meeting the steam load demand at any given time...A MAKE/ BUY DECISION ANALYSIS AND ITS COMPUTER PROGRAM FOR OPTIM--ETC(U) UNCLASSIFIED CEL-TN-1596mniIIIIEEEEIIEIIII EEIIIIIIIIIIIE EIIIIIEEEEEIII...LEVELS ~TN no. N- 1596 A MAKE/ BUY DECISION ANALYSIS AND ITS COMPUTER PROGRAM title: FOR OPTIMIZATION OF COGENERATION PLANT OPERATION AT NAVAL SUBMARINE

  18. Comparative analysis of instance selection algorithms for instance-based classifiers in the context of medical decision support

    NASA Astrophysics Data System (ADS)

    Mazurowski, Maciej A.; Malof, Jordan M.; Tourassi, Georgia D.

    2011-01-01

    When constructing a pattern classifier, it is important to make best use of the instances (a.k.a. cases, examples, patterns or prototypes) available for its development. In this paper we present an extensive comparative analysis of algorithms that, given a pool of previously acquired instances, attempt to select those that will be the most effective to construct an instance-based classifier in terms of classification performance, time efficiency and storage requirements. We evaluate seven previously proposed instance selection algorithms and compare their performance to simple random selection of instances. We perform the evaluation using k-nearest neighbor classifier and three classification problems: one with simulated Gaussian data and two based on clinical databases for breast cancer detection and diagnosis, respectively. Finally, we evaluate the impact of the number of instances available for selection on the performance of the selection algorithms and conduct initial analysis of the selected instances. The experiments show that for all investigated classification problems, it was possible to reduce the size of the original development dataset to less than 3% of its initial size while maintaining or improving the classification performance. Random mutation hill climbing emerges as the superior selection algorithm. Furthermore, we show that some previously proposed algorithms perform worse than random selection. Regarding the impact of the number of instances available for the classifier development on the performance of the selection algorithms, we confirm that the selection algorithms are generally more effective as the pool of available instances increases. In conclusion, instance selection is generally beneficial for instance-based classifiers as it can improve their performance, reduce their storage requirements and improve their response time. However, choosing the right selection algorithm is crucial.

  19. 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.

  20. 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

  1. 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…

  2. Feature Extraction Based on Decision Boundaries

    NASA Technical Reports Server (NTRS)

    Lee, Chulhee; Landgrebe, David A.

    1993-01-01

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

  3. Computer Based Decision Support in Dentistry.

    ERIC Educational Resources Information Center

    Wagner, Ina-Veronika; Schneider, Werner

    1991-01-01

    The paper discusses computer-based decision support in the following areas: the dental patient record system; diagnosis and treatment of diseases of the oral mucosa; treatment strategy in complex clinical situations; diagnosis and treatment of functional disturbances of the masticatory system; and patient recall. (DB)

  4. 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…

  5. 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.

  6. Cabergoline versus levodopa monotherapy: a decision analysis.

    PubMed

    Smala, Antje M; Spottke, E Annika; Machat, Olaf; Siebert, Uwe; Meyer, Dieter; Köhne-Volland, Rudolf; Reuther, Martin; DuChane, Janeen; Oertel, Wolfgang H; Berger, Karin B; Dodel, Richard C

    2003-08-01

    We evaluated the incremental cost-effectiveness of cabergoline compared with levodopa monotherapy in patients with early Parkinson's disease (PD) in the German healthcare system. The study design was based on cost-effectiveness analysis using a Markov model with a 10-year time horizon. Model input data was based on a clinical trial "Early Treatment of PD with Cabergoline" as well as on cost data of a German hospital/office-based PD network. Direct and indirect medical and nonmedical costs were included. Outcomes were costs, disease stage, cumulative complication incidence, and mortality. An annual discount rate of 5% was applied and the societal perspective was chosen. The target population included patients in Hoehn and Yahr Stages I to III. It was found that the occurrence of motor complications was significantly lower in patients on cabergoline monotherapy. For patients aged >/=60 years of age, cabergoline monotherapy was cost effective when considering costs per decreased UPDRS score. Each point decrease in the UPDRS (I-IV) resulted in costs of euro;1,031. Incremental costs per additional motor complication-free patient were euro;104,400 for patients <60 years of age and euro;57,900 for patients >/=60 years of age. In conclusion, this decision-analytic model calculation for PD was based almost entirely on clinical and observed data with a limited number of assumptions. Although costs were higher in patients on cabergoline, the corresponding cost-effectiveness ratio for cabergoline was at least as favourable as the ratios for many commonly accepted therapies.

  7. 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.

  8. 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…

  9. Benefit-Risk Analysis for Decision-Making: An Approach.

    PubMed

    Raju, G K; Gurumurthi, K; Domike, R

    2016-12-01

    The analysis of benefit and risk is an important aspect of decision-making throughout the drug lifecycle. In this work, the use of a benefit-risk analysis approach to support decision-making was explored. The proposed approach builds on the qualitative US Food and Drug Administration (FDA) approach to include a more explicit analysis based on international standards and guidance that enables aggregation and comparison of benefit and risk on a common basis and a lifecycle focus. The approach is demonstrated on six decisions over the lifecycle (e.g., accelerated approval, withdrawal, and traditional approval) using two case studies: natalizumab for multiple sclerosis (MS) and bedaquiline for multidrug-resistant tuberculosis (MDR-TB).

  10. 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.

  11. Medical and nursing clinical decision making: a comparative epistemological analysis.

    PubMed

    Rashotte, Judy; Carnevale, F A

    2004-07-01

    The aim of this article is to explore the complex forms of knowledge involved in diagnostic and interventional decision making by comparing the processes in medicine and nursing, including nurse practitioners. Many authors assert that the practice of clinical decision making involves the application of theoretical knowledge (acquired in the classroom and textbooks) as well as research evidence, upon concrete particular cases. This approach draws on various universal principles and algorithms to facilitate the task. On the other hand, others argue that this involves an intuitive form of judgement that is difficult to teach, one that is acquired principally through experience. In an exploration of these issues, this article consists of three sections. A clarification of terms commonly used when discussing decision making is provided in the first section. In the second section, an epistemological analysis of decision making is presented by examining several perspectives and comparing them for their use in the nursing and medical literature. Bunge's epistemological framework for decision making (based on scientific realism) is explored for its fit with the aims of medicine and nursing. The final section presents a discussion of knowledge utilization and decision making as it relates to the implications for the education and ongoing development of nurse practitioners. It is concluded that Donald Schön's conception of reflective practice best characterizes the skillful conduct of clinical decision making.

  12. Defense against nuclear weapons: a decision analysis.

    PubMed

    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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  18. Application Analysis and Decision with Dynamic Analysis

    DTIC Science & Technology

    2014-12-01

    analysis functionality. This will allow A2D to run an application in a controlled, virtual environment, and interact with it in ways similar to a human...extension. This new functionality installs and launches the application on 1 of several virtual machines (VMs) that sit on top of a simulation of a...standard network. The application will not be capable of reaching the wider Internet. As it runs, A2D will interact with the virtual phone and perform

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

    DOE PAGES

    Yatsalo, Boris; Didenko, Vladimir; Gritsyuk, Sergey; ...

    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.

  20. 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

  1. [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.

  2. Development of Automated Aids for Decision Analysis

    DTIC Science & Technology

    1976-05-01

    called state variables (or environ- mental variables) since they define the state of the decision environment. Decision variables must be defined in such...Vaibeison Endlogetious STRUCTURAL MODELO Varabls ~State Variables* (INTERACTION MODEL) Outcome Variables’ (Either State or Prefeence$Decision...decisions and states of the environment. This type of model requires the decision maker to aggregate mentally the effects of the interactions among his

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. Qualitative Analysis of Partially-Observable Markov Decision Processes

    NASA Astrophysics Data System (ADS)

    Chatterjee, Krishnendu; Doyen, Laurent; Henzinger, Thomas A.

    We study observation-based strategies for partially-observable Markov decision processes (POMDPs) with parity objectives. An observation-based strategy relies on partial information about the history of a play, namely, on the past sequence of observations. We consider qualitative analysis problems: given a POMDP with a parity objective, decide whether there exists an observation-based strategy to achieve the objective with probability 1 (almost-sure winning), or with positive probability (positive winning). Our main results are twofold. First, we present a complete picture of the computational complexity of the qualitative analysis problem for POMDPs with parity objectives and its subclasses: safety, reachability, Büchi, and coBüchi objectives. We establish several upper and lower bounds that were not known in the literature. Second, we give optimal bounds (matching upper and lower bounds) for the memory required by pure and randomized observation-based strategies for each class of objectives.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. The Implementation of Kentucky's School-Based Decision Making Program.

    ERIC Educational Resources Information Center

    Kentucky Univ., Lexington. Inst. on Education Reform.

    This report describes what schools and educators across Kentucky are doing to implement school reform in school-based decision-making based on the Kentucky Education Reform Act of 1990 (KERA). The School-Based Decision Making (SBDM) component of KERA is a decentralized governance structure that vests great authority in SBDM councils operating at…

  17. 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.

  18. 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...

  19. 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...

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

    PubMed Central

    Dolan, James G.

    2010-01-01

    Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers. Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine “hard data” with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings. The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP) PMID:21394218

  1. 75 FR 58374 - 2010 Release of CADDIS (Causal Analysis/Diagnosis Decision Information System)

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-24

    ... AGENCY 2010 Release of CADDIS (Causal Analysis/Diagnosis Decision Information System) AGENCY... Decision Information System (CADDIS). This Web site was developed to help scientists find, develop... information useful for causal evaluations in aquatic systems. CADDIS is based on EPA's Stressor...

  2. 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

  3. 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.

  4. CUDT: a CUDA based decision tree algorithm.

    PubMed

    Lo, Win-Tsung; Chang, Yue-Shan; Sheu, Ruey-Kai; Chiu, Chun-Chieh; Yuan, Shyan-Ming

    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.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

    Berner, D. E.

    2012-12-01

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

  7. NATO Guide for Judgement-Based Operational Analysis in Defence Decision Making (Guide OTAN pour l’analyse operationnelle basee sur le jugement dans la prise de decision de defense). Analyst-Oriented Volume: Code of Best Practice for Soft Operational Analysis

    DTIC Science & Technology

    2012-06-01

    Alternative One of two or more possibilities that can be chosen for addressing, improving or (re)solving a problematic situation. Analysis A set of... strategies , etc.) alternatives . Critically, many decisions are required where judgement rather than known facts plays a key role. NATO practitioners...OA study pertains to a choice between alternatives : ways forward (‘actions’), (organisational) strategies , policy options, and the like

  8. The potential use of decision analysis to support shared decision making in the face of uncertainty: the example of atrial fibrillation and warfarin anticoagulation

    PubMed Central

    Robinson, A; Thomson, R

    2000-01-01

    The quality of patient care is dependent upon the quality of the multitude of decisions that are made daily in clinical practice. Increasingly, modern health care is seeking to pursue better decisions (including an emphasis on evidence-based practice) and to engage patients more in decisions on their care. However, many treatment decisions are made in the face of clinical uncertainty and may be critically dependent upon patient preferences. This has led to attempts to develop decision support tools that enable patients and clinicians to make better decisions. One approach that may be of value is decision analysis, which seeks to create a rational framework for evaluating complex medical decisions and to provide a systematic way of integrating potential outcomes with probabilistic information such as that generated by randomised controlled trials of interventions. This paper describes decision analysis and discusses the potential of this approach with reference to the clinical decision as to whether to treat patients in atrial fibrillation with warfarin to reduce their risk of stroke. (Quality in Health Care 2000;9:238–244) Key Words: decision analysis; quality of care; atrial fibrillation PMID:11101709

  9. 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.

  10. 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

  11. 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.…

  12. 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.

  13. 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.

  14. Distinct neural mechanisms of risk and ambiguity: a meta-analysis of decision-making.

    PubMed

    Krain, Amy L; Wilson, Amanda M; Arbuckle, Robert; Castellanos, F Xavier; Milham, Michael P

    2006-08-01

    Converging evidence from human and animal studies suggests that decision-making relies upon a distributed neural network based in the frontal lobes. In particular, models of decision-making emphasize the involvement of orbitofrontal cortices (OFC) and the medial wall. While decision-making has been studied broadly as a class of executive function, recent models have suggested the differentiation between risky and ambiguous decision-making. Given recent emphasis on the role of OFC in affectively laden "hot" executive function and dorsolateral prefrontal cortex (DLPFC) in more purely cognitive "cool" executive function, we hypothesize that the neural substrates of decision-making may differ depending on the nature of the decision required. To test this hypothesis, we used recently developed meta-analytic techniques to examine the existent functional neuroimaging literature. An initial meta-analysis of decision-making, both risky and ambiguous, found significantly elevated probabilities of activation in frontal and parietal regions, thalamus, and caudate. Ambiguous decision-making was associated with activity in DLPFC, regions of dorsal and subcallosal anterior cingulate cortex (ACC), and parietal cortex. Risky decision-making was associated with activity in OFC, rostral portions of the ACC, and parietal cortex. Direct statistical comparisons revealed significant differences between risky and ambiguous decision-making in frontal regions, including OFC, DLPFC, and ACC, that were consistent with study hypotheses. These findings provide evidence for the dissociation of neural circuits underlying risky and ambiguous decision-making, reflecting differential involvement of affective "hot" and cognitive "cool" processes.

  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. Extracting clinical information to support medical decision based on standards.

    PubMed

    Gomoi, Valentin; Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara; Stoicu-Tivadar, Vasile

    2011-01-01

    The paper presents a method connecting medical databases to a medical decision system, and describes a service created to extract the necessary information that is transferred based on standards. The medical decision can be improved based on many inputs from different medical locations. The developed solution is described for a concrete case concerning the management for chronic pelvic pain, based on the information retrieved from diverse healthcare databases.

  17. 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...

  18. Causal Analysis/Diagnosis Decision Information System (CADDIS)

    EPA Pesticide Factsheets

    The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.

  19. A Framework for Decision Analysis and Critique.

    DTIC Science & Technology

    1981-07-01

    strategies and mechanisms of judgment and choice as well as the phases of decision evaluation and the roles of feedback and learning in individual...o 𔃻 I14 - -4 C3 0 E H 41 -4 CJ EQ U) )4.w H Efl -- 40 H c 0 - 0 U) 4 E-1 0~ C44 P4 0 ca) V0- z LI, H Q) - 104. 00 -c -4Ln 4 I

  20. Decision theoretic analysis of improving epidemic detection.

    PubMed

    Izadi, Masoumeh T; Buckeridge, David L

    2007-10-11

    The potentially catastrophic impact of an epidemic specially these 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.

  1. 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.

  2. 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

  3. Enlistment Decisions of the Millennial Generation: An Analysis of Micro-Level Data

    DTIC Science & Technology

    2007-09-01

    THE MILLENNIAL GENERATION : AN ANALYSIS OF MICRO-LEVEL DATA by Kevin M. Halfacre September 2007 Thesis Advisor: Stephen Mehay Co...TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE Enlistment Decisions of the Millennial Generation : An Analysis of Micro-Level Data 6...DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) This thesis examines enlistment decisions of youth in the Millennial Generation based on individual

  4. 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

  5. Selection of invasive wild pig countermeasures using multicriteria decision analysis.

    PubMed

    Brondum, Matthew C; Collier, Zachary A; Luke, Christopher S; Goatcher, Buddy L; Linkov, Igor

    2017-01-01

    Wild pigs are a widespread invasive species that pose significant environmental and social risks. A number of wild pig eradication and control measures exist, but many eradication campaigns are ultimately unsuccessful. Decision making regarding how to design and execute an eradication plan is difficult because of multiple costs and benefits spanning various decision criteria that are associated with different eradication and control countermeasures. Moreover, multiple stakeholders are often involved with differing and sometimes competing objectives, and wild pigs are adaptive adversaries, meaning that the ideal countermeasure may change over time. In this paper, we propose the use of formal decision analytic tools which can structure decision problems into a set of relevant criteria, countermeasures, and stakeholder preferences to facilitate the evaluation of tradeoffs. We operationalize this method in a simple Excel-based decision tool and conclude with a path forward regarding how to successfully implement such tools for effective wild pig control.

  6. 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.

  7. 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

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

    PubMed Central

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

    2015-01-01

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

  9. Robustness of Multiple Objective Decision Analysis Preference Functions

    DTIC Science & Technology

    2002-06-01

    among multiple objectives makes it valuable for government decision making. Within decision analysis, multiattribute utility theory is considered...involves multiple objectives – and this is almost always the case with important problems – multiattribute utility theory forms the basic...November 3, 2000). (3) “A preference function under uncertainty” ( Dyer and Sarin, 1979: 810). UTILITY THEORY – See EXPECTED UTILITY . TIER – See

  10. Decision Making Under Uncertainty: A Neural Model Based on Partially Observable Markov Decision Processes

    PubMed Central

    Rao, Rajesh P. N.

    2010-01-01

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

  11. 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

  12. Knowledge-Based Decision Support in Department of Defense Acquisitions

    DTIC Science & Technology

    2010-09-01

    2005) reviewed and analyzed the National Aeronautics and Space Administration ( NASA ) project management policies and compared them to the GAO’s best...practices on knowledge-based decision making. The study was primarily focused on the Goddard Space Flight Center, the Jet Propulsion Lab, Johnson ...Space Center, and Marshall Space Flight Center. During its investigation, the GAO found NASA deficient in key criteria and decision reviews to fully

  13. Cognitive and Motivational Biases in Decision and Risk Analysis.

    PubMed

    Montibeller, Gilberto; von Winterfeldt, Detlof

    2015-07-01

    Behavioral decision research has demonstrated that judgments and decisions of ordinary people and experts are subject to numerous biases. Decision and risk analysis were designed to improve judgments and decisions and to overcome many of these biases. However, when eliciting model components and parameters from decisionmakers or experts, analysts often face the very biases they are trying to help overcome. When these inputs are biased they can seriously reduce the quality of the model and resulting analysis. Some of these biases are due to faulty cognitive processes; some are due to motivations for preferred analysis outcomes. This article identifies the cognitive and motivational biases that are relevant for decision and risk analysis because they can distort analysis inputs and are difficult to correct. We also review and provide guidance about the existing debiasing techniques to overcome these biases. In addition, we describe some biases that are less relevant because they can be corrected by using logic or decomposing the elicitation task. We conclude the article with an agenda for future research.

  14. 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.

  15. 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

  16. [Decision analysis in radiology using Markov models].

    PubMed

    Golder, W

    2000-01-01

    Markov models (Multistate transition models) are mathematical tools to simulate a cohort of individuals followed over time to assess the prognosis resulting from different strategies. They are applied on the assumption that persons are in one of a finite number of states of health (Markov states). Each condition is given a transition probability as well as an incremental value. Probabilities may be chosen constant or varying over time due to predefined rules. Time horizon is divided into equal increments (Markov cycles). The model calculates quality-adjusted life expectancy employing real-life units and values and summing up the length of time spent in each health state adjusted for objective outcomes and subjective appraisal. This sort of modeling prognosis for a given patient is analogous to utility in common decision trees. Markov models can be evaluated by matrix algebra, probabilistic cohort simulation and Monte Carlo simulation. They have been applied to assess the relative benefits and risks of a limited number of diagnostic and therapeutic procedures in radiology. More interventions should be submitted to Markov analyses in order to elucidate their cost-effectiveness.

  17. Improvements to Air Force Strategic Basing Decisions

    DTIC Science & Technology

    2016-01-01

    MOB main operating base NEPA National Environmental Policy Act NSC-68 National Security Council Report 68 OCONUS outside of the continental United...6.3 !  GS Locality – 2.7 Criteria to Base Active Duty-Led 36-PAA KC-46A Classic Association ( MOB 1) (SecAF Approved 27 Apr 12) 6 10 survey...eliminate static formations in Europe and Asia by moving away from large main operating bases ( MOBs ) in favor of access to cold and warm facilities that

  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. 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.

  20. 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.

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

    PubMed

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

    2016-05-01

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

  2. MADAM: Multiple-Attribute Decision Analysis Model. Volume 2

    DTIC Science & Technology

    1981-12-01

    CONTAINED A SIGNIFICANT NUMBER OF PAGES WHICH DO NOT REPRODUCE LEGIBLY. AFIT/GOR/AA/81 0-1 MADAM : MULTIPLE-ATTRIBUTE DECISION ANALYSIS MODEL VOLUME...11 T!IFSIS w T C AFIT/GOR/AA/81D-I Wayne A. Stimpson (J> CC’ T 2Lt USAFR ~~FEB 1 9 1982 AFITj,0R/AA/81 D-1 Thes is t", MADAM : MULTIPLE-ATTRIBUTE...objectives to be satisfied. The program is MADAM : Multiple-Attribute Decision Analysis Model, and it is written in FORTRAN V and is implemented on the

  3. 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.

  4. Multiattribute Decision Modeling Techniques: A Comparative Analysis

    DTIC Science & Technology

    1988-08-01

    Rating Technique (SMART) as a direct response to Raiffa’s (1969) article on multiattribute utility theory , which Edwards found extremcy stimulating but...approaches such as multiattribute utility /value assessment and hierarchical analysis and have applied these techniques to a number of non-military... multiattributed ) outcomes O(l)...O(k), and if the utility function is denoted by u and the probabilities of the k events are p(l)...p(k), then the

  5. Decision Aids Using Heterogeneous Intelligence Analysis

    DTIC Science & Technology

    2010-08-20

    Document Date 08/20/10 To enable all of this, several COTS and developed technolgies and tools were utilized in the im- plementation of the Android-based... Mobile augmented reality (AR) browser that displays points of interest (POls) on top of the phone’s camera view NutiTeq - Mobile mapping SDK SQLlite

  6. Using the Situated Clinical Decision-Making framework to guide analysis of nurses' clinical decision-making.

    PubMed

    Gillespie, Mary

    2010-11-01

    Nurses' clinical decision-making is a complex process that holds potential to influence the quality of care provided and patient outcomes. The evolution of nurses' decision-making that occurs with experience has been well documented. In addition, literature includes numerous strategies and approaches purported to support development of nurses' clinical decision-making. There has been, however, significantly less attention given to the process of assessing nurses' clinical decision-making and novice clinical educators are often challenged with knowing how to best support nurses and nursing students in developing their clinical decision-making capacity. The Situated Clinical Decision-Making framework is presented for use by clinical educators: it provides a structured approach to analyzing nursing students' and novice nurses' decision-making in clinical nursing practice, assists educators in identifying specific issues within nurses' clinical decision-making, and guides selection of relevant strategies to support development of clinical decision-making. A series of questions is offered as a guide for clinical educators when assessing nurses' clinical decision-making. The discussion presents key considerations related to analysis of various decision-making components, including common sources of challenge and errors that may occur within nurses' clinical decision-making. An exemplar illustrates use of the framework and guiding questions. Implications of this approach for selection of strategies that support development of clinical decision-making are highlighted.

  7. 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

  8. Decision analysis: a primer and application to pain-related studies.

    PubMed

    Kim, Jaewhan; Nelson, Richard; Biskupiak, Joseph

    2008-01-01

    Decision analysis is a quantitative approach to decision making under uncertainty that explicitly states all relevant components of the decision, including statement of the problem, identification of the perspective of the decision maker, alternative courses of action and their consequences, and a model that illustrates the decision-making process. Decision trees and Markov models are used to provide a simplified version of complex clinical problems to help decision makers understand the risks and benefits of several clinical options. This article provides an introduction to decision analysis by describing the construction of decision trees and Markov models and employing examples from the recent literature.

  9. 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.

  10. Decision making in flood risk based storm sewer network design.

    PubMed

    Sun, S A; Djordjević, S; Khu, S T

    2011-01-01

    It is widely recognised that flood risk needs to be taken into account when designing a storm sewer network. Flood risk is generally a combination of flood consequences and flood probabilities. This paper aims to explore the decision making in flood risk based storm sewer network design. A multiobjective optimization is proposed to find the Pareto front of optimal designs in terms of low construction cost and low flood risk. The decision making process then follows this multi-objective optimization to select a best design from the Pareto front. The traditional way of designing a storm sewer system based on a predefined design storm is used as one of the decision making criteria. Additionally, three commonly used risk based criteria, i.e., the expected flood risk based criterion, the Hurwicz criterion and the stochastic dominance based criterion, are investigated and applied in this paper. Different decisions are made according to different criteria as a result of different concerns represented by the criteria. The proposed procedure is applied to a simple storm sewer network design to demonstrate its effectiveness and the different criteria are compared.

  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. 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.

  13. 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.

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

    PubMed

    Crofts, Gillian; Padman, Rema; Maharaja, Nisha

    2013-01-01

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

  15. 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.

  16. 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

  17. Demystifying the Data-Based Decision-Making Process

    ERIC Educational Resources Information Center

    Cramer, Elizabeth D.; Little, Mary E.; McHatton, Patricia Alvarez

    2014-01-01

    Across the United States, teachers and teacher educators are facing increased accountability for improved student achievement. Using assessment results to inform instruction provides a catalyst to improve student outcomes and is a key skill for preservice teacher candidates. The process of data-based decision making is integral to performance…

  18. Data-Based Decision Making in Teams: Enablers and Barriers

    ERIC Educational Resources Information Center

    Bolhuis, Erik; Schildkamp, Kim; Voogt, Joke

    2016-01-01

    Data use is becoming more important in higher education. In this case study, a team of teachers from a teacher education college was supported in data-based decision making by means of the data team procedure. This data team studied the reasons why students drop out. A team's success depends in part on whether the team is able to develop and apply…

  19. A knowledge-based decision support system for payload scheduling

    NASA Technical Reports Server (NTRS)

    Tyagi, Rajesh; Tseng, Fan T.

    1988-01-01

    This paper presents the development of a prototype Knowledge-based Decision Support System, currently under development, for scheduling payloads/experiments on space station missions. The DSS is being built on Symbolics, a Lisp machine, using KEE, a commercial knowledge engineering tool.

  20. Design and optimization of a ground water monitoring system using GIS and multicriteria decision analysis

    SciTech Connect

    Dutta, D.; Gupta, A.D.; Ramnarong, V.

    1998-12-31

    A GIS-based methodology has been developed to design a ground water monitoring system and implemented for a selected area in Mae-Klong River Basin, Thailand. A multicriteria decision-making analysis has been performed to optimize the network system based on major criteria which govern the monitoring network design such as minimization of cost of construction, reduction of kriging standard deviations, etc. The methodology developed in this study is a new approach to designing monitoring networks which can be used for any site considering site-specific aspects. It makes it possible to choose the best monitoring network from various alternatives based on the prioritization of decision factors.

  1. The online community based decision making support system for mitigating biased decision making

    NASA Astrophysics Data System (ADS)

    Kang, Sunghyun; Seo, Jiwan; Choi, Seungjin; Kim, Junho; Han, Sangyong

    2016-10-01

    As the Internet technology and social media advance, various information and opinions are shared and distributed through the online communities. However, the existence of implicit and explicit bias of opinions may have a potential influence on the outcomes. Compared to the importance of mitigating biased information, the study in this field is relatively young and does not address many important issues. In this paper we propose the noble approach to mitigate the biased opinions using conventional machine learning methods. The proposed method extracts the useful features such as inclination and sentiment of the community members. They are classified based on their previous behavior, and the propensity of the members is understood. This information on each community and its members is very useful and improve the ability to make an unbiased decision. The proposed method presented in this paper is shown to have the ability to assist optimal, fair and good decision making while also reducing the influence of implicit bias.

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

    PubMed

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

    2015-06-01

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

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

    PubMed

    Ito, Makoto; Doya, Kenji

    2009-08-05

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

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

    PubMed

    Maguire, Lynn A

    2004-08-01

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

  5. Insurance Contract Analysis for Company Decision Support in Acquisition Management

    NASA Astrophysics Data System (ADS)

    Chernovita, H. P.; Manongga, D.; Iriani, A.

    2017-01-01

    One of company activities to retain their business is marketing the products which include in acquisition management to get new customers. Insurance contract analysis using ID3 to produce decision tree and rules to be decision support for the insurance company. The decision tree shows 13 rules that lead to contract termination claim. This could be a guide for the insurance company in acquisition management to prevent contract binding with these contract condition because it has a big chance for the customer to terminate their insurance contract before its expired date. As the result, there are several strong points that could be the determinant of contract termination such as: 1) customer age whether too young or too old, 2) long insurance period (above 10 years), 3) big insurance amount, 4) big amount of premium charges, and 5) payment method.

  6. 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…

  7. 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

  8. 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

  9. 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.

  10. Evidence-based decision-making: an argumentative approach.

    PubMed

    Dickinson, H D

    1998-01-01

    A practical theory of argumentation is outlined and applied to a hypothetical clinical scenario to elucidate the use of research evidence in individual treatment decisions. The primary role of research evidence is to establish warrants as opposed to warrant using. Warrants are defined as the rules, principles or interpretive rationales used to justify an inference from observed data to conclusion, or clinical claim. Clarity on the appropriate use of research evidence in clinical decision-making can help resolve current debates over the nature and consequences of evidence-based medicine. The theory of argumentation has potential to inform both the design of decision support tools and to provide criteria for assessing decisional performance.

  11. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

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

  13. Distributed-sensor-system decision analysis using team strategies

    NASA Astrophysics Data System (ADS)

    Choe, Howard C.; Kazakos, Demetrios

    1992-11-01

    A distributed (or decentralized) multiple sensor system is considered under binary hypothesis environments. The system is deployed with a host sensor (HS) and multiple slave sensors (SSs). All sensors have their own independent decision makers which are capable of declaring local decisions based solely on their own observation of the environment. The communication between the HS and the SSs is conditional upon the HS's command. Each communication that takes place involves a communication cost which plays an important role in the approaches taken in this study. The conditional communication with the cost initiates the team strategy in making the final decisions at the HS. The objectives are not only to apply the team strategy method in the decision making process, but also to minimize the expected system cost (or the probability of error in making decisions) by optimizing thresholds in the HS> The analytical expression of the expected system cost (C) is numerically evaluated for Gaussian statistics over threshold locations in the HS to find an optimal threshold location for a given communication cost. The computer simulations of various sensor systems for Gaussian observations are also performed in order to understand the behavior of each system with respect to correct detections, false, alarms, and target misses.

  14. Distributed sensor system decision analysis using team strategies

    NASA Astrophysics Data System (ADS)

    Choe, Howard C.; Kazakos, Dimitri

    1991-07-01

    A distributed (or decentralized) multiple sensor system is considered under binary hypothesis environments. The system is deployed with a host sensor and multiple slave sensors. All sensors have their own independent decision makers (DM) which are capable of declaring local decisions based only on their own observation of the environment. The communication between the host sensor (HS) and the slave sensors (SS) is conditional upon the host sensor's command. Each communication that takes place involves a communication cost which plays an important role in approaches taken in this study. The conditional communication with cost initiates the team strategy in making the final decisions at the host sensor. The objectives are not only to apply the team strategy method in the decision making process, but also to minimize the expected system cost (or the probability or error in making decisions) by optimizing thresholds in the host sensor. The analytical expression of the expected system cost is numerically evaluated for Gaussian statistics over threshold locations in the host sensor to find an optimal threshold location for a given communication cost. The computer simulations of various sensor systems for Gaussian observations are also performed to understand the behavior of each system with respect to correct detections, false alarms, and target misses.

  15. 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

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

    PubMed

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

    2015-12-28

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    PubMed Central

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

    2014-01-01

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

  19. 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.

  20. 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.

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

    PubMed

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

    2014-06-23

    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.

  2. 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…

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

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

    SciTech Connect

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

    1980-11-01

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

  9. The Extended Multi-Attribute Decision Analysis Model (EMADAM).

    DTIC Science & Technology

    1983-08-01

    Transactions on Systems, Man, and Cybernetics, Vol. SMC-7, No. 5, May, 1977. . 7. Farquhar, P.H., "A Survey of Multiattribute Utility Theory and...Multi-Attribute Decision Analysis Model. The theoretical underpinnings of MADAM involve portions of multi-attribute utility theory . This interactive...Attribute Utility Theory (MAUT) model is discussed in Section 2. The actual computer program modifications developed and then implemented in code

  10. 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.

  11. Hierarchical Goal Analysis of Dynamic Decision Making in Microworld Experiments

    DTIC Science & Technology

    2009-03-01

    Hierarchical Goal Analysis of dynamic decision making in microworld experiments Vlad Zotov Renee Chow Defence R& D Canada Technical Memorandum DRDC...7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Defence R& D Canada - Toronto,1133 Sheppard Avenue West,PO Box 2000,Toronto, Ontario, Canada M3M...Defence R& D Canada – Toronto Technical Memorandum DRDC Toronto TM 2008-211 March 2009 Principal Author

  12. The ethical dilemma of population-based medical decision making.

    PubMed

    Kirsner, R S; Federman, D G

    1998-11-01

    Over the past several years, there has been a growing interest in population-based medicine. Some elements in healthcare have used population-based medicine as a technique to decrease healthcare expenditures. However, in their daily practice of medicine, physicians must grapple with the question of whether they incorporate population-based medicine when making decisions for an individual patient. They therefore may encounter an ethical dilemma. Physicians must remember that the physician-patient relationship is of paramount importance and that even well-conducted research may not be applicable to an individual patient.

  13. Clinical data warehousing for evidence based decision making.

    PubMed

    Narra, Lekha; Sahama, Tony; Stapleton, Peta

    2015-01-01

    Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.

  14. 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

  15. Proposal for Development of EBM-CDSS (Evidence-Based Clinical Decision Support System) to Aid Prognostication in Terminally Ill Patients

    DTIC Science & Technology

    2010-10-01

    regarding continuation of life-sustaining vs. palliative care . Finally, using regret DCA, the optimal decision for the specific patient is suggested...is to develop an Evidence-based Clinical Decision Support (CDSS-EBM) system and make it available at the point of care to improve prognostication of...Analysis and Regret theory to compare multiple decision strategies based on the decision maker’s personal attitudes towards each strategy

  16. A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Non-Small Cell Lung Cancer.

    PubMed

    Raju, G K; Gurumurthi, K; Domike, R; Kazandjian, D; Blumenthal, G; Pazdur, R; Woodcock, J

    2016-12-01

    Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analyses. There is much interest in quantifying regulatory approaches to benefit and risk. In this work the use of a quantitative benefit-risk analysis was applied to regulatory decision-making about new drugs to treat advanced non-small cell lung cancer (NSCLC). Benefits and risks associated with 20 US Food and Drug Administration (FDA) decisions associated with a set of candidate treatments submitted between 2003 and 2015 were analyzed. For benefit analysis, the median overall survival (OS) was used where available. When not available, OS was estimated based on overall response rate (ORR) or progression-free survival (PFS). Risks were analyzed based on magnitude (or severity) of harm and likelihood of occurrence. Additionally, a sensitivity analysis was explored to demonstrate analysis of systematic uncertainty. FDA approval decision outcomes considered were found to be consistent with the benefit-risk logic.

  17. 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.

  18. An Analysis of the Initial Decision Process of Organizing the Navy Medical Departments Executive Management Education Module Conversion to Network-Based Instruction

    DTIC Science & Technology

    1998-06-01

    1. Origins 9 2. Why Network-Based Instruction? ; 9 3. Educational Uses of the Internet 11 4. Learning Styles 13 5. Cost Effectiveness 15 H...for organizations to train and educate their personnel anytime and anywhere. [Ref. 6] 4. Learning Styles Distance learning may extend access...the conventional classroom will not benefit students. To create options that enhance learning, we must consider different learning styles in the

  19. A Dynamic Interval Decision-Making Method Based on GRA

    NASA Astrophysics Data System (ADS)

    Xue-jun, Tang; Jia, Chen

    According to the basic theory of grey relational analysis, this paper constructs a three-dimensional grey interval relation degree model for the three dimensions of time, index and scheme. On its basis, it sets up and solves a single-targeted optimization model, and obtains each scheme's affiliate degree for the positive/negative ideal scheme and also arranges the schemes in sequence. The result shows that the three-dimensional grey relation degree simplifies the traditional dynamic multi-attribute decision-making method and can better resolve the dynamic multi-attribute decision-making method of interval numbers. Finally, this paper proves the practicality and efficiency of the model through a case study.

  20. 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.

  1. 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...

  2. Decision-directed entropy-based adaptive filtering

    NASA Astrophysics Data System (ADS)

    Myler, Harley R.; Weeks, Arthur R.; Van Dyke-Lewis, Michelle

    1991-12-01

    A recurring problem in adaptive filtering is selection of control measures for parameter modification. A number of methods reported thus far have used localized order statistics to adaptively adjust filter parameters. The most effective techniques are based on edge detection as a decision mechanism to allow the preservation of edge information while noise is filtered. In general, decision-directed adaptive filters operate on a localized area within an image by using statistics of the area as a discrimination parameter. Typically, adaptive filters are based on pixel to pixel variations within a localized area that are due to either edges or additive noise. In homogeneous areas within the image where variances are due to additive noise, the filter should operate to reduce the noise. Using an edge detection technique, a decision directed adaptive filter can vary the filtering proportional to the amount of edge information detected. We show an approach using an entropy measure on edges to differentiate between variations in the image due to edge information as compared against noise. The method uses entropy calculated against the spatial contour variations of edges in the window.

  3. Basing perceptual decisions on the most informative sensory neurons.

    PubMed

    Scolari, Miranda; Serences, John T

    2010-10-01

    Single unit recording studies show that perceptual decisions are often based on the output of sensory neurons that are maximally responsive (or "tuned") to relevant stimulus features. However, when performing a difficult discrimination between two highly similar stimuli, perceptual decisions should instead be based on the activity of neurons tuned away from the relevant feature (off-channel neurons) as these neurons undergo a larger firing rate change and are thus more informative. To test this hypothesis, we measured feature-selective responses in human primary visual cortex (V1) using functional magnetic resonance imaging and show that the degree of off-channel activation predicts performance on a difficult visual discrimination task. Moreover, this predictive relationship between off-channel activation and perceptual acuity is not simply the result of extensive practice with a specific stimulus feature (as in studies of perceptual learning). Instead, relying on the output of the most informative sensory neurons may represent a general, and optimal, strategy for efficiently computing perceptual decisions.

  4. Probabilistic confidence for decisions based on uncertain reliability estimates

    NASA Astrophysics Data System (ADS)

    Reid, Stuart G.

    2013-05-01

    Reliability assessments are commonly carried out to provide a rational basis for risk-informed decisions concerning the design or maintenance of engineering systems and structures. However, calculated reliabilities and associated probabilities of failure often have significant uncertainties associated with the possible estimation errors relative to the 'true' failure probabilities. For uncertain probabilities of failure, a measure of 'probabilistic confidence' has been proposed to reflect the concern that uncertainty about the true probability of failure could result in a system or structure that is unsafe and could subsequently fail. The paper describes how the concept of probabilistic confidence can be applied to evaluate and appropriately limit the probabilities of failure attributable to particular uncertainties such as design errors that may critically affect the dependability of risk-acceptance decisions. This approach is illustrated with regard to the dependability of structural design processes based on prototype testing with uncertainties attributable to sampling variability.

  5. 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.

  6. 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…

  7. 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.

  8. [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.

  9. Doctors' attitudes to risk in difficult clinical decisions: application of decision analysis in hepatobiliary disease.

    PubMed

    Theodossi, A; Spiegelhalter, D J; McFarlane, I G; Williams, R

    1984-07-28

    Twelve doctors with special training in hepatology independently reviewed two to five cases each from a group of seven cases of complicated hepatobiliary problems. A doctor's willingness to take risks to improve his patients' health was quantified by a wagering technique based on the probability of achieving a successful intervention. These probabilities were then used to calculate "utilities," which represented the average opinion of the doctors about the relative worth of each of six predefined states of health. The results showed that, in the context of risky decisions for severely ill patients, a year of life was considered by the doctors to be worth 44% of a full recovery; being mobile for that year increased this value to 57%. Survival for up to five years with restricted mobility was considered to be worth 70% of a full recovery and the ability to work during that period increased this value to 85%. It is concluded that in clinical decision making the uncertainty and preferences implicit in a course of action can be quantified and thus made explicit.

  10. 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.

  11. Decision Analysis in the U.S. Army’s Capabilties Needs Analysis: Applications of Decision Analysis Methods to Capabilities Resource Allocation and Capabilities Development Decisions

    DTIC Science & Technology

    2015-10-01

    value functions and their scales; the use of a modified Delphi method to refine the analysis results; and the implementation of an open architecture web ...analysis results; and the implementation of an open architecture web -based tool to collect and analyze data and socialize results. Finally, the...greatly from an application of web -based assessment tools to collect data from a diverse and geographically dispersed community of practice, assess

  12. 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…

  13. 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.

  14. Engaging stakeholders for adaptive management using structured decision analysis

    USGS Publications Warehouse

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

    2009-01-01

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

  15. 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

  16. 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.

  17. Neural systems analysis of decision making during goal-directed navigation.

    PubMed

    Penner, Marsha R; Mizumori, Sheri J Y

    2012-01-01

    The ability to make adaptive decisions during goal-directed navigation is a fundamental and highly evolved behavior that requires continual coordination of perceptions, learning and memory processes, and the planning of behaviors. Here, a neurobiological account for such coordination is provided by integrating current literatures on spatial context analysis and decision-making. This integration includes discussions of our current understanding of the role of the hippocampal system in experience-dependent navigation, how hippocampal information comes to impact midbrain and striatal decision making systems, and finally the role of the striatum in the implementation of behaviors based on recent decisions. These discussions extend across cellular to neural systems levels of analysis. Not only are key findings described, but also fundamental organizing principles within and across neural systems, as well as between neural systems functions and behavior, are emphasized. It is suggested that studying decision making during goal-directed navigation is a powerful model for studying interactive brain systems and their mediation of complex behaviors.

  18. Cost-Benefit Analysis in Environmental Decision Making.

    ERIC Educational Resources Information Center

    Singer, S. Fred

    1977-01-01

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

  19. 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.

  20. 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

  1. Parameter uncertainty-based pattern identification and optimization for robust decision making on watershed load reduction

    NASA Astrophysics Data System (ADS)

    Jiang, Qingsong; Su, Han; Liu, Yong; Zou, Rui; Ye, Rui; Guo, Huaicheng

    2017-04-01

    Nutrients loading reduction in watershed is essential for lake restoration from eutrophication. The efficient and optimal decision-making on loading reduction is generally based on water quality modeling and the quantitative identification of nutrient sources at the watershed scale. The modeling process is influenced inevitably by inherent uncertainties, especially by uncertain parameters due to equifinality. Therefore, the emerging question is: if there is parameter uncertainty, how to ensure the robustness of the optimal decisions? Based on simulation-optimization models, an integrated approach of pattern identification and analysis of robustness was proposed in this study that focuses on the impact of parameter uncertainty in water quality modeling. Here the pattern represents the discernable regularity of solutions for load reduction under multiple parameter sets. Pattern identification is achieved by using a hybrid clustering analysis (i.e., Ward-Hierarchical and K-means), which was flexible and efficient in analyzing Lake Bali near the Yangtze River in China. The results demonstrated that urban domestic nutrient load is the most potential source that should be reduced, and there are two patterns for Total Nitrogen (TN) reduction and three patterns for Total Phosphorus (TP) reduction. The patterns indicated different total reduction of nutrient loads, which reflect diverse decision preferences. The robust solution was identified by the highest accomplishment with the water quality at monitoring stations that were improved uniformly with this solution. We conducted a process analysis of robust decision-making that was based on pattern identification and uncertainty, which provides effective support for decision-making with preference under uncertainty.

  2. 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

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

    PubMed

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

    2010-07-01

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

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

    NASA Technical Reports Server (NTRS)

    Evans, Gerald W.

    1995-01-01

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

  6. When the business of sharing treatment decisions is not the same as shared decision making: A discourse analysis of decision sharing in general practice.

    PubMed

    Robertson, Maggie; Moir, Jim; Skelton, John; Dowell, Jon; Cowan, Sue

    2011-01-01

    Although shared decision making (SDM) in general practice continues to be promoted as a highly desirable means of conducting consultations it is rarely observed in practice. The aim of this study is to identify the discursive features and conversational strategies particular to the negotiation and sharing of treatment decisions in order to understand why SDM is not yet embedded into routine practice. Consultations from Scottish general practices were examined using discourse analysis. Two themes were identified as key components for when the doctor and the patient were intent on sharing decisions: the generation of patient involvement using first-person pronouns, and successful and unsuccessful patient requesting practices. This article identifies a number of conversational activities found to be successful in supporting doctors' agendas and reducing their responsibility for decisions made. Doctor's use of 'partnership talk' was found to minimize resistance and worked to invite consensus rather than involvement. The information from this study provides new insight into the consultation process by identifying how treatment decisions are arrived at through highlighting the complexities involved. Notably, shared decision making does not happen with the ease implied by current models and appears to work to maintain a biomedical 'GP as expert' approach rather than one in which the patient is truly involved in partnership. We suggest that further research on the impact of conversational activities is likely to benefit our understanding of shared decision making and hence training in and the practice of SDM.

  7. 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.

  8. 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.

  9. Data-Based Decision-Making: Developing a Method for Capturing Teachers' Understanding of CBM Graphs

    ERIC Educational Resources Information Center

    Espin, Christine A.; Wayman, Miya Miura; Deno, Stanley L.; McMaster, Kristen L.; de Rooij, Mark

    2017-01-01

    In this special issue, we explore the decision-making aspect of "data-based decision-making". The articles in the issue address a wide range of research questions, designs, methods, and analyses, but all focus on data-based decision-making for students with learning difficulties. In this first article, we introduce the topic of…

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

    PubMed

    Convertino, Matteo; Valverde, L James

    2013-01-01

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

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

    PubMed Central

    Convertino, Matteo; Valverde, L. James

    2013-01-01

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

  12. Measurement Decision Theory.

    ERIC Educational Resources Information Center

    Rudner, Lawrence M.

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

  13. 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

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

    PubMed

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

    2015-01-01

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

  15. Vascular Access Choice in Incident Hemodialysis Patients: A Decision Analysis

    PubMed Central

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

    2015-01-01

    Hemodialysis vascular access recommendations promote arteriovenous (AV) fistulas first; however, it may not be the best approach for all hemodialysis patients, because likelihood of successful fistula placement, procedure-related and subsequent costs, and patient survival modify the optimal access choice. We performed a decision analysis evaluating AV fistula, AV graft, and central venous catheter (CVC) strategies for patients initiating hemodialysis with a CVC, a scenario occurring in over 70% of United States dialysis patients. A decision tree model was constructed to reflect progression from hemodialysis initiation. Patients were classified into one of three vascular access choices: maintain CVC, attempt fistula, or attempt graft. We explicitly modeled probabilities of primary and secondary patency for each access type, with success modified by age, sex, and diabetes. Access-specific mortality was incorporated using preexisting cohort data, including terms for age, sex, and diabetes. Costs were ascertained from the 2010 USRDS report and Medicare for procedure costs. An AV fistula attempt strategy was found to be superior to AV grafts and CVCs in regard to mortality and cost for the majority of patient characteristic combinations, especially younger men without diabetes. Women with diabetes and elderly men with diabetes had similar outcomes, regardless of access type. Overall, the advantages of an AV fistula attempt strategy lessened considerably among older patients, particularly women with diabetes, reflecting the effect of lower AV fistula success rates and lower life expectancy. These results suggest that vascular access-related outcomes may be optimized by considering individual patient characteristics. PMID:25063436

  16. 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.

  17. 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%.

  18. 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…

  19. 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.

  20. The NATO SOF Air Wing: A Basing Decision

    DTIC Science & Technology

    2012-12-01

    59 2. Medical and Dental Analysis...33. Alternative’s Current Base Medical and Dental Capacity ...............................60 Table 34. Pairwise Comparison of Alternatives on the...Medical and Dental Sub- criterion ............................................................................................................61 Table

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

    PubMed

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

    2014-01-01

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

  2. 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.

  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. Decision Analysis Tool to Compare Energy Pathways for Transportation

    SciTech Connect

    Bloyd, Cary N.

    2010-06-30

    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). Biomass is seen as an important domestic energy feedstock, and there are multiple pathways in which it can be linked to the transport sector. Contenders include the use of cellulosic ethanol from biomass to replace gasoline or the use of a biomass-fueled combined cycle electrical power generation facility in conjunction plug-in hybrid electric vehicles (PHEVs). This paper reviews a project that is developing a scenario decision analysis tool to assist policy makers, program managers, and others to obtain a better understanding of these uncertain possibilities and how they may interact over time.

  5. 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.

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

    ERIC Educational Resources Information Center

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

    2015-01-01

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

  7. 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.

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

    PubMed

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

    2010-10-15

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

  9. 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

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

    DOEpatents

    Hodgin, C Reed [Westminster, CO

    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.

  11. A Decision Analytic Approach to Exposure-Based Chemical ...

    EPA Pesticide Factsheets

    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. The National Exposure Research Laboratory′s (NERL′s) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in suppor

  12. 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

  13. 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

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

    PubMed

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

    2015-11-19

    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.

  15. 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.

  16. 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

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

    SciTech Connect

    Schlagheck, D.M.

    1985-01-01

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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Six Heads Are Better than One? School-Based Decision Making in Rural Kentucky.

    ERIC Educational Resources Information Center

    Kannapel, Patricia J.; And Others

    1995-01-01

    A 3-year examination of school-based decision-making (SBDM) councils in four rural Kentucky school districts revealed that, similar to findings in urban and suburban settings, SBDM councils in rural schools experienced difficulties in achieving true shared decision making. Decisions regarding hiring and budget management were most likely to lead…

  3. 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...

  4. 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.

  5. 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.

  6. Decision Maker based on Nanoscale Photo-excitation Transfer

    PubMed Central

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

    2013-01-01

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

  7. Towards a Judgement-Based Statistical Analysis

    ERIC Educational Resources Information Center

    Gorard, Stephen

    2006-01-01

    There is a misconception among social scientists that statistical analysis is somehow a technical, essentially objective, process of decision-making, whereas other forms of data analysis are judgement-based, subjective and far from technical. This paper focuses on the former part of the misconception, showing, rather, that statistical analysis…

  8. 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.

  9. 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

  10. 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.

  11. Medical communication and technology: a video-based process study of the use of decision aids in primary care consultations

    PubMed Central

    Kaner, Eileen; Heaven, Ben; Rapley, Tim; Murtagh, Madeleine; Graham, Ruth; Thomson, Richard; May, Carl

    2007-01-01

    Background Much of the research on decision-making in health care has focused on consultation outcomes. Less is known about the process by which clinicians and patients come to a treatment decision. This study aimed to quantitatively describe the behaviour shown by doctors and patients during primary care consultations when three types of decision aids were used to promote treatment decision-making in a randomised controlled trial. Methods A video-based study set in an efficacy trial which compared the use of paper-based guidelines (control) with two forms of computer-based decision aids (implicit and explicit versions of DARTS II). Treatment decision concerned warfarin anti-coagulation to reduce the risk of stroke in older patients with atrial fibrillation. Twenty nine consultations were video-recorded. A ten-minute 'slice' of the consultation was sampled for detailed content analysis using existing interaction analysis protocols for verbal behaviour and ethological techniques for non-verbal behaviour. Results Median consultation times (quartiles) differed significantly depending on the technology used. Paper-based guidelines took 21 (19–26) minutes to work through compared to 31 (16–41) minutes for the implicit tool; and 44 (39–55) minutes for the explicit tool. In the ten minutes immediately preceding the decision point, GPs dominated the conversation, accounting for 64% (58–66%) of all utterances and this trend was similar across all three arms of the trial. Information-giving was the most frequent activity for both GPs and patients, although GPs did this at twice the rate compared to patients and at higher rates in consultations involving computerised decision aids. GPs' language was highly technically focused and just 7% of their conversation was socio-emotional in content; this was half the socio-emotional content shown by patients (15%). However, frequent head nodding and a close mirroring in the direction of eye-gaze suggested that both parties

  12. 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.

  13. 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.

  14. 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.

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

    PubMed Central

    Wiesmann, Martin; Ishai, Alumit

    2008-01-01

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

  16. 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.

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

    PubMed

    Garfì, M; Tondelli, S; Bonoli, A

    2009-10-01

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

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

    PubMed Central

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

    2016-01-01

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

  19. 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.

  20. [Postmastectomy pain syndrome evidence based guidelines and decision trees].

    PubMed

    Labrèze, Laurent; Dixmérias-Iskandar, Florence; Monnin, Dominique; Bussières, Emmanuel; Delahaye, Evelyne; Bernard, Dominique; Lakdja, Fabrice

    2007-03-01

    A multidisciplinary expert group had reviewed all scientific data available of post mastectomy pain syndrome. Seventy six publications were retained and thirty evidence based diagnosis, treatment and follow-up recommendations are listed. Few of theses recommendations are classed level A. Datas analysis make possible to propose a strategy based on systematic association of drugs, kinesitherapy and psychological support. Evaluation and closer follow-up are necessary. Several decisional trees are proposed.

  1. Decision analysis and cost-effectiveness analysis for comparative effectiveness research--a primer.

    PubMed

    Sher, David J; Punglia, Rinaa S

    2014-01-01

    Although the analysis of real-world data is the foundation of comparative effectiveness analysis, not all clinical questions are easily approached with patient-derived information. Decision analysis is a set of modeling and analytic tools that simulate treatment and disease processes, including the incorporation of patient preferences, thus generating optimal treatment strategies for varying patient, disease, and treatment conditions. Although decision analysis is informed by evidence-derived outcomes, its ability to test treatment strategies under different conditions that are realistic but not necessarily reported in the literature makes it a useful and complementary technique to more standard data analysis. Similarly, cost-effectiveness analysis is a discipline in which the relative costs and benefits of treatment alternatives are rigorously compared. With the well-recognized increase in highly technical, costly radiation therapy technologies, the cost-effectiveness of these different treatments would come under progressively more scrutiny. In this review, we discuss the theoretical and practical aspects of decision analysis and cost-effectiveness analysis, providing examples that highlight their methodology and utility.

  2. Decision analysis in clinical cardiology: When is coronary angiography required in aortic stenosis

    SciTech Connect

    Georgeson, S.; Meyer, K.B.; Pauker, S.G. )

    1990-03-15

    Decision analysis offers a reproducible, explicit approach to complex clinical decisions. It consists of developing a model, typically a decision tree, that separates choices from chances and that specifies and assigns relative values to outcomes. Sensitivity analysis allows exploration of alternative assumptions. Cost-effectiveness analysis shows the relation between dollars spent and improved health outcomes achieved. In a tutorial format, this approach is applied to the decision whether to perform coronary angiography in a patient who requires aortic valve replacement for critical aortic stenosis.

  3. 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

  4. 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. ...

  5. 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....

  6. 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…

  7. 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.

  8. 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.

  9. Clinical Decision Support Systems for the Practice of Evidence-based Medicine

    PubMed Central

    Sim, Ida; Gorman, Paul; Greenes, Robert A.; Haynes, R. Brian; Kaplan, Bonnie; Lehmann, Harold; Tang, Paul C.

    2001-01-01

    Background: The use of clinical decision support systems to facilitate the practice of evidence-based medicine promises to substantially improve health care quality. Objective: To describe, on the basis of the proceedings of the Evidence and Decision Support track at the 2000 AMIA Spring Symposium, the research and policy challenges for capturing research and practice-based evidence in machine-interpretable repositories, and to present recommendations for accelerating the development and adoption of clinical decision support systems for evidence-based medicine. Results: The recommendations fall into five broad areas—capture literature-based and practice-based evidence in machine-interpretable knowledge bases; develop maintainable technical and methodological foundations for computer-based decision support; evaluate the clinical effects and costs of clinical decision support systems and the ways clinical decision support systems affect and are affected by professional and organizational practices; identify and disseminate best practices for work flow–sensitive implementations of clinical decision support systems; and establish public policies that provide incentives for implementing clinical decision support systems to improve health care quality. Conclusions: Although the promise of clinical decision support system–facilitated evidence-based medicine is strong, substantial work remains to be done to realize the potential benefits. PMID:11687560

  10. 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

  11. 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.

  12. Creating a GIS-Based Decision-Support System

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

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

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

    PubMed

    Custer, Brian; Janssen, Mart P

    2015-08-01

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

  14. 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.

  15. 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…

  16. 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...

  17. 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.

  18. 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

  19. Age Differences in Road Crossing Decisions Based on Gap Judgements

    PubMed Central

    Oxley, J. A.; Fildes, B. N.; Ihsen, E.; Charlton, J. L.; Day, R. H.

    1999-01-01

    Older pedestrians are over-involved in serious injury and fatal crashes compared to younger adults. This may be due, in part, to diminished perceptual, cognitive and motor skills which act to reduce the older person’s ability to sense danger and take measures to avoid hazards. Two experiments are described in this paper which examine age differences in gap selection decisions in a simulated road crossing environment. The results demonstrated age differences in the decision-making process, particularly a difficulty in estimating appropriate time-of-arrival of oncoming traffic along with an inability to allow for slower decision times and walking speeds. A two-phase model of road crossing decisions is discussed within a limited information processing approach and it is suggested that older adults experience problems in quickly and instantaneously calculating distance and velocity information in order to select safe margins in which to cross the road.

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

    EPA Science Inventory

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

  1. 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.

  2. A risk-based decision support framework for selection of appropriate safety measure system for underground coal mines.

    PubMed

    Samantra, Chitrasen; Datta, Saurav; Mahapatra, Siba Sankar

    2017-03-01

    In the context of underground coal mining industry, the increased economic issues regarding implementation of additional safety measure systems, along with growing public awareness to ensure high level of workers safety, have put great pressure on the managers towards finding the best solution to ensure safe as well as economically viable alternative selection. Risk-based decision support system plays an important role in finding such solutions amongst candidate alternatives with respect to multiple decision criteria. Therefore, in this paper, a unified risk-based decision-making methodology has been proposed for selecting an appropriate safety measure system in relation to an underground coal mining industry with respect to multiple risk criteria such as financial risk, operating risk, and maintenance risk. The proposed methodology uses interval-valued fuzzy set theory for modelling vagueness and subjectivity in the estimates of fuzzy risk ratings for making appropriate decision. The methodology is based on the aggregative fuzzy risk analysis and multi-criteria decision making. The selection decisions are made within the context of understanding the total integrated risk that is likely to incur while adapting the particular safety system alternative. Effectiveness of the proposed methodology has been validated through a real-time case study. The result in the context of final priority ranking is seemed fairly consistent.

  3. A Psychometric Method for Determining Optimum, Tactical Paths in Combat Decision Making and Analysis

    DTIC Science & Technology

    1989-09-01

    small unit based on the operator’s cognitive decision processes , as well as the physical effects of terrain and environment on mobility. The approach...Thurstone and W.S. Torgerson. The -cognitive -time % alue based on the user’s decision process is then added to the physical- traversal times for each...could be applied to almost any tactical decision process in the development of expert systems and-models. 20 Distribution Availability of Abstract 21

  4. How Reasoning, Judgment, and Decision Making are Colored by Gist-based Intuition: A Fuzzy-Trace Theory Approach

    PubMed Central

    Corbin, Jonathan C.; Reyna, Valerie F.; Weldon, Rebecca B.; Brainerd, Charles J.

    2015-01-01

    Fuzzy-trace theory distinguishes verbatim (literal, exact) from gist (meaningful) representations, predicting that reliance on gist increases with experience and expertise. Thus, many judgment-and-decision-making biases increase with development, such that cognition is colored by context in ways that violate logical coherence and probability theories. Nevertheless, this increase in gist-based intuition is adaptive: Gist is stable, less sensitive to interference, and easier to manipulate. Moreover, gist captures the functionally significant essence of information, supporting healthier and more robust decision processes. We describe how fuzzy-trace theory accounts for judgment-and-decision making phenomena, predicting the paradoxical arc of these processes with the development of experience and expertise. We present data linking gist memory processes to gist processing in decision making and provide illustrations of gist reliance in medicine, public health, and intelligence analysis. PMID:26664820

  5. How Reasoning, Judgment, and Decision Making are Colored by Gist-based Intuition: A Fuzzy-Trace Theory Approach.

    PubMed

    Corbin, Jonathan C; Reyna, Valerie F; Weldon, Rebecca B; Brainerd, Charles J

    2015-12-01

    Fuzzy-trace theory distinguishes verbatim (literal, exact) from gist (meaningful) representations, predicting that reliance on gist increases with experience and expertise. Thus, many judgment-and-decision-making biases increase with development, such that cognition is colored by context in ways that violate logical coherence and probability theories. Nevertheless, this increase in gist-based intuition is adaptive: Gist is stable, less sensitive to interference, and easier to manipulate. Moreover, gist captures the functionally significant essence of information, supporting healthier and more robust decision processes. We describe how fuzzy-trace theory accounts for judgment-and-decision making phenomena, predicting the paradoxical arc of these processes with the development of experience and expertise. We present data linking gist memory processes to gist processing in decision making and provide illustrations of gist reliance in medicine, public health, and intelligence analysis.

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

    NASA Astrophysics Data System (ADS)

    Rodríguez, Rosa M.; Martínez, Luis

    2013-01-01

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

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

    PubMed

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

    2015-01-01

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

  8. Brain networks of perceptual decision-making: an fMRI ALE meta-analysis

    PubMed Central

    Keuken, Max C.; Müller-Axt, Christa; Langner, Robert; Eickhoff, Simon B.; Forstmann, Birte U.; Neumann, Jane

    2014-01-01

    In the recent perceptual decision-making literature, a fronto-parietal network is typically reported to primarily represent the neural substrate of human perceptual decision-making. However, the view that only cortical areas are involved in perceptual decision-making has been challenged by several neurocomputational models which all argue that the basal ganglia play an essential role in perceptual decisions. To consolidate these different views, we conducted an Activation Likelihood Estimation (ALE) meta-analysis on the existing neuroimaging literature. The results argue in favor of the involvement of a frontal-parietal network in general perceptual decision-making that is possibly complemented by the basal ganglia, and modulated in substantial parts by task difficulty. In contrast, expectation of reward, an important aspect of many decision-making processes, shows almost no overlap with the general perceptual decision-making network. PMID:24994979

  9. Analysis of Decisions Made Using the Analytic Hierarchy Process

    DTIC Science & Technology

    2013-09-01

    AHP, and how this information can be utilized, permitting U.S. and allied forces to execute efficient and effective military operations. A case study...military decision-maker who uses the AHP, and how this information can be utilized, permitting U.S. and allied forces to execute efficient and effective ...this information can be utilized, permitting U.S. and allied forces to execute efficient and effective military operations. A case study of a decision

  10. CorRECTreatment: A Web-based Decision Support Tool for Rectal Cancer Treatment that Uses the Analytic Hierarchy Process and Decision Tree

    PubMed Central

    Karakülah, G.; Dicle, O.; Sökmen, S.; Çelikoğlu, C.C.

    2015-01-01

    Summary Background The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians’ decision making. Objective The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. Methods The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. Results In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. Conclusions The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options

  11. 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…

  12. 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…

  13. An image feature-based approach to automatically find images for application to clinical decision support.

    PubMed

    Stanley, R Joe; De, Soumya; Demner-Fushman, Dina; Antani, Sameer; Thoma, George R

    2011-07-01

    The illustrations in biomedical publications often provide useful information in aiding clinicians' decisions when full text searching is performed to find evidence in support of a clinical decision. In this research, image analysis and classification techniques are explored to automatically extract information for differentiating specific modalities to characterize illustrations in biomedical publications, which may assist in the evidence finding process. Global, histogram-based, and texture image illustration features were compared to basis function luminance histogram correlation features for modality-based discrimination over a set of 742 manually annotated images by modality (radiological, photo, etc.) selected from the 2004-2005 issues of the British Journal of Oral and Maxillofacial Surgery. Using a mean shifting supervised clustering technique, automatic modality-based discrimination results as high as 95.57% were obtained using the basis function features. These results compared favorably to other feature categories examined. The experimental results show that image-based features, particularly correlation-based features, can provide useful modality discrimination information.

  14. Decision tree and PCA-based fault diagnosis of rotating machinery

    NASA Astrophysics Data System (ADS)

    Sun, Weixiang; Chen, Jin; Li, Jiaqing

    2007-04-01

    After analysing the flaws of conventional fault diagnosis methods, data mining technology is introduced to fault diagnosis field, and a new method based on C4.5 decision tree and principal component analysis (PCA) is proposed. In this method, PCA is used to reduce features after data collection, preprocessing and feature extraction. Then, C4.5 is trained by using the samples to generate a decision tree model with diagnosis knowledge. At last the tree model is used to make diagnosis analysis. To validate the method proposed, six kinds of running states (normal or without any defect, unbalance, rotor radial rub, oil whirl, shaft crack and a simultaneous state of unbalance and radial rub), are simulated on Bently Rotor Kit RK4 to test C4.5 and PCA-based method and back-propagation neural network (BPNN). The result shows that C4.5 and PCA-based diagnosis method has higher accuracy and needs less training time than BPNN.

  15. 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.

  16. Priority setting of health interventions: the need for multi-criteria decision analysis

    PubMed Central

    Baltussen, Rob; Niessen, Louis

    2006-01-01

    Priority setting of health interventions is often ad-hoc and resources are not used to an optimal extent. Underlying problem is that multiple criteria play a role and decisions are complex. Interventions may be chosen to maximize general population health, to reduce health inequalities of disadvantaged or vulnerable groups, ad/or to respond to life-threatening situations, all with respect to practical and budgetary constraints. This is the type of problem that policy makers are typically bad at solving rationally, unaided. They tend to use heuristic or intuitive approaches to simplify complexity, and in the process, important information is ignored. Next, policy makers may select interventions for only political motives. This indicates the need for rational and transparent approaches to priority setting. Over the past decades, a number of approaches have been developed, including evidence-based medicine, burden of disease analyses, cost-effectiveness analyses, and equity analyses. However, these approaches concentrate on single criteria only, whereas in reality, policy makers need to make choices taking into account multiple criteria simultaneously. Moreover, they do not cover all criteria that are relevant to policy makers. Therefore, the development of a multi-criteria approach to priority setting is necessary, and this has indeed recently been identified as one of the most important issues in health system research. In other scientific disciplines, multi-criteria decision analysis is well developed, has gained widespread acceptance and is routinely used. This paper presents the main principles of multi-criteria decision analysis. There are only a very few applications to guide resource allocation decisions in health. We call for a shift away from present priority setting tools in health – that tend to focus on single criteria – towards transparent and systematic approaches that take into account all relevant criteria simultaneously. PMID:16923181

  17. Finding shared decisions in stakeholder networks: An agent-based approach

    NASA Astrophysics Data System (ADS)

    Le Pira, Michela; Inturri, Giuseppe; Ignaccolo, Matteo; Pluchino, Alessandro; Rapisarda, Andrea

    2017-01-01

    We address the problem of a participatory decision-making process where a shared priority list of alternatives has to be obtained while avoiding inconsistent decisions. An agent-based model (ABM) is proposed to mimic this process in different social networks of stakeholders who interact according to an opinion dynamics model. Simulations' results show the efficacy of interaction in finding a transitive and, above all, shared decision. These findings are in agreement with real participation experiences regarding transport planning decisions and can give useful suggestions on how to plan an effective participation process for sustainable policy-making based on opinion consensus.

  18. Aeromedical decision-making: an evidence-based risk management paradigm.

    PubMed

    Watson, Dougal B

    2005-01-01

    Aeromedical decisions take many forms and are made by different groups and individuals. Because of the ubiquity of aviation in the world today, it is important that aeromedical decisions are of the highest quality that can be reasonably achieved. A paradigm of evidence-based aeromedical risk management is reported on here. It combines the concept of evidence-based medicine with structured risk management methodologies to produce a methodology capable of delivering the highest quality of aeromedical decisions. While neither of these concepts is new, practitioners do need to ensure that they have the skills and knowledge to maximize the quality of their aeromedical decisions.

  19. The case-based decision support system in the field of IT-consulting

    NASA Astrophysics Data System (ADS)

    Avdeenko, T. V.; Makarova, E. S.

    2017-01-01

    In the present paper, we propose an approach to facilitation of decision-making in the field of IT-consulting. The approach is based on knowledge representation in the form of cases containing past history about decision making. We also proposed an ontology to store the cases as instances of classes. Classification of cases in the ontology is executed by means of fuzzy inference. The method of classification is based on the original algorithm of transformation of cases (precedents) sample to the set of linguistic rules allowing one to make relevant decisions. Research of the method has shown good accuracy of the decisions classification according to test data.

  20. Analysis of Community Practice Clinical Decision-Making Skills in Pharmacy Students.

    ERIC Educational Resources Information Center

    Greer, Marianne L.; Kirk, Kenneth W.

    1988-01-01

    A computerized, simulation-based instrument, consisting of four community practice clinical scenarios, collected information-searching data and the students' decisions. The appropriateness of the decisions, assessed by three clinical judges, and the focus of information search, based on the computer-collected process data, were the dependent…

  1. 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.

  2. 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.

  3. 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

  4. Estradiol modulates effort-based decision making in female rats.

    PubMed

    Uban, Kristina A; Rummel, Julia; Floresco, Stan B; Galea, Liisa A M

    2012-01-01

    Disorders of the dopamine system, such as schizophrenia or stimulant addiction, are associated with impairments in different forms of cost/benefit decision making. The neural circuitry (ie amygdala, prefrontal cortex, nucleus accumbens) underlying these functions receives dopamine input, which is thought to have a central role in mediating cost/benefit decisions. Estradiol modulates dopamine activity, and estrogen receptors (ERs) are found within this neurocircuitry, suggesting that decision making may be influenced by estradiol. The present study examined the contribution of estradiol and selective ERα and β agonists on cost/benefit decision making in adult female Long-Evans rats. An effort-discounting task was utilized, where rats could either emit a single response on a low-reward lever to receive two pellets, or make 2, 5, 10, or 20 responses on a high-reward lever to obtain four pellets. Ovariectomy increased the choice on the high-reward lever, whereas replacement with high (10 μg), but not low (0.3 μg), levels of estradiol benzoate reduced the choice on the high-reward lever. Interestingly, both an ERα agonist (propyl-pyrazole triol (PPT)) and an ERβ agonist (diarylpropionitrile (DPN)) increased choice on the high-reward lever when administered independently, but when these two agonists were combined, a decrease in choice for the high-reward lever was observed. The effects of estradiol, PPT, and DPN were more pronounced 24 h post-administration, suggesting that these effects may be genomic in nature. Together, these results demonstrate that estradiol modulates cost/benefit decision making in females, whereby concomitant activation of ERα and β receptors shifts the decision criteria and reduces preference for larger, yet more costly rewards.

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

    PubMed Central

    Kariman, Nourossadat; Amerian, Maliheh; Jannati, Padideh; Salmani, Fatemeh

    2016-01-01

    Background: Factors that influence men’s childbearing intentions have been relatively unexplored in the literature. Objective: This study aimed to determine the influencing factors about the first childbearing timing decisions of men. Materials and Methods: In this cross-sectional study, 300 men who were referred to private and governmental healthcare centers in Shahrood, Iran were randomly recruited from April to September 2014. Data were collected using a demographic questionnaire, the Quality of Life Questionnaire; ENRICH Marital Satisfaction Questionnaire, Synder’s Hope Scale, and the Multidimensional Scale of Perceived Social Support. Results: After removing the statistically insignificant paths, men’s age at marriage had the highest direct effect (β=0.86) on their first childbearing decision. Marital satisfaction (β=-0.09), social support (β=0.06), economic status (β=0.06), and quality of life (β=-0.08) were other effective factors on men’s first childbearing decisions. Moreover, marital satisfaction and social support had significant indirect effects on men’s childbearing decisions (β=-0.04 and -0.01, respectively). Conclusion: Many factors, including personal factors (age at marriage and quality of life), family factors (marital satisfaction), and social factors (social support), can affect men’s decision to have a child. Policymakers are hence required to develop strategies to promote the socioeconomic and family conditions of the couples and to encourage them to have as many children as they desire at an appropriate time. PMID:27738661

  6. EEG-fMRI based information theoretic characterization of the human perceptual decision system.

    PubMed

    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.

  7. 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

  8. Analysis of energy-efficiency investment decisions by small and medium-sized manufacturers

    SciTech Connect

    Woodruff, M.G.; Roop, J.M.; Seely, H.E.; Muller, M.R.; Jones, T.W.; Dowd, J.

    1996-05-01

    This report highlights the results of a comprehensive analysis of investment decisions regarding energy-efficiency measures at small and medium-sized manufacturing plants. The analysis is based on the experiences of companies participating in the DOE Industrial Assessment Center (IAC) program. The IAC program is a network of university-based centers that provides energy and waste assessments to small and medium-sized manufacturing plants. The purposes of this report are to do the following: (1) Examine what the data collected reveal about patterns of implementation of recommended energy- efficiency measures, (2) Evaluate how various factors, such as the type of industry, the characteristics of the manufacturing plants, or the cost of the measures, appear to effect implementation rates, (3) Examine reasons why recommended energy-saving measures are accepted or rejected.

  9. Developing Evidence-Based Care Standards and a Decision-Making Support System for Pain Management.

    PubMed

    Feng, Rung-Chuang; Chang, Polun

    2016-01-01

    Pain is a crucial sign and symptom in hospitalised patients. This paper describes how a medical centre created a knowledge-based, computerised pain management decision-making process to support nurses in personalising preventive interventions based on patient requirements.

  10. 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.

  11. A meta-analysis of confidence and judgment accuracy in clinical decision making.

    PubMed

    Miller, Deborah J; Spengler, Elliot S; Spengler, Paul M

    2015-10-01

    The overconfidence bias occurs when clinicians overestimate the accuracy of their clinical judgments. This bias is thought to be robust leading to an almost universal recommendation by clinical judgment scholars for clinicians to temper their confidence in clinical decision making. An extension of the Meta-Analysis of Clinical Judgment (Spengler et al., 2009) project, the authors synthesized over 40 years of research from 36 studies, from 1970 to 2011, in which the confidence ratings of 1,485 clinicians were assessed in relation to the accuracy of their judgments about mental health (e.g., diagnostic decision making, violence risk assessment, prediction of treatment failure) or psychological issues (e.g., personality assessment). Using a random effects model a small but statistically significant effect (r = .15; CI = .06, .24) was found showing that confidence is better calibrated with accuracy than previously assumed. Approximately 50% of the total variance between studies was due to heterogeneity and not to chance. Mixed effects and meta-regression moderator analyses revealed that confidence is calibrated with accuracy least when there are repeated judgments, and more when there are higher base rate problems, when decisions are made with written materials, and for earlier published studies. Sensitivity analyses indicate a bias toward publishing smaller sample studies with smaller or negative confidence-accuracy effects. Implications for clinical judgment research and for counseling psychology training and practice are discussed.

  12. 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.

  13. An analysis of the buy-vs-lease decision.

    PubMed

    Berlin, Jonathan W; Lexa, Frank J

    2006-02-01

    This article presents a financial model to analyze the buy-vs-lease decision. The model is constructed from the perspective of a lessee with an operating lease and uses the concept of net present value, which calculates the current value of predicted cash flows in the future. Predicted cash flows of an operating lease compared with buying are presented in the model, as is the after-tax borrowing rate, the appropriate discount rate used in a model of this type. The article also discusses nonfinancial factors that may influence the buy-vs-lease decision, including the need for flexibility in working capital and the anticipated technological obsolescence of equipment.

  14. Analysis of commercial health newsletters by worksite decision makers.

    PubMed

    Miller, R E; Golaszewski, T J

    1992-01-01

    Health newsletters are an important component of worksite wellness, and human resource program managers believe these publications motivate employees and promote health services. Research has identified employee segments more likely to read health newsletters as well as how these publications may contribute to better medical self-care decision making. Even so, virtually no data exist on the factors contributing to newsletter selection and purchase except proprietary, anecdotal information collected by commercial vendors. Therefore, the purpose of this research was to investigate how newsletter features are rated by decision makers and determine factors predicting intent to purchase a health newsletter.

  15. 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…

  16. Decision Support for Patient Preference-based Care Planning

    PubMed Central

    Ruland, Cornelia M.

    1999-01-01

    Objective: While preference elicitation techniques have been effective in helping patients make decisions consistent with their preferences, little is known about whether information about patient preferences affects clinicians in clinical decision making and improves patient outcomes. The purpose of this study was to evaluate a decision support system for eliciting elderly patients' preferences for self-care capability and providing this information to nurses in clinical practice—specifically, its effect on nurses' care priorities and the patient outcomes of preference achievement and patient satisfaction. Design: Three-group quasi-experimental design with one experimental and two control groups (N = 151). In the experimental group computer-processed information about individual patient's preferences was placed in patients' charts to be used for care planning. Results: Information about patient preferences changed nurses' care priorities to be more consistent with patient preferences and improved patients' preference achievement and physical functioning. Further, higher consistency between patient preferences and nurses' care priorities was associated with higher preference achievement, and higher preference achievement with greater patient satisfaction. Conclusion: This study demonstrated that decision support for eliciting patient preferences and including them in nursing care planning is an effective and feasible strategy for improving nursing care and patient outcomes. PMID:10428003

  17. [Evidence-based decision-making: when it is worthwhile].

    PubMed

    Neumann, Ignacio; Rada, Gabriel

    2014-06-11

    Every day health professionals have to make dozens of decisions regarding patient care and management. It is not easy to integrate scientific evidence in this process. The primary ability we need in order to achieve successful results is learning how to recognize the circumstances in which evidence arising from results of scientific trials may help.

  18. 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…

  19. Classic EEG motor potentials track the emergence of value-based decisions.

    PubMed

    Gluth, Sebastian; Rieskamp, Jörg; Büchel, Christian

    2013-10-01

    Making a value-based decision is a cognitively complex phenomenon and divisible into several sub-processes, such as the perception, evaluation, and final selection of choice options. Although previous research has attempted to dissociate these processes in the brain, there is emerging evidence that late action selection mechanisms are influenced continuously throughout the entire decision act. We used electroencephalography (EEG) and an established sequential decision making paradigm to investigate the extent to which the readiness potential (RP) and the lateralized readiness potential (LRP), two classic preparatory EEG motor components, reflect the ongoing evaluation process in value-based choices. During the task, human participants sequentially sampled probabilistic information to buy or reject offers of unknown value (using both hands) and were allowed to respond at any time. The pressure to respond was manipulated by charging low or high costs for collecting information. We modeled how and when decisions were made and found that participants adaptively lowered their threshold for required evidence with information costs and elapsed time. These shifts were accompanied by an increased RP-like signal during the decision process. The RP was further influenced by the amount of accumulated evidence. In addition, an LRP could be measured from the start of the decision process, well in advance and independent of the final decision. Our results are consistent with a continuous involvement of the brain's motor system in emerging value-based decisions and advocate using classic EEG motor potentials for studying neurocognitive theories of decision making.

  20. Enhancing the Systems Decision Process with Flexibility Analysis for Optimal Unmanned Aircraft System Selection

    DTIC Science & Technology

    2008-06-01

    42 Figure 2-2: The TDR -1 UAS...basis for much of the work in decision analysis past and present. The SDP has four major phases : (1) Problem Definition; (2) Solution Design; (3...Decision Making; and (4) Solution Implementation. Each phase decomposes into three steps. For example, the problem definition phase consists of stakeholder

  1. 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.

  2. A Cercla-Based Decision Support System for Environmental Remediation Strategy Selection.

    DTIC Science & Technology

    1997-03-01

    A CERCLA -BASED DECISION SUPPORT SYSTEM FOR ENVIRONMENTAL REMEDIATION STRATEGY SELECTION 2Lt Brian J. Grelk AFIT/GORI97M- 10 DEPARTMENT OF THE AIR...FORCE AIR UNIVERSITY AIR FORCE INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio vimC ’QEjA BP3f AFIT/GOR/ENS/97M- 10 A CERCLA -BASED DECISION...unlimited MC QULM TnpEOM1 AFIT/GOR/ENS/97M- 10 A CERCLA -BASED DECISION SUPPORT SYSTEM FOR ENVIRONMENTAL REMEDIATION STRATEGY SELECTION THESIS Presented to

  3. 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.

  4. Strategic rehabilitation planning of piped water networks using multi-criteria decision analysis.

    PubMed

    Scholten, Lisa; Scheidegger, Andreas; Reichert, Peter; Maurer, Max; Mauer, Max; Lienert, Judit

    2014-02-01

    To overcome the difficulties of strategic asset management of water distribution networks, a pipe failure and a rehabilitation model are combined to predict the long-term performance of rehabilitation strategies. Bayesian parameter estimation is performed to calibrate the failure and replacement model based on a prior distribution inferred from three large water utilities in Switzerland. Multi-criteria decision analysis (MCDA) and scenario planning build the framework for evaluating 18 strategic rehabilitation alternatives under future uncertainty. Outcomes for three fundamental objectives (low costs, high reliability, and high intergenerational equity) are assessed. Exploitation of stochastic dominance concepts helps to identify twelve non-dominated alternatives and local sensitivity analysis of stakeholder preferences is used to rank them under four scenarios. Strategies with annual replacement of 1.5-2% of the network perform reasonably well under all scenarios. In contrast, the commonly used reactive replacement is not recommendable unless cost is the only relevant objective. Exemplified for a small Swiss water utility, this approach can readily be adapted to support strategic asset management for any utility size and based on objectives and preferences that matter to the respective decision makers.

  5. 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…

  6. 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…

  7. 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,…

  8. 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…

  9. 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.

  10. 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.

  11. Decision Analysis Methods Used to Make Appropriate Investments in Human Exploration Capabilities and Technologies

    NASA Technical Reports Server (NTRS)

    Williams-Byrd, Julie; Arney, Dale C.; Hay, Jason; Reeves, John D.; Craig, Douglas

    2016-01-01

    NASA is transforming human spaceflight. The Agency is shifting from an exploration-based program with human activities in low Earth orbit (LEO) and targeted robotic missions in deep space to a more sustainable and integrated pioneering approach. Through pioneering, NASA seeks to address national goals to develop the capacity for people to work, learn, operate, live, and thrive safely beyond Earth for extended periods of time. However, pioneering space involves daunting technical challenges of transportation, maintaining health, and enabling crew productivity for long durations in remote, hostile, and alien environments. Prudent investments in capability and technology developments, based on mission need, are critical for enabling a campaign of human exploration missions. There are a wide variety of capabilities and technologies that could enable these missions, so it is a major challenge for NASA's Human Exploration and Operations Mission Directorate (HEOMD) to make knowledgeable portfolio decisions. It is critical for this pioneering initiative that these investment decisions are informed with a prioritization process that is robust and defensible. It is NASA's role to invest in targeted technologies and capabilities that would enable exploration missions even though specific requirements have not been identified. To inform these investments decisions, NASA's HEOMD has supported a variety of analysis activities that prioritize capabilities and technologies. These activities are often based on input from subject matter experts within the NASA community who understand the technical challenges of enabling human exploration missions. This paper will review a variety of processes and methods that NASA has used to prioritize and rank capabilities and technologies applicable to human space exploration. The paper will show the similarities in the various processes and showcase instances were customer specified priorities force modifications to the process. Specifically

  12. 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.

  13. 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

  14. 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

  15. A new web-based framework development for fuzzy multi-criteria group decision-making.

    PubMed

    Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

    2016-01-01

    Fuzzy multi-criteria group decision making (FMCGDM) process is usually used when a group of decision-makers faces imprecise data or linguistic variables to solve the problems. However, this process contains many methods that require many time-consuming calculations depending on the number of criteria, alternatives and decision-makers in order to reach the optimal solution. In this study, a web-based FMCGDM framework that offers decision-makers a fast and reliable response service is proposed. The proposed framework includes commonly used tools for multi-criteria decision-making problems such as fuzzy Delphi, fuzzy AHP and fuzzy TOPSIS methods. The integration of these methods enables taking advantages of the strengths and complements each method's weakness. Finally, a case study of location selection for landfill waste in Morocco is performed to demonstrate how this framework can facilitate decision-making process. The results demonstrate that the proposed framework can successfully accomplish the goal of this study.

  16. 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.

  17. 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

  18. 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.

  19. 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...

  20. Overview of Results from 1994 & 1995 School-Based Decision Making Surveys.

    ERIC Educational Resources Information Center

    Lindle, Jane Clark; Gale, Bruce S.; Curry-White, Brenda

    The 1994 and 1995 School-Based Decision Making (SBDM) Surveys were conducted in the fall of each of those years for the Study of Education Policy. This report compares the 1994 and 1995 responses to three questions: (1) What do people think of the effectiveness of SBDM? (2) Who is involved in the SBDM decisions? and (3) What are councils doing?…

  1. Distance-Based and Distributed Learning: A Decision Tool for Education Leaders.

    ERIC Educational Resources Information Center

    McGraw, Tammy M.; Ross, John D.

    This decision tool presents a progression of data collection and decision-making strategies that can increase the effectiveness of distance-based or distributed learning instruction. A narrative and flow chart cover the following steps: (1) basic assumptions, including purpose of instruction, market scan, and financial resources; (2) needs…

  2. Integration or Fragmentation: The Impact of Site-Based Decision-Making.

    ERIC Educational Resources Information Center

    Avila, Linda, Ed.

    Early efforts at site-based decision making in Texas created many diverse questions about how to proceed. In some school districts, the change to a new decision-making balance centered around the district office. In others, strong campus control was established and effective self-governance plans were created. This monograph presents the…

  3. 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…

  4. Using Multicriteria Decision Analysis to Support Research Priority Setting in Biomedical Translational Research Projects

    PubMed Central

    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. 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.

  6. FWFA Optimization based Decision Support System for Road Traffic Engineering

    NASA Astrophysics Data System (ADS)

    Utama, D. N.; Zaki, F. A.; Munjeri, I. J.; Putri, N. U.

    2017-01-01

    Several ways and efforts have been already conducted to formally solve the road traffic congestion. However, the objective strategy type of road traffic engineering could not be proven truly. Try and error is one inefficient way in road traffic engineering to degrade the level of congestion. The combination between fuzzy-logic and water flow algorithm methods (called FWFA) was used as a main method to construct the decision support system (DSS) for selecting the objective strategy in road traffic engineering. The proposed DSS can suggest the most optimal strategy decision in road traffic engineering. Here, a main traffic road of Juanda in area Ciputat, Tangerang Selatan, province Banten, Indonesia; was selected as a research object in this study. The constructed DSS for road traffic engineering was structurally delivered in this paper.

  7. The multi-objective decision making methods based on MULTIMOORA and MOOSRA for the laptop selection problem

    NASA Astrophysics Data System (ADS)

    Aytaç Adalı, Esra; Tuş Işık, Ayşegül

    2016-10-01

    A decision making process requires the values of conflicting objectives for alternatives and the selection of the best alternative according to the needs of decision makers. Multi-objective optimization methods may provide solution for this selection. In this paper it is aimed to present the laptop selection problem based on MOORA plus full multiplicative form (MULTIMOORA) and multi-objective optimization on the basis of simple ratio analysis (MOOSRA) which are relatively new multi-objective optimization methods. The novelty of this paper is solving this problem with the MULTIMOORA and MOOSRA methods for the first time.

  8. Rule acquisition in formal decision contexts based on formal, object-oriented and property-oriented concept lattices.

    PubMed

    Ren, Yue; Li, Jinhai; 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.

  9. 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.

  10. 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.

  11. 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

  12. 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…

  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. 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.

  15. 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.

  16. Recurrent neural networks in computer-based clinical decision support for laryngopathies: an experimental study.

    PubMed

    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.

  17. Model-based knowledge acquisition in environmental decision support system for wastewater integrated management.

    PubMed

    Prat, Pau; Benedetti, Lorenzo; Corominas, Lluís; Comas, Joaquim; Poch, Manel

    2012-01-01

    The main goal of the Water Framework Directive is to achieve good chemical and ecological status of water bodies by 2015. The implementation of integrated river basin management, including sewer systems, wastewater treatment plants and receiving water bodies, is essential to accomplishing this objective. Integrated management is complex and therefore the implementation of control systems and the development of decision support systems are needed to facilitate the work of urban wastewater system (UWS) managers. Within this context, the objective of this paper is to apply integrated modelling of an UWS to simulate and analyse the behaviour of the 'Congost' UWS in Spain, and to optimize its performance against different types of perturbations. This analysis results in optimal operating set-points for each perturbation, improves river water quality, minimizes combined sewer overflows and optimizes flow lamination from storm water tanks. This is achieved by running Monte Carlo simulations and applying global sensitivity analysis. The set-points will become part of the knowledge base composed of a set of IF-THEN rules of the environmental decision support system being developed for this case study.

  18. The Interplay of Hippocampus and Ventromedial Prefrontal Cortex in Memory-Based Decision Making

    PubMed Central

    Weilbächer, Regina A.; Gluth, Sebastian

    2016-01-01

    Episodic memory and value-based decision making are two central and intensively studied research domains in cognitive neuroscience, but we are just beginning to understand how they interact to enable memory-based decisions. The two brain regions that have been associated with episodic memory and value-based decision making are the hippocampus and the ventromedial prefrontal cortex, respectively. In this review article, we first give an overview of these brain–behavior associations and then focus on the mechanisms of potential interactions between the hippocampus and ventromedial prefrontal cortex that have been proposed and tested in recent neuroimaging studies. Based on those possible interactions, we discuss several directions for future research on the neural and cognitive foundations of memory-based decision making. PMID:28036071

  19. 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.

  20. 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.

  1. 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…

  2. Hesitant Fuzzy Thermodynamic Method for Emergency Decision Making Based on Prospect Theory.

    PubMed

    Ren, Peijia; Xu, Zeshui; Hao, Zhinan

    2016-12-30

    Due to the timeliness of emergency response and much unknown information in emergency situations, this paper proposes a method to deal with the emergency decision making, which can comprehensively reflect the emergency decision making process. By utilizing the hesitant fuzzy elements to represent the fuzziness of the objects and the hesitant thought of the experts, this paper introduces the negative exponential function into the prospect theory so as to portray the psychological behaviors of the experts, which transforms the hesitant fuzzy decision matrix into the hesitant fuzzy prospect decision matrix (HFPDM) according to the expectation-levels. Then, this paper applies the energy and the entropy in thermodynamics to take the quantity and the quality of the decision values into account, and defines the thermodynamic decision making parameters based on the HFPDM. Accordingly, a whole procedure for emergency decision making is conducted. What is more, some experiments are designed to demonstrate and improve the validation of the emergency decision making procedure. Last but not the least, this paper makes a case study about the emergency decision making in the firing and exploding at Port Group in Tianjin Binhai New Area, which manifests the effectiveness and practicability of the proposed method.

  3. 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

  4. Learning to maximize reward rate: a model based on semi-Markov decision processes.

    PubMed

    Khodadadi, Arash; Fakhari, Pegah; Busemeyer, Jerome R

    2014-01-01

    WHEN ANIMALS HAVE TO MAKE A NUMBER OF DECISIONS DURING A LIMITED TIME INTERVAL, THEY FACE A FUNDAMENTAL PROBLEM: how much time they should spend on each decision in order to achieve the maximum possible total outcome. Deliberating more on one decision usually leads to more outcome but less time will remain for other decisions. In the framework of sequential sampling models, the question is how animals learn to set their decision threshold such that the total expected outcome achieved during a limited time is maximized. The aim of this paper is to provide a theoretical framework for answering this question. To this end, we consider an experimental design in which each trial can come from one of the several possible "conditions." A condition specifies the difficulty of the trial, the reward, the penalty and so on. We show that to maximize the expected reward during a limited time, the subject should set a separate value of decision threshold for each condition. We propose a model of learning the optimal value of decision thresholds based on the theory of semi-Markov decision processes (SMDP). In our model, the experimental environment is modeled as an SMDP with each "condition" being a "state" and the value of decision thresholds being the "actions" taken in those states. The problem of finding the optimal decision thresholds then is cast as the stochastic optimal control problem of taking actions in each state in the corresponding SMDP such that the average reward rate is maximized. Our model utilizes a biologically plausible learning algorithm to solve this problem. The simulation results show that at the beginning of learning the model choses high values of decision threshold which lead to sub-optimal performance. With experience, however, the model learns to lower the value of decision thresholds till finally it finds the optimal values.

  5. Recognition of Protozoa and Metazoa using image analysis tools, discriminant analysis, neural networks and decision trees.

    PubMed

    Ginoris, Y P; Amaral, A L; Nicolau, A; Coelho, M A Z; Ferreira, E C

    2007-07-09

    Protozoa and metazoa are considered good indicators of the treatment quality in activated sludge systems due to the fact that these organisms are fairly sensitive to physical, chemical and operational processes. Therefore, it is possible to establish close relationships between the predominance of certain species or groups of species and several operational parameters of the plant, such as the biotic indices, namely the Sludge Biotic Index (SBI). This procedure requires the identification, classification and enumeration of the different species, which is usually achieved manually implying both time and expertise availability. Digital image analysis combined with multivariate statistical techniques has proved to be a useful tool to classify and quantify organisms in an automatic and not subjective way. This work presents a semi-automatic image analysis procedure for protozoa and metazoa recognition developed in Matlab language. The obtained morphological descriptors were analyzed using discriminant analysis, neural network and decision trees multivariable statistical techniques to identify and classify each protozoan or metazoan. The obtained procedure was quite adequate for distinguishing between the non-sessile protozoa classes and also for the metazoa classes, with high values for the overall species recognition with the exception of sessile protozoa. In terms of the wastewater conditions assessment the obtained results were found to be suitable for the prediction of these conditions. Finally, the discriminant analysis and neural networks results were found to be quite similar whereas the decision trees technique was less appropriate.

  6. Partially observable Markov decision processes for risk-based screening

    NASA Astrophysics Data System (ADS)

    Mrozack, Alex; Liao, Xuejun; Skatter, Sondre; Carin, Lawrence

    2016-05-01

    A long-term goal for checked baggage screening in airports has been to include passenger information, or at least a predetermined passenger risk level, in the screening process. One method for including that information could be treating the checked baggage screening process as a system-of-systems. This would allow for an optimized policy builder, such as one trained using the methodology of partially observable Markov decision processes (POMDP), to navigate the different sensors available for screening. In this paper we describe the necessary steps to tailor a POMDP for baggage screening, as well as results of simulations for specific screening scenarios.

  7. Combination of material flow analysis and substance flow analysis: a powerful approach for decision support in waste management.

    PubMed

    Stanisavljevic, Nemanja; Brunner, Paul H

    2014-08-01

    The novelty of this paper is the demonstration of the effectiveness of combining material flow analysis (MFA) with substance flow analysis (SFA) for decision making in waste management. Both MFA and SFA are based on the mass balance principle. While MFA alone has been applied often for analysing material flows quantitatively and hence to determine the capacities of waste treatment processes, SFA is more demanding but instrumental in evaluating the performance of a waste management system regarding the goals "resource conservation" and "environmental protection". SFA focuses on the transformations of wastes during waste treatment: valuable as well as hazardous substances and their transformations are followed through the entire waste management system. A substance-based approach is required because the economic and environmental properties of the products of waste management - recycling goods, residues and emissions - are primarily determined by the content of specific precious or harmful substances. To support the case that MFA and SFA should be combined, a case study of waste management scenarios is presented. For three scenarios, total material flows are quantified by MFA, and the mass flows of six indicator substances (C, N, Cl, Cd, Pb, Hg) are determined by SFA. The combined results are compared to the status quo in view of fulfilling the goals of waste management. They clearly point out specific differences between the chosen scenarios, demonstrating potentials for improvement and the value of the combination of MFA/SFA for decision making in waste management.

  8. Measuring preferences for cost-utility analysis: how choice of method may influence decision-making.

    PubMed

    McDonough, Christine M; Tosteson, Anna N A

    2007-01-01

    Preferences for health are required when the economic value of healthcare interventions are assessed within the framework of cost-utility analysis. The objective of this paper was to review alternative methods for preference measurement and to evaluate the extent to which the method may affect healthcare decision-making. Two broad approaches to preference measurement that provide societal health state values were considered: (i) direct measurement; and (ii) preference-based health state classification systems. Among studies that compared alternative preference-based systems, the EQ-5D tended to provide larger change scores and more favourable cost-effectiveness ratios than the Health Utilities Index (HUI)-2 and -3, while the SF-6D provided smaller change scores and less favourable ratios than the other systems. However, these patterns may not hold for all applications. Empirical evidence comparing systems and decision-making impact suggests that preferences will have the greatest impact on economic analyses when chronic conditions or long-term sequelae are involved. At present, there is no clearly superior method, and further study of cost-effectiveness ratios from alternative systems is needed to evaluate system performance. Although there is some evidence that incremental cost-effectiveness ratio (ICER) thresholds (e.g. $US50,000 per QALY gained) are used in decision-making, they are not strictly applied. Nonetheless, as ICERs rise, the probability of acceptance of a new therapy is likely to decrease, making the differences in QALYs obtained using alternative methods potentially meaningful. It is imperative that those conducting cost-utility analyses characterise the impact that uncertainty in health state values has on the economic value of the interventions studied. Consistent reporting of such analyses would provide further insight into the policy implications of preference measurement.

  9. LANL Institutional Decision Support By Process Modeling and Analysis Group (AET-2)

    SciTech Connect

    Booth, Steven Richard

    2016-04-04

    AET-2 has expertise in process modeling, economics, business case analysis, risk assessment, Lean/Six Sigma tools, and decision analysis to provide timely decision support to LANS leading to continuous improvement. This capability is critical during the current tight budgetary environment as LANS pushes to identify potential areas of cost savings and efficiencies. An important arena is business systems and operations, where processes can impact most or all laboratory employees. Lab-wide efforts are needed to identify and eliminate inefficiencies to accomplish Director McMillan’s charge of “doing more with less.” LANS faces many critical and potentially expensive choices that require sound decision support to ensure success. AET-2 is available to provide this analysis support to expedite the decisions at hand.

  10. 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

  11. 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.

  12. 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.

  13. Neural oscillations and synchronization differentially support evidence accumulation in perceptual and value-based decision making.

    PubMed

    Polanía, Rafael; Krajbich, Ian; Grueschow, Marcus; Ruff, Christian C

    2014-05-07

    Organisms make two types of decisions on a regular basis. Perceptual decisions are determined by objective states of the world (e.g., melons are bigger than apples), whereas value-based decisions are determined by subjective preferences (e.g., I prefer apples to melons). Theoretical accounts suggest that both types of choice involve neural computations accumulating evidence for the choice alternatives; however, little is known about the overlap or differences in the processes underlying perceptual versus value-based decisions. We analyzed EEG recordings during a paradigm where perceptual- and value-based choices were based on identical stimuli. For both types of choice, evidence accumulation was evident in parietal gamma-frequency oscillations, whereas a similar frontal signal was unique for value-based decisions. Fronto-parietal synchronization of these signals predicted value-based choice accuracy. These findings uncover how decisions emerge from topographic- and frequency-specific oscillations that accumulate distinct aspects of evidence, with large-scale synchronization as a mechanism integrating these spatially distributed signals.

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. 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

  19. Big-Data Based Decision-Support Systems to Improve Clinicians’ Cognition

    PubMed Central

    Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

    2016-01-01

    Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians’ cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems. PMID:27990498

  20. Big-Data Based Decision-Support Systems to Improve Clinicians' Cognition.

    PubMed

    Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

    2016-01-01

    Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems.

  1. Orbitofrontal Cortex Is Required for Optimal Waiting Based on Decision Confidence

    PubMed Central

    Lak, Armin; Costa, Gil M.; Romberg, Erin; Koulakov, Alexei A.; Mainen, Zachary F.; Kepecs, Adam

    2015-01-01

    SUMMARY Confidence judgments are a central example of metacognition—knowledge about one’s own cognitive processes. According to this metacognitive view, confidence reports are generated by a second-order monitoring process based on the quality of internal representations about beliefs. Although neural correlates of decision confidence have been recently identified in humans and other animals, it is not well understood whether there are brain areas specifically important for confidence monitoring. To address this issue, we designed a postdecision temporal wagering task in which rats expressed choice confidence by the amount of time they were willing to wait for reward. We found that orbitofrontal cortex inactivation disrupts waiting-based confidence reports without affecting decision accuracy. Furthermore, we show that a normative model can quantitatively account for waiting times based on the computation of decision confidence. These results establish an anatomical locus for a metacognitive report, confidence judgment, distinct from the processes required for perceptual decisions. PMID:25242219

  2. Cortical and Hippocampal Correlates of Deliberation during Model-Based Decisions for Rewards in Humans

    PubMed Central

    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

  3. 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…

  4. 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…

  5. Cost-effectiveness of different interferon beta products for relapsing-remitting and secondary progressive multiple sclerosis: Decision analysis based on long-term clinical data and switchable treatments

    PubMed Central

    2013-01-01

    Background Multiple sclerosis (MS) is a highly debilitating immune mediated disorder and the second most common cause of neurological disability in young and middle-aged adults. Iran is amongst high MS prevalence countries (50/100,000). Economic burden of MS is a topic of important deliberation in economic evaluations study. Therefore determining of cost-effectiveness interferon beta (INF β) and their copied biopharmaceuticals (CBPs) and biosimilars products is significant issue for assessment of affordability in Lower-middle-income countries (LMICs). Methods A literature-based Markov model was developed to assess the cost-effectiveness of three INF βs products compared with placebo for managing a hypothetical cohort of patients diagnosed with relapsing remitting MS (RRMS) in Iran from a societal perspective. Health states were based on the Kurtzke Expanded Disability Status Scale (EDSS). Disease progression transition probabilities for symptom management and INF β therapies were obtained from natural history studies and multicenter randomized controlled trials and their long term follow up for RRMS and secondary progressive MS (SPMS). A cross sectional study has been developed to evaluate cost and utility. Transitions among health states occurred in 2-years cycles for fifteen cycles and switching to other therapies was allowed. Calculations of costs and utilities were established by attachment of decision trees to the overall model. The incremental cost effectiveness ratio (ICER) of cost/quality adjusted life year (QALY) for all available INF β products (brands, biosimilars and CBPs) were considered. Both costs and utilities were discounted. Sensitivity analyses were done to assess robustness of model. Results ICER for Avonex, Rebif and Betaferon was 18712, 11832, 15768 US Dollars ($) respectively when utility attained from literature review has been considered. ICER for available CBPs and biosimilars in Iran was $847, $6964 and $11913. Conclusions The Markov

  6. 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.

  7. 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.)

  8. Decision-making in rectal and colorectal cancer: systematic review and qualitative analysis of surgeons' preferences.

    PubMed

    Broc, Guillaume; Gana, Kamel; Denost, Quentin; Quintard, Bruno

    2017-04-01

    Surgeons are experiencing difficulties implementing recommendations not only owing to incomplete, confusing or conflicting information but also to the increasing involvement of patients in decisions relating to their health. This study sought to establish which common factors including heuristic factors guide surgeons' decision-making in colon and rectal cancers. We conducted a systematic literature review of surgeons' decision-making factors related to colon and rectal cancer treatment. Eleven of 349 identified publications were eligible for data analyses. Using the IRaMuTeQ (Interface of R for the Multidimensional Analyses of Texts and Questionnaire), we carried out a qualitative analysis of the significant factors collected in the studies reviewed. Several validation procedures were applied to control the robustness of the findings. Five categories of factors (i.e. patient, surgeon, treatment, tumor and organizational cues) were found to influence surgeons' decision-making. Specifically, all decision criteria including biomedical (e.g. tumor information) and heuristic (e.g. surgeons' dispositional factors) criteria converged towards the factor 'age of patient' in the similarity analysis. In the light of the results, we propose an explanatory model showing the impact of heuristic criteria on medical issues (i.e. diagnosis, prognosis, treatment features, etc.) and thus on decision-making. Finally, the psychosocial complexity involved in decision-making is discussed and a medico-psycho-social grid for use in multidisciplinary meetings is proposed.

  9. Usability testing of ANSWER: a web-based methotrexate decision aid for patients with rheumatoid arthritis

    PubMed Central

    2013-01-01

    Background Decision aids are evidence-based tools designed to inform people of the potential benefit and harm of treatment options, clarify their preferences and provide a shared decision-making structure for discussion at a clinic visit. For patients with rheumatoid arthritis (RA) who are considering methotrexate, we have developed a web-based patient decision aid called the ANSWER (Animated, Self-serve, Web-based Research Tool). This study aimed to: 1) assess the usability of the ANSWER prototype; 2) identify strengths and limitations of the ANSWER from the patient’s perspective. Methods The ANSWER prototype consisted of: 1) six animated patient stories and narrated information on the evidence of methotrexate for RA; 2) interactive questionnaires to clarify patients’ treatment preferences. Eligible participants for the usability test were patients with RA who had been prescribed methotrexate. They were asked to verbalize their thoughts (i.e., think aloud) while using the ANSWER, and to complete the System Usability Scale (SUS) to assess overall usability (range = 0-100; higher = more user friendly). Participants were audiotaped and observed, and field notes were taken. The testing continued until no new modifiable issues were found. We used descriptive statistics to summarize participant characteristics and the SUS scores. Content analysis was used to identified usability issues and navigation problems. Results 15 patients participated in the usability testing. The majority were aged 50 or over and were university/college graduates (n = 8, 53.4%). On average they took 56 minutes (SD = 34.8) to complete the tool. The mean SUS score was 81.2 (SD = 13.5). Content analysis of audiotapes and field notes revealed four categories of modifiable usability issues: 1) information delivery (i.e., clarity of the information and presentation style); 2) navigation control (i.e., difficulties in recognizing and using the navigation control buttons); 3

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

    PubMed

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

    2015-01-01

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

  11. 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. 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.

  13. 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

  14. 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

  15. Evaluation of a rule base for decision making in general practice.

    PubMed Central

    Essex, B; Healy, M

    1994-01-01

    BACKGROUND. Decision making in general practice relies heavily on judgmental expertise. It should be possible to codify this expertise into rules and principles. AIM. A study was undertaken to evaluate the effectiveness, of rules from a rule base designed to improve students' and trainees' management decisions relating to patients seen in general practice. METHOD. The rule base was developed after studying decisions about and management of thousands of patients seen in one general practice over an eight year period. Vignettes were presented to 93 fourth year medical students and 179 general practitioner trainees. They recorded their perception and management of each case before and after being presented with a selection of relevant rules. Participants also commented on their level of agreement with each of the rules provided with the vignettes. A panel of five independent assessors then rated as good, acceptable or poor, the participants' perception and management of each case before and after seeing the rules. RESULTS. Exposure to a few selected rules of thumb improved the problem perception and management decisions of both undergraduates and trainees. The degree of improvement was not related to previous experience or to the stated level of agreement with the proposed rules. The assessors identified difficulties students and trainees experienced in changing their perceptions and management decisions when the rules suggested options they had not considered. CONCLUSION. The rules developed to improve decision making skills in general practice are effective when used with vignettes. The next phase is to transform the rule base into an expert system to train students and doctors to acquire decision making skills. It could also be used to provide decision support when confronted with difficult management decisions in general practice. PMID:8204334

  16. 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

  17. The challenge of predicting problematic chemicals using a decision analysis tool: Triclosan as a case study.

    PubMed

    Perez, Angela L; Gauthier, Alison M; Ferracini, Tyler; Cowan, Dallas M; Kingsbury, Tony; Panko, Julie

    2017-01-01

    Manufacturers lack a reliable means for determining whether a chemical will be targeted for deselection from their supply chain. In this analysis, 3 methods for determining whether a specific chemical (triclosan) would meet the criteria necessary for being targeted for deselection are presented. The methods included a list-based approach, use of a commercially available chemical assessment software tool run in 2 modes, and a public interest evaluation. Our results indicated that triclosan was included on only 6 of the lists reviewed, none of which were particularly influential in chemical selection decisions. The results from the chemical assessment tool evaluations indicated that human and ecological toxicity for triclosan is low and received scores indicating that the chemical would be considered of low concern. However, triclosan's peak public interest tracked several years in advance of increased regulatory scrutiny of this chemical suggesting that public pressure may have been influential in deselection decisions. Key data gaps and toxicity endpoints not yet regulated such as endocrine disruption potential or phototoxicity, but that are important to estimate the trajectory for deselection of a chemical, are discussed. Integr Environ Assess Manag 2017;13:198-207. © 2016 SETAC.

  18. 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.

  19. Electrophysiological correlates reflect the integration of model-based and model-free decision information.

    PubMed

    Eppinger, Ben; Walter, Maik; Li, Shu-Chen

    2017-01-03

    In this study, we investigated the interplay of habitual (model-free) and goal-directed (model-based) decision processes by using a two-stage Markov decision task in combination with event-related potentials (ERPs) and computational modeling. To manipulate the demands on model-based decision making, we applied two experimental conditions with different probabilities of transitioning from the first to the second stage of the task. As we expected, when the stage transitions were more predictable, participants showed greater model-based (planning) behavior. Consistent with this result, we found that stimulus-evoked parietal (P300) activity at the second stage of the task increased with the predictability of the state transitions. However, the parietal activity also reflected model-free information about the expected values of the stimuli, indicating that at this stage of the task both types of information are integrated to guide decision making. Outcome-related ERP components only reflected reward-related processes: Specifically, a medial prefrontal ERP component (the feedback-related negativity) was sensitive to negative outcomes, whereas a component that is elicited by reward (the feedback-related positivity) increased as a function of positive prediction errors. Taken together, our data indicate that stimulus-locked parietal activity reflects the integration of model-based and model-free information during decision making, whereas feedback-related medial prefrontal signals primarily reflect reward-related decision processes.

  20. A Web-based environmental decision support system (WEDSS) for environmental planning and watershed management

    NASA Astrophysics Data System (ADS)

    Sugumaran, Ramanathan; Meyer, James C.; Davis, Jim

    2004-10-01

    Local governments often struggle to balance competing demands for residential, commercial and industrial development with imperatives to minimize environmental degradation. In order to effectively manage this development process on a sustainable basis, local planners and government agencies are increasingly seeking better tools and techniques. In this paper, we describe the development of a Web-Based Environmental Decision Support System (WEDSS), which helps to prioritize local watersheds in terms of environmental sensitivity using multiple criteria identified by planners and local government staff in the city of Columbia, and Boone County, Missouri. The development of the system involved three steps, the first was to establish the relevant environmental criteria and develop data layers for each criterion, then a spatial model was developed for analysis, and lastly a Web-based interface with analysis tools was developed using client-server technology. The WEDSS is an example of a way to run spatial models over the Web and represents a significant increase in capability over other WWW-based GIS applications that focus on database querying and map display. The WEDSS seeks to aid in the development of agreement regarding specific local areas deserving increased protection and the public policies to be pursued in minimizing the environmental impact of future development. The tool is also intended to assist ongoing public information and education efforts concerning watershed management and water quality issues for the City of Columbia, Missouri and adjacent developing areas within Boone County, Missouri.

  1. 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.

  2. Make better decisions.

    PubMed

    Davenport, Thomas H

    2009-11-01

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

  3. Risk patterns and correlated brain activities. Multidimensional statistical analysis of FMRI data in economic decision making study.

    PubMed

    van Bömmel, Alena; Song, Song; Majer, Piotr; Mohr, Peter N C; Heekeren, Hauke R; Härdle, Wolfgang K

    2014-07-01

    Decision making usually involves uncertainty and risk. Understanding which parts of the human brain are activated during decisions under risk and which neural processes underly (risky) investment decisions are important goals in neuroeconomics. Here, we analyze functional magnetic resonance imaging (fMRI) data on 17 subjects who were exposed to an investment decision task from Mohr, Biele, Krugel, Li, and Heekeren (in NeuroImage 49, 2556-2563, 2010b). We obtain a time series of three-dimensional images of the blood-oxygen-level dependent (BOLD) fMRI signals. We apply a panel version of the dynamic semiparametric factor model (DSFM) presented in Park, Mammen, Wolfgang, and Borak (in Journal of the American Statistical Association 104(485), 284-298, 2009) and identify task-related activations in space and dynamics in time. With the panel DSFM (PDSFM) we can capture the dynamic behavior of the specific brain regions common for all subjects and represent the high-dimensional time-series data in easily interpretable low-dimensional dynamic factors without large loss of variability. Further, we classify the risk attitudes of all subjects based on the estimated low-dimensional time series. Our classification analysis successfully confirms the estimated risk attitudes derived directly from subjects' decision behavior.

  4. Spatial multi-criteria decision analysis to predict suitability for African swine fever endemicity in Africa

    PubMed Central

    2014-01-01

    Background African swine fever (ASF) is endemic in several countries of Africa and may pose a risk to all pig producing areas on the continent. Official ASF reporting is often rare and there remains limited awareness of the continent-wide distribution of the disease. In the absence of accurate ASF outbreak data and few quantitative studies on the epidemiology of the disease in Africa, we used spatial multi-criteria decision analysis (MCDA) to derive predictions of the continental distribution of suitability for ASF persistence in domestic pig populations as part of sylvatic or domestic transmission cycles. In order to incorporate the uncertainty in the relative importance of different criteria in defining suitability, we modelled decisions within the MCDA framework using a stochastic approach. The predictive performance of suitability estimates was assessed via a partial ROC analysis using ASF outbreak data reported to the OIE since 2005. Results Outputs from the spatial MCDA indicate that large areas of sub-Saharan Africa may be suitable for ASF persistence as part of either domestic or sylvatic transmission cycles. Areas with high suitability for pig to pig transmission (‘domestic cycles’) were estimated to occur throughout sub-Saharan Africa, whilst areas with high suitability for introduction from wildlife reservoirs (‘sylvatic cycles’) were found predominantly in East, Central and Southern Africa. Based on average AUC ratios from the partial ROC analysis, the predictive ability of suitability estimates for domestic cycles alone was considerably higher than suitability estimates for sylvatic cycles alone, or domestic and sylvatic cycles in combination. Conclusions This study provides the first standardised estimates of the distribution of suitability for ASF transmission associated with domestic and sylvatic cycles in Africa. We provide further evidence for the utility of knowledge-driven risk mapping in animal health, particularly in data

  5. Fuzzy Cognitive Map scenario-based medical decision support systems for education.

    PubMed

    Georgopoulos, Voula C; Chouliara, Spyridoula; Stylios, Chrysostomos D

    2014-01-01

    Soft Computing (SC) techniques are based on exploiting human knowledge and experience and they are extremely useful to model any complex decision making procedure. Thus, they have a key role in the development of Medical Decision Support Systems (MDSS). The soft computing methodology of Fuzzy Cognitive Maps has successfully been used to represent human reasoning and to infer conclusions and decisions in a human-like way and thus, FCM-MDSSs have been developed. Such systems are able to assist in critical decision-making, support diagnosis procedures and consult medical professionals. Here a new methodology is introduced to expand the utilization of FCM-MDSS for learning and educational purposes using a scenario-based learning (SBL) approach. This is particularly important in medical education since it allows future medical professionals to safely explore extensive "what-if" scenarios in case studies and prepare for dealing with critical adverse events.

  6. Fuzzy rule-based models for decision support in ecosystem management.

    PubMed

    Adriaenssens, Veronique; De Baets, Bernard; Goethals, Peter L M; De Pauw, Niels

    2004-02-05

    To facilitate decision support in the ecosystem management, ecological expertise and site-specific data need to be integrated. Fuzzy logic can deal with highly variable, linguistic, vague and uncertain data or knowledge and, therefore, has the ability to allow for a logical, reliable and transparent information stream from data collection down to data usage in decision-making. Several environmental applications already implicate the use of fuzzy logic. Most of these applications have been set up by trial and error and are mainly limited to the domain of environmental assessment. In this article, applications of fuzzy logic for decision support in ecosystem management are reviewed and assessed, with an emphasis on rule-based models. In particular, the identification, optimisation, validation, the interpretability and uncertainty aspects of fuzzy rule-based models for decision support in ecosystem management are discussed.

  7. A decision model for cost effective design of biomass based green energy supply chains.

    PubMed

    Yılmaz Balaman, Şebnem; Selim, Hasan

    2015-09-01

    The core driver of this study is to deal with the design of anaerobic digestion based biomass to energy supply chains in a cost effective manner. In this concern, a decision model is developed. The model is based on fuzzy multi objective decision making in order to simultaneously optimize multiple economic objectives and tackle the inherent uncertainties in the parameters and decision makers' aspiration levels for the goals. The viability of the decision model is explored with computational experiments on a real-world biomass to energy supply chain and further analyses are performed to observe the effects of different conditions. To this aim, scenario analyses are conducted to investigate the effects of energy crop utilization and operational costs on supply chain structure and performance measures.

  8. Eielson Air Force Base operable unit 2 and other areas record of decision

    SciTech Connect

    Lewis, R.E.; Smith, R.M.

    1994-10-01

    This decision document presents the selected remedial actions and no action decisions for Operable Unit 2 (OU2) at Eielson Air Force Base (AFB), Alaska, chosen in accordance with state and federal regulations. This document also presents the decision that no further action is required for 21 other source areas at Eielson AFB. This decision is based on the administrative record file for this site. OU2 addresses sites contaminated by leaks and spills of fuels. Soils contaminated with petroleum products occur at or near the source of contamination. Contaminated subsurface soil and groundwater occur in plumes on the top of a shallow groundwater table that fluctuates seasonally. These sites pose a risk to human health and the environment because of ingestion, inhalation, and dermal contact with contaminated groundwater. The purpose of this response is to prevent current or future exposure to the contaminated groundwater, to reduce further contaminant migration into the groundwater, and to remediate groundwater.

  9. Architecture-Level Dependability Analysis of a Medical Decision Support System

    SciTech Connect

    Pullum, Laura L; Symons, Christopher T; Patton, Robert M; Beckerman, Barbara G

    2010-01-01

    Recent advances in techniques such as image analysis, text analysis and machine learning have shown great potential to assist physicians in detecting and diagnosing health issues in patients. In this paper, we describe the approach and findings of an architecture-level dependability analysis for a mammography decision support system that incorporates these techniques. The goal of the research described in this paper is to provide an initial understanding of the dependability issues, particularly the potential failure modes and severity, in order to identify areas of potential high risk. The results will guide design decisions and provide the basis of a dependability and performance evaluation program.

  10. Prevalence of clinically significant decisional conflict: an analysis of five studies on decision-making in primary care

    PubMed Central

    Thompson-Leduc, Philippe; Turcotte, Stéphane; Labrecque, Michel; Légaré, France

    2016-01-01

    Objectives Unresolved clinically significant decisional conflict (CSDC) in patients following a consultation with health professionals is often the result of inadequate patient involvement in decision-making and may result in poor outcomes. We sought to identify the prevalence of CSDC in studies on decision-making in primary care and to explore its risk factors. Setting We performed a secondary analysis of existing data sets from studies conducted in Primary Care Practice-Based Research Networks in Québec and Ontario, Canada. Participants Eligible studies included a patient-reported measure on the 16-item Decisional Conflict Scale (DCS) following a decision made with a healthcare professional with no study design restriction. Primary and secondary outcome measures CSDC was defined as a score ≥25/100 on the DCS. The prevalence of CSDC was stratified by sex; and patient-level logistic regression analysis was performed to explore its potential risk factors. Data sets of studies were analysed individually and qualitatively compared. Results 5 projects conducted between 2003 and 2010 were included. They covered a range of decisions: prenatal genetic screening, antibiotics for acute respiratory infections and miscellaneous. Altogether, the 5 projects gathered data from encounters with a total of 1338 primary care patients (69% female; range of age 15–83). The prevalence of CSDC in patients varied across studies and ranged from 10.3% (95% CI 7.2% to 13.4%) to 31.1% (95% CI 26.6% to 35.6%). Across the 5 studies, risk factors of CSDC included being male, living alone and being 45 or older. Conclusions Prevalence of CSDC in patients who had enrolled in studies conducted in primary care contexts was substantial and appeared to vary according to the type of decision as well as to patient characteristics such as sex, living arrangement and age. Patients presenting risk factors of CSDC should be offered tools to increase their involvement in decision-making. PMID:27354076

  11. Negative decision outcomes are more common among people with lower decision-making competence: an item-level analysis of the Decision Outcome Inventory (DOI)

    PubMed Central

    Parker, Andrew M.; Bruine de Bruin, Wändi; Fischhoff, Baruch

    2015-01-01

    Most behavioral decision research takes place in carefully controlled laboratory settings, and examination of relationships between performance and specific real-world decision outcomes is rare. One prior study shows that people who perform better on hypothetical decision tasks, assessed using the Adult Decision-Making Competence (A-DMC) measure, also tend to experience better real-world decision outcomes, as reported on the Decision Outcomes Inventory (DOI). The DOI score reflects avoidance of outcomes that could result from poor decisions, ranging from serious (e.g., bankruptcy) to minor (e.g., blisters from sunburn). The present analyses go beyond the initial work, which focused on the overall DOI score, by analyzing the relationships between specific decision outcomes and A-DMC performance. Most outcomes are significantly more likely among people with lower A-DMC scores, even after taking into account two variables expected to produce worse real-world decision outcomes: younger age and lower socio-economic status. We discuss the usefulness of DOI as a measure of successful real-world decision-making. PMID:25904876

  12. Genetic-program-based data mining for hybrid decision-theoretic algorithms and theories

    NASA Astrophysics Data System (ADS)

    Smith, James F., III

    2005-03-01

    A genetic program (GP) based data mining (DM) procedure has been developed that automatically creates decision theoretic algorithms. A GP is an algorithm that uses the theory of evolution to automatically evolve other computer programs or mathematical expressions. The output of the GP is a computer program or mathematical expression that is optimal in the sense that it maximizes a fitness function. The decision theoretic algorithms created by the DM algorithm are typically designed for making real-time decisions about the behavior of systems. The database that is mined by the DM typically consists of many scenarios characterized by sensor output and labeled by experts as to the status of the scenario. The DM procedure will call a GP as a data mining function. The GP incorporates the database and expert"s rules into its fitness function to evolve an optimal decision theoretic algorithm. A decision theoretic algorithm created through this process will be discussed as well as validation efforts showing the utility of the decision theoretic algorithm created by the DM process. GP based data mining to determine equations related to scientific theories and automatic simplification methods based on computer algebra will also be discussed.

  13. Decision-making ability in current and past users of opiates: A meta-analysis.

    PubMed

    Biernacki, Kathryn; McLennan, Skye N; Terrett, Gill; Labuschagne, Izelle; Rendell, Peter G

    2016-12-01

    Opiate use is associated with deficits in decision-making. However, the impact of abstinence and co-morbid factors, like head injury and poly-substance abuse, on this ability, is currently unclear. This meta-analysis aimed to assess 1) the magnitude of decision-making deficits in opiate users; 2) whether co-morbid factors moderate the severity of these deficits; 3) whether ex-opiate users demonstrate smaller decision-making deficits than current users; and 4) whether the length of abstinence is related to the magnitude of decision-making deficits. We analysed 22 studies that compared the performance of current and ex-opiate users to healthy controls on decision-making measures such as the Iowa Gambling Task. Current users demonstrated a moderately strong impairment in decision-making relative to controls, which was not significantly moderated by co-morbid factors. The magnitude of the impairment did not significantly differ between studies assessing current or ex-users, and this impairment was not related to length of abstinence. Thus, it appears that opiate users have relatively severe decision-making deficits that persist at least 1.5 years after cessation of use.

  14. Evidence-Based Practice: A Framework for Making Effective Decisions

    ERIC Educational Resources Information Center

    Spencer, Trina D.; Detrich, Ronnie; Slocum, Timothy A.

    2012-01-01

    The research to practice gap in education has been a long-standing concern. The enactment of No Child Left Behind brought increased emphasis on the value of using scientifically based instructional practices to improve educational outcomes. It also brought education into the broader evidence-based practice movement that started in medicine and has…

  15. Graph-based Models for Data and Decision Making

    DTIC Science & Technology

    2014-01-01

    signed// DR. LESLIE M. BLAHA JEFFREY L. CRAIG, Chief Work Unit Manager Battlespace Visualization Branch Battlespace Visualization...Performance Wing Human Effectiveness Directorate Crew Systems Interface Division Battlespace Visualization Branch Wright-Patterson Air Force Base...information transmission through a network. Additionally, new visual tools for pattern discovery and visual analytics are proposed based on topological data

  16. Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies

    PubMed Central

    2011-01-01

    Background Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. Methods We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. Results We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. Conclusions We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application. PMID:21696604

  17. General Formalism of Decision Making Based on Theory of Open Quantum Systems

    NASA Astrophysics Data System (ADS)

    Asano, M.; Ohya, M.; Basieva, I.; Khrennikov, A.

    2013-01-01

    We present the general formalism of decision making which is based on the theory of open quantum systems. A person (decision maker), say Alice, is considered as a quantum-like system, i.e., a system which information processing follows the laws of quantum information theory. To make decision, Alice interacts with a huge mental bath. Depending on context of decision making this bath can include her social environment, mass media (TV, newspapers, INTERNET), and memory. Dynamics of an ensemble of such Alices is described by Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) equation. We speculate that in the processes of evolution biosystems (especially human beings) designed such "mental Hamiltonians" and GKSL-operators that any solution of the corresponding GKSL-equation stabilizes to a diagonal density operator (In the basis of decision making.) This limiting density operator describes population in which all superpositions of possible decisions has already been resolved. In principle, this approach can be used for the prediction of the distribution of possible decisions in human populations.

  18. Knowledge-based goal-driven approach for information extraction and decision making for target recognition

    NASA Astrophysics Data System (ADS)

    Wilson, Roderick D.; Wilson, Anitra C.

    1996-06-01

    This paper presents a novel goal-driven approach for designing a knowledge-based system for information extraction and decision-making for target recognition. The underlying goal-driven model uses a goal frame tree schema for target organization, a hybrid rule-based pattern- directed formalism for target structural encoding, and a goal-driven inferential control strategy. The knowledge-base consists of three basic structures for the organization and control of target information: goals, target parameters, and an object-rulebase. Goal frames represent target recognition tasks as goals and subgoals in the knowledge base. Target parameters represent characteristic attributes of targets that are encoded as information atoms. Information atoms may have one or more assigned values and are used for information extraction. The object-rulebase consists of pattern/action assertional implications that describe the logical relationships existing between target parameter values. A goal realization process formulates symbolic patten expressions whose atomic values map to target parameters contained a priori in a hierarchical database of target state information. Symbolic pattern expression creation is accomplished via the application of a novel goal-driven inference strategy that logically prunes an AND/OR tree constructed object-rulebase. Similarity analysis is performed via pattern matching of query symbolic patterns and a priori instantiated target parameters.

  19. Reward-Based Decision Signals in Parietal Cortex Are Partially Embodied

    PubMed Central

    Snyder, Lawrence H.

    2015-01-01

    Recordings in the lateral intraparietal area (LIP) reveal that parietal cortex encodes variables related to spatial decision-making, the selection of desirable targets in space. It has been unclear whether parietal cortex is involved in spatial decision-making in general, or whether specific parietal compartments subserve decisions made using specific actions. To test this, we engaged monkeys (Macaca mulatta) in a reward-based decision task in which they selected a target based on its desirability. The animals' choice behavior in this task followed the molar matching law, and in each trial was governed by the desirability of the choice targets. Critically, animals were instructed to make the choice using one of two actions: eye movements (saccades) and arm movements (reaches). We recorded the discharge activity of neurons in area LIP and the parietal reach region (PRR) of the parietal cortex. In line with previous studies, we found that both LIP and PRR encode a reward-based decision variable, the target desirability. Crucially, the target desirability was encoded in LIP at least twice as strongly when choices were made using saccades compared with reaches. In contrast, PRR encoded target desirability only for reaches and not for saccades. These data suggest that decisions can evolve in dedicated parietal circuits in the context of specific actions. This finding supports the hypothesis of an intentional representation of developing decisions in parietal cortex. Furthermore, the close link between the cognitive (decision-related) and bodily (action-related) processes presents a neural contribution to the theories of embodied cognition. PMID:25810518

  20. Cost-benefit analysis in decision making for diagnostic radiology

    SciTech Connect

    Fabrikant, J.I.; Hilberg, A.W.

    1982-02-01

    This paper reviews certain current concepts and methods relating to benefit-risk analysis, in terms of economic costs and raidation risks to health, in relation to the benefits from diagnostic radiology in clinical medicine.

  1. Realtime Decision Making on EO-1 Using Onboard Science Analysis

    NASA Technical Reports Server (NTRS)

    Sherwood, Robert; Chien, Steve; Davies, Ashley; Mandl, Dan; Frye, Stu

    2004-01-01

    Recent autonomy experiments conducted on Earth Observing 1 (EO-1) using the Autonomous Sciencecraft Experiment (ASE) flight software has been used to classify key features in hyperspectral images captured by EO-1. Furthermore, analysis is performed by this software onboard EO-1 and then used to modify the operational plan without interaction from the ground. This paper will outline the overall operations concept and provide some details and examples of the onboard science processing, science analysis, and replanning.

  2. A Pharmacoeconomics and Formulary Management Collaborative Project to Teach Decision Analysis Principles

    PubMed Central

    Buring, Shauna; Cluxton, Robert

    2012-01-01

    Objective. To implement and assess the effectiveness of a 2-course collaborative decision analysis project intended to help students understand the relevance of pharmacoeconomics to clinical pharmacy practice and provide them an opportunity to apply skills taught in pharmacoeconomics to a “real world” problem. Design. Students were assigned a pair of drugs, 1 commonly used as standard therapy and 1 newly approved, and conducted a decision analysis. The results were then used in a mock pharmacy and therapeutics (P&T) committee meeting. Assessment. Ninety-eight of 106 (92%) students completed a 4-question survey instrument. Ninety-six percent of students agreed or somewhat agreed that the decision analysis project met the learning objectives. Students felt the shared assignment influenced their choice of formulary drug, augmented understanding of factors influencing decisions, broadened their thinking about drug costs, and was a good approximation of a “real world” application. Conclusion. An innovative joint-course assignment proved to be a successful technique for teaching decision analysis. PMID:22919091

  3. Orbitofrontal contributions to value-based decision making: evidence from humans with frontal lobe damage.

    PubMed

    Fellows, Lesley K

    2011-12-01

    The work described here aims to isolate the component processes of decision making that rely critically on particular subregions of the human prefrontal cortex, with a particular focus on the orbitofrontal cortex. Here, experiments isolating specific aspects of decision making, using very simple preference judgment and reinforcement learning paradigms, were carried out in patients with focal frontal damage. The orbitofrontal cortex and the adjacent ventromedial prefrontal cortex play a critical role in decisions based on subjective value, across many categories of stimuli, and in learning to choose between stimuli based on value feedback. However, these regions are not required for learning to choose between actions based on feedback, which instead seems to rely critically on the dorsomedial prefrontal cortex. These results point to a potentially common role for the orbitofrontal cortex in representing the context-sensitive, subjective value of stimuli to allow consistent choices between them. They also argue for multiple, parallel, value-based processes that influence behavior through dissociable mechanisms.

  4. Development of a Geographic Information System-Based Decision Support Tool for Evaluating Windfarm Sitings in Great Lakes Aquatic Habitats

    SciTech Connect

    Wehrly, Kevin E.; Rutherford, Edward S.; Wang, Lizhu; Breck, Jason; Mason, Lacey; Nelson, Scott

    2011-07-31

    As an outcome of our research project, we developed software and data for the Lakebed Alteration Decision Support Tool (LADST), a web-based decision support program to assist resource managers in making siting decisions for offshore wind farms (as well as other lakebed-altering projects) in the United States' waters of the Great Lakes. Users of the LADST can create their own offshore wind farm suitability maps, based upon suitability criteria of their own choosing by visiting a public web site. The LADST can be used to represent the different priorities or values of different Great Lakes stakeholders for wind farm siting, as well as the different suitability requirements of wind farms (or different types of development projects) in a single suitability analysis system. The LADST makes this type of customized suitability analysis easily accessible to users who have no specialized software or experience with geographic information systems (GIS). It also may increase the transparency of the siting and permitting process for offshore wind farms, as it makes the suitability analysis equally accessible to resource managers, wind farm developers, and concerned citizens.

  5. Shaping the Conversation: A Secondary Analysis of Reproductive Decision-Making Among Black Mothers with HIV

    PubMed Central

    Amutah, Ndidiamaka N.; Gifuni, Jacqueline; Wesley, Yvonne

    2016-01-01

    The purpose of this qualitative secondary data analysis is to examine the major influencers on mothers with HIV in their childbearing decisions, as well as how those influencers shape conversations with clinicians and health-care providers regarding HIV treatment and prevention. The original study gained insight into the reproductive decision-making of mothers with HIV. By analyzing a subsample of 15 interviews from an original cohort of 25 participants in the earlier study, three major themes were identified as follows: (1) family members, not health-care providers, influence reproductive decisions; (2) negative attitudes toward subsequent pregnancies are mainly due to HIV transmission; and (3) birth control decisions were predominately supported by family members, while health-care providers were not consulted. PMID:27158227

  6. Shaping the Conversation: A Secondary Analysis of Reproductive Decision-Making Among Black Mothers with HIV.

    PubMed

    Amutah, Ndidiamaka N; Gifuni, Jacqueline; Wesley, Yvonne

    2016-01-01

    The purpose of this qualitative secondary data analysis is to examine the major influencers on mothers with HIV in their childbearing decisions, as well as how those influencers shape conversations with clinicians and health-care providers regarding HIV treatment and prevention. The original study gained insight into the reproductive decision-making of mothers with HIV. By analyzing a subsample of 15 interviews from an original cohort of 25 participants in the earlier study, three major themes were identified as follows: (1) family members, not health-care providers, influence reproductive decisions; (2) negative attitudes toward subsequent pregnancies are mainly due to HIV transmission; and (3) birth control decisions were predominately supported by family members, while health-care providers were not consulted.

  7. Learning from examples - Generation and evaluation of decision trees for software resource analysis

    NASA Technical Reports Server (NTRS)

    Selby, Richard W.; Porter, Adam A.

    1988-01-01

    A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for software resource data analysis. The trees identify classes of objects (software modules) that had high development effort. Sixteen software systems ranging from 3,000 to 112,000 source lines were selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4,700 objects, captured information about the development effort, faults, changes, design style, and implementation style. A total of 9,600 decision trees were automatically generated and evaluated. The trees correctly identified 79.3 percent of the software modules that had high development effort or faults, and the trees generated from the best parameter combinations correctly identified 88.4 percent of the modules on the average.

  8. Patient-Focused Benefit-Risk Analysis to Inform Regulatory Decisions: The European Union Perspective.

    PubMed

    Mühlbacher, Axel C; Juhnke, Christin; Beyer, Andrea R; Garner, Sarah

    Regulatory decisions are often based on multiple clinical end points, but the perspectives used to judge the relative importance of those end points are predominantly those of expert decision makers rather than of the patient. However, there is a growing awareness that active patient and public participation can improve decision making, increase acceptance of decisions, and improve adherence to treatments. The assessment of risk versus benefit requires not only information on clinical outcomes but also value judgments about which outcomes are important and whether the potential benefits outweigh the harms. There are a number of mechanisms for capturing the input of patients, and regulatory bodies within the European Union are participating in several initiatives. These can include patients directly participating in the regulatory decision-making process or using information derived from patients in empirical studies as part of the evidence considered. One promising method that is being explored is the elicitation of "patient preferences." Preferences, in this context, refer to the individual's evaluation of health outcomes and can be understood as statements regarding the relative desirability of a range of treatment options, treatment characteristics, and health states. Several methods for preference measurement have been proposed, and pilot studies have been undertaken to use patient preference information in regulatory decision making. This article describes how preferences are currently being considered in the benefit-risk assessment context, and shows how different methods of preference elicitation are used to support decision making within the European context.

  9. Using Decision Analysis to Select Facility Maintenance Management Information Systems

    DTIC Science & Technology

    2010-03-01

    OF THE AIR FORCE AIR UNIVERSITY AIR FORCE INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio APPROVED FOR PUBLIC RELEASE...Systems and Engineering Management Graduate School of Engineering and Management Air Force Institute of Technology Air University Air...increased (Garg & Deshmukh, 2006). According to Teicholz and Ikeda (1995), the support for technology -based maintenance systems began during the

  10. Accelerating Policy Decisions to Adopt Haemophilus influenzae Type b Vaccine: A Global, Multivariable Analysis

    PubMed Central

    Shearer, Jessica C.; Stack, Meghan L.; Richmond, Marcie R.; Bear, Allyson P.; Hajjeh, Rana A.; Bishai, David M.

    2010-01-01

    Background Adoption of new and underutilized vaccines by national immunization programs is an essential step towards reducing child mortality. Policy decisions to adopt new vaccines in high mortality countries often lag behind decisions in high-income countries. Using the case of Haemophilus influenzae type b (Hib) vaccine, this paper endeavors to explain these delays through the analysis of country-level economic, epidemiological, programmatic and policy-related factors, as well as the role of the Global Alliance for Vaccines and Immunisation (GAVI Alliance). Methods and Findings Data for 147 countries from 1990 to 2007 were analyzed in accelerated failure time models to identify factors that are associated with the time to decision to adopt Hib vaccine. In multivariable models that control for Gross National Income, region, and burden of Hib disease, the receipt of GAVI support speeded the time to decision by a factor of 0.37 (95% CI 0.18–0.76), or 63%. The presence of two or more neighboring country adopters accelerated decisions to adopt by a factor of 0.50 (95% CI 0.33–0.75). For each 1% increase in vaccine price, decisions to adopt are delayed by a factor of 1.02 (95% CI 1.00–1.04). Global recommendations and local studies were not associated with time to decision. Conclusions This study substantiates previous findings related to vaccine price and presents new evidence to suggest that GAVI eligibility is associated with accelerated decisions to adopt Hib vaccine. The influence of neighboring country decisions was also highly significant, suggesting that approaches to support the adoption of new vaccines should consider supply- and demand-side factors. Please see later in the article for the Editors' Summary PMID:20305714

  11. Inductive Decision Tree Analysis of the Validity Rank of Construction Parameters of Innovative Gear Pump after Tooth Root Undercutting

    NASA Astrophysics Data System (ADS)

    Deptuła, A.; Partyka, M. A.

    2017-02-01

    The article presents an innovative use of inductive algorithm for generating the decision tree for an analysis of the rank validity parameters of construction and maintenance of the gear pump with undercut tooth. It is preventet an alternative way of generating sets of decisions and determining the hierarchy of decision variables to existing the methods of discrete optimization.

  12. Effects of stress on decisions under uncertainty: A meta-analysis.

    PubMed

    Starcke, Katrin; Brand, Matthias

    2016-09-01

    [Correction Notice: An Erratum for this article was reported in Vol 142(9) of Psychological Bulletin (see record 2016-39486-001). It should have been reported that the inverted u-shaped relationship between cortisol stress responses and decision-making performance was only observed in female, but not in male participants as suggested by the study by van den Bos, Harteveld, and Stoop (2009). Corrected versions of the affected sentences are provided.] The purpose of the present meta-analysis was to quantify the effects that stress has on decisions made under uncertainty. We hypothesized that stress increases reward seeking and risk taking through alterations of dopamine firing rates and reduces executive control by hindering optimal prefrontal cortex functioning. In certain decision situations, increased reward seeking and risk taking is dysfunctional, whereas in others, this is not the case. We also assumed that the type of stressor plays a role. In addition, moderating variables are analyzed, such as the hormonal stress response, the time between stress onset and decisions, and the participants' age and gender. We included studies in the meta-analysis that investigated decision making after a laboratory stress-induction versus a control condition (k = 32 datasets, N = 1829 participants). A random-effects model revealed that overall, stress conditions lead to decisions that can be described as more disadvantageous, more reward seeking, and more risk taking than nonstress conditions (d = .17). In those situations in which increased reward seeking and risk taking is disadvantageous, stress had significant effects (d = .26), whereas in other situations, no effects were observed (d = .01). Effects were observed under processive stressors (d = .19), but not under systemic ones (d = .09). Moderation analyses did not reveal any significant results. We concluded that stress deteriorates overall decision-making performance through the mechanisms proposed. The effects differ

  13. Evaluation of a Decision Support System for Obstructive Sleep Apnea with Nonlinear Analysis of Respiratory Signals

    PubMed Central

    Kaimakamis, Evangelos; Tsara, Venetia; Bratsas, Charalambos; Sichletidis, Lazaros; Karvounis, Charalambos; Maglaveras, Nikolaos

    2016-01-01

    Introduction Obstructive Sleep Apnea (OSA) is a common sleep disorder requiring the time/money consuming polysomnography for diagnosis. Alternative methods for initial evaluation are sought. Our aim was the prediction of Apnea-Hypopnea Index (AHI) in patients potentially suffering from OSA based on nonlinear analysis of respiratory biosignals during sleep, a method that is related to the pathophysiology of the disorder. Materials and Methods Patients referred to a Sleep Unit (135) underwent full polysomnography. Three nonlinear indices (Largest Lyapunov Exponent, Detrended Fluctuation Analysis and Approximate Entropy) extracted from two biosignals (airflow from a nasal cannula, thoracic movement) and one linear derived from Oxygen saturation provided input to a data mining application with contemporary classification algorithms for the creation of predictive models for AHI. Results A linear regression model presented a correlation coefficient of 0.77 in predicting AHI. With a cutoff value of AHI = 8, the sensitivity and specificity were 93% and 71.4% in discrimination between patients and normal subjects. The decision tree for the discrimination between patients and normal had sensitivity and specificity of 91% and 60%, respectively. Certain obtained nonlinear values correlated significantly with commonly accepted physiological parameters of people suffering from OSA. Discussion We developed a predictive model for the presence/severity of OSA using a simple linear equation and additional decision trees with nonlinear features extracted from 3 respiratory recordings. The accuracy of the methodology is high and the findings provide insight to the underlying pathophysiology of the syndrome. Conclusions Reliable predictions of OSA are possible using linear and nonlinear indices from only 3 respiratory signals during sleep. The proposed models could lead to a better study of the pathophysiology of OSA and facilitate initial evaluation/follow up of suspected patients OSA

  14. Energy efficiency in the US economy technical report four: Analysis of energy-efficiency investment decisions by small and medium-sized manufacturers

    SciTech Connect

    1996-03-01

    This report highlights the results of a comprehensive analysis of investment decisions regarding energy-efficiency measures at small and medium-sized manufacturing plants. The analysis is based primarily on the experiences of companies participating in the US Department of Energy`s Industrial Assessment Center (IAC) program.

  15. A Cross-Layer User Centric Vertical Handover Decision Approach Based on MIH Local Triggers

    NASA Astrophysics Data System (ADS)

    Rehan, Maaz; Yousaf, Muhammad; Qayyum, Amir; Malik, Shahzad

    Vertical handover decision algorithm that is based on user preferences and coupled with Media Independent Handover (MIH) local triggers have not been explored much in the literature. We have developed a comprehensive cross-layer solution, called Vertical Handover Decision (VHOD) approach, which consists of three parts viz. mechanism for collecting and storing user preferences, Vertical Handover Decision (VHOD) algorithm and the MIH Function (MIHF). MIHF triggers the VHOD algorithm which operates on user preferences to issue handover commands to mobility management protocol. VHOD algorithm is an MIH User and therefore needs to subscribe events and configure thresholds for receiving triggers from MIHF. In this regard, we have performed experiments in WLAN to suggest thresholds for Link Going Down trigger. We have also critically evaluated the handover decision process, proposed Just-in-time interface activation technique, compared our proposed approach with prominent user centric approaches and analyzed our approach from different aspects.

  16. Reliability of Laparoscopic Compared With Hysteroscopic Sterilization at One Year: A Decision Analysis

    PubMed Central

    Gariepy, Aileen M.; Creinin, Mitchell D.; Schwarz, Eleanor B.; Smith, Kenneth J.

    2011-01-01

    OBJECTIVE To estimate the probability of successful sterilization after hysteroscopic or laparoscopic sterilization procedure. METHODS An evidence-based clinical decision analysis using a Markov model was performed to estimate the probability of a successful sterilization procedure using laparoscopic sterilization, hysteroscopic sterilization in the operating room, and hysteroscopic sterilization in the office. Procedure and follow-up testing probabilities for the model were estimated from published sources. RESULTS In the base case analysis, the proportion of women having a successful sterilization procedure on first attempt is 99% for laparoscopic, 88% for hysteroscopic in the operating room and 87% for hysteroscopic in the office. The probability of having a successful sterilization procedure within one year is 99% with laparoscopic, 95% for hysteroscopic in the operating room, and 94% for hysteroscopic in the office. These estimates for hysteroscopic success include approximately 6% of women who attempt hysteroscopically but are ultimately sterilized laparoscopically. Approximately 5% of women who have a failed hysteroscopic attempt decline further sterilization attempts. CONCLUSIONS Women choosing laparoscopic sterilization are more likely than those choosing hysteroscopic sterilization to have a successful sterilization procedure within one year. However, the risk of failed sterilization and subsequent pregnancy must be considered when choosing a method of sterilization. PMID:21775842

  17. On the Development of a Computing Infrastructure that Facilitates IPPD from a Decision-Based Design Perspective

    NASA Technical Reports Server (NTRS)

    Hale, Mark A.; Craig, James I.; Mistree, Farrokh; Schrage, Daniel P.

    1995-01-01

    Integrated Product and Process Development (IPPD) embodies the simultaneous application of both system and quality engineering methods throughout an iterative design process. The use of IPPD results in the time-conscious, cost-saving development of engineering systems. Georgia Tech has proposed the development of an Integrated Design Engineering Simulator that will merge Integrated Product and Process Development with interdisciplinary analysis techniques and state-of-the-art computational technologies. To implement IPPD, a Decision-Based Design perspective is encapsulated in an approach that focuses on the role of the human designer in product development. The approach has two parts and is outlined in this paper. First, an architecture, called DREAMS, is being developed that facilitates design from a decision-based perspective. Second, a supporting computing infrastructure, called IMAGE, is being designed. The current status of development is given and future directions are outlined.

  18. A cloud theory-based particle swarm optimization for multiple decision maker vehicle routing problems with fuzzy random time windows

    NASA Astrophysics Data System (ADS)

    Ma, Yanfang; Xu, Jiuping

    2015-06-01

    This article puts forward a cloud theory-based particle swarm optimization (CTPSO) algorithm for solving a variant of the vehicle routing problem, namely a multiple decision maker vehicle routing problem with fuzzy random time windows (MDVRPFRTW). A new mathematical model is developed for the proposed problem in which fuzzy random theory is used to describe the time windows and bi-level programming is applied to describe the relationship between the multiple decision makers. To solve the problem, a cloud theory-based particle swarm optimization (CTPSO) is proposed. More specifically, this approach makes improvements in initialization, inertia weight and particle updates to overcome the shortcomings of the basic particle swarm optimization (PSO). Parameter tests and results analysis are presented to highlight the performance of the optimization method, and comparison of the algorithm with the basic PSO and the genetic algorithm demonstrates its efficiency.

  19. Picture Exchange Communication System (PECS) or Sign Language: An Evidence-Based Decision-Making Example

    ERIC Educational Resources Information Center

    Spencer, Trina D.; Petersen, Douglas B.; Gillam, Sandra L.

    2008-01-01

    Evidence-based practice (EBP) refers to clinical decisions as a result of the careful integration of research evidence and student needs. Legal mandates such as No Child Left Behind require teachers to employ evidence-based practices in their classrooms, yet teachers receive little guidance regarding how to determine which practices are…

  20. Examining Preservice Teachers' Classroom Management Decisions in Three Case-Based Teaching Approaches

    ERIC Educational Resources Information Center

    Demiraslan-Çevik, Yasemin; Andre, Thomas

    2013-01-01

    This study was aimed at comparing the impact of three types of case-based approaches (worked example, faded work example, and case-based reasoning) on preservice teachers' decision making and reasoning skills related to realistic classroom management situations. Participants in this study received a short-term implementation of one of these three…

  1. Diverter AI based decision aid, phases 1 and 2

    NASA Technical Reports Server (NTRS)

    Sexton, George A.; Bayles, Scott J.; Patterson, Robert W.; Schulke, Duane A.; Williams, Deborah C.

    1989-01-01

    It was determined that a system to incorporate artificial intelligence (AI) into airborne flight management computers is feasible. The AI functions that would be most useful to the pilot are to perform situational assessment, evaluate outside influences on the contemplated rerouting, perform flight planning/replanning, and perform maneuver planning. A study of the software architecture and software tools capable of demonstrating Diverter was also made. A skeletal planner known as the Knowledge Acquisition Development Tool (KADET), which is a combination script-based and rule-based system, was used to implement the system. A prototype system was developed which demonstrates advanced in-flight planning/replanning capabilities.

  2. Effects-Based Decision Making in the War on Terror

    DTIC Science & Technology

    2005-06-01

    Further, Renfro and Deckro observe two key characteristics of a maximum influence node. First, the node with the maximum influence is a pressure point... Renfro and Richard F Deckro, “A Flow Model Social Network Analysis of the Iranian Government,” Military Operations Research V8 N1: 2003, pp 5-15...to a lesser extent, the operational level but have limited value at the tactical level due to the pace of operations. Social Networks Renfro and

  3. Using Anticipative Malware Analysis to Support Decision Making

    DTIC Science & Technology

    2010-11-01

    malware behaviour from a network point of view. The AES supports the execution of malware in a customisable virtual network that aims to emulate a...necessary to demonstrate the usefulness of the AES. We used virtualisation to facilitate mass analysis. However, this strategy presents the

  4. Portfolio theory and the alternative decision rule of cost-effectiveness analysis: theoretical and practical considerations.

    PubMed

    Sendi, Pedram; Al, Maiwenn J; Gafni, Amiram; Birch, Stephen

    2004-05-01

    Bridges and Terris (Soc. Sci. Med. (2004)) critique our paper on the alternative decision rule of economic evaluation in the presence of uncertainty and constrained resources within the context of a portfolio of health care programs (Sendi et al. Soc. Sci. Med. 57 (2003) 2207). They argue that by not adopting a formal portfolio theory approach we overlook the optimal solution. We show that these arguments stem from a fundamental misunderstanding of the alternative decision rule of economic evaluation. In particular, the portfolio theory approach advocated by Bridges and Terris is based on the same theoretical assumptions that the alternative decision rule set out to relax. Moreover, Bridges and Terris acknowledge that the proposed portfolio theory approach may not identify the optimal solution to resource allocation problems. Hence, it provides neither theoretical nor practical improvements to the proposed alternative decision rule.

  5. Web-enabled spatial decision analysis using Ordered Weighted Averaging (OWA)

    NASA Astrophysics Data System (ADS)

    Rinner, Claus; Malczewski, Jacek

    This paper presents a spatial decision support tool that implements the Ordered Weighted Averaging (OWA) method. OWA is a family of multicriteria evaluation operators characterised by two sets of weights: criterion importance weights and order weights. We propose a highly interactive way of choosing, modifying, and fine-tuning the decision strategy defined by the order weights. This exploratory approach to OWA is supported by a graphical representation of the operator's behaviour in terms of decision risk and tradeoff/dispersion between criteria. Our prototype implementation is based on the CommonGIS software, and thus, Web-enabled and working with vector data. We successfully demonstrate online, exploratory support of spatial decision strategies using a data set of skiing resorts in Wallis, Switzerland.

  6. Women's Values and Preferences for Thromboprophylaxis during Pregnancy: A Comparison of Direct-choice and Decision Analysis using Patient Specific Utilities

    PubMed Central

    Eckman, Mark H.; Alonso-Coello, Pablo; Guyatt, Gordon H.; Ebrahim, Shanil; Tikkinen, Kari A.O.; Lopes, Luciane Cruz; Neumann, Ignacio; McDonald, Sarah D.; Zhang, Yuqing; Zhou, Qi; Akl, Elie A.; Jacobsen, Ann Flem; Santamaría, Amparo; Annichino-Bizzacchi, Joyce Maria; Bitar, Wael; Sandset, Per Morten; Bates, Shannon M.

    2016-01-01

    Background Women with a history of venous thromboembolism (VTE) have an increased recurrence risk during pregnancy. Low molecular weight heparin (LMWH) reduces this risk, but is costly, burdensome, and may increase risk of bleeding. The decision to start thromboprophylaxis during pregnancy is sensitive to women's values and preferences. Our objective was to compare women's choices using a holistic approach in which they were presented all of the relevant information (direct-choice) versus a personalized decision analysis in which a mathematical model incorporated their preferences and VTE risk to make a treatment recommendation. Methods Multicenter, international study. Structured interviews were on women with a history of VTE who were pregnant, planning, or considering pregnancy. Women indicated their willingness to receive thromboprophylaxis based on scenarios using personalized estimates of VTE recurrence and bleeding risks. We also obtained women's values for health outcomes using a visual analog scale. We performed individualized decision analyses for each participant and compared model recommendations to decisions made when presented with the direct-choice exercise. Results Of the 123 women in the study, the decision model recommended LMWH for 51 women and recommended against LMWH for 72 women. 12% (6/51) of women for whom the decision model recommended thromboprophylaxis chose not to take LMWH; 72% (52/72) of women for whom the decision model recommended against thromboprophylaxis chose LMWH. Conclusions We observed a high degree of discordance between decisions in the direct-choice exercise and decision model recommendations. Although which approach best captures individuals’ true values remains uncertain, personalized decision support tools presenting results based on personalized risks and values may improve decision making. PMID:26033397

  7. Climate change, land slide risks and sustainable development, risk analysis and decision support process tool

    NASA Astrophysics Data System (ADS)

    Andersson-sköld, Y. B.; Tremblay, M.

    2011-12-01

    aspects in the decision making process on adaptation measures has been developed and is currently being tested in municipalities including central Gothenburg, and smaller municipalities in Sweden and Norway. The tool is a matrix based decision support tool (MDST) aiming for encoring discussion among experts and stakeholders. The first steps in the decision process include identification, inventory and assessment of the potential impacts of climate change such as landslides (or other events or actions). These steps are also included in general technical/physical risk and vulnerability analyses such as the risk analysis of the Göta älv valley. The MDST also includes further subsequent steps of the risk management process, and the full sequence of the MDST includes risk identification, risk specification, risk assessment, identification of measures, impact analysis of measures including an assessment of environmental, social and economical costs and benefits, a weight process and visualisation of the result. Here the MDST with some examples from the methodology for the Göta river valley analysis and the risk mitigation analysis from Sweden and Norway will be presented.

  8. A decision analysis framework for stakeholder involvement and learning in groundwater management

    NASA Astrophysics Data System (ADS)

    Karjalainen, T. P.; Rossi, P. M.; Ala-aho, P.; Eskelinen, R.; Reinikainen, K.; Kløve, B.; Pulido-Velazquez, M.; Yang, H.

    2013-12-01

    Multi-criteria decision analysis (MCDA) methods are increasingly used to facilitate both rigorous analysis and stakeholder involvement in natural and water resource planning. Decision-making in that context is often complex and multi-faceted with numerous trade-offs between social, environmental and economic impacts. However, practical applications of decision-support methods are often too technically oriented and hard to use, understand or interpret for all participants. The learning of participants in these processes is seldom examined, even though successful deliberation depends on learning. This paper analyzes the potential of an interactive MCDA framework, the decision analysis interview (DAI) approach, for facilitating stakeholder involvement and learning in groundwater management. It evaluates the results of the MCDA process in assessing land-use management alternatives in a Finnish esker aquifer area where conflicting land uses affect the groundwater body and dependent ecosystems. In the assessment process, emphasis was placed on the interactive role of the MCDA tool in facilitating stakeholder participation and learning. The results confirmed that the structured decision analysis framework can foster learning and collaboration in a process where disputes and diverse interests are represented. Computer-aided interviews helped the participants to see how their preferences affected the desirability and ranking of alternatives. During the process, the participants' knowledge and preferences evolved as they assessed their initial knowledge with the help of fresh scientific information. The decision analysis process led to the opening of a dialogue, showing the overall picture of the problem context and the critical issues for the further process.

  9. A decision analysis framework for stakeholder involvement and learning in groundwater management

    NASA Astrophysics Data System (ADS)

    Karjalainen, T. P.; Rossi, P. M.; Ala-aho, P.; Eskelinen, R.; Reinikainen, K.; Kløve, B.; Pulido-Velazquez, M.; Yang, H.

    2013-07-01

    Multi-criteria decision analysis (MCDA) methods are increasingly used to facilitate both rigorous analysis and stakeholder involvement in natural and water resource planning. Decision making in that context is often complex and multi-faceted with numerous trade-offs between social, environmental and economic impacts. However, practical applications of decision-support methods are often too technically oriented and hard to use, understand or interpret for all participants. The learning of participants in these processes is seldom examined, even though successful deliberation depends on learning. This paper analyzes the potential of an interactive MCDA framework, the decision analysis interview (DAI) approach, for facilitating stakeholder involvement and learning in groundwater management. It evaluates the results of an MCDA process in assessing land-use management alternatives in a Finnish esker aquifer area where conflicting land uses affect the groundwater body and dependent ecosystems. In the assessment process, emphasis was placed on the interactive role of the MCDA tool in facilitating stakeholder participation and learning. The results confirmed that the structured decision analysis framework can foster learning and collaboration in a process where disputes and diverse interests are represented. Computer-aided interviews helped the participants to see how their preferences affected the desirability and ranking of alternatives. During the process, the participants' knowledge and preferences evolved as they assess their initial knowledge with the help of fresh scientific information. The decision analysis process led to the opening of a dialogue, showing the overall picture of the problem context, and the critical issues for the further process.

  10. A decision analysis of the appropriate R and D strategy for enchanced oil recovery (EOR)

    SciTech Connect

    Phillips, R.L.; Nesbitt, D.M.

    1983-01-01

    This paper describes a decision analysis of the appropriate level of national aggregate research and development expenditure on Enhanced Oil Recovery (EOR) R and D. The analysis concludes that under the assumptions used a high level of R and D effort on EOR R and D is justified. The analysis also suggests that larger EOR RandD programs entail less overall economic risk than smaller programs by serving as a hedge against high world oil prices.

  11. Integrating conflict analysis and consensus reaching in a decision support system for water resource management.

    PubMed

    Giordano, R; Passarella, G; Uricchio, V F; Vurro, M

    2007-07-01

    The importance of shared decision processes in water management derives from the awareness of the inadequacy of traditional--i.e. engineering--approaches in dealing with complex and ill-structured problems. It is becoming increasingly obvious that traditional problem solving and decision support techniques, based on optimisation and factual knowledge, have to be combined with stakeholder based policy design and implementation. The aim of our research is the definition of an integrated decision support system for consensus achievement (IDSS-C) able to support a participative decision-making process in all its phases: problem definition and structuring, identification of the possible alternatives, formulation of participants' judgments, and consensus achievement. Furthermore, the IDSS-C aims at structuring, i.e. systematising the knowledge which has emerged during the participative process in order to make it comprehensible for the decision-makers and functional for the decision process. Problem structuring methods (PSM) and multi-group evaluation methods (MEM) have been integrated in the IDSS-C. PSM are used to support the stakeholders in providing their perspective of the problem and to elicit their interests and preferences, while MEM are used to define not only the degree of consensus for each alternative, highlighting those where the agreement is high, but also the consensus label for each alternative and the behaviour of individuals during the participative decision-making. The IDSS-C is applied experimentally to a decision process regarding the use of treated wastewater for agricultural irrigation in the Apulia Region (southern Italy).

  12. RiskChanges Spatial Decision Support system for the analysis of changing multi-hazard risk

    NASA Astrophysics Data System (ADS)

    van Westen, Cees; Zhang, Kaixi; Bakker, Wim; Andrejchenko, Vera; Berlin, Julian; Olyazadeh, Roya; Cristal, Irina

    2015-04-01

    Within the framework of the EU FP7 Marie Curie Project CHANGES and the EU FP7 Copernicus project INCREO a spatial decision support system was developed with the aim to analyse the effect of risk reduction planning alternatives on reducing the risk now and in the future, and support decision makers in selecting the best alternatives. Central to the SDSS are the stakeholders. The envisaged users of the system are organizations involved in planning of risk reduction measures, and that have staff capable of visualizing and analyzing spatial data at a municipal scale. The SDSS should be able to function in different countries with different legal frameworks and with organizations with different mandates. These could be subdivided into Civil protection organization with the mandate to design disaster response plans, Expert organizations with the mandate to design structural risk reduction measures (e.g. dams, dikes, check-dams etc), and planning organizations with the mandate to make land development plans. The SDSS can be used in different ways: analyzing the current level of risk, analyzing the best alternatives for risk reduction, the evaluation of the consequences of possible future scenarios to the risk levels, and the evaluation how different risk reduction alternatives will lead to risk reduction under different future scenarios. The SDSS is developed based on open source software and following open standards, for code as well as for data formats and service interfaces. Code development was based upon open source software as well. The architecture of the system is modular. The various parts of the system are loosely coupled, extensible, using standards for interoperability, flexible and web-based. The Spatial Decision Support System is composed of a number of integrated components. The Risk Assessment component allows to carry out spatial risk analysis, with different degrees of complexity, ranging from simple exposure (overlay of hazard and assets maps) to

  13. Perspectives about Living on the Horns of Dilemmas: An Analysis of Gender Factors Related to Superintendent Decision-Making and Problem-Solving

    ERIC Educational Resources Information Center

    Polka, Walter S.; Litchka, Peter R.; Calzi, Frank F.; Denig, Stephen J.; Mete, Rosina E.

    2014-01-01

    The major focus of this paper is a gender-based analysis of school superintendent decision-making and problem-solving as well as an investigation of contemporary leadership dilemmas. The findings are based on responses from 258 superintendents of K-12 school districts in Delaware, Maryland, New Jersey, New York, and Pennsylvania collected over a…

  14. CODE: Coherence Based Decision Boundaries for Feature Correspondence.

    PubMed

    Lin, Wen-Yan; Wang, Fan; Cheng, Ming-Ming; Yeung, Sai-Kit; Torr, Philip H S; Do, Minh N; Lu, Jiangbo

    2017-01-16

    A key challenge in feature correspondence is the difficulty in differentiating true and false matches at a local descriptor level. This forces adoption of strict similarity thresholds that discard many true matches. However, if analyzed at a global level, false matches are usually randomly scattered while true matches tend to be coherent (clustered around a few dominant motions), thus creating a coherence based separability constraint. This paper proposes a non-linear regression technique that can discover such a coherence based separability constraint from highly noisy matches and embed it into a correspondence likelihood model. Once computed, the model can filter the entire set of nearest neighbor matches (which typically contains over 90% false matches) for true matches. We integrate our technique into a full feature correspondence system which reliably generates large numbers of good quality correspondences over wide baselines where previous techniques provide few or no matches.

  15. Rapid Prototyping of Hyperspectral Image Analysis Algorithms for Improved Invasive Species Decision Support Tools

    NASA Astrophysics Data System (ADS)

    Bruce, L. M.; Ball, J. E.; Evangilista, P.; Stohlgren, T. J.

    2006-12-01

    Nonnative invasive species adversely impact ecosystems, causing loss of native plant diversity, species extinction, and impairment of wildlife habitats. As a result, over the past decade federal and state agencies and nongovernmental organizations have begun to work more closely together to address the management of invasive species. In 2005, approximately 500M dollars was budgeted by U.S. Federal Agencies for the management of invasive species. Despite extensive expenditures, most of the methods used to detect and quantify the distribution of these invaders are ad hoc, at best. Likewise, decisions on the type of management techniques to be used or evaluation of the success of these methods are typically non-systematic. More efficient methods to detect or predict the occurrence of these species, as well as the incorporation of this knowledge into decision support systems, are greatly needed. In this project, rapid prototyping capabilities (RPC) are utilized for an invasive species application. More precisely, our recently developed analysis techniques for hyperspectral imagery are being prototyped for inclusion in the national Invasive Species Forecasting System (ISFS). The current ecological forecasting tools in ISFS will be compared to our hyperspectral-based invasives prediction algorithms to determine if/how the newer algorithms enhance the performance of ISFS. The PIs have researched the use of remotely sensed multispectral and hyperspectral reflectance data for the detection of invasive vegetative species. As a result, the PI has designed, implemented, and benchmarked various target detection systems that utilize remotely sensed data. These systems have been designed to make decisions based on a variety of remotely sensed data, including high spectral/spatial resolution hyperspectral signatures (1000's of spectral bands, such as those measured using ASD handheld devices), moderate spectral/spatial resolution hyperspectral images (100's of spectral bands, such

  16. Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China

    PubMed Central

    Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

    2016-01-01

    Background: In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. Methods: As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6–12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. Results: The prevalence of anemia was 12.60% with a range of 3.47%–40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. Conclusions: The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities. PMID:27174328

  17. Using Decision Analysis to Understand the Indications for Unilateral Hand Transplantation.

    PubMed

    McClelland, Brett; Novak, Christine B; Hanna, Steven; McCabe, Steven J

    2016-12-01

    Background: Upper extremity transplantation has been performed to improve quality of life, the benefit which must be traded off for the risk created by life-long immunosuppression. We believe the process of decision analysis is well suited to improve our understanding of these trade-offs. Method: We created a decision tree to include a branch point to illustrate the expected recovery of useful function in the transplant, using the best estimates for utility and probability that exist. Results: Our model revealed that when the probability of achieving a good result, graded as Chen level one or two is greater than 73%, transplantation is preferred over no transplantation. The decision is sensitive to the probability of major complications and the utility of a transplanted limb with minimal function. Conclusions: The results of this analysis show that under some circumstances given a high probability of satisfactory functional recovery, unilateral hand transplantation can be justified.

  18. CEOS Contributions to Informing Energy Management and Policy Decision Making Using Space-Based Earth Observations

    NASA Technical Reports Server (NTRS)

    Eckman, Richard S.

    2009-01-01

    Earth observations are playing an increasingly significant role in informing decision making in the energy sector. In renewable energy applications, space-based observations now routinely augment sparse ground-based observations used as input for renewable energy resource assessment applications. As one of the nine Group on Earth Observations (GEO) societal benefit areas, the enhancement of management and policy decision making in the energy sector is receiving attention in activities conducted by the Committee on Earth Observation Satellites (CEOS). CEOS has become the "space arm" for the implementation of the Global Earth Observation System of Systems (GEOSS) vision. It is directly supporting the space-based, near-term tasks articulated in the GEO three-year work plan. This paper describes a coordinated program of demonstration projects conducted by CEOS member agencies and partners to utilize Earth observations to enhance energy management end-user decision support systems. I discuss the importance of engagement with stakeholders and understanding their decision support needs in successfully increasing the uptake of Earth observation products for societal benefit. Several case studies are presented, demonstrating the importance of providing data sets in formats and units familiar and immediately usable by decision makers. These projects show the utility of Earth observations to enhance renewable energy resource assessment in the developing world, forecast space-weather impacts on the power grid, and improve energy efficiency in the built environment.

  19. Semisupervised classification for hyperspectral image based on multi-decision labeling and deep feature learning

    NASA Astrophysics Data System (ADS)

    Ma, Xiaorui; Wang, Hongyu; Wang, Jie

    2016-10-01

    Semisupervised learning is widely used in hyperspectral image classification to deal with the limited training samples, however, some more information of hyperspectral image should be further explored. In this paper, a novel semisupervised classification based on multi-decision labeling and deep feature learning is presented to exploit and utilize as much information as possible to realize the classification task. First, the proposed method takes two decisions to pre-label each unlabeled sample: local decision based on weighted neighborhood information is made by the surrounding samples, and global decision based on deep learning is performed by the most similar training samples. Then, some unlabeled ones with high confidence are selected to extent the training set. Finally, self decision, which depends on the self features exploited by deep learning, is employed on the updated training set to extract spectral-spatial features and produce classification map. Experimental results with real data indicate that it is an effective and promising semisupervised classification method for hyperspectral image.

  20. [Prediction of regional soil quality based on mutual information theory integrated with decision tree algorithm].

    PubMed

    Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu

    2012-02-01

    In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.